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2016-05-12T22:15:10.714Z

2015-07-15T00:00:00.000Z

2555481

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Changes in Olsen Phosphorus Concentration and Its Response to Phosphorus Balance in Black Soils under Different Long-Term Fertilization Patterns The Olsen phosphorus (P) concentration of a soil is a key index that can be used to evaluate the P supply capacity of the soil and to estimate the optimal P fertilization rate. A study of the relationship between the soil Olsen P concentration and the P balance (P input minus P output) and their variations among different fertilization patterns will help to provide useful information for proper management of P fertilization. In this paper, the two investigated long-term experiments were established on black soils in the northeast region of China. Six fertilization treatments were selected: (1) unfertilized (CK); (2) nitrogen only (N); (3) nitrogen and potassium (NK); (4) nitrogen and phosphorus (NP); (5) nitrogen, phosphorus, and potassium (NPK); and (6) nitrogen, phosphorus, potassium and manure (NPKM). The results showed that the average Olsen P concentrations in the black soils at Gongzhuling and Harbin (16- and 31-year study periods, respectively), decreased by 0.49 and 0.56 mg kg-1 a-1, respectively, without P addition and increased by 3.17 and 1.78 mg kg-1 a-1, respectively, with P fertilization. The changes in soil Olsen P concentrations were significantly (P<0.05) correlated with the P balances at both sites except for the NP and NPK treatments at Gongzhuling. Under an average deficit of 100 kg ha-1 P, the soil Olsen P concentration at both sites decreased by 1.36~3.35 mg kg-1 in the treatments without P addition and increased by 4.80~16.04 mg kg-1 in the treatments with 100 kg ha-1 of P accumulation. In addition, the changes in Olsen P concentrations in the soil with 100 kg ha-1of P balance were significantly correlated with the P activation coefficient (PAC, percentage of Olsen P to total P, r=0.99, P<0.01) and soil organic matter content (r=0.91, P<0.01). A low pH was related to large changes of Olsen P by 1 kg ha-1 of P balance. These results indicated that soil organic matter and pH have important effects on the change in soil Olsen P by 1 kg ha-1 of P balance. Introduction Soil phosphorus (P) deficiencies can result in the imbalance of soil nutrient and low crop yields in agricultural practice. In this case, P fertilizer must be applied to the soils to improve the soil P levels and crop production. However, about 80%-90% of the added inorganic P fertilizer becomes unavailable to crops in the year of application due to adsorption and precipitation with Ca, Fe and Al in soils [1,2]. These mineral associated P in the soil can be converted among them, and the conversion processes could have effect on the available P level [3]. Available P in the soil, which is the most effective P sink, has been considered an important indicator for evaluating the capacity of the soil to supply P and for estimating the P fertilization rate and P loss risk from runoff [4,5]. Soil Olsen P is a routine available P index of soil in north China. Therefore, agronomic P management strategies can be based on the changes in soil Olsen P [6]. The changes in soil Olsen P following the application of P fertilizer (P input) have been examined in many studies [7][8][9]. Along with the high P uptake of crops, changes in soil Olsen P are driven by the P balance (P input minus P output) actually [10][11][12]. Moreover, a significantly positive linear correlation existed between the change in soil Olsen P concentration and the P balance that was first considered by the Rothamsted Experimental Station [13]. Related studies in the UK, India and China showed that each 100 kg P ha -1 P surplus increase the Olsen P by 1~6 mg P kg -1 [10,14,15]. The variations among the seven long-term experimental sites located in different provinces across China were attributed to the different environments, crop systems and soil physico-chemical properties, as well as suitable temperatures and higher clay content that enhanced the change in Olsen P by each 100 kg ha -1 P accumulation [16]. At a particular site that has the same environmental and crop system conditions, the soil physico-chemical properties caused by various fertilizations are the sole factors that have an impact on the relationship between the Olsen P and P balance of the treatments [17,18]. The change in Olsen P by each 1 kg ha -1 P balance indicates the P activating ability from sparingly P to available P. Therefore, the soil properties that impact sparingly P activation (desorption, dissolution and mineralization) should be considered. It has been proven that various fertilization patterns can increase or decrease the soil pH and organic matter content [19,20]. The soil pH is one of the most important factors affecting P activation process, including sorption-adsorption, precipitation-solubilization and other chemical reactions related to P fractions transformation [21]. For example, study found that when the rhizosphere pH of rape seedlings decreased from 6.5 to 4, the rhizosphere available P increased by 10 times after the growth of 35 days [22]. Studies have also proved that the pH reduction mainly increases the dissolution of Ca associated P [23]. Soil organic matter is another factor that activates the sparingly P. Because the soil organic matter can decrease the P adsorption due to the competing adsorption sites by organic anion; and dissolve the mineral associated P by low-molecular-weight organic acids [24]. For black loess soils in Gansu, China, the Olsen P concentration decreased by 3.18 mg kg -1 (control) and 1.95 mg kg -1 (nitrogen fertilizer only) per 100 kg ha -1 of P deficit and increased by 0.29~3.85 mg kg -1 per 100 kg ha -1 of P accumulation when P (chemical P and manure) was added [17]. Few papers have focused on the variations and especially their possible mechanism(s) of different soil physico-chemical properties among different fertilization patterns. Black soil, which is a typical soil in Northeast China, plays an important role in Chinese crop production. In Northeast China, understanding the variations and their possible mechanism(s) that result in the changes in Olsen P and the P balance under different fertilization patterns is useful for predicting the Olsen P dynamics and optimal P fertilization of black soils. The hypothesis of this study is that soil pH and organic matter would be important influence factors that affect the differences in changes in Olsen P by 1 kg ha -1 P balance among fertilization patterns. Here, we developed a minimal dataset of the changes in the Olsen P and P balance of two long-term experimental sites located on the black soil. The objectives of this study were to (i) investigate the temporal changes in the Olsen P concentration under long term fertilization; (ii) quantify the relationship between the Olsen P concentration and the P balance under different treatments; and (iii) determine the effects of soil pH and organic matter on the changes in Olsen P by 1 kg ha -1 P balance under long-term fertilization in Northeast China. Experimental sites The two long-term experimental sites, which were established in 1989 and 1979, are located in Gongzhuling Jilin province and Harbin Heilongjiang province, respectively, in Northeast China. The authorities of the two field sites are the Jilin Academy of Agricultural Sciences and the Heilongjiang Academy of Agricultural Sciences of China, both of which granted permission for the research work. No specific field permits were required for this study, and no locations used in our study involved endangered or protected species. The study period presented in this paper is from 1989 to 2005 at Gongzhuling (16 years) and from 1979 to 2010 at Harbin (31 years). The black soils at the two sites are classified as Udic Mollisols [25]. The climatic types of the two sites are mid-temperate, semi-humid, continental monsoon climate. Descriptions of the experimental sites and the initial soil (0-20 cm) properties are summarized in Table 1. Experimental design The Gongzhuling and Harbin experimental plots covered 400 and 168 m 2 , respectively. Numerous treatments were implemented at these two sites, and six treatments that included no P, chemical P, and chemical and organic P were selected at each site: unfertilized (CK); nitrogen only (N); nitrogen and potassium (NK); nitrogen and phosphorus (NP); nitrogen, phosphorus, and potassium (NPK); and nitrogen, phosphorus, potassium and manure (NPKM) ( Table 2). These two long term experiments were not replicated. Urea, diammonium phosphate or superphosphate, and potassium chloride (KCl) or potassium sulfate (K 2 SO 4 ) were used as the N, P, and K fertilizers, respectively, at the two sites. The organic fertilizer was pig manure (30 t ha -1 , equivalent to 115 kg ha -1 N and 52 kg ha -1 P) at Gongzhuling and horse dung (18.6 t ha -1 , equivalent to 75 kg ha -1 N and 25 kg ha -1 P) at Harbin [26]. The inorganic and organic fertilizers were applied annually at Gongzhuling before seeding. At Harbin, chemical fertilizers were applied each fall after harvest, and organic fertilizer was only applied after maize culture [27]. Soil and plant sampling and chemical analysis Soil samples were collected from the top 20 cm of the soil, which was considered the active depth, after crop harvest each year. Five fresh soil samples were randomly sampled from the middle area of each plot. The soil samples were mixed, air-dried and sieved through 2.0 mm mesh screens for the determination of available nutrients, and through 0.25 mm mesh screens prior to total nutrient analyses. Subsamples were stored prior to analyzing their physicochemical properties. Total soil P was digested with H 2 SO 4 -HClO 4 and measured using the molybdenum-blue colorimetric method. The soil Olsen P concentration was determined using 0.5 mol L -1 NaHCO 3 (pH 8.5) and the molybdenum-blue colorimetric method. In addition, other initial soil samples were analyzed for organic matter, total nitrogen, total potassium, alkalinehydrolyzable N, NH 4 OAc-extractable K and pH. The grains and straws of wheat and maize were manually harvested, dried at 70°C to a uniform moisture level, weighed and then the P concentrations were measured separately. All the indexes mentioned above were analyzed according to the methods presented by Lu [28]. Calculations and statistical analysis The P activation coefficient (PAC, %) represents the proportion of Olsen P to total P [29]. The PAC (%) was calculated as follows: where Po is the concentration of Olsen P (mg kg -1 ), and Pt is the concentration of total P (mg kg -1 ) in the soil. The change in soil Olsen P (ΔOlsen P, mg kg -1 ) was calculated as follows: where Pi is the soil Olsen P concentration (mg kg -1 ) at year i and P0 is the initial concentration of soil Olsen P(mg kg -1 ). The crop P offtake (P C , kg ha -1 a -1 ) was calculated as follows: where Y G is the grain yield(kg ha -1 ), C G is the grain P concentration (%), Y S is the straw yield (kg ha -1 ) and C S is the straw P concentration (%). The annual apparent P balance in the soil was calculated as the P input minus the P output each year. The P balance was calculated as the sum of the annual apparent P balance, which represents the total cumulative P in the surface layers (0-20 cm) of the soil. This study was based on the soil surface (0-20 cm) balance but not the potential losses resulting from runoff and soil erosion [30]. Thus, the P balance (kg ha -1 ) was calculated as follows: where P F is the P application (kg ha -1 a -1 ). The average level of soil organic matter and soil PAC was analyzed using one-way ANOVA in SAS V8 (SAS Institute, USA). The means were compared using the Duncan method. The significance level used in this paper is P = 0.05. A linear regression was used to determine the relationships between the ΔOlsen P and the P balance, the Olsen P changes by each 100 kg ha -1 P balance and the PAC, the Olsen P changes by each 100 kg ha -1 P balance and the organic matter, and the changing trends of the Olsen P in soil under various fertilization patterns. The Olsen P concentrations in black soils The number of experimental years that were selected for this study was 16 years for Gongzhuling and 31 years for Harbin. Without the application of P fertilizer (CK, N and NK), the Olsen P concentration declined significantly (P<0.01) over time at the two sites. The Olsen P concentration decreased by 0.48~0.50 mg kg -1 a -1 at Gongzhuling and by 0.49~0.65 mg kg -1 a -1 at Harbin. But we cannot compare the Olsen P decrease at the two sites due to the difference of fertilization years. So, what is the situation of Olsen P decrease after 16-year at Harbin? Data showed that the Olsen P concentration of CK, N and NK decreased at a rate of approximately 0.50, 0.50 and 0.48 mg kg -1 a -1 at Gongzhuling, and at 1.17, 1.10 and 1.14 mg kg -1 a -1 at Harbin after the same 16 years' experiment. Generally, the Olsen P concentration increased over time at the two sites, and the correlation coefficients were significant (P<0.01) for this relationship. The order of the increase in the Olsen P concentration at the Gongzhuling site was NPKM>NP>NPK. After 16 years of fertilization at the Gongzhuling site, the NPK treatment had an Olsen P concentration that was 184% greater than that of the NK treatment, and the NPKM treatment showed an increase of 217% relative to the NPK treatment. The order of the increase in the Olsen P concentration at the Harbin site was NPKM>NPK>NP. After 31 years of fertilization at this site, the NPK treatment yielded an Olsen P concentration that was 249% greater than that of the NK treatment, while the addition of manure improved the soil Olsen P concentration by 8% (Fig 1). P balance in black soils The soil P content was depleted each year in the three no-P treatments at both sites. After the 16-and 31-year fertilization periods, the P contents of the Gongzhuling and Harbin sites were depleted by 245 and 518 kg ha -1 in the CK, 527 and 586 kg ha -1 in the N, and 585 and 648 kg ha -1 in the NK treatments, respectively. The P balances were -20.22, -47.20, and 778 kg ha -1 for the NP, NPK and NPKM treatments, respectively, after 16 years of P fertilization at Gongzhuling. At Harbin, 687, 656 and 894 kg ha -1 of P was accumulated after 31 years in the NP, NPK and NPKM treatments, respectively (Fig 2). The response of the change in the Olsen P concentrations to the P balance of the black soils The responses of the changes in the Olsen P concentrations to the P balances of the two black soils are shown in Fig 3. In the regression equation, x indicates the P balance of the soil, and y indicates the change in the soil Olsen P (ΔOlsen P) concentration. Thus, the slope of the regression equation represents a change in the Olsen P (mg kg -1 ) concentration per unit of P surplus or deficit (kg ha -1 P) [31]. A significant positive linear relationship was observed between the changes in the soil Olsen P concentration and P balance for all fertilization patterns except the NP and NPK treatments at Gongzhuling. The soil Olsen P concentration decreased by 2.97, 1.57 and 1.36 mg kg -1 for for each 100 kg ha -1 P deficit in the CK, N and NK treatments, respectively, at Gongzhuling. At Harbin, the Olsen P decreased by more than that observed at Gongzhuling, with values of 3.35, 2.43 and 1.39 mg kg -1 for the CK, N and NK treatments, respectively. In addition, the changes in the Olsen P concentrations for each 100 kg ha -1 P deficit were larger at Harbin than Gongzhuling. For each 100 kg ha -1 P surplus, the Olsen P concentration increased by 16.04 mg kg -1 under the NPKM treatment at Gongzhuling. The Olsen P concentration increased at the Harbin site in the following order: NPK>NPKM>NP (i.e. 7.75, 6.95, 4.80 mg kg -1 , respectively), and the NPKM value was considerably higher, for Gongzhuling than for Harbin. In addition, the increases in the Olsen P concentrations with each 1 kg ha -1 P for the P treatments were greater than the decreases in the treatments without P addition. Change of soil pH and organic matter in black soils Soil pH remained stable under the CK treatment, and declined under all fertilizer application treatments with experimental years due to N fertilization at the two sites. At Gongzhuling, the decrease value of pH was about 1.5 units for chemical fertilizer treatments and 0.3 units for NPKM after 16-year fertilization; at Harbin, the pH value declined about 1.2 units for all fertilizer treatments after 31-year fertilization. That means that chemical fertilizer plus manure (NPKM) slowed down the decrease of pH in comparison of NPK at Gongzhuling, but not for Harbin, which is due to the different amount and type of manure (Material and method) (Fig 4). Fig 5 shows the average level of soil organic matter after long term fertilizer at the two sites. After 16-year experiment, soil organic matter of NPKM was significant higher than other five treatments, and the NPKM significantly enhanced the soil organic matter level by 17.3% in comparison with NPK at Gongzhuling. For the site of Harbin, the lowest organic matter level was the CK treatment and the highest level was the NPKM treatment. There was no significant difference between NPK and NPKM. Discussion The Olsen P concentrations changed with year, fertilization and the P balance Without P fertilizer (CK, N and NK), the Olsen P concentration significantly (P<0.01) decreased at the two sites. Soil Olsen P concentration at Harbin decreased faster in comparison with Gongzhuling after the same 16 years' experiment. Colomb [32] suggests that in the absence of fertilizer, the conversation rate of soil available P from inorganic and organic P depends on the initial P level. Therefore, the more rapid decrease at Harbin in this study could be related to its higher initial Olsen P concentration (22.27 mg kg -1 ) compared with Gongzhuling (11.79 mg kg -1 ). This viewpoint was also expressed by Qu [8,9] who studied 11 typical Chinese soils in a long-term experiment and found that soils with higher initial Olsen P concentrations resulted in more rapid decreases in Olsen P. When P fertilizer was applied, the Olsen P concentration increased especially when chemical and manure fertilizers were used together. Similar results have been reported in other papers [33]. Negative P balances were observed in all treatments that did not receive any P fertilizer input (Fig 2), and the decreases in the soil Olsen P concentrations were significantly (P<0.05) correlated with the P balances at both sites (Fig 3). A decrease in the Olsen P decrease by each 100 kg ha -1 P balance was observed at Harbin (CK, N and NK) and Gongzhuling (CK, N and NK); a greater decrease occurred at Harbin for each of these treatments. This result likely occurred because of the greater initial Olsen P concentration at Harbin. In addition, the Harbin soil had lower clay content (12.9%), which presented a low soil P sorption capacity [34,35], compared with the Gongzhuling (32.1%) soil. However, Cao [16] proved that the soil clay content was significantly positively correlated with the change in of Olsen P across six long term experimental sites in China. This may be attributed to a decrease in phosphate run off as a result of higher clay content [36]. Generally, positive P balances are observed in most P application treatments [3,12], and the Olsen P concentration increases under a P surplus [11]. In this study, the Olsen P concentrations increased significantly as a result of a P surplus, except for the NP and NPK treatments at Gongzhuling (Fig 1). This result occurred because the P balances (Fig 2) of the NP and NPK treatments were nearly 0, and the Olsen P concentration also increased with the number of experimental years (Fig 1). In addition, the soil total P of these two treatments, which verified the result of the P balance, changed only a little (NP: an increase of 5% and NPK: a decrease of 11%) in comparison with the other four treatments at the 16-year experiment. This result potentially occurred because when there was no P surplus, various forms of residual soil P, e.g., Ca-P, Fe-P, Al-P could interchange and transferred to Olsen P through a dynamic P transformation [33]. These dynamic processes include the transformation of the inorganic P fractions to available P through desorption and dissolution, and the organic P fractions to the available P fraction by mineralization [1,37]. The inorganic and organic P fractions should to be analyzed to explain the difference in the Olsen P change by each 100 kg ha -1 P balance. Relationships between the changes in the soil Olsen P by each 100 kg ha -1 P balance and the P activation coefficient Within a site, the change in the soil Olsen P caused by each 100 kg ha -1 P balance for the different fertilizer patterns was affected by the soil properties, including the soil P activation coefficient (PAC), soil organic matter and pH [18,38]. The proportion of the soil Olsen P relative to the total P (PAC) indicates the capacity of the soil to bind P in relatively soluble fractions [18]. Greater PAC values indicate that the soil total phosphorus is more easily converted to Olsen P. The PAC value of the P treatments was much greater than that of the no P treatments (Fig 6). This could verify that the increase in Olsen P caused by each 100 kg ha -1 P surplus was larger than the decrease in Olsen P caused by each 100 kg ha -1 P depletion. The reason is that the P application can result in a greater P desorption ability compared with those treatments where P is not applied [39,40]. Selles [41] also found that the increase in Olsen P by each 100 kg ha -1 P surplus was substantially greater than the decrease in Olsen P by each 100 kg ha -1 P depletion in no P treatments in two wheat production systems in a 39-year study in Canada. Under the combined application of organic manure and chemical fertilizer in this study, the soil PAC was 5.8% at Harbin and 9.9% at Gongzhuling, and these values differed significantly. This result is similar to the observed changes in the soil Olsen P by each 100 kg ha -1 P balance between the two sites. The statistical data (Fig 7a) showed that the changes in the soil Olsen P by each 100 kg ha -1 P balance were significantly correlated with the PAC (r = 0.99, P<0.01). Relationships between changes in soil Olsen P by each 100 kg ha -1 P balance, soil organic matter and pH The different fertilization patterns had obvious effects on soil organic matter level [42], and this viewpoint is similar with us ( Fig 5). The organic matter play an important role on P availability by decreasing the P adsorption due to the competing adsorption sites by organic anion and dissolving the mineral associated P by low-molecular-weight organic acids [24]. In this study, the statistical data (Fig 7b) showed that changes in the soil Olsen P by each 100 kg ha -1 P balance were strongly related to the soil organic matter (r = 0.91, P<0.01) across all treatments at the two sites. Shen [43] found that the change in the soil Olsen P by each 100 kg ha -1 P balance in the NPK treatment was lower than that of the NPKM treatment at three long term experimental sites (Changping, Yangling and Zhengzhou) in China. However, in this paper, compared with NPK, the NPKM treatment significantly increased the Olsen P (Fig 1) and resulted in P accumulation at Harbin (Fig 2), but did not affect the value of the changes in the soil Olsen P by each 100 kg ha -1 P balance (Fig 3), Pei [17] obtained the same result on black loess soil. In addition, the change in the soil Olsen P by each 100 kg ha -1 P balance for the chemical fertilizer plus manure at Gongzhuling was much greater than Harbin (Fig 3) and Pingliang [17]. It can be concluded that chemical fertilizer plus manure does not always enhance the changes in the soil Olsen P by each 100 kg ha -1 P balance compared with NPK, and the situation depends on the P availability of the manure. In this paper, the organic P of horse dung (Harbin) is difficult to activate, and pig manure (Gongzhuling) contains highly active organic P according the study [44]. That is to say, if the organic P in manure mineralizes readily, the soil Olsen P will increase rapidly. Future research should focus on the organic P activity of manure. During the long term experiment, soil pH was often influenced by fertilizations. The pH values for N and NK treatments reduced in comparison with CK at the two sites (Fig 4), as urea behaves similar to ammonia and H + ions are produced during the ammonication-nitrication process [45]. Lower pH value can promote more dissolution of sparingly P into Olsen P [23]. This could explain why the change in soil Olsen P by each 100 kg ha -1 P balance decreased less Relationship of Olsen P and P Balance in the N and NK treatments than in the CK treatment. For the treatment of NPKM, the humus acid of manure can prevent soil from acidifying due to its buffering action [24]. So the average pH value in the NPK treatment (6.16) during the previous 9 years was lower than that in NPKM (6.24) treatment. More P activation at lower pH may be one of the reasons that NPK expressed higher changes in the soil Olsen P concentration by each 100 kg ha -1 P balance than NPKM at Harbin site. Meanwhile, Zhang [46] showed that the acid phosphatase contents that were related to soil pH in the N and NK treatments were higher than those measured in the CK treatment. This can potentially explain the smaller decrease in the soil Olsen P concentration changes by each 100 kg ha -1 P balance in the N and NK treatments relative to the CK treatment. Acid phosphatase can slow the decrease in Olsen P because acid phosphatase is an important root exudate that hydrolyzes organic P [47]. Conclusion 1. In this study, average Olsen P concentrations in the black soils at Gongzhuling (16-year) and Harbin (31-year) decreased by 0.49 and 0.56 mg kg -1 a -1 without P addition and increased by 3.17 and 1.78 mg kg -1 a -1 with P fertilization. 2. Under an average deficit of 100 kg ha -1 P, the soil Olsen P concentration at both sites decreased by 1.36~3.35 mg kg -1 in the treatments without P addition and increased by 4.80~16.04 mg kg -1 in the P treatments with 100 kg ha -1 of P accumulation. 3. In addition, the soil with the higher initial Olsen P content and lower clay content resulted in more rapid decreases in Olsen P when P was not added; the P fertilization models with Fig 7. Relationships between the of PAC, soil organic matter and changes in the soil Olsen P in black soils under long-term fertilization. Note: To distinguish the no P and P addition treatments, the changes in soil Olsen P by each 100 kg ha -1 P balance of no P treatments (CK, N and NK) were defined to the negative values in this figure. doi:10.1371/journal.pone.0131713.g007 higher soil organic matter lower pH resulted in more rapid increase rates of Olsen P by 100 kg ha -1 P balance.

v3-fos

2016-05-12T22:15:10.714Z

2015-08-07T00:00:00.000Z

14747917

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Molecular and Cytogenetic Characterization of Wild Musa Species The production of bananas is threatened by rapid spreading of various diseases and adverse environmental conditions. The preservation and characterization of banana diversity is essential for the purposes of crop improvement. The world's largest banana germplasm collection maintained at the Bioversity International Transit Centre (ITC) in Belgium is continuously expanded by new accessions of edible cultivars and wild species. Detailed morphological and molecular characterization of the accessions is necessary for efficient management of the collection and utilization of banana diversity. In this work, nuclear DNA content and genomic distribution of 45S and 5S rDNA were examined in 21 diploid accessions recently added to ITC collection, representing both sections of the genus Musa. 2C DNA content in the section Musa ranged from 1.217 to 1.315 pg. Species belonging to section Callimusa had 2C DNA contents ranging from 1.390 to 1.772 pg. While the number of 45S rDNA loci was conserved in the section Musa, it was highly variable in Callimusa species. 5S rRNA gene clusters were found on two to eight chromosomes per diploid cell. The accessions were genotyped using a set of 19 microsatellite markers to establish their relationships with the remaining accessions held at ITC. Genetic diversity done by SSR genotyping platform was extended by phylogenetic analysis of ITS region. ITS sequence data supported the clustering obtained by SSR analysis for most of the accessions. High level of nucleotide diversity and presence of more than two types of ITS sequences in eight wild diploids pointed to their origin by hybridization of different genotypes. This study significantly expands the number of wild Musa species where nuclear genome size and genomic distribution of rDNA loci is known. SSR genotyping identified Musa species that are closely related to the previously characterized accessions and provided data to aid in their classification. Sequence analysis of ITS region provided further information about evolutionary relationships between individual accessions and suggested that some of analyzed accessions were interspecific hybrids and/or backcross progeny. The production of bananas is threatened by rapid spreading of various diseases and adverse environmental conditions. The preservation and characterization of banana diversity is essential for the purposes of crop improvement. The world's largest banana germplasm collection maintained at the Bioversity International Transit Centre (ITC) in Belgium is continuously expanded by new accessions of edible cultivars and wild species. Detailed morphological and molecular characterization of the accessions is necessary for efficient management of the collection and utilization of banana diversity. In this work, nuclear DNA content and genomic distribution of 45S and 5S rDNA were examined in 21 diploid accessions recently added to ITC collection, representing both sections of the genus Musa. 2C DNA content in the section Musa ranged from 1.217 to 1.315 pg. Species belonging to section Callimusa had 2C DNA contents ranging from 1.390 to 1.772 pg. While the number of 45S rDNA loci was conserved in the section Musa, it was highly variable in Callimusa species. 5S rRNA gene clusters were found on two to eight chromosomes per diploid cell. The accessions were genotyped using a set of 19 microsatellite markers to establish their relationships with the remaining accessions held at ITC. Genetic diversity done by SSR genotyping platform was extended by phylogenetic analysis of ITS region. ITS sequence data supported the clustering obtained by SSR analysis for most of the accessions. High level of nucleotide diversity and presence of more than two types of ITS sequences in eight wild diploids pointed to their origin by hybridization of different genotypes. This study significantly expands the number of wild Musa species where nuclear genome size and genomic distribution of rDNA loci is known. SSR genotyping identified Musa species that are closely related to the previously characterized accessions and provided data to aid in their classification. Sequence analysis of ITS region provided further information about evolutionary relationships between individual accessions and suggested that some of analyzed accessions were interspecific hybrids and/or backcross progeny. Introduction Bananas and plantains (Musa spp.) are one of the most important food crops with the global annual production exceeding 130 Mt (faostat.fao.org). They are grown mainly by smallholder farmers for local consumption and only about 10% of the world's production is exported. Most of the cultivated bananas are parthenocarpic triploid clones (although diploids and tetraploids also occur), which originated from natural intra-and interspecific hybridizations between various subspecies of M. acuminata (A genome) and M. balbisiana (B genome) [1] within the genus Musa. The triploids are then classified as AAA, AAB and ABB and include a range of varieties of dessert bananas, cooking bananas and plantains, which provide essential nutrition for millions of people in the humid tropics. Minor group of cultivated bananas derived from the hybridization between the A, B and one of the other recognized Musa genomes, the S genome and T genome (M. schizocarpa and M. textilis, respectively) [2,3]. The production of bananas is threatened by various diseases, pests and adverse environmental conditions. This imposes the need for varietal testing and crop improvement supported by preservation of characterized banana diversity. The global Musa collection is maintained at the Bioversity International Transit Centre (ITC) hosted by the Katholieke Universiteit Leuven in Belgium [4]. The ITC collection was originally established for long term conservation of diploid, triploid and tetraploid edible cultivars, but eventually it started to be expanded by different wild species and subspecies. Currently, the collection contains more than 1,500 accessions in tissue culture. Newly introduced accessions of wild Musa species are a significant source of material to study diversity in Musa on a broader scale. The difficulties with the classification of new cultivars and newly discovered wild Musa species using morphological descriptors call for characterization of Musa accessions using stable and reproducible characters. One of the basic characteristics of a species is its nuclear genome size. In earlier studies, the nuclear genome size was estimated mainly on edible bananas and their wild ancestors. A genome size of 600-650 Mbp was determined in M. acuminata and 550 Mbp in M. balbisiana, clearly discriminating both species [14][15][16]. Bartoš et al. [9] extended the knowledge of nuclear DNA content by representatives of former sections Rhodochlamys, Australimusa and Callimusa. Flow cytometric analysis showed that 2C nuclear DNA contents of Eumusa and Rhodochlamys accessions were overlapping, ranging from 1.130 to 1.377 pg in Eumusa and from 1.191 to 1.299 pg in Rhodochlamys. Species belonging to section Australimusa had 2C nuclear DNA content between 1.435 and 1.547 pg. M. beccarii, the only studied representative of Callimusa section, had the highest 2C nuclear DNA content (1.561 pg). However, only nineteen accessions were included in that study and the knowledge about genome size remained limited, especially in the section Callimusa. The number and morphology of chromosomes describe a karyotype, another important characteristic of a species. In case of the genus Musa, chromosome number determines sectional classification of individual species. More detailed cytogenetic studies are, however, complicated by the small size of chromosomes, their morphological similarity and lack of chromosome-specific landmarks. To date, identification of all chromosomes within the karyotype is not possible. The only sequences cytogenetically mapped to chromosomes of a wider range of Musa accessions are ribosomal RNA (rRNA) genes. While the number of 45S rDNA loci was found conserved within individual sections, the number of 5S rDNA loci ranged from 4 to 8 per mitotic metaphase plate and varied within sections and even within different accessions of a single species [9,[16][17][18]. Similarly to genome size, genomic distribution of rRNA genes was studied mainly in M. acuminata, M. balbisiana and some cultivated varieties. Unlike the methods mentioned above, genotyping using DNA markers provides higher resolution and is suitable for analysis of genetic diversity and establishment of phylogenetic relationships. Different types of molecular markers, such as RAPDs [19], RFLPs [20,21], AFLPs [22,23] or DArT markers [24], were used in diversity studies and molecular characterization of Musa. In 2011, a standardized microsatellite-based genotyping platform for molecular characterization of Musa germplasm was established [13]. Microsatellites (SSRs) are popular molecular markers because of their high abundance in the genome, co-dominant inheritance, extent of allelic diversity, good reproducibility and the potential for high-throughput analysis and automatisation. They proved to be useful in molecular genotyping of many economically important crops [25][26][27]. The microsatellite genotyping platform of Christelová et al. [13] is based on 19 microsatellite loci [28][29][30], which are scored using fluorescently labelled primers and high-throughput, high-resolution capillary electrophoresis. The platform enables discrimination between individual species, subspecies and subgroups of Musa accessions and is suitable for characterization of unknown accessions. Based on the results of Christelová et al. [13], the Musa Genotyping Centre was established at the Institute of Experimental Botany in Olomouc (Czech Republic) [31] under the auspices of Bioversity International. The database of reference SSR profiles they generate is enlarged with every new accession passing through the pipeline and consequently improves the grouping and enhances the probability of identifying the closest relative or an exact match for unknown accessions. Increasing the number of analysed wild species would give more accuracy to the grouping of the genus Musa. When SSR genotyping provides incongruent results, or in case there is a need to support putative hybrid character of particular Musa accessions, the ITS sequence analysis can be used. The analysis of internal transcribed spacer region (ITS1-5.8S-ITS2) of nuclear ribosomal DNA provides additional information on genetic diversity and evolutionary relationships among individual accessions. The ITS region has been one of the most widely used markers in phylogenetic studies of flowering plants [32] and has recently been successfully employed in phylogenetic reconstruction in the family Musaceae [10,11,33]. It has been shown that ITS locus can be used for verification of genome constitution of inter-and intraspecific banana hybrids [33]. The aim of this work was to characterize a set of 21 Musa accessions which were newly introduced into the ITC collection from Helsinki University Botanic garden with a goal to increase the knowledge about the genetic diversity of wild Musa species. Most of the Musa accessions have been analyzed for the first time. Nuclear genome size, chromosome number and genomic distribution of rDNA were determined in individual accessions to shed light on their genome structure and evolution. Molecular characterization was performed using SSR genotyping platform and was extended by the analysis of ITS sequence region to verify a putative hybrid origin of some accessions. The analysis was also used to support incongruous results of SSR genotyping and to strengthen the previous knowledge on phylogenetic relationships within the Musaceae family. Plant Material and Genomic DNA Extraction In vitro rooted plants of 21 Musa accessions (S1 Table; basic description of accessions available at [5] were obtained from the International Transit Centre (ITC, Katholieke Universiteit, Leuven, Belgium). The plants were transferred to soil and maintained in a greenhouse. Fresh unopened (cigar) leaves were harvested, their segments lyophilized and maintained at room temperature until use. Genomic DNA of all Musa species used for the SSR genotyping and ITS analysis was isolated from lyophilized leaves using the NucleoSpin PlantII kit (Macherey-Nagel GmbH & Co. KG, Düren, Germany) following the manufacturer's recommendations. Estimation of Genome Size Nuclear genome size was estimated according to Bartoš et al. [9]. Approximately 50 mg of a young Musa leaf and 10 mg of a soybean leaf (Glycine max L. cv. Polanka, 2C = 2.5 pg DNA) which served as internal standard [14] were used for sample preparation. Suspensions of cell nuclei were prepared by simultaneous chopping of leaf tissues of Musa and Glycine in a glass Petri dish containing 500 μl Otto I solution (0.1 M citric acid, 0.5% v/v Tween 20). Crude homogenate was filtered through a 50 μm nylon mesh. Nuclei were then pelleted (300 g, 5 min) and resuspended in 300 μl Otto I solution. After 1 hour incubation at room temperature, 900 μl Otto II solution (0.4 M Na 2 HPO 4 ) [34] supplemented with 50 μg/ml RNase, 50 μg/ml propidium iodide and 3 μl/ml 2-mercaptoethanol, were added. Samples were analyzed using Partec PAS flow cytometer (Partec GmbH, Münster, Germany) equipped with 488-nm argon laser. At least 5,000 nuclei were analyzed per sample. Three individuals were analyzed in each accession, and each individual was measured three times on three different days. Nuclear DNA content was then calculated from individual measurements following the formula: 2C nuclear DNA content ½pg ¼ 2:5 x G 1 peak mean of Musa=G 1 peak mean of Glycine Mean nuclear DNA content (2C) was then calculated for each plant. Genome size (1C value) was then determined considering 1 pg DNA equal to 0.978×10 9 bp [35]. Statistical analysis was performed using NCSS 97 statistical software (Statistical Solutions Ltd., Cork, Ireland). One-way ANOVA and a Bonferoni's (All-Pairwise) multiple comparison test were used for analysis of variation in nuclear DNA content. The significance level α = 0.01 was used. Spearman's correlation analysis was used to test the relationship between chromosome number and nuclear DNA content of studied accessions. SSR Genotyping The standardized platform for molecular characterization of Musa germplasm [12] was used to genotype all 21 Musa accessions. The system is based on 19 microsatellite loci that are scored after the PCR with fluorescently labeled primers and capillary electrophoretic separation with internal standard (GeneScan 500 LIZ size standard, Applied Biosystems). The PCR products were multiplexed prior to the separation and loaded onto the automatic 96-capillary ABI 3730xl DNA Analyzer. Electrophoretic separation and signal detection was carried out with default module settings. The resulting data were analyzed and called for alleles using GeneMarker v1.75 (Softgenetics), manually checked and implemented into the marker panels [12]. The SSR profiles of newly analyzed accessions were integrated to the binary table of SSR profiles obtained in the work of Christelová et al. [12] and analyzed together. The genetic similarity matrices based on Nei´s genetic distance coefficient [36] were calculated using PowerMarker v3.25 [37] and the unweighted pair-group method with arithmetic mean (UPGMA) [38] was used to assess the relationship between individual genotypes. The results of UPGMA cluster analysis were visualized in a form of a tree using FigTree v1.4.0 [39]. PCR products were purified using ExoSAP-IT (USB, Cleveland, OH, USA) according to the manufacturer's instructions, cloned into TOPO vector, and transformed into E. coli electrocompetent cells (Invitrogen Life Technologies, Carlsbad, USA). For each accession, at least 28 cloned PCR products were sequenced. Sequencing was carried out using the BigDye Terminator v3.1 Cycle Sequencing kit (Applied Biosystems, Foster City, USA) according to the manufacturer's instructions and run on ABI 3730xl DNA analyzer (Applied Biosystems, Foster City, USA). Nucleotide sequences were edited using Staden Package [41]. Sequence boundaries of the spacers were assessed and phylogenetic relationships analysis was performed according to Hřibová et al. [33]. Sequence diversity was identified using DnaSAM program [42] with 1000 simulations. SplitsTree4 v4.1.11 [43] was used to construct phylograms based on the Jukes-Cantor model. Non-parametric bootstrapping with 1000 pseudoreplicates was performed to assess the nodal support. Phylogenetic trees were drawn and edited using FigTree program [39]. Chromosome Preparations and Chromosome Counting Mitotic metaphase spreads were prepared according to Doleželová et al. [17]. Actively growing root tips were pre-treated in 0.05% (w/v) 8-hydroxyquinoline for 3 hrs at room temperature and then fixed in 3:1 ethanol: acetic acid overnight. Fixed roots were washed in a solution of 75 mM KCl and 7.5 mM EDTA (pH 4) and meristem tips were digested in a mixture of 2% (w/v) pectinase and 2% (w/v) cellulase in 75 mM KCl and 7.5 mM EDTA (pH 4) for 90 min at 30°C. Protoplast suspension was then filtered through a 150 μm nylon mesh and pelleted. The pellet was resuspended in 75 mM KCl and 7.5 mM EDTA (pH 4) and incubated for 5 min at room temperature. After pelleting, the protoplasts were washed three times with 70% ethanol. Five μl of the suspension were dropped onto a slide and shortly before drying out, 5 μl of 3:1 fixative were added to the drop to induce protoplast bursting. Finally, the slide was rinsed in 100% ethanol and air-dried. For chromosome counting, the preparations were stained with DAPI (Vectashield Mounting Medium with DAPI; Vector laboratories). Slides were examined with Olympus AX70 fluorescence microscope. Images were captured using a cooled high-resolution black and white camera and processed using MicroImage software (Olympus, Tokyo, Japan). In each plant, two slides were observed, each with at least five metaphase plates. Fluorescence In Situ Hybridization (FISH) Probes for 45S rDNA and 5S rDNA were prepared by labeling Radka1 DNA clone (45S rDNA) and Radka2 DNA clone (5S rDNA) [44] with digoxigenin-11-dUTP or biotin-16-dUTP (Roche Applied Science). Both probes were labeled by PCR using M13 forward and reverse primers (Invitrogen). Hybridization mixture consisting of 50% formamide, 10% dextran sulfate in 1×SSC and 1 μg/ml of each labeled probe was added onto slides and denatured at 80°C for 3 min. The hybridization was carried out at 37°C overnight. The sites of probe hybridization were detected using anti-digoxigenin-FITC (Roche Applied Science) and streptavidin-Cy3 (Vector Laboratories, Burlingame, USA), and the chromosomes were counterstained with DAPI. The slides were examined with Olympus AX70 fluorescence microscope and the images of DAPI, FITC and Cy-3 fluorescence were acquired separately with a cooled high-resolution black and white CCD camera. The camera was interfaced to a PC running the MicroImage software (Olympus, Tokyo, Japan). At least ten complete metaphases were examined for every accession. Estimation of Genome Size The amount of nuclear DNA was estimated after flow cytometric analysis of propidium iodidestained nuclei. All analyses resulted in histograms of relative DNA content with two dominant peaks corresponding to G 1 nuclei of Musa and Glycine, the latter serving as internal reference standard (Fig 1). The 2C nuclear DNA content determined based on the ratio of G 1 peaks positions ranged from 1.217 to 1.772 pg ( Table 1). The differences between the accessions from section Musa were statistically significant with 2C DNA content ranging between 1.217 and 1.315 pg. Much higher interspecific variation (27.5%) of 2C DNA content was observed within the section Callimusa (2C = 1.390-1.772 pg). Bonferoni's (All-Pairwise) multiple comparison test revealed twelve groups based on the differences in the nuclear DNA content ( Table 1) Spearman's correlation coefficient showed a strong negative correlation (r = -0.88) between 2n chromosome number and 2C nuclear DNA content among the Musa accessions. The same trend (r = -0.85) was observed when the results of Bartoš et al. [9] were included in the analysis (Fig 2). On the other hand, after including representatives of two other genera of the family Musaceae, Ensete gilletii [9] and Musella lasiocarpa (not published) the strong negative correlation between nuclear DNA content and chromosome number was no longer observed (r = -0.63). Chromosome Counting and Cytogenetic Mapping of rRNA Genes Protoplast dropping technique was used to prepare metaphase spreads for chromosome counting and localization of rRNA genes. All accessions were confirmed to be diploid and their chromosome numbers corresponded to section-specific classification ( Table 1) FISH with probes for 45S rDNA revealed distinct hybridization sites on one chromosome pair in the secondary constriction in all accessions of the section Musa (Table 1, Fig 3). Table 1). Two of these signals were observed in the secondary constriction of one chromosome pair, while the other sites of probe hybridization were localized in interstitial chromosome regions. A significantly higher variation was detected in the number of 5S rDNA loci (Table 1). In a majority of accessions from the Musa section, 5S rDNA sites were localized on two or three chromosome pairs. Three signals were observed on chromosomes of M. mannii (ITC.1574, Fig 3B) and seven signals per metaphase plate were detected in M. rosea x siamensis (ITC.1592, Fig 3C). Callimusa species contained 5S rDNA gene clusters on two to eight chromosomes per metaphase plate. In M. beccarii var. beccarii (ITC.1516), M. beccarii var. hottana (ITC.1529) and M. borneensis (ITC.1531), two of the 5S rDNA sites co-localized with interstitially localized 45S rDNA genes. SSR Genotyping Molecular characterization of the newly introduced ITC accessions based on SSR markers included inspection of their clustering pattern within the reference set of diploid entries used in the study of Christelová et al. [13]. The UPGMA cluster analysis based on the Nei [37] genetic distance resulted in relatively clear grouping of genotype groups and subgroups (Fig 4). Inclusion of the new accessions did not change the overall grouping of the species as compared to the results of Christelová et al. [13]. Most of the entries under this study clustered with the reference accessions as shown in our previous study [12] in accordance to their expected classification based on plant morphology. Newly introduced accessions belonging to the Musa section were grouped within the cluster A comprising other species from section Musa. The two accessions described as M. itinerans (ITC.1526 and ITC.1571) and M. rubinea (ITC.1518) formed a separate clade within the cluster A. Accessions described as Callimusa species were grouped within the cluster B together with reference accessions from this section. The allele sizes of analyzed accessions which were converted into binary code and added to the previous set of analyzed diploid Musa accessions [12] are available on the web pages of the Musa Genotyping Centre [31]. (Table 2, S2 Table). GC content of ITS1 varied from 57.41 to 65.02% and was slightly Identification of rDNA Pseudogenes and Phylogenetic Analysis The secondary structure of ITS2 and 5.8S rDNA sequence regions was reconstructed for all accessions under study. ITS2 sequences formed specific four-helices structure with typical pyrimidine-pyrimidine bulge in helix II and the most conserved primary sequence included the TGGT in the helix III. Secondary structure of 5.8S rDNA sequence was reconstructed under specific settings for base pairing as described by Hřibová et al. [33]. Moreover, 5.8S rDNA sequences were checked for the presence of three conserved motives [45]. The nucleotide changes in conserved motives of 5.8S rDNA of analyzed accessions, the information on GC content, presence of conserved motives in the 5.8S rDNA sequence and ability of ITS2 and 5.8S rDNA sequence to fold into a conserved secondary structure enabled identification of putative pseudogenes ( Table 2). As shown in Table 2, more than half of the analyzed accessions contained at least two types of ITS sequences. On the contrary, M. rosea x siamensis ITC.1598 which has been described as hybrid clone had only one type of ITS sequence region. With the aim to support clustering based on SSR markers, phylogenetic analysis of the ITS sequence region was done. Dataset for this analysis comprised ITS sequences of the Musa spp. previously described by Hřibová et al. [33] and ITS types of the 21 studied accessions, excluding the putative pseudogenic ITS types (S1 Fig). Inclusion of the new accessions did not change the overall grouping of the species as compared to the results of Hřibová et al. [33]. Phylogenetic analysis of ITS region supported the clustering obtained by SSR analysis for majority of the studied accessions. Close relationships of M. itinerans and M. rubinea accessions was supported by SSR as well as ITS analysis. On the other hand, ITS analysis indicated close relationships of these accessions to M. balbisiana, but this observation was not supported by the SSR analysis. Similarly, close relationships of M. yunnanensis (ITC.1573) and M. rosea hybrid (ITC.1598) to M. ornata and M. velutina obtained after SSR analysis was not supported by ITS analysis. Finally, different clustering was observed for accession Musa x fennicae (Musa siamensis (male) x Musa rosea (female) (ITC.1522) which is found in the cluster containing ornamental bananas (former Rhodochlamys section) in the SSR cladogram while using ITS analysis, all ITS sequence types including putative pseudogenes are clustered together with AA genotypes. In our previous study [33], we have shown that, with certain caution, pseudogenic rDNA sequences can be used to identify parental genotypes of hybrid clones. Considering the fact that more than a half of the analyzed accessions contained at least two types of ITS sequences, phylogenetic reconstruction with ITS sequences including putative pseudogenes was done (S2 Fig). As it is visible from the ITS clustering, the genome of Musa yunnanensis (ITC.1573) contains divergent ITS sequence types which clustered together with ornamental bananas as well as with AA genotypes. Similar observation was obtained also for genotype described as hybrid clones of ornamental banana genotypes-M. rosea x siamensis (ITC.1592), while hybrid clone Musa x fennicae (Musa siamensis (male) x Musa rosea (female) (ITC.1522) contained only ITS sequence types which clustered together with the AA genotypes (see above). Nuclear DNA Content and Distribution of rDNA Most of the knowledge on nuclear genome size and genomic distribution of rDNA loci in banana comes from the analysis of triploid cultivars and their wild ancestors [14-16, 17, 18, 46]. Only the study of Bartoš et al. [9] included a wider range of Musa species and provided the first complex picture of the whole genus. Our study significantly expands the number of wild Musa species where these key characteristics of nuclear genome are described. The diversity in genome size observed in species belonging to the section Musa is in line with previous studies [9,[14][15][16]46] which estimated 2C nuclear DNA content ranging from 1.108 pg in M. balbisiana to 1.377 pg in M. schizocarpa. The genome size of M. laterita and M. mannii were determined by Bartoš et al. [9]. However, in both cases, different ITC accessions (ITC.0627 and ITC.1411, respectively) were used. While the difference in 2C nuclear DNA content estimates between both accessions (ITC.1411 and ITC.1574) of M. mannii is negligible (1.0%), there is much higher difference (7.7%) between M. laterita accessions (ITC.0627 and ITC.1575). This observation suggests that accessions ITC.0627 and ITC.1575 could represent different varieties of M. laterita. Genomic distribution of 45S and 5S rDNA clusters in Musa accessions as observed in this study is similar to the results obtained by Bartoš et al. [9] and together with overlapping genome size values brings further evidence about the close relationships between representatives of former sections Eumusa and Rhodochlamys. The traditional division into sections Eumusa and Rhodochlamys was mainly based on morphological characters. The separation of these sections was however doubtful, because morphological differences were difficult to detect in some species and interspecific hybridization was frequent [6,47]. Our findings, as well as previous analyses based on different molecular markers [8,10,21,23], support the recent merger of sections Eumusa and Rhodochlamys into the section Musa. The presence of odd numbers of 5S rDNA loci has been previously observed in some edible cultivars and wild species [9,17] and could be explained by structural chromosome heterozygosity and/or as a result of hybridization between two genotypes bearing different 5S rDNA sites. However, it is also possible that one of 5S rDNA loci contained a lower number of repeat units and the resulting signal was below the detection limit of FISH. The representatives of the section Callimusa showed high variation in nuclear genome size as well as in the number of rDNA loci and were clearly discriminated from the accessions of the section Musa. For M. borneensis (ITC.1531), the highest nuclear DNA content (2C = 1.772 pg) known for diploid Musa species was determined. The increased genome size was accompanied by a higher number of 45S and 5S rDNA loci in comparison with other Callimusa accessions. Until now, the largest genome size was detected in M. beccarii [9,48], which has also been characterized by more abundant distribution of rRNA genes. The present estimates of genome sizes as well as chromosome number and distribution of rDNA loci in both M. beccarii varieties are in line with previous investigations [9,48]. An interesting outcome of this study is the observation of a negative correlation between the basic chromosome number (x) and nuclear genome size (1C), which became evident in this study after a wider range of Musa species was analyzed. This trend could be explained by the evolution from a common ancestor by chromosome fission accompanied by DNA loss. This hypothesis is in line with Simmonds [49], who speculated that the lower chromosome number [50] suggested that Ensete glaucum and M. beccarii are ancestral forms of Ensete and Musa with a common ancestor that is yet to be established and the ancestral chromosomal number of both genera is x = 9. On the other hand, if this hypothesis was true, representatives of the genera Ensete and Musella would be expected to have a genome size comparable to that of and other Callimusa species. A more extensive study of the karyotype evolution in the family Musaceae will be necessary to explain this "the less chromosomes, the larger genome" trend emerging in the genus Musa, but not observed in other genera of the family. SSR and ITS Analysis SSR analysis provided important information about the genomes of 21 accessions of wild Musa species, which were genotyped using molecular markers for the first time. The grouping of the accessions within the diploid reference set was revealed by the UPGMA cluster analysis. In most cases, the results of this grouping (Fig 3) were consistent with the characterization based on traditional morpho-taxonomic classification. Apart from better characterization of the wild Musa species, the SSR profiles obtained in this work expand the database of reference SSR profiles and thus improves the grouping and enhances the probability of identifying the closest relative or an exact match for unknown accessions. Short length, utilization of highly conserved primers and relatively fast evolution of internal transcribed spacers ITS1 and ITS2 as compared to rRNA genes, made the ITS region one of the most popular markers in phylogenetic studies. The first detailed information about the structure and diversity of ITS region in the genus Musa was provided by Hřibová et al. [33], while the work of Christelová et al. [12] showed the usefulness of the ITS for further analysis of accessions which give incongruous results with SSRs. High level of nucleotide diversity and presence of more than two types of ITS1-5. The close relationship of M. itinerans to B genome representatives observed after ITS analysis is in agreement with the study of Liu et al. [11]. This relationship was not supported by the SSR analysis. It is, however, possible that the grouping of some species will change after more representatives from both sections pass through the SSR genotyping pipeline. In a similar way, we have observed discrepancies in the position of M. yunnanensis (ITC.1573) and M. rosea hybrid (ITC.1598), as well as Musa x fennicae (Musa siamensis (male) x Musa rosea (female) (ITC.1522) in the tree constructed from SSR and ITS data (see above ; Fig 4, and S1 and S2 Figs). The ITS analysis indicates that the M. yunnanensis accessions included in our study originated from hybridization of different genotypes (subspecies?) ( Table 2), while the presence of only one ITS type sequence in the accession labeled as M. rosea hybrid (ITC.1598) does not support its hybrid character. In Musa x fennicae (Musa siamensis (male) x Musa rosea (female) (ITC.1522), divergent types of ITS sequences were identified but all of them were related to AA genotypes, while SSR analysis showed close relationships of this clone with ornamental bananas (genotypes of former Rhodochlamys section). These observed discrepancies could be a consequence of dominance of one type of rDNA sequence in hybrids, which may lead to complete homogenization of rDNA locus originating from the second parent [51][52][53]. Our results confirm the usefulness of SSR markers for molecular characterization of unknown accessions of Musa [12]. As the SSR genotyping is based on scoring alleles, it may not be appropriate for diversity and phylogenetic inference estimation in case of inter-specific hybrids and their backcross progenies [33]. Thus, we performed a detailed analysis of the nucleotide composition and structure of the ITS region and showed that some of the wild diploids contained polymorphic ITS regions. Moreover, in silico analysis of the ITS sequences indicated the presence of putative pseudogenic ITS types. These observations indicate that some of the analyzed accessions of wild Musa species originated from hybridization between different genotypes within a species or between putative subspecies [33,54].

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Temporal analysis reveals a key role for VTE5 in vitamin E biosynthesis in olive fruit during on-tree development The aim of this work was to generate a high resolution temporal mapping of the biosynthetic pathway of vitamin E in olive fruit (Olea europaea cv. “Koroneiki”) during 17 successive on-tree developmental stages. Fruit material was collected from the middle of June until the end of January, corresponding to 6–38 weeks after flowering (WAF). Results revealed a variable gene regulation pattern among 6–38 WAF studied and more pronounced levels of differential regulation of gene expression for the first and intermediate genes in the biosynthetic pathway (VTE5, geranylgeranyl reductase, HPPD, VTE2, HGGT and VTE3) compared with the downstream components of the pathway (VTE1 and VTE4). Notably, expression of HGGT and VTE2 genes were significantly suppressed throughout the developmental stages examined. Metabolite analysis indicated that the first and intermediate stages of development (6–22 WAF) have higher concentrations of tocochromanols compared with the last on-tree stages (starting from 24 WAF onwards). The concentration of α-tocopherol (16.15 ± 0.60−32.45 ± 0.54 mg/100 g F.W.) were substantially greater (up to 100-fold) than those of β-, γ-, and δ-tocopherols (0.13 ± 0.01−0.25 ± 0.03 mg/100 g F.W., 0.13 ± 0.01−0.33 ± 0.04 mg/100 g F.W., 0.14 ± 0.01−0.28 ± 0.01 mg/100 g F.W., respectively). In regard with tocotrienol content, only γ-tocotrienol was detected. Overall, olive fruits (cv. “Koroneiki”) exhibited higher concentrations of vitamin E until 22 WAF as compared with later WAF, concomitant with the expression profile of phytol kinase (VTE5), which could be used as a marker gene due to its importance in the biosynthesis of vitamin E. To the best of our knowledge, this is the first study that explores the complete biosynthetic pathway of vitamin E in a fruit tree crop of great horticultural importance such as olive, linking molecular gene expression analysis with tocochromanol content. INTRODUCTION Olive tree products are essential elements of Mediterranean diet (Ziogas et al., 2010;Anastasopoulos et al., 2011). Olive fruit is highly enriched in antioxidants such as vitamin E, carotenoids, and phenolic compounds (Aliakbarian et al., 2009;Muzzalupo et al., 2011;Goulas et al., 2012), which are known to provide several health-promoting benefits and reduce the risk of chronic diseases (Aliakbarian et al., 2009). Despite its relatively small fruit size, "Koroneiki" represents ca. 60% of the total olive-growing area in Greece due to its high yield of high quality olive oil (Anastasopoulos et al., 2011), thus rendering it a model cultivar for further studies. The olive fruit on-tree developmental phases can be distinguished into five interrelated stages. The first one refers to flowering, fertilization and fruit set. During this phase rapid, early cell division takes place, which enhances embryonic development. The second stage concerns the growth of the seed, which includes intense cell division, resulting in the development of the endocarp (seed/pit) and in the slight growth of the mesocarp (flesh). The hardening of the seed/pit occurs during the third stage, while during the fourth stage, the mesocarp develops and the pre-existing flesh cells expand and oil is accumulated. Ripening is the fifth stage when the fruit changes color from dark green to lighter green/purple and the softening process is initiated (Conde et al., 2008;Alagna et al., 2009). Tocochromanols are comprised of eight forms which are divided in two groups with four forms each, namely α-, β-, γ-, and δ-tocopherols and tocotrienols, respectively. In this study, the high resolution temporal expression profiles of tocopherol and tocotrienol biosynthetic genes were determined in parallel with the content of the four tocopherol and four tocotrienol forms during on-tree olive fruit developmental stages. These developmental programs in olive fruit are comprised of a period of 8 months starting in June and ending in January. Results suggest a high level of transcriptional regulation of α-tocopherol biosynthesis in mesocarp fruit tissue; furthermore, the regulatory importance of the first steps in biosynthetic pathway is highlighted. Fruit Material and Experimental Design This study was conducted using olive fruits (cv. "Koroneiki") during 17 different developmental stages, designated as S 1 -S 17 . These stages correspond to 6-38 weeks after flowering (WAF). Supplementary Table 1 provides a detailed list of the harvesting days and weeks after flowering. Fruit material was harvested from the Experimental Farm at the Mediterranean Agronomic Institute of Chania, Crete. Detailed meteorological data (air temperature, rainfall, and air relative humidity) in the experimental orchard during the 38 weeks after flowering are shown in Supplementary Figure 1. Olive fruits were collected at 1.7 m height around the tree canopy (symmetrically around the crown) of four trees with similar bearing habits and maturation. Approximately 25 olive fruits per tree were collected, pooled and transferred into the laboratory. Olive fruits were grouped based on the phenological growth stages in accordance with the BBCH (Biologische Bundesanstalt, Bundessortenamt, Chemische Industrie) scale (Sanz-Cortes et al., 2002; see Supplementary Table 2). The mesocarp developmental stage corresponds to 6-22 WAF, while the ripening stage of the olive fruit corresponds to 22-38 WAF (Conde et al., 2008;Alagna et al., 2009). Subsequently, fruit weight and diameter (n = 100) was monitored (Supplementary Figure 2). Dry content was also determined: ca. 3.5 g of olives fruits were dried in a forced air oven at 65 • C for about 3-4 days to constant weight, based on which % humidity was calculated (Supplementary Figure 3). The rest of the olives were washed with household bleach:ddH 2 O (1:1) for 3 min and rinsed several times (5-6) with ddH 2 O. Subsequently, the olive fruit were separated from its olive seed. The flesh was cut and put immediately in liquid nitrogen, ground and kept at −80 • C until needed as elsewhere described (Beltran et al., 2004). RNA Extraction and rDNase Treatment Total RNA was extracted from three independent tissue samples of 100 mg olive fruit material per fruit developmental stage following the protocol described by Christou et al. (2014). RNA was treated with RNase-free DNase (Cat. No. 04716728001, Roche), in order to completely remove gDNA. Subsequently, ddH 2 O was added to a final volume of 300 µL, along with an equal volume of chloroform, mixed in a vortex, and centrifuged on bench-top centrifuge (Eppendorf Centrifuge 5415 R) at 16000 × g for 30 min at 4 • C. The upper phase was transferred to a new, cold tube. Finally, 2.5 volumes of absolute ethanol and 1/10 volume 3 M CH 3 COONa (pH 4.8) was added for precipitation. The sample was mixed, incubated at −80 • C overnight and centrifuged at 16000 × g for 30 min at 4 • C. The supernatant was discarded and incubated at 50 • C for 2-3 min. RNA was dissolved in 20 µL ddH 2 O. The RNA integrity was analyzed spectrophotometrically (Nanodrop 1000 Spectrophotometer, Thermo Scientific), confirmed with gel electrophoresis and stored at −20 • C until use. cDNA Synthesis and Real-Time RT-PCR Analysis For first-strand cDNA synthesis, 1 µg of total RNA from each RNA extraction was converted into cDNA using the Primescript 1st Strand cDNA synthesis kit according to the manufacturer's instructions (Takara Bio, Japan). Real-time PCR was also performed with Biorad IQ5 real-time PCR cycler (Biorad, USA). In total, three biological replicates were performed for each developmental stage. The reaction mix contained 4 µL cDNA in reaction buffer (5-fold diluted first-strand cDNA), 0.5 µL of each primer (10 pmol/µl; Supplementary Table 4) and 5 µL 2X master mix (KAPA SYBR R FAST qPCR Kit, Kapa-Biosystems). The total reaction volume was 10 µL. The initial denaturation stage was at 95 • C for 5 min, followed by 40 cycles of amplification [95 • C for 30 s, annealing temperature (Tm • C) for 30 s, and 72 • C for 30 s] and a final elongation stage at 72 • C for 5 min. Gene amplification cycle was followed by a melting curve run, carrying out 61 cycles with 0.5 • C increment between 65 and 95 • C. The annealing temperature of the primers used ranged between 54 and 65 • C as shown in Supplementary Table 4. The UBQ2 gene was used as a housekeeping reference gene. Phylogenetic Analysis The Olea europaea VTE5, HPPD, VTE2, HGGT, VTE3, VTE1, and VTE4 amino acid residues were queried for homology against known proteins in the NCBI database, employing the Blastp algorithm (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Around thirty proteins that had similarity to the olive VTE5, HPPD, VTE2, HGGT, VTE3, VTE1, and VTE4 (and were also characterized as VTE5, HPPD, VTE2, HGGT, VTE3, VTE1, and VTE4) were selected in order to construct a phylogenetic tree. An amino acid alignment was conducted using the MUSCLE algorithm and all positions that had gaps were removed using alignment curation. The Maximum Likelihood (ML) method and an approximate Likelihood-Ratio Test (aLRT) were selected for the construction of the dendrogram and for statistical support testing of branch lengths. All the above procedures were conducted using the "A la Carte" workflow as implemented in the http://phylogeny.lirmm.fr/phylo_cgi/index.cgi site, as reported by Dereeper et al. (2008). Visualization of the tree was possible via the Treeview software (Page, 1996). Chromatographic Determination of Tocochromanols For the recovery of tocopherols and tocotrienols, approximately 100 mg of olive fruit was extracted with 1 ml acetonitrilemethanol-water (72/18/10, v/v/v) in 2-ml Eppendorf tube. The mixture was shaken for 15 min at 60 • C in Lab Companion SI-600R benchtop shaker in the dark following 5 min preincubation. Then, the mixture was centrifuged on bench-top centrifuge at 16000 × g for 5 min at 4 • C (Eppendorf Centrifuge 5415 R) and the supernatant was collected and stored at −20 • C until HPLC analysis (Gruszka and Kruk, 2007). Three biological replicates were performed for each developmental stage. A Waters series HPLC (Model "e2695") equipped with vacuum degasser, quaternary pump, autosampler, thermostatted column compartment, multi λ fluorescence detector, and Empower software (Waters Corporation, Milford, Ireland) for data collection and analysis was used. After filtration on Millipore paper (0.22 µm), 20 µL of each extract were injected on a reverse phase XTerra RP18 (5 µm; 4.6 × 250 mm) column (Waters Corporation, Milford, Ireland). An isocratic elution was also performed using a mobile phase composed of acetonitrile/ methanol/ 2-propanol (40/55/5, v/v/v) at a flow rate of 0.8 ml min −1 . The fluorescence detector was set at an excitation wavelength of 292 nm and an emission wavelength of 335 nm (Tsochatzis et al., 2012). A six-level calibration curve was constructed for each of the studied tocochromanols, with triplicate determinations at each level. The chromatographic peaks were identified by the retention times of the standard compounds. Statistical Analysis All real-time RT-PCR data analyses were performed using the REST-XL software according to Pfaffl et al. (2002) for relative quantification of gene expression and statistical analysis (pairwise fixed reallocation randomization test). The 6 week after flowering (WAF) sampling point was used for calibrating gene expression values. Statistical analysis of the results from the HPLC-Fluorescence detector analysis was carried out using the software package SPSS v17.0 (SPSS Inc., Chicago, USA) and the comparison of averages of each treatment was based on the analysis of variance (One-way ANOVA) according to Duncan's multiple range test at significance level 5% (P ≤ 0.05). In Silico Analysis of Genes Involved in the Biosynthetic Pathway of Vitamin E BLAST analysis on NCBI and OLEA EST db databases resulted in the identification of single cDNAs for each of VTE5, HPPD, geranylgeranyl reductase, VTE2, HGGT, VTE3, VTE1, and VTE4. The deduced amino acid sequences of VTE5, HPPD, VTE2, HGGT, VTE3, VTE1, and VTE4 reveal high similarities with homologs of other plant species, suggesting that the components of the pathway are highly conserved between plants (Supplementary Tables 5-11). This was further illustrated following phylogenetic analysis of all examined components of the pathway, where olive tocochromanol biosynthesis genes grouped together with other genes of similar function from other dicotyledonous plants (Supplementary Figures 4-10). Quantification of Gene Expression Profiles during Fruit Development and Ripening Transcript abundance of VTE5, geranylgeranyl reductase, HPPD, VTE2, HGGT, VTE3, VTE1, and VTE4 was determined using a qRT-PCR approach. The expression of VTE5 was up-regulated during 8-20 WAF of fruit development with higher levels observed at 10 WAF and 18 WAF (Figures 2, 5). At the 22 WAF, a significant drop in expression was detected. This drop was lower than the calibrator of 6 WAF levels and sustained up to 34 WAF, while it further decreased for the over-ripe stages of olive fruit. Geranylgeranyl reductase mRNA expression was higher compared with 6 WAF throughout fruit development and ripening, with highest levels at 10, 36, and 38 WAF. A decrease in expression was detected only after 32 WAF. Similar expression pattern was observed also for HPPD with peaks in expression after 16 and 30 WAF, while only two stages (8 and 32 WAF), exhibited a suppressed expression profile. The highest expression levels were at 16, 36, and 38 WAF. Transcript levels of VTE2 and HGGT were down-regulated throughout fruit development and ripening with the highest decrease for both genes after 8, 20, and 32 WAF. Different patterns of expression were observed for VTE3 and VTE1 with up-regulation observed during most of the developmental stages and down-regulation during late stages of development and the entire ripening process. Specifically, VTE3 mRNA levels were lower compared with the calibrator (6 WAF) after 8 WAF and increased up to 14 WAF; thereafter, its expression went descending, culminating during the over-ripe stages. VTE1 expression increased after 10 WAF all the way to 18 WAF, as well as after 22 WAF while it decreased thereafter up to the 38 WAF. This pattern of transcript abundance resembles the pattern of both VTE3 and VTE5. The highest suppression levels were also observed after 32 WAF. VTE4 expression was increased during 10-14 WAF and decreased at 8, 16, 20, and 22 WAF. Similarly, up-regulation was observed during the early stages of fruit ripening and down-regulation thereafter with the exception of 34 WAF. The pattern of VTE4 expression can be considered unique among all the genes involved in the vitamin E pathway. Quantification of Tocopherols and Tocotrienols during Fruit Development and Ripening The abundance of α, β, γ, and δ forms of tocochromanols was determined on 17 successive developmental stages of fruit development and on-tree ripening in cv. "Koroneiki" in order to study their temporal variation. All forms of tocopherols and one form of tocotrienol (γ-tocotrienol) were detected (Figures 3-5). Alpha-tocopherol was the most abundant form of tocochromanols in accordance with previous studies (e.g., Bodoira et al., 2015). The highest concentrations of αtocopherol were observed within the period 6-22 WAF with maximum content detected at 18 WAF (32.45 ± 0.54 mg/100 g F.W.). Alpha-tocopherol content was then stabilized at lower concentrations at the early stages of fruit ripening, after 22 WAF, and remained at those concentrations up to 38 WAF (16.86 ± 0.53 mg/100 g F.W.). Similar patterns of abundance were also observed for δ-tocopherol with a shift to lower concentrations after 26 WAF (0.20 ± 0.01 mg/100 g F.W.), while the highest concentration was detected at 22 WAF (0.28 ± 0.01 mg/100 g F.W.). Highest concentrations of β-tocopherol were observed at the early stages of fruit development, after 6 and 8 WAF, and fruit ripening, after 22, 24, and 26 WAF. Low concentrations of β-tocopherol were quantified between 10-20 WAF and 28-38 WAF. γ-tocopherol exhibited similar fluctuations in content to those observed for β-tocopherol. In regard with tocotrienol content, only γ-tocotrienol was detected, displaying increased concentrations between 6 and 28 WAF with the highest concentration being observed at 6 WAF (0.33 ± 0.01 mg/100 g F.W.). Finally, the concentrations of all tocopherols and γ-tocotrienol were lowered after 24 WAF when the ripening process was initiated, concomitant with the recorded increase in rainfall, relative humidity and reduction of air temperature in the experimental orchard (Supplementary Figure 1). DISCUSSION Temporal biosynthesis of tocochromanols in olive fruit was explored using a combined analytical/molecular approach during on-tree development and ripening. Molecular gene expression analysis revealed highly differential levels of regulation during 6-38 weeks after flowering (WAF). Results revealed pronounced levels of differential regulation of gene expression for the first and intermediate genes in the biosynthetic pathway (VTE5, geranylgeranyl reductase, HPPD, VTE2, HGGT, and VTE3) compared with downstream components of the pathway (VTE1 and VTE4). Notably, expression of HGGT and VTE2 genes is significantly suppressed in all the weeks after flowering (Figure 2). VTE5 was up-regulated during the period of mesocarp development until 22 WAF followed by marked down regulation at the breaker stage and throughout ripening starting from 24 WAF. Similar transition in concentration was observed for tocopherols and tocotrienols with significantly higher amounts FIGURE 2 | Relative expression levels of vitamin E biosynthesis genes (VTE5, geranylgeranyl reductase, HPPD, VTE2, HGGT, VTE3, VTE1, and VTE4) in olive fruit (cv. "Koroneiki") during 6-38 WAF (n = 3). The olives on top demonstrate the phenotypes of olive fruit at the different sampling stages. Values that differ from the control (6 WAF) with significance level P ≤ 0.05 are marked with *. Data are based on a statistical analysis of the means of three replications (Pfaffl et al., 2002). Frontiers in Plant Science | www.frontiersin.org until the breaker stage (22 WAF) and much lower thereafter indicating tight correlation with the expression profile of VTE5. These results are in agreement with those reported in tomato fruit (Quadrana et al., 2013), which present a decrease in VTE5 gene expression associated with tomato ripening. This decrease, directly limits phytol diphosphate [Phytyl-PP (PDP)] input supply toward VTE biosynthesis (Quadrana et al., 2013) and correlates with the low concentrations of tocopherols and tocotrienols in the olive fruit during ripening (starting from 24 WAF). These results suggest that VTE5 is particularly important in the biosynthesis of vitamin E in olive fruit and is thus proposed as a marker gene in relevant studies. The highest levels of expression among all all genes examined were detected for HPPD during not only mesocarp development but also ripening without any similar expression trend to VTE5 at the breaker stage. At the same time, geranylgeranyl reductase appears to be induced as well possibly in order to counter-balance the down-regulation of VTE5. A key observation in the metabolite/transcript profile was that the highest levels of up-regulation of VTE5 were detected at 18 WAF, concomitant with highest levels of α-tocopherol content (Figures 2, 3, 5). Interestingly, olive fruit reaches 90% of its final size at that point, thus rendering it suitable for harvesting green as this point would coincide with maximum α-tocopherol content. Furthermore, oil production in the olive fruit increases and reaches a maximum at "breaker stage" (color turned from green to purple, 22 WAF) (Conde et al., 2008;Alagna et al., 2009;Bodoira et al., 2015). Present results indicate that vitamin E content increases and reaches its maximum levels at 22 WAF (breaker stage), providing evidence that VTE5 plays an important role in olive tocochromanol biosynthesis. Conversely, the lowest expression levels of VTE5 was detected at 36 WAF and as a result low concentrations of all tocochromanols were observed, both likely being affected by over-ripening. Numerous reports have previously shown that olive oil synthesis starts after pit hardening, showing an increase in oil production and phenolic fraction and reaching its highest levels towards the end of the mesocarp development, concomitant with the initiation of color change (Conde et al., 2008;Alagna et al., 2009;Sakouhi et al., 2011;Bodoira et al., 2015). Furthermore, during the mesocarp development, carbohydrate metabolism (glycolysis/glyconeogenesis, citrate cycle, and fructose, manose and galactose metabolism) is more prevalent. In addition, increasing vitamin E content and oil production occurs during mesocarp development (6-22 WAF), while highest amounts are reached at breaker stage (22 WAF). During this period there is also a decrease in chlorophyll content in fruit mesocarp (Alagna et al., 2009). In contrast, olive oil production decreases, after 22 WAF along with vitamin E content. The processes of carbohydrate metabolism, fatty acid biosynthesis, and triacylglycerols (TAGs) are more evident at the beginning of the color change phase (22 WAF) and may have an effect on oil and vitamin E content. Phytol can be transformed in Phytyl-P, then in Phytyl-PP, finally producing chlorophyll, phylloquinone (vitamin K) and tocopherols. In addition, the active fatty acyl group can restrict the free phytol through the reaction of acyltransferase and produce fatty acid phyrol ester synthesis (Ischebeck et al., 2006). It has been reported FIGURE 5 | Heat map of the metabolite content and relative expression levels of genes in the biosynthetic pathway of vitamin E of olive fruit (cv. "Koroneiki") during 6-38 WAF. α-, β-, δ-tocotrienols are non-detectable. that the majority of phytyl-PP for tocopherol biosynthesis in Arabidopsis seeds is derived from chlorophyll degradation (Ischebeck et al., 2006;Valentin et al., 2006). However, further research is warranted on tocopherol biosynthesis-related phytol hydrolyzing activities, an area not yet adequately investigated (Zhang et al., 2014). The plastidal metabolite geranylgeranyl-PP (GGPP) is an intermediate in the phytyl-PP biosynthetic pathway originating from chlorophyll (Chl), and it is active throughout ripening of the olive fruit (Tanaka et al., 1999), further supported from the up-regulation observed in geranylgeranyl reductase expression. During the early stage of mesocarp development, elevated levels of Chl lead to an increased production of phytyl-PP, which in turn fuels the development of tocopherols and tocotrienols. As the olive fruit is changing color and the quantity of Chl is decreasing, the reaction is still active (geranylgeranyl reductase is up-regulated) but leads to lower production of phytyl-PP and, hence, lower production of tocopherols and tocotrienols. After the olive fruit becomes completely black and Chl degrades completely, a transient increase in expression levels geranylgeranyl reductase was observed, signaling a potential involvement of the specific metabolite in a different pathway. Overall, the up-regulation levels of geranylgeranyl reductase in green olive fruit were lower than those of the black olive fruit, in agreement with previous reports (Bruno et al., 2009;Muzzalupo et al., 2011). As far as the intermediate genes in the biosynthetic pathway are concerned, HGGT and VTE2 were both suppressed in all weeks after flowering. It should be noted that VTE2 and HGGT are involved in tocopherol and tocotrienol biosynthesis, respectively. These two genes demonstrated the highest levels of down-regulation at 8, 20, and 32 WAF (Figure 2). Low levels of all tocochromanols were also detected at 32 WAF which can be partially justified by the low expression levels of geranylgeranyl reductase, VTE2, HGGT, VTE3, VTE1, and VTE4. Such low transcript and metabolite levels might be attributed at harvest maturity. The same pattern was observed with highest levels of down-regulation for VTE2 and HGGT, while high levels of all tocochromanols were monitored at 8 WAF. At this stage, the fruit is 50% of its final size and the stone becomes lignified. It is also possible that higher concentrations of all tocochromanols result in a negative feedback regulatory mechanism, thus inhibiting these HPPD, VTE2, and HGGT biosynthetic enzymes. The same negative feedback regulation pattern has been also observed in other biological systems such as that in M. truncatula plants where nitric oxide (NO) accumulation results in a decline in nitrate reductase (NR) activity, the major contributor of NO biosynthesis (Antoniou et al., 2013). It should be pointed out that the characterization of gene expression using a qRT-PCR approach with a single reference gene in a time-course experiment comprising a large number of time points could potentially pose problems, particularly in the case that more than one developmental programmes are involved such as fruit growth and ripening. There is the possibility that slight variations in expression of the reference gene might prevent detection of expression alterations with biological significance. In addition, it might increase the variation of its expression due to the biological replicates which have to be performed. Nevertheless, Ct values obtained for UBQ2 in this setup were very similar across all samples examined (mean Ct value 21.15, standard error of 0.12, standard deviation of 0.85). The highest concentrations of metabolites (tocopherols and tocotrienols) were detected during the first and intermediate stages of olive fruit development, peaking at 22 WAF. Starting with fruit ripening (after 22 WAF), a steady decrease of tocochromanols was detected (Figure 3). Recently, Bodoira et al. (2015) also showed high amounts of tocochromanol content during the early stages of olive fruit (cv. Arauco) development, but observed a decreasing pattern throughout all developmental stages. The concentration of α-tocopherol (16.15 ± 0.60−32.45± 0.54 mg/100 g F.W.) in olive fruit is significantly greater than those of the β-, γ-, and δ-tocopherols (0.13 ± 0.01−0.25 ± 0.03 mg/100 g F.W., 0.13 ± 0.01−0.33 ± 0.04 mg/100 g F.W., 0.14 ± 0.01−0.28 ± 0.01 mg/100 g F.W., respectively), similar to the results by Hassapidou and Manoukas (1993), Bruno et al. (2009), Muzzalupo et al. (2011), and Bodoira et al. (2015. Interestingly, the concentrations of γ-tocopherol are only slightly lower than those of α-tocopherol at the early stages of "Arauco" olive fruit (Bodoira et al., 2015). The γ-tocotrienol was detected at low concentrations and α-, β-, and δ-tocotrienols were non-detectable (Figure 4); thus indicating that varietal differences expected to occur in tocochromanol content among olive cultivars. Overall, olive fruit contained significantly higher concentrations of tocopherols and tocotrienols until 22 WAF (concomitant with the end of mesocarp development) compared with later stages, thus suggesting that the color change phase might be of critical importance in vitamin E content of olive fruit. From all the tocochromanols examined, α-tocopherol was the most abundant with an average percentage of 96.72 ± 0.16% of total concentration in 6-38 WAF, with higher concentrations being detected within the period starting 6 WAF (24.41 ± 1.99 mg/100 g F.W.) and ending at 22 WAF (27.01 ± 1.05 mg/100 g F.W., the period of mesocarp development). α-tocopherol content remained stable and at the lowest concentrations from the color change ("breaker stage") up to over-ripe phase. The abundance of α-tocopherol in olive fruit is evident in several other studies, where it reaches concentration percentages between 60.9 and 88.6% depending on cultivar and developmental stage considered. The content of the other tocopherols fluctuated between 2.7 and 14.2% β-tocopherol, 0.6-41.8% γ-tocopherol, and 3.8-25.9% δ-tocopherol (Hassapidou and Manoukas, 1993;Bruno et al., 2009;Muzzalupo et al., 2011;Bodoira et al., 2015). Finally, low concentrations of all tocochromanols were detected at 36 WAF, concomitant with the highest levels of induction in HPPD gene expression. Such low concentrations of tocochromanols and up-regulation of HPPD might be affected by the over-ripening processes. Even though the levels of HPPD increased at 36 WAF, tocochromanol content decreased, probably due to the presence of other enzymes in the pathway (Ren et al., 2011). It is possible that when a metabolite reaches low threshold concentrations, its biosynthesis is subsequently induced at a transcript level. In various plants, where an induction in HPPD is observed, such increases normally concur with small to moderate increases in total concentration of vitamin E (Zhang et al., 2013). CONCLUSIONS This report is a first attempt for the temporal characterization of the vitamin E biosynthesis in olive fruit during on-tree development and ripening (Figure 5). Current findings suggest that olive fruits have increased amounts of all tocopherols and γ-tocotrienol up to 22 WAF (beginning of color change) in comparison with later WAFs, correlating with the expression profile of VTE5 which could thus be proposed as a marker gene for vitamin E analyses. Alpha-tocopherol is the predominant tocochromanol, similar to other plant species. Further research on vitamin E biosynthetic enzyme activities and protein abundance (components shown in Figure 1) could provide valuable biochemical evidence toward the complete mapping of the biosynthetic pathway of vitamin E in olive fruit.

v3-fos

2016-05-17T23:21:25.518Z

2015-12-01T00:00:00.000Z

5647

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Effects of Temperature on Systemic Infection and Symptom Expression of Turnip mosaic virus in Chinese cabbage (Brassica campestris) Using the Chinese cabbage (Brassica campestris) cultivar ‘Chun-goang’ as a host and turnip mosaic virus (TuMV) as a pathogen, we studied the effects of ambient temperature (13°C, 18°C, 23°C, 28°C and 33°C) on disease intensity and the speed of systemic infection. The optimal temperature for symptom expression of TuMV was 18–28°C. However, symptoms of viral infection were initiated at 23–28°C and 6 days post infection (dpi). Plants maintained at 33°C were systemically infected as early as 6 dpi and remained symptomless until 12 or 22 dpi, depending on growth stage at the time of inoculation. It took 45 days for infection of plants grown at 13°C. Quantitative real-time polymerase chain reaction (q-PCR) results showed that the accumulation of virus coat protein was greater in plants grown at 23–28°C. The speed of systemic infection increased linearly with rising ambient temperature, up to 23°C. The zero-infection temperature was 10.1°C. To study the effects of abruptly elevated temperatures on systemic infection, plants inoculated with TuMV were maintained at 10°C for 20 d; transferred to a growth chamber at temperatures of 13°C, 18°C, 23°C, 28°C, or 33°C for 1, 2, or 3 d; and then moved back to 10°C. The numbers of plants infected increased as duration of exposure to higher temperatures and dpi increased. Chinese cabbage is a widely cultivated crop in Korea, where it occupies approximately 35,513 ha annually (Food, Agriculture, Forestry and Fisheries Statistical Yearbook, 2012). The cropping system is divided into three types: spring cabbage (planted in April, harvested in June), autumn cabbage (planted in September, harvested in November), and summer cabbage (planted in May, harvested in September). Summer cabbage is cultivated in the alpine mountainous area of Gangwon Province, above 400 m altitude. TuMV infects most cruciferous plants, but it is particularly damaging to Chinese cabbage, turnip, mustard, and radish (Chivasa et al., 2001;Nguyen et al., 2013). It also attacks beets, spinach, and tobacco (Provvidenti, 1981;Walsh and Jenner, 2002), with a host range of at least 318 species representing 156 genera and 43 families. TuMV occurs in many parts of the world, including temperate, subtropical, and tropical regions of Africa, Asia, Europe, Oceania, and North and South America (Ha et al., 2008;Ohshima et al., 2002;Spence, 1999). TuMV causes stunted, coarsely mottled, and distorted symptoms in Chinese cabbage (Cho et al., 2003). Black spots develop on leaves, which subsequently drop prematurely. There is also yellowing along the leaf veins, leading to early senescence (Tomlinson, 1970). In recent years, as summers have tended to begin earlier, viral damage has increased in summer cabbage cultivated in highlands, reducing the production of marketable cabbage in Korea. Plant viruses and their vectors are strongly influenced by weather and climate. Climate changes are expected to affect the establishment, spread, and reproduction potential of viruses (Kido et al., 2008;Tamada and Harrison, 1981). In the present study, we investigated the effects of temperature on systemic infection and symptom severity by varying the temperature at the time of infection of TuMV in Chinese cabbage. Material and Methods Virus inoculation and temperature treatment. Seeds of the Chinese cabbage cultivar 'Chun-goang', which is generally known as a susceptible cultivar to TuMV, were sowed in a commercial soil 'Barok' and were grown in the insect proof glasshouse until using. At the two-(14-dayold) and four-(35-day-old) true-leaf stages, seedlings were mechanically inoculated with TuMV Virus inoculum was obtained from infected Chinese cabbage plants and prepared by pulverizing infected leaves with a mortar and pestle in 0.1 M PBS buffer (pH 7.2) at an approximate dilution of 1:5 (w/v). A constant volume of crude sap of the inoculum was rubbed on each test plant after dusting the plant with carborundum. TuMV-inoculated plants were immediately transferred to a growth chamber, set at 16-h day length and constant temperature treatments of 13 o C, 18 o C, 23 o C, 28 o C and 33 o C. Fifteen plants were included in each temperature treatment. Inoculated plants were monitored regularly, over a period of 30 d, for symptom development. To study the effects of an abrupt increase in temperature on systemic infection by TuMV, inoculated plants were initially maintained at 10 o C. After 20 d, they were transferred to a growth chamber at a temperature of 13 o C, 18 o C, 23 o C, 28 o C or 33 o C for 1, 2, or 3 d, and then they were moved back to 10 o C. Detection of virus infection. To study systemic infection, upper leaves of TuMV-inoculated plants were collected at intervals of 2 d over a 30-d period, starting at 6 days post infection (dpi). Systemic infection was determined based on ELISA results. The ELISA procedure was performed according to the manufacturer's instructions (Agdia, USA). Assessment of disease severity. The severity of viral symptoms of infected plants was scored as the symptoms started appearing at 6 dpi. The symptom severity score was rated on a 4.0-point scale: 0 = symptomless, 0.5 = slight leaf stunt, 1.0 = slight leaf stunt with mottle, 1.5 = clear leaf stunt with leaf deformation, 2 = leaf stunt with some chlorosis or yellow spots, 2.5 = leaf chlorosis half of the leaflets, 3 = leaf stunt and severe chlorosis over all of the leaflets, 3.5 = severe necrosis, 4 = withering. The SAS 4.2 statistical package (SAS Inc., Cary, NC, USA) was used for data analysis. Speed of systemic infection. The mean systemic infection rate was expressed as the reciprocal of the systemic infection time (days) as suggested by Wagner et al. (Wagner et al., 1984). A linear equation fitted to the systemic infection rate showed a linear relationship in the range of 13-23 o C. The best-fit linear lines were obtained using the TableCurve 2D program (Jandel Scientific, 1996). The infection zero temperature was calculated by solving the -intercept/slope of the fitted equation. Quantitative Real-Time PCR. Accumulation of virus coat protein (CP) was measured by real-time qPCR analysis at 10, 17, and 22 dpi under the five temperature treatments, following inoculation with TuMV at the two-trueleaf stage. RNA was extracted with an RNeasy mini kit (Qiagen, German, Hilden) and 200 ng RNA was used for cDNA synthesis. A total of 1 μl cDNA was used for qPCR analysis. Reactions were performed in a C1000 Touch thermal cycler (Bio-Rad, USA) using the SYBR-Green method (Universal SYBR-Green Supermix, Bio-Rad) according to the following protocol: 1 cycle at 95 o C for 30 s, 39 cycles at 95 o C for 10 s, 60 o C for 30 s, and 65-95 o C in increments of 0.5 o C at intervals of 5 s. The q-PCR primers (Supplementary Table S2) were designed using Integrated DNA technology (www.idtdna.com). The gene fragments amplified were TuMV-122 (accession no. NC_002509, nucleotides 177 to 299) and ACT1 (accession no. FJ969844, nucleotides 170 to 279). TuMV-RNA (target) was normalized to ACT1 expression (internal reference) to calculate the normalized target gene expression using CFX Manager v3.0 (Bio-rad, USA). Time required for systemic infection. A higher proportion of plants inoculated at the four-true-leaf stage were infected compared to those inoculated at the two-true-leaf stage ( Table 1). The time until systemic infection did not vary at temperatures from 23 o C to 33 o C or from 8 to 10 dpi (Table 1) Symptom severity. The optimal temperature for symptom expression of TuMV was within the 18-28 o C range. Symptom severity was much higher in plants inoculated at the four-true-leaf stage than in those inoculated at the twotrue-leaf stage. The low proportion of plants infected at the two-true-leaf stage was attributed to the difference in symp- tom severity between the two-true-leaf and four-true-leaf stages. This was particularly the case for plants maintained at 18 o C (Fig. 2). At 33 o C, plants inoculated at the two-trueleaf stage did not show symptoms until 22 dpi, whereas those inoculated at the four-true-leaf stage started to show symptoms at 12 dpi. For plants inoculated at the two-or four-true-leaf stages and maintained at 23-28 o C, symptoms started to appear within 6-8 dpi, reaching a maximum severity (i.e., severe necrosis, withering) at 26-30 dpi (Supplementary Table S1). At 18 o C, symptom appearance was delayed by about 4 d compared to the 23-28 o C range, regardless of plant growth stage at the time of inoculation. Symptom expression increased quickly thereafter, and plants inoculated at the four-true-leaf stage achieved maximum symptom expression at 28 dpi (Supplementary Table S1). TuMV caused slight leaf stunting, with mottling, at an early stage of infection, and leaf chlorosis or yellow spots appeared at 12 dpi (Fig. 3). Necrosis was visible at 24-26 dpi and withering was observed at 18-28 o C (Fig. 3). Yellows spots were observed only at 18 o C. At 33 o C, the symptoms were no longer typical for TuMV and the appearance of symptoms was delayed. Mottling was observed at 22 dpi and persisted until 30 dpi (Fig. 3). Accumulation of CP. Real-time qPCR results showed that plants maintained at 23-28 o C had higher levels of CP than those maintained at 13-18 o C or 33 o C, starting at 10 dpi ( Fig. 4). At 13 o C, virus accumulation was not detected until 22 dpi. Abrupt temperature increase. To study the effects of abrupt temperature increases on systemic infection of TuMV, two-and four-true-leaf-stage plants inoculated with TuMV were maintained at 10 o C for 20 d. After 20 d, the plants were transferred to a growth chamber with different temperature settings (13 o C, 18 o C, 23 o C, 28 o C and 33 o C) for 1, 2, or 3 d, and then they were moved back to 10 o C. Virus infection was determined at 6, 10, and 28 dpi after com- pleting the treatments (Table 2). More plants inoculated at the two-true-leaf stage were infected compared with those inoculated at the four-true-leaf stage. However, plants maintained at 10 o C were not infected. The virus symptoms were detected at temperatures of 18 o C or higher in plants inoculated at the two-true-leaf stage and exposed to higher temperatures ( Table 2). The number of plants infected increased with increased exposure to each temperature regime and with increases in temperature. This phenomenon was even more pronounced in plants inoculated at the twotrue-leaf stage ( Table 2). Discussion Using the Chinese cabbage cultivar Chun-goang as a host and TuMV as a pathogen, we studied the effects of temperature ( However, at 33 o C, a complete loss of typical TuMV symptoms was observed and the appearance of symptoms was delayed. The first visual symptoms were observed at 22 dpi. Symptoms included mottling and persisted until 30 dpi. This was probably attributed to the defense responses of the host plants to TuMV being much stronger at 33 o C than below 28 o C. Viral replication may have been negatively affected by the higher temperature.Inhibition of symptoms at 33 o C was associated with low accumulation of CP. It was assumed that extremely high temperatures prohibit virus replication and movement. Similar results have been reported for potato leaf roll virus at elevated temperatures (Tamada and Harrison, 1981). It has been demonstrated that the temperature at which virus transmission occurs affects the efficiency of pathogen multiplication (Feil and Purcell, 2001) and the establishment of infection in the host (Chu and volety, 1997). In protoplasts of Nicotiana benthamiana inoculated with Tomato bushy stunt virus (TBSV) genomic RNA and one of its defective interfering (DI) RNAs, replication of both genomic RNAs and DI RNAs were attenuated at elevated temperatures (32 o C), and they concluded that symptom atteunation of TBSV at elevated temperatures are primarily the result of reduced viral replication (Jones et al., 1990). N. benthamiana plants inoculated with Cymbidium ring spot virus (CymRSV) and grown at different temperatures died within 2 weeks at 15, 21 and 24 o C, however at 27 o C CymRSV symptoms were 'heat masked', and revealed that the attenuated symptoms were associated with reduced virus level (Szittya et al., 2003). RNA silencing plays a natural role in plant defense against molecular parasites, including viruses (reviewed in Voinnet, 2001). Szittya et al. (2003) showed that RNA silencing is a temperature dependent as it is activated and the amount of siRNAs gradually increased with rising temperature from 21 to 27 o C. Plants grown at 18 o C showed symptoms later, but over time the symptoms became severe, with a maximum severity of necrosis at 28 dpi. Virus replication or movement was slow at 18 o C during the early stages of infection, thus more time was needed to establish a systemic infection. One to three days of short exposure of Chinese cabbage (inoculated with TuMV and maintained at 10 o C) to the higher temperatures would be sufficient to show symptoms. Plants exposed to 33 o C for 24 h showed symptoms 28 d after being moved back to the 10 o C chamber. We also found that a greater number of plants were infected when inoculated at the two-true leaf stage than when inoculated at the four-true-leaf stage. This results indicate that young plants are more susceptible to virus infection than old plants with short time exposure to high temperature. This was probably because the defense responses of host plants to virus infection were much stronger in older plants, which explains the apparent need for more exposure time to establish infection. An example of this age effect is seen when okra plants are infected with virus at growth stages earlier than four weeks has more severe effect on the physiological performance of okra plant (Fajinmi and Fajinmi, 2010). Plant age affected the time of symptom appearance of Chinese cabbage with TuMV infection. The time needed to show systemic infection was similar in plants inoculated at the two-and four-true-leaf stages, but symptoms appeared earlier in plants inoculated at the four-true-leaf stage. It is presumed that, although the same amount of virus was inoculated for each plant, symptom development might be faster in older plants growing quickly, with concurrent proliferation of the virus throughout the plants. Direct evidence in support of this hypothesis is lacking, but higher infection rate of four-true-leaf stage plants in Table 1 shows consistency. During host-virus interactions, virus establishment in the host is affected by several factors, including growth stage, temperature, virus replication, virus movement, and RNA silencing (Chellappan et al., 2005;Soler et al., 1998;Szittya et al., 2003;Zhang et al., 2012;Zitter and Murphy, 2009). The involment of the developmental stage of the host plant in systemic infection has been mainly examined with cauliflower mosaic virus (CaMV) in turnip (Leisner et al., 1992). It was demonstrated that CaMV moved passively through the plant within the phloem, following the flow of photoassimilates from source to sink leavesm, and the flow fluctuates depending on the growth and developmental conditions of the plant. The developmental stage of the host plant can have a strong impact on vascular movement of certain viruses. Thus, further studies are required to clarify the effects of developmental stage of Chinese cabbage on systemic infection of TuMV.. According to a previous report, early exposure of cabbage to TuMV results in plants being 50% lighter than plants that have not been infected, but later infection is less damaging (Spence et al., 2007). In the present study, temperature at the time of TuMV infection had a strong effect on the productivity of Chinese cabbage. Average temperatures of 20-24 o C at the time of planting summer Chinese cabbage in alpine areas of Korea are suitable for TuMV symptom expression. Though virus infection of plants are affected by several other factors including virus strains and plant cultivars besides temperature, as the spring temperatures rise, if aphids emerge earlier, viral damage is expected to increase. If growers cannot control aphids, they must destroy plants infected with TuMV. These plants may include weed host plants growing around fields. Another option is to move to higher altitudes, where aphids are not present.

v3-fos

2022-11-26T15:26:15.828Z

2015-08-08T00:00:00.000Z

253892787

s2

Physiological characterization of maize tolerance to low dose of aluminum, highlighted by promoted leaf growth Effects of a low aluminum (Al) dose were characterized. The Al supplement inhibited root growth but enhanced leaf growth in maize lines with different Al sensitivities. High levels of Al are phytotoxic especially in acidic soils. The beneficial effects of low Al levels have been reported in some plant species, but not in maize. Maize is relatively more sensitive to Al toxicity than other cereals. Seedlings, at the three leaf stage, of four Chinese maize foundation parent inbred lines with different Al tolerances, were exposed to complete Hoagland’s nutrient solution at pH 4.5 supplemented with 48 μM Al3+ under controlled growth conditions, and then the Al stress (AS) was removed. The leaf and root growth, root cell viability, superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), ions (K+, Ca++ and Mg++), photosynthetic rate and chlorophyll, protein and malondialdehyde contents in tissues were assayed. In conclusion, a low Al dose inhibits root growth but enhances leaf growth in maize. The Al-promoted leaf growth is likely a result of increased protein synthesis, a lowered Ca++ level, and the discharge of the growth-inhibitory factors. The Al-promoted leaf growth may be a ‘memory’ effect caused by the earlier AS in maize. Al causes cell wall rupture, and a loss of K+, Ca++ and Mg++ from root cells. CAT is an auxiliary antioxidant enzyme that works selectively with either SOD or POD against AS-related peroxidation, depending on the maize tissue. CAT is a major antioxidant enzyme responsible for root growth, but SOD is important for leaf growth during AS and after its removal. Our results contribute to understanding how low levels of Al affect maize and Al-resistant mechanisms in maize. Maize (Zea mays L.) is relatively more sensitive to Al toxicity than other cereals (Doncheva et al. 2005;Poschenrieder et al. 2008). Maize responses to AS have been investigated, but the results have been varied (Boscolo et al. 2003;Giannakoula et al. 2008Giannakoula et al. , 2010Mihailovic et al. 2008). In soybean, a high level of AS caused plasmolysis, cell wall rupture, and the leakage of cellular contents (Yu et al. 2011). However, apparently no more attention was paid to AS effects on maize cells and their growth. Interestingly, it may be possible to mitigate soil Al toxicity using appropriate methods, such as the application of dolomite (Holmström et al. 2005). This raises the question of whether maize subjected to AS could resume its growth after the removal of AS (RAS). We characterize the maize responses to AS and RAS at organ, tissue, physiological, and cellular levels in four Chinese maize foundation parent inbred lines (two Alsensitive lines, and two relatively Al-tolerant lines). Maize inbred lines and growth conditions The maize inbred lines used were Huangzao4 (H4), Chang7-2 (C7-2), Ye478 (Y478) and Zheng58 (Z58), of which H4 and C7-2 are more sensitive to AS relative to Y478 and Z58. The maize seeds were kindly supplied by Professor Yu Li of the Institute of Crop Sciences, CAAS. The seeds were surface sterilized by soaking for 12 h at 28°C in distilled water, and then for 6 min in 75 % ethanol. The surface-sterilized seeds were grown at 28°C in fresh moist river sand. After emergence, seedlings with the same growth potential were selected and carefully transferred into holes in perforated polystyrene foam boards that were fixed 0.5 cm above the surface of the complete Hoagland's nutrient solution at pH 7. The nutrient solution was vigorously aerated for 15 min every 1 h, adjusted daily to maintain the pH at 7 ± 0.2, and renewed every 3 days. When reached the three leaf stage, the seedlings were subjected to the AS treatment in the nutrient solution at pH 4.5 supplemented with AlCl 3 Á7H 2 O, where the active Al 3? concentration was 48 lM. After a 72-h AS treatment, the seedlings were transferred and grown for 72 h at 28°C in an Al-free nutrient solution, representing RAS treatment. The seedling control treatment was performed using the Al-free nutrient solution in parallel with the AS treatment. All of the seedlings were grown in a chamber with 60-80 % humidity, a 12 h of light and a constant temperature of 28°C. The tissues were sampled at 10 a.m. every 24 h. The sampled tissues were directly used, immediately frozen in liquid nitrogen and then stored at -80°C, or immediately fixed in a solution containing 5 of 37 % formalin, 90 of 70 % alcohol and 5 of 37 % glacial acetic acid (GAA), depending on the analysis requirements. Measurement of leaf and root growth rates The absolute length of primary roots from the root-stem transition zone to the root tip, and the absolute length of the third leaves from the petiole base to the apex were measured. For both, leaves and roots, growth was expressed as the relative growth rates, which were estimated by (the length under AS/the length under parallel Al-free control) 9100 %. Assay of tissue Al ion contents The Al contents in the tissues were assayed using the conventional S-chromium azure (SCA) chromogenic method. Briefly, the tissues were oven dried. A 0.1-g aliquots of the dried samples was digested for 24 h in 1.5 mL of 2 mM HNO 3 , and then diluted 20 times with deionized water. A 1-mL aliquot of the dilution was transferred to a 25-mL volumetric flask, and then 1 mL HNO 3 (0.1 M), 2 mL cetyltrimethylammonium bromide (CTAB 5 mM), 2 mL EDTA-Zn (0.05 mM), 2 mL SCA (0.05 %), and 4 mL six-methyl tetramine solution (40 %) were added in that order. Finally, the volume was adjusted to 25 mL volume by adding deionized water, and then sufficiently mixed. The flask was placed for 20 min at room temperature, and the optic density (OD) of the mixed solution at 635 nm was assayed. The resulting OD 635 values were used to estimate the Al content in the tissues against a standard solution curve prepared with different AlCl 3 Á7H 2 O concentrations. Preparation of the plant tissue extract A 0.25-g aliquot of the fresh tissues was homogenized by grinding in 5 mL pre-cooled phosphate buffer solution (PBS) at pH 7.4 containing 1 mM EDTA, and then centrifuged for 20 min at 16,2009g at 4°C. The resulting supernatant was stored at -80°C. Assay of tissue total protein contents The total protein contents in the tissues were quantified according to the Coomassie Brilliant Blue-based method. In brief, a 1-mL aliquot of the protein extract was fully mixed with 1 mL G-250 Coomassie. Then, the OD 620 value of the solution was assayed and used to estimate the protein content against the standard solution curve prepared with different calf serum concentrations. Assay of antioxidant enzyme activities The SOD activity was assayed following the methods described in Tang (1999) with some modifications. Briefly, the following solutions were added, in order, to a tuber: 1.5 mL of PBS at pH 7.4, 0.3 mL of 130 mM methionine, 0.3 mL of 750 lM nitroblue tetrazolium (NTB), 0.3 mL of 110 lM EDTA-Na 2 , 0.3 mL of 110 lM riboflavin, 0.1 mL of the plant tissue extract, and 0.5 mL deionized water. The solution mix was allowed to react for 20 min at a light intensity of 3000 lux at 25°C, and the OD 560 value of the mix was assayed. A SOD activity unit (U) was defined as a 50 % inhibition of NTB photochemical reduction. The SOD activity was expressed as a specific activity of U mg -1 protein. POD activity was assayed as described in Tang (1999) with minor modifications. Briefly, a 20-lL aliquot of the plant tissue extraction compound was added to, and well mixed with 3 mL PBS (pH 7.4) containing 1 % (v/v) H 2 O 2 and 5 % (v/v) guaiacol, and then the OD 470 value was assayed. The POD activity U was defined as an increase in the OD 470 value of 0.01 min -1 . The POD activity was determined as the specific activity of DA 470 min -1 mg -1 protein. CAT activity was assayed following the methods of Cakmak and Horst (1991) with some modifications. Briefly, a 100-lL aliquot of the plant tissue extract was well mixed with 3 mL PBS (pH 7.4) containing 0.1 M H 2 O 2 , and then its OD 240 value was assayed. The CAT activity U was defined as a decrease in the OD 240 value of 0.01 min -1 . Assay of superoxide radicals (SORs) A 0.5-mL aliquot of the plant tissue extract was well mixed with 0.5 mL PBS (pH 7.4) and 1 mL of 1 mM hydroxylamine hydrochloride, and allowed to react for 1 h at 25°C. Then, 1 mL sulfanilic acid (17 mM) and 1 mL anaphthylamine (7 mM) were added, and allowed to react for 20 min at 25°C. The OD 530 values of the reaction solution were then measured and used to estimate SOR values against a curve generated by the standard solution, which was made with the above-mentioned reaction solution supplemented with NaNO 2 , at OD 530 . The SOR production was expressed as nM min -1 mg -1 protein. Assay of the malondialdehyde (MDA) content A 1-mL aliquot of the plant tissue extract was mixed with 2 mL solution containing 0.6 % (m/v) thiobarbituric acid and 10 % (m/v) trichloroacetic acid, reacted for 30 min in a boiling water bath, and immediately cooled on ice. The reaction solution was then centrifuged for 5 min at 11,600 9g. The OD 532 and OD 450 values of the resulting supernatant were measured, respectively. The MDA content was estimated using the formula of [(6.45 9 OD 532 ) -(0.56 9 OD 450 )] 9 plant tissue extraction compound (L)/the sample weight (g). Evaluation of root cell viability The cell viability of fresh roots was evaluated as described previously (Tamás et al. 2006) with some modifications. The roots were rinsed for 5 min with deionized water to fully remove the residues on the surface, and then stained for 30 min in 0.25 % (m/v) Evans blue. After staining, the roots were rinsed for 15 min with deionized water to fully remove the dye on the surface and then photographed. Microscopic observation of root tip cells The root tips (0.5 cm long) from formalin-GAA-alcoholfixed roots were sectioned lengthwise using a paraffin slicing machine. The thickness of the slices was 6 lm. The resulting slices were stained for 15 min in a solution that was prepared with equal volume of the staining stock solution and 50 % ethanol-GAA solution, where the staining stock solution was composed of 0.66 g hematoxylin, 3 mL GAA, 32 mL glycerol, 32 mL of 95 % ethanol, 1.66 g aluminum potassium sulfate, and 33 mL deionized water. The stained slices were observed by light microscopy. Assay of K, Ca, and Mg ions The tissues were fully oven dried. For each sample, a 0.1-g aliquot of the dried tissues was used to measure K, Ca, and Mg ions in a 6400 atomic absorption spectrophotometer (Shanghai, China) following the conventional atomic absorption analysis method. Chlorophyll content assay A 0.5-g aliquot of fresh leaves, the main veins of which were removed, was homogenized in 10 mL acetone. A 2-mL aliquot of the homogenate was centrifuged for 5 min at 2400 9g. The resulting supernatant was diluted five times with 80 % acetone, and then measured for OD 663 and OD 645 values, respectively. The OD values were normalized against the OD value of 80 % acetone, and then used to estimate the chlorophyll content based on the formula: the chlorophyll content [mg g -1 fresh weight (FW)] = [(8.02 9 OD 663 ? 20.21 9 OD 645 ) 9 10 mL 9 5]/(1000 9 0.5). Measurement of the photosynthetic rate The photosynthetic rate measurements were taken at 9:00 a.m. on the middle part of the second leaves by using a Li-6400 portable photosynthesis analyzer (Lincoln, NE, USA) under an artificial red and blue light source. Statistical analyses of the data The significant differences among the data were analyzed through one-way analysis of variance software, and the correlation analyses among the data were conducted based on the Pearson's correlation coefficient using the SPSS 13.0 software (http://www.spss.com/). Maize growth No Al toxicity-related symptoms were found on the shoots of the tested maize seedlings ( Fig. 1a-d). However, the root growth rate was significantly reduced under AS (Fig. 1e). Unexpectedly, the leaf growth rate in all of the maize lines was accelerated under AS, starting at 24 h after AS and increasing more significantly with the duration of AS (Fig. 1f). After RAS, the roots of the seedlings of the AS-treated maize lines grew in a significantly increased way although the growth rate was still slower than that of the respective control lines (Fig. 1e). Interestingly, the leaves of the AStreated maize lines had higher growth rates than the respective Al-free controls even after RAS treatment, especially in H4 and Z58 lines (Fig. 1f). Al ion content The Al ion content was much higher in the roots and leaves of the stressed lines under AS than in the respective Al-free controls (Fig. 1g, h). After RAS, the Al content decreased significantly in all of the AS-treated roots (Fig. 1g) and slightly in the stressed leaves (Fig. 1h), when compared with those at the 72-h AS time point. SOD activity The SOD activity levels in the roots of the AS-treated maize lines started to significantly decrease 24 h after AS, remained almost unchanged 48 h after AS, and then sharply dropped 72 h after AS, while the activity levels in the roots of the control maize lines did not obviously change (Fig. 2a). The SOD activity levels in the leaves of the AStreated maize lines were approximate to those in the respective controls for 48 h, but significantly decreased 72 h after AS (Fig. 2b). The SOD activity levels in the roots of the stressed maize lines at 72 h post AS were obviously increased by RAS (Fig. 2a). However, only the activity in the roots of the AS-treated H4 line reached the level of the corresponding control roots (Fig. 2a). Overall, the SOD activity levels in the leaves of the AS-treated maize lines did recover to levels of respective control leaves after RAS treatment (Fig. 2b). Change in POD activity The POD activity levels in the roots of the AS-treated C7-2 and Y478 lines were almost constant within 48 h after AS but increased slightly in the roots of the AS-treated H4 and Z58 lines at 24 h after AS. However, the activity levels in the roots of the AS-treated maize lines significantly decreased 72 h after AS when compared with the activity levels in respective control roots (Fig. 2c). In contrast, the POD activity levels in the leaves of the AS-treated maize lines started to significantly decrease early at 24 h after AS, and then sluggishly declined with AS when compared with the activity levels in respective control leaves (Fig. 2d). After 48 h of RAS treatment, the POD activity levels in the roots of the AS-treated maize lines almost reached the activity levels in the respective control roots (Fig. 2c). The POD activity levels in the leaves of AS-treated H4, C7-2 and Y478 lines indeed increased but did not reach the activity levels of the respective control leaves (Fig. 2d). Only the activity level in the leaves of AS-treated Z58 line reached to control level (Fig. 2d). The decreased activity levels of SOD and POD in the roots and leaves of all of the AS-treated maize lines ( Fig. 2a-d) were not in agreement with the results previously reported in maize under AS (Boscolo et al. 2003). Change in CAT activity The CAT activity levels in the roots of the AS-treated maize lines started to significantly decrease 24 h after AS, and then remained almost unchanged during further AS treatment (Fig. 2e). After RAS, the activity levels significantly increased but did not reach the activity levels in the respective control roots (Fig. 2e). During AS and RAS, the changes in the CAT activity levels in the leaves of the AStreated maize lines (Fig. 2f) were similar to the changes in SOD activity levels in the leaves of the AS-treated maize lines (Fig. 2b). MDA content and SOR production The MAD contents in the roots of the AS-treated maize lines started to significantly increase 24 h after AS ( Fig. 3a). After the RAS treatment, the contents in the roots of the AS-treated maize lines significantly declined when compared with those of the respective roots at the 72-h time point of AS. However, only the MDA content in the roots of the AS-treated Z58 line was similar to that in the corresponding control after RAS treatment (Fig. 3a). The MDA contents in the leaves of the AS-treated maize lines started to significantly increase 48 h after AS (Fig. 3b), lagging behind the changes in the MDA contents in the roots of the AS-treated maize lines (Fig. 3a). However, the MDA contents in the leaves of the 72-h-stressed maize lines almost recovered after RAS treatment to the respective control level (Fig. 3b). The increased MDA contents in the roots and leaves of the AS-treated maize lines did not support the previous conclusion that the presence of Al did not cause lipid peroxidation (Boscolo et al. 2003). With the increase in MDA contents, SOR production in the roots and leaves of all the AS-treated maize lines increased at 24 h, decreased at 48 h, and then increased again at 72 h after AS (Fig. 3c, d). Viability of the root cells AS (h) RAS (h) AS (h) RAS (h) The Evans blue staining indicated that decreased root cell viability under AS occurred in cells near the root tips at 24 h after AS, and then was found in the cells in the upper tissues with AS, being more obvious in the roots of the AS-treated H4 and C7-2 lines (Fig. 4). Notably, a decreased root cell viability in Z58 line during AS seemed to be limited to the cells near the root tip zone (Fig. 4). The decrease in root cell viability in the AStreated maize lines could be alleviated by RAS treatment, especially in the roots of AS-treated Y478 and Z58 lines (Fig. 4). The cells in the root tip zones of the AS-treated maize lines showed plasmolysis and cell wall rupture, and had concentrated and enlarged nuclei, while the cellular contents leaked (Fig. 4). These symptoms started 48 h after AS, and were more serious in H4, C7-2 and Y478 lines than in Z58 line (Fig. 4). Interestingly, the symptoms were greatly alleviated by 48 h of RAS treatment (Fig. 4). K, Ca, and Mg ions in the tissues The K, Ca, and Mg ion contents in the roots and leaves of all the AS-treated maize lines declined when compared with the levels in the respective controls ( Fig. 5a-f). The contents of these ions in tissues of the AS-treated maize lines were significantly enhanced by RAS treatment (Fig. 5a-f). These results echoed the changes in cell structure in the root tip zone (Fig. 4). Protein and chlorophyll contents, and the photosynthetic rate The total protein contents were significantly higher in the roots and leaves of the AS-treated maize lines than in the roots and leaves of respective control lines (Fig. 6a, b). The protein content started to significantly increase 24 h after AS in the roots (Fig. 6a) and 48 h after AS in the leaves (Fig. 6b). After RAS treatment, the protein contents in the tissues of the AS-treated maize lines significantly declined when compared with protein content levels in corresponding AS-treated maize lines before RAS (Fig. 6a, b). The chlorophyll contents in the leaves of the AS-treated Z58 line decreased slightly within 48 h of AS and significantly 72 h after AS when compared with the chlorophyll levels in the control line (Fig. 6c). A significant decrease in the chlorophyll content was found in three AS-treated maize lines (H4, C7-2 and Y478), starting 24 h or 48 h after AS depending on the lines. After RAS treatment, the chlorophyll contents in the leaves of the AS-treated maize lines reached the levels in the respective controls (Fig. 6c). AS (h) RAS (h) AS (h) RAS (h) AS (h) RAS (h) The photosynthetic rates in the leaves of all the AStreated maize lines started to significantly decrease 24 h after AS (Fig. 6d). After RAS treatment, the photosynthetic rates in the leaves of the AS-treated maize lines obviously increased when compared with the photosynthetic rate levels in respective maize lines treated by AS for 72 h (Fig. 6d). Discussion Al toxicity in plants occurs in acidic soils (Matsumoto 2000). However, the beneficial effects of low Al doses on plants in acidic soils may occur in both Al-tolerant plants and many Al-stimulated plants (Osaki et al. 1997), and is characterized by growth promotion. The seedlings of Altolerant triticale and alfalfa showed large root regrowth during AS (Zhang et al. 1999(Zhang et al. , 2007. Additionally, lower Al concentrations significantly stimulated the root growth of Al-tolerant soybean PI 416937 (Du et al. 2010). All of the maize lines tested in this study showed similar changes in leaf and root growth rates, root cell viability, SOD, POD, and CAT activities, of K, Ca and Mg ion contents, protein contents, chlorophyll and MDA contents, and photosynthetic rates under AS and after RAS, but the magnitudes and response time of the changes differed depending on the maize line, suggesting differences in AS- AS (h) RAS (h) AS (h) RAS (h) (a) (c) (b) (d) Fig. 3 The MAD contents, and SOR production rate in the maize tissues under AS and after RAS. The MDA contents in roots (a) and leaves (b). The SOR production rates in roots (c) and leaves (d). The values are mean ± SE from at least five individual seedlings tolerant mechanisms. The increased MAD contents in the tissues of the AS-treated maize lines (Fig. 3a, b) indirectly supported the previous conclusion that the Al treatment could trigger lipid peroxidation in the sensitive maize lines (Giannakoula et al. 2008), but they did not corroborate the view that Al treatments did not induce lipid peroxidation in both sensitive and tolerant maize lines (Boscolo et al. 2003). Our results showed that in maize, AS can cause decreases in the Ca and Mg ion contents in Al-tolerant Y478 and Z58 lines and Al-sensitive H4 and C7-2 lines ( Fig. 5c-f), which supported previous conclusions (Giannakoula et al. 2008;Mihailovic et al. 2008). However, AS caused a significant decrease in K ion contents (Fig. 5a, b), which was in contrast to the previous conclusion (Yu et al. 2011). The discrepancies in the above-mentioned results likely resulted from the differences among the maize lines and/or partly from the experimental conditions, such as applied Al 3? concentrations and/or stress duration. During AS or after RAS, changes in the contents of Ca, Mg and K ions (Fig. 5) were closely related to changes in the cell structure in the root tip zone (Fig. 4), suggesting that low external Al concentrations can also lead to the loss of Ca, Mg, and K ions by disrupting the cell's integrity. Additionally, the decreased ion contents in the roots of the AStreated maize lines may be partially ascribed to impaired root uptake capacity during AS. Considering the promotion of leaf growth (Fig. 1a-c) during AS as well as the recovery of AS-damaged cell walls in the root tip zone after RAS (Fig. 4) and other parameters of AS-treated maize lines after RAS treatment, we conclude that low doses of Al only decrease root growth rate and that the AS-caused inhibition of root growth of maize can be alleviated by appropriate RAS treatments. For AS-treated maize lines, changes in the chlorophyll contents (Fig. 6c) did not correspond with changes in the photosynthetic rates (Fig. 6d), suggesting that the differences among photosynthetic rates in maize lines under AS result from differences in photosystems rather than chlorophyll contents. This reasoning partly confirms a previous finding that AS led to a severe decrease in activity of photosystem 2 activity (Mihailovic et al. 2008). For an in-depth analysis of the correlation among the parameters, we conducted a multiple factor correlation analysis of the data resulting from AS and RAS treatments (Tables 1, 2). SODs together with PODs form the first line of antioxidant defense against ROS (Ito-kuwa et al. 1999;Veljovic-Jovanovic et al. 2006). In the SOD-POD system, SODs first degrade O 2 -1 into O 2 and H 2 O 2 , and the latter is then degraded by POD into H 2 O and O 2 (Boscolo et al. 2003;Wang et al. 2013). CAT scavenges photorespiratory H 2 O 2 by a catalytic reaction of 2H 2 O 2 ? O 2 ? 2H 2 O (Willekens et al. 1997). As expected, there was a positive correlation between SOD and POD activities in the roots (Table 1) and leaves (Table 2) of AS-treated maize lines. Interestingly, the CAT activity showed a positive correlation with the SOD activity in the roots of the AS-treated maize lines (Table 1) but showed a negative correlation with the POD activity in the leaves of the AS-treated maize lines (Table 2). This suggests that the roots of the AStreated maize lines require more antioxidant enzymes to cope with AS-triggered peroxidation relative to the AStreated leaves. This appears reasonable because SOR production was greater in the AS-treated roots than in the AStreated leaves (Fig. 3c, d). Thus, CAT is likely an auxiliary antioxidant enzyme that selectively cooperates with either SOD or POD to play a role in antioxidation under AS and after RAS, depending on maize tissues. The CAT activity positively correlated with root growth rate (Table 1), while the SOD activity showed a positive correlation with the leaf growth rate (Table 2). This suggests that CAT is a major antioxidant enzyme responsible for root growth, and that SOD is an important enzyme for leaf growth under AS and after RAS. There was a strong correlation between the Mg ion content and K ion content in the roots of the AS-treated maize lines (Table 1), and among Ca, K, and Mg ion contents in the leaves of the AS-treated maize lines (Table 2). This strongly suggests that there is a synergetic leakage from and/or uptake of Ca, K, and Mg ions by the roots under AS, depending on the maize tissues. The chlorophyll content positively correlated with the Mg ion content, but the photosynthetic rate positively correlated with the K ion content in the leaves of the AS-treated maize lines (Table 2), indicating differential differences in roles of Mg and K ions in photosynthesis under AS and during RAS. AS (h) RAS (h) AS (h) RAS (h) AS (h) RAS (h) The promotion of leaf growth in the AS-treated maize lines not only occurred during AS but also lasted during RAS (Fig. 1f), suggesting that the AS-promoting effect on leaf growth is in the 'memory' of AS-treated maize. Reportedly, the growth stimulation in plants receiving Al applications was ascribed not only to the alleviation of H ? toxicity but also to the increase in root uptake activity of nutrient elements, such as P (Osaki et al. 1997). However, this conclusion was not supported by the research in which the soybean roots were exposed to Al in a 0.5 mM Ca solution at pH 4.5 without other nutrients (Du et al. 2010). In the Al-accumulating plant Mel. malabathricum, Al, together with other nutrients, could promote the synthesis of adequate amounts of citrate (Watanabe et al. 2005) and could also induce a reduction in toxic Fe accumulation in roots and shoots (Watanabe et al. 2006). Therefore, the exact mechanisms for the AS-promoting effect on plant growth are still not fully understood (Ma 2007). The analyses indicated that AS-promoted leaf growth correlated positively to protein content and negatively to Ca ion content (Table 2). An increased protein content is undoubtedly conducive to plant growth at least because proteins are important ''raw materials'' (precursors) for important metabolites such as amino acids. Although the Ca ion content in roots and leaves of the AS-treated maize lines decreased (Fig. 5c, d), it correlated positively with root growth (Table 1) and negatively with AS-promoted leaf growth (Table 2). These results supported the conclusion that elevating Ca inhibits shoot growth and promotes root growth (Hepler 2005). This may be because reducing the Ca ion concentration promotes cell and tissue elongation and elevating Ca ion inhibits cytoplasmic streaming (Hepler 2005). The stresses, to some extent, lead to ubiquitin-mediated proteasomal degradation of growthrepressing proteins, such as DELLA in plants and consequently promote growth (Conti et al. 2014). Therefore, another reason for AS-promoted leaf growth is also likely Conclusion Low doses of Al inhibit root growth but enhance leaf growth in maize lines. The AS-promoted leaf growth is likely associated with increased protein synthesis, a lowered Ca ion content, and the discharge of growth-inhibitory factors from the growth-regulating molecules. Some unknown compensating mechanisms regulate AS-promoted leaf growth. Additionally, AS-promoted leaf growth is in the 'memory' of AS-treated maize plants. CAT is an auxiliary antioxidant enzyme that work selectively with either SOD or POD against AS-caused peroxidation. CAT is a major antioxidant enzyme responsible for root growth, but SOD is important for leaf growth under AS and during RAS.

v3-fos

2018-12-03T17:27:29.964Z

2015-07-23T00:00:00.000Z

54222977

s2

Dairy herd-level prevalence of Johne's disease and BVD in the Intermountain West of the U.S.A. and farm management practices and characteristics for test-positive herds Herd-level prevalence of Mycobacterium avium subsp. paratuberculosis (MAP), causative agent of Johne’s disease (JD) and Bovine Viral Diarrhea (BVD) virus were estimated on dairy farms in Utah. Duplicate milks were collected at 3-4 day intervals on 5 dates from each bulk tank on participating farms. Samples were tested at separate laboratories for BVD (real-time, RT-PCR) and for JD/MAP (ELISA and qPCR). 151/209 (72%) eligible dairy farms participated. Farms detected positive were: 58 JD (38%) and 14 BVD (9%); 5 farms had both diseases. Follow up visited farms’ (n=22) means, medians: 778,420 milking cows; 20,052 lbs, 20,311 lbs 305d milk; 175,545/ml, 178,000/ml bulk milk SCC; stalls visibly soiled in rear one-third 37%, 32%, range 5% to 90%. Seventeen of 21 (81%) farms with JD had observed adult cows becoming thin while retaining appetite, 52% had seen adult cows contract diarrhea and subsequently die. Both BVD-positive farms had observed abortions. Free stalls housed milking cows on 91% of farms; dry lots housed dry cows on 55%. Nine farms (41%) had purchased animals within the past year: 27% pregnant heifers, 18% bulls, 9% calves, 14% cows; 9% had purchased only bulls. Whenever animals were last purchased, 14 farms (64%) had performed no disease testing or segregation; 8 farms (36%) utilized at least one biosecurity practice for replacements. Most common were 9-way vaccine including BVD on arrival (27%), 14% segregated replacements for any time, 11% tested for any diseases (none for JD). Fourteen (67%) farms with JD would identify known positive cows; none would segregate positives. Most producers (57%) allowed known JDpositive cows to calve again, farms with BVD were equivocal. No producers would have a separate calving area for JD or BVD-positive cows. Six farms (27%) fed calves only individual cow colostrum and pasteurized milk. All 22 farms vaccinated against BVD. Estimated financial losses associated with JD range from $250 million to $1.5 billion annually in the U.S., possibly underestimated [4,6]. Loss estimates in JD-positive cows range from $83 to $380 per infected cow depending on parity/age, $77 in increased culling losses per cow for all cows within a herd, and $49 to $200 per cow for all cows within infected herds [5,[7][8][9]. Definitive data is lacking regarding the proportion of dairy herds infected with JD; estimates vary between different studies, countries and regions. Nevertheless, it is generally agreed that herd-level prevalence of JD has increased in developed countries, from approximately 10% to 30% of herds positive 20 to 25 years ago [10][11][12] to 38% to 74% of herds at present, with most regional estimates at approximately 43% of dairy herds positive for JD [13][14][15]. Bovine viral diarrhea (BVD) is another costly disease of ruminants, including dairy cattle [9,[16][17][18][19]. A review in Denmark estimated that BVD losses ranged between $10 and $40 dollars per dairy cow calving [19]. Direct BVD costs were estimated in Canada, including premature culling, lost milk production, reduced slaughter value, abortion and reproductive loss, and mortality, estimated that mean annual costs were $48 across all cows in an infected herd [9]. This was similar to estimated BVD losses among all cows in a U.S. study [18]. Cattle are infected with the BVD virus via transient, usually selfeliminating, episodes of viral transmission or from animals that were persistently infected (PI) during gestation. Animals infected with BVD in utero during the first few months of pregnancy, while fetal immunity is being developed, recognize the virus as "self". There is no resultant immune response, and the virus persists in these animals which are therefore born and remain PI. Large amounts of virus are shed by PI animals, and they represent the most likely reason that BVD circulates within herds [20]. While many PI animals eventually contract clinical signs of the disease, most of the clinical cases of BVD develop in cattle that are transiently infected. Effects of BVD infection include respiratory disease, gastrointestinal disease, immunosuppression, abortions, stillbirths, infertility, congenital defects, and lost meat and milk production [20]. There is reported worldwide distribution of BVD [21]. In the U.S., it is estimated that 0.13% of cows are PI [22]. Few studies have used PCR bulk milk sampling to estimate the percentage of herds with at least one PI, ranging from 15% in the U.S. [22] to 39% in Denmark [23]. Earlier surveillance projects of Utah and adjacent areas of the Intermountain West detected JD in 39% of dairy herds in 2009 [24]. Statewide or regional surveillance of dairy herds for BVD had not been done. The objectives of the study reported here were estimation of the dairy herd-level prevalence of JD and BVD virus in Utah and the nearby Intermountain West using a repeated sampling scheme, and summarizing management practices and characteristics of farms with test-positive herds that participated in follow up farm visits. Study farms In order to sample bulk tank milk for testing for JD and BVD, written permission of dairy producers was obtained. Information and permission forms were distributed both electronically and personally by milk buying company field personnel to dairy producers in Utah and some producers from surrounding states that sold milk to either of the 2 major milk processors in Utah. Collection and handling of bulk tank milk samples Milk was collected from each bulk tank on participating farms at 3-4 day intervals on 5 sampling dates (duplicate samples each time) over approximately 15 days. Following agitation of milk for at least 5 min, milk haulers collected 2 extra samples into sterile vials at the same time they collected their routine testing samples. All samples were frozen at the processing plants at -20°C and remained frozen until analysis. Using portable -20°C freezers, all samples were transported to the Utah Veterinary Diagnostic Laboratory from the collection locations and then shipped frozen overnight by courier. One sample was sent to The Dairy Authority laboratory in Greeley, CO and the other sample collected on the same day was sent to Antel Bio Systems in Lansing, MI for testing. MAP detection in bulk tank milk samples At Antel Bio Systems all bulk tank samples were tested using 2 test methods as described previously [24,25]. Each bulk tank sample was analyzed for MAP-specific IgG antibody by a commercial ELISA (IDEXX Laboratories, Westbrook, ME) and for presence of MAP organism by quantitative real-time PCR (qPCR). ELISA scores above 0.1 optical density (OD) were considered positive for JD, resulting in test sensitivity and specificity of 52% and 94%, respectively, when environmental fecal analysis was used as the "gold standard" for MAP detection [25,26]. Cycle threshold (Ct) values below 41 were defined as positive PCR results for the presence of MAP. Sensitivity and specificity are 40% and 94%, respectively, when compared to environmental fecal analysis for MAP detection [25,26]. BVD detection in bulk tank milk samples Screening of milk samples for BVD virus utilized a commercial BVD real-time reverse transcription PCR (Applied Bio systems, Carlsbad, CA) per manufacturer's instructions as previously reported [27][28][29]. Case definitions and test sensitivity and specificity The specificity of milk testing for JD and BVD has been reported previously as nearly 100%; false positive results are uncommon [25,26,30]. Therefore for each of the diseases JD or BVD, the finding of at least 1 positive test result for that disease in a herd was defined as a "true positive". Specificity (avoidance of false positives) was 100% by definition; no positive results were defined as "false positive". Test sensitivity (avoidance of false negatives) was calculated for detection of each of the disease agents. Sensitivity was defined as the total number of positive test results for either agent divided by the total number of tests performed on all bulk milk samples from the herds defined as true positive for that agent. For example, if there were 284 JD-positive bulk tank samples among a total of 528 bulk tank samples from all farms that tested positive for JD/MAP, sensitivity=284/528=54% for a single bulk tank sample test to detect JD/MAP. Confidentiality of results Investigators did not know the dairy producers' identities because farms were coded by number for anonymity by the 2 milk buyers. Owners of herds positive for either of the diseases were contacted through the milk buyer field personnel using their number code; their identities were revealed to the investigators if the producers agreed. Those producers were contacted for a follow up program including possible farm visits. Farm follow up questionnaire Two of the investigators (DW, KR) modified a questionnaire that they had developed and used during previous surveillance and outreach projects, designed to evaluate farm management practices and characteristics associated with JD and BVD. Initially, 6 farm visits were made by all 4 field investigators (DW, KR, CW, and JB) together to standardize observations and interview methods. The remaining farm visits were made in pairs (DW/CW, KR/JB, or CW/JB) or singly by DW or KR. Surveillance results were compiled and analyzed using a data management program (Microsoft Excel, Bellevue, WA). Sample collection Signed forms authorizing milk sample collection and testing were returned by 151/209 (72%) of the dairy producers in the study area of Utah and adjacent areas of the Intermountain West. There were 179 bulk tanks on the 151 participating dairy farms, from which 1,822 bulk tank milk samples (911 pairs) were collected, sampled 3-4 days apart. Samples were maintained frozen at -20°C as described earlier and arrived frozen at both testing laboratories. Number of dairy herds testing positive for at least one disease There were 67 herds (44%) that tested positive for either JD or BVD; 62 herds were positive for one of the diseases and 5 herds were positive for both diseases. The remaining 84 herds (56%) tested negative for JD and BVD. Herd-level prevalence of JD Bulk tank milk tested positive for JD at least once from 58/151 dairy herds (38%) in the study area. Five of these herds were also positive for BVD. Among the JD-positive herds, the proportion of their bulk tank samples that tested positive ranged from 100% (19 herds) to 5% (one herd). Median proportion of bulk tanks testing JD-positive among all positive herds was 3/5 (60%). The farm with the largest number of bulk tank samples collected (38 samples) showed how variable the shedding of MAP can be; that farm had 3 bulk tanks, all with milk picked up twice every day, sometimes 3 times within 24 h. For all 6 JDpositive tank results on that farm -only 2 of the 3 tanks on the farm were ever positive -milk from the same tanks was JD-negative when collected approximately 12 hours earlier or later on the same day. Herd-level prevalence of BVD Bulk tank milk tested positive for BVD at least once from 14/151 herds (9%), including the 5 that also were JD-positive. The proportion of their bulk tanks testing BVD-positive ranged from 100% (3 herds) to 6% (one herd). The median proportion of their bulk tanks testing BVD-positive was 1/4 (25%). Bulk tank test sensitivity Test sensitivity for JD detection was calculated by dividing the total number of JD-positive bulk tank results by the total number of bulk tank milk samples tested from the JD-positive farms. There were 284 JD-positive bulk tank samples among the 528 bulk tank samples from the 58 positive farms; therefore 284/528=54% sensitivity of a single bulk tank sample test for detection of JD. Similarly, sensitivity of a single sample for detection was 41/117=35% for BVD. Descriptive statistics and farm facilities of herds positive for JD and/or BVD One of the milk buying companies did not cooperate with the follow up program; they did not reveal any identities of producers with positive herds to the investigators as previously agreed upon. Of the test-positive herd owners who shipped milk to the other milk processor, 22 agreed to follow up farm visits. On the 22 farms visited, personnel interviewed included at least one owner and usually the herdsperson as well, sometimes the herd health veterinarian and other farm employees, and observations were made to complete the questionnaire; 20 herds were JD-positive only, one was BVD-positive only, and one was positive for both diseases. Mean and median lactating herd size were 778 cows and 420 cows, respectively, ranging from 52 to 6523 cows. Mean and median 305 d milk productions were 20,052 lbs (9240 kg) and 20,311 lbs (9221 kg), respectively, ranging from 14,918 lbs (6773 kg) to 25,350 lbs (11,509 kg). Mean and median somatic cell count (SCC) in bulk tank milk (from all milk plant records available over the previous 6 months) were 175,545/ml and 178,000/ml, respectively, ranging from 94,000/ml to 300,000/ml. Primary lactating cow housing was outdoor free stalls with small roofs above on 16 farms (73%), free stalls in covered barns on 4 farms (18%), and dry lot on 2 farms (9%). Four of the free stall operations also had some dry lot housing (one also had some pasture as well), and 3 had some loose housing. The primary dry cow housing was dry lot on 12 farms (55%), free stalls in covered barns on 4 farms (18%) (none were the same 4 farms that had that type of lactating cow housing), outdoor free stalls with small roofs above on 3 farms (14%), loose housing on 2 farms (9%), and pasture on one farm (5%). Six of the dry lot operations also had some loose housing (one also had some pasture as well) for dry cows; 2 of the free stall farms also had dry lot housing, one had some loose housing, and one had an exercise lot for dry cows. On the 20 farms with lactating cow free stall housing, at least 20 stalls in each row in each pen were observed and the percentage of stalls with visible manure or urine in the back one-third of the stall was calculated. Usually at least 40 stalls per pen were graded in this way. The goal is 5% or fewer visibly soiled stalls. Mean and median percentages of stalls visibly soiled in the back one-third were 37% and 32%, respectively, ranging from 5% to 90%. One farm reached the goal of 5% soiled stalls, and 2 farms had 90% soiled, one of which was the farm detected with BVD and JD. Bedding used in free stalls (n=20 farms) had an unexpected association with percentage of soiled stalls (this observational finding was not tested statistically because it was not a planned experiment), which was not consistent with the experience of the authors. There was one farm (5%) bedding with sawdust that had 5% soiled stalls; 3 farms (15%) bedding with sand had 15%, 15% and 30% soiled stalls. The 16 farms (80%) that bedded with straw (2 also mixed in recycled manure, one also used mats, one also use water beds) had mean and median of 43% and 44% soiled stalls, respectively, ranging from 10% (the farm that also used water beds under the straw) to 90%. Eight of the 16 farms bedding with straw had 50% to 90% of stalls with visible manure or urine in the back one-third. Free stall maintenance was evaluated based upon stall width 44" (112 cm) to 50" (127 cm), stall dividers firmly in place rather than loose, broken or absent, and position of brisket (held by neck rail or brisket board) 5' 4" (163 cm) to 5' 10" (178 cm) from the back edge of the stall. All 20 farms had stall dimensions within standards; therefore the de facto indicator of stall maintenance was whether stall dividers were firmly in place rather than loose, broken or absent. One or two poor stall dividers were considered acceptable. If multiple poor stall dividers were observed in multiple areas of the cow housing, this was defined as poor free stall maintenance. Stalls were well maintained on 15 (75%) of farms, and poorly maintained on 5 (25%) of the farms with free stalls. Farms with well-maintained stalls had mean and median of 31% and 30% soiled stalls, respectively; farms with poorly maintained stalls had 50% (n=4 farms) and 90% (one farm) of stalls with visible manure or urine in the back one-third. Biosecurity and herd replacement practices Thirteen (59%) of the farms, 12 with JD only and the one with BVD only, had been closed for at least one year to any purchased animals, including pregnant replacement heifers, bulls or calves as well as cows, for a mean of 4 years, median of 5 years, ranging from 1.5 to 7 years. The other 9 farms (41%), including 8 with JD only and the one with BVD and JD, had purchased animals within the past year. Six farms (27% of all farms) had purchased pregnant replacement heifers, 4 farms (18%) had purchased bulls, 2 farms (9%) had purchased calves, and 3 farms (14%) had purchased cows within the past year. Most farms had purchased multiple categories of animals, but one farm had purchased only calves, and 2 farms had purchased only bulls. Whether or not the farms were closed to purchase animals, the owners were asked about biosecurity practices whenever animals were last purchased. Fourteen farms (64%) had performed no disease testing, segregation or any biosecurity practices when buying replacement animals (this included 10 of the 13 with closed herds, and 4 of the 9 farms that had purchased animals during the previous year). One of the open farms with no biosecurity practices was the farm with both BVD and JD detected in the herd. The other 8 farms (36%) utilized at least one biosecurity practice the last time they purchased animals: the 3 closed farms had all used IBR-BVD-PI3-BRSV-Lepto 5way vaccine (9-way vaccine) on arrival, and 2 of those farms had also used segregation of new additions for an unspecified amount of time, and were currently furnishing plastic boots to any farm visitors who did not bring their own disinfected boots; the 5 open farms included 3 that used 9-way vaccine on arrival, one of which also cleaned livestock trailers after unloading the replacement animals, one farm that tested replacements for BVD (antigen capture ear notch ELISA) [17] and tuberculosis (caudal fold tuberculin test), and one farm that tested replacements for BVD (antigen capture ear notch ELISA), Mycoplasma spp. (accepted mycoplasma culture methods) [31], and segregated new additions for an unspecified amount of time. Independent of testing replacement animals, producers were asked whether they had ever previously tested their herds for JD or BVD. Eleven (50%) of the farms answered that they had tested for JD, primarily by occasionally testing individual cows with clinical signs of the disease; these included 5 with closed herds and 6 farms that had purchased replacements during the previous year. None of the farms had tested the whole herd on any regular basis for JD. The remaining 11 farms (50%) could recall no previous testing for JD, including 8 with closed herds and 3 with open herds. None of the producers had tested the entire herd or tested part of the herd on a regular basis for BVD; some had tested some animals periodically for PI status, but details of their previous BVD testing programs were not clear, and records were not found. Among the farms having done no previous testing for either disease were the farm that was positive only for BVD and the farm with both JD and BVD detected. Sixteen (73%) of the 22 farms had had at least one previous positive test for JD before the current surveillance project. This included 7 of the 11 farms that could recall no previous JD testing, but they had participated in an earlier statewide JD surveillance project with one of the authors (DW), and had been test-positive in bulk tank milk for JD. They had been informed of the previous positive results, but this had not persuaded the owners to perform any additional JD testing. Of the 11 farms that had performed JD testing on some cows, 9 had at least one previous positive result. Segregation or identification of known JD-positive cows Producers were asked about the possibility of segregating all known JD-positive cows; none said they would segregate. Five (24%) of the 21 farms detected with JD would not segregate, and the remaining 16 (76%) producers were not sure. When asked regarding adopting some form of identification of known JD-positive cows, 14 (67%) of the 21 producers whose herds were detected with JD said they would identify the positive cows. Calving practices Producers were asked whether known JD-positive cows, or when applicable, BVD-positive cows would be allowed to calve again on the farm, and if they were allowed to calve again, whether known JDpositive cows, or when applicable, BVD-positive cows, would calve in a different area than test-negative cows. Twelve (57%) of the 21 farms that were detected positive for JD would allow JD-positive cows to calve again on the farm, including 9 of the 16 that had had at least one positive test for JD, and 3 of the 5 that had never had any positive JD results before the current surveillance project. Six (29%) producers answered that they would not let any known JD-positive cows calve again on the farm, 5 that had had some positive results previously, and one that had tested individual cows but never had any positive results before the current project. Three (14%) answered that they were not sure whether they would let known JD-positive cows calve again on the farm, 2 with some previous positive results, and one that had never tested for JD before the current project. Both producers whose herds were detected BVD-positive said that whether BVD-positive cows would calve again on the farm would depend on how many there were; if "only a few PI's" were found, they would all be culled right away. The farm with both JD and BVD was one of those described above that would allow JD-positive cows to calve again on the farm. No producers who would allow JD-positive or BVD-positive cows to calve again on the farm said that such cows would have a separate calving area. All 12 who said that positive cows would calve again (including the farm with both JD and BVD) said they would calve in the same calving area as other cows and all 4 who were not sure about allowing positive cows to calve again also said they were not sure regarding a separate calving area. Calf feeding procedures Calves were fed pooled (mixed from > 1 cow) colostrum on 14 (64%) farms, including both farms detected BVD-positive. Of the remaining 8 farms that fed only colostrum from individual cows, 6 (75%) also pasteurized all discard milk fed to calves. Only 2 (14%) of the 14 farms feeding pooled colostrum also pasteurized their discard milk fed to calves. Thus 12 farms (55%) fed both pooled colostrum and unpasteurized discard milk to calves. BVD vaccination, manure handling, and clinical signs observed All 22 farms used 9-way vaccine which included BVD vaccine (some killed, some modified live, some farms used a combination of both at different times). Six (27%) farms used machinery to move manure and also to handle feed; 3 (50%) of them did not wash machinery after contacting manure and before the next contact with feed. Of the 21 farms detected with JD, 17 (81%) had observed adult cows becoming thin while maintaining a good appetite; 11 (52%) had seen adult cows contract diarrhea and subsequently die. Both BVDpositive farms had observed abortions. The farm that was positive only for BVD had 30 sheep of all ages mixed with dairy animals. The sheep were not vaccinated against BVD. On the 16 farms where milking was observed, evaluation was made regarding whether teats were covered with predip well, fair or poor according to a visual scale standardized among the 4 investigators (the udder wash farm was one where milking was not observed). Teats were covered with predip well on 12 farms (75%) and fair on 4 farms (25%). Three of the 4 farms with only fair teat dip coverage spray dipped, but one farm cup dipped. A common (used on multiple cows) cloth (n=8) or common paper towel (n=4) was used to wipe off teats following disinfection on 12 (55%) of farms; the other 10 farms (45%) used an individual-cow cloth (n=8) or paper towel (n=2). On 18 farms, there was sufficient information available to calculate turns of the milking parlor per hour. Mean and median turns/hour were 3.8 and 3.7, respectively, ranging from 2 to 5.9/hour. Four of the 6 farms with < 3 turns/hour had 12 to 18 milking units, and 4 of the 6 farms with >4 turns/hour had 32 to 160 milking units. Rubber inflations (teat cup liners) were used on 17 farms (77%) and silicone inflations were used on 5 farms (23%). Frequency of changing inflations was known by the managers of 16 farms (13 using rubber, 3 using silicone), therefore the number of individual cow milking's (ICM) for which inflations were used could be calculated. For rubber inflations, mean and median ICM of use were 1867 and 1710, respectively, ranging from 660 to 3119 ICM. The upper limit of recommended use for rubber inflations is 1200 ICM [32], so 11 of the 13 farms (85%) overused rubber inflations. For silicone inflations, the 3 farms used them for 2835, 3982 and 9000 ICM. The upper limit of recommended use for silicone inflations is 7000 ICM, therefore one of the 3 farms (33%) overused silicone inflations. Lactating and dry cow treatments for mastitis Lactating cows with clinical signs of mastitis were treated with intramammary antibiotics on 20 (91%) farms. The most commonly used antibiotics for lactating cows were: ceftiofur, 10 farms (50%); cephapirin, 4 farms (20%); pirlimycin, 3 farms (15%); amoxicillin, 2 farms (10%); ampicillin, one farm (5%). One farm (the only organic dairy) used no treatment for mastitis cases, and one farm used I.M. oxytocin only. Five of the above farms that routinely used antibiotics sometimes treated clinical mastitis cases with I.M. oxytocin as the only treatment. None of the farms treated clinical mastitis cases with antiinflammatory therapy. Dry cow therapy -intramammary infusion of long-acting, slow release antibiotics at the beginning of the non-lactating period -was administered to all cows when they were dried off on 20 (91%) farms. The most commonly used dry cow antibiotics were: cephapirin, 6 farms (30%); penicillin and novobiocin, 6 farms (30%); ceftiofur, 5 farms (25%); penicillin-dihydrostreptomycin, 2 farms (10%); cloxacillin, one farm (5%). The organic farm used a wax and oil teat sealant on selected cows, but no dry treatment on most cows, and one farm used no dry treatment of any kind because of fear of adulteration of milk. Seven farms (32%), all of which also used antibiotic dry cow therapy, used a teat sealant following dry cow treatment. Feeding monensin The 21 producers with JD detected in their herds were asked regarding feeding of the ionophore monensin to different age groups of dairy animals. Monensin has been reported as a chemoprophylactic agent associated with reduction of the new infection rate, decreased inflammation within affected tissues, and reduced prevalence of milkpositive cows and fecal-positive calves with JD [33]. Seventeen (81%) farms fed monensin: 10 (48%) fed mature cows, 9 (43%) fed first lactation cows, 14 (67%) fed breeding age heifers and 7 (33%) fed calves monensin. Other management practices Tail docking was practiced on 12 (55%) of farms; neither of the BVD-positive farms docked tails. Coliform mastitis vaccine using J5 antigen was administered to cows on 19 (86%) of farms, including both farms with herds detected BVD-positive. Discussion Mean herd size and milk production of JD and BVD-positive herds were both above Utah average, and SCC/ml in bulk tank milk was below (better than) average. Many herds test-positive for JD or BVD had been closed to any outside animals for years. Biosecurity measures on most farms, whether they had purchased animals recently or not, were lacking; most producers did not test for BVD or JD (or most other diseases) when purchasing replacement animals of any age or sex into their herds, or even segregate new additions for any time before mixing them into the resident herd. This continues a longstanding pattern of dairy producers poorly adopting recommended screening or quarantine practices when adding replacements to their herds [15,34]. The majority of farms had observed clinical signs typically associated with JD or sometimes BVD such as adult cows developing diarrhea progressing to death, and nearly all had seen cows losing weight and becoming thin while maintaining a good appetite [2,6,19,21]. Previously positive tests for JD or BVD, either in bulk tank milk or on occasional individual animals, did not induce most producers to do further individual testing or institute specific control measures. While two-thirds of producers stated that they would uniquely identify known JD-positive cows, none were willing to segregate the positive cows. The majority of producers would allow known JDpositive cows to calve again on their farms, and producers with BVD detected in their herds were equivocal. No producers would have a separate calving area for JD or BVD-positive cows either. This was despite previous information and recommendations regarding the importance of separate calving areas for and preferably isolation of JDpositive cows to reduce the spread of the disease within dairy herds [1,15]. It is often recommended that BVD-positive cows (in the U.S. those detected are nearly all PI animals) be culled (19,20), but economic studies do not conclusively find this to be cost-effective, including the practice of culling PI animals [19,21]. In this study, producers were not committed to culling BVD-positive cows. Of the one-fourth of producers who used the same equipment to move manure and handle feed, half would not wash the equipment between contact with the manure and feed. Most farms fed both pooled colostrum and unpasteurized discard milk to calves, while less than one-third of farms fed only individual-cow colostrum and only pasteurized milk to calves. These practices were in place regardless of the evidence and recommendations within the industry that the above control measures help reduce the likelihood of calves contracting JD [14]. One farm positive for BVD had sheep of all ages mixed with the dairy cattle. The sheep were not vaccinated against BVD. It is common for sheep to be infected with BVD virus, and although considered an unusual route, they can be infectious to cattle, including being associated with the birth of PI calves [35]. While not directly related to JD or BVD, it was of interest that 85% of farms overused rubber inflations (teat cup liners), and one-third overused silicone inflations. Inflations are the only part of the milking system that touches cows, and an important source of some kinds of new intramammary infections and teat end irritation [36]. Nevertheless, it has been the experience of the authors (DW, GG) for over 25 years that one of the most common categories of inadequate maintenance of milking systems on most dairy farms is overuse of inflations. Many recommended control measures for prevention of introduction and/or to reduce the new infection rate of JD or BVD were poorly adopted. Most farms in the study had previous diagnostic evidence of the presence of JD in their dairy herds, whether from bulk tank milk or individual cow testing and all had recently been informed through their participation in a voluntary surveillance project that they had tested positive for JD or BVD. This continues a decades-old pattern of general apathy by many producers regarding attempted elimination or reduction of the prevalence of JD or BVD, or even elimination of only the clinical JD cases and/or only the PI BVD cattle from their herds. Dairy producers often respond that they think control measures for JD, BVD or other diseases recommended to them by veterinarians and other herd health advisors make sense, including financial sense, and would be beneficial, but they either find them unimportant, impractical, or inconvenient [35,37,38].

v3-fos

2017-08-03T02:54:31.617Z

2015-12-18T00:00:00.000Z

4802017

s2

Fecal microbiome of growing pigs fed a cereal based diet including chicory (Cichorium intybus L.) or ribwort (Plantago lanceolata L.) forage Background The purpose of this study was to investigate how inclusion of chicory forage or ribwort forage in a cereal-based diet influenced the fecal microbial community (microbiome) in newly weaned (35 days of age) piglets. The piglets were fed a cereal-based diet without (B) and with inclusion (80 and 160 g/kg air-dry forage) of vegetative shoots of chicory (C) and leaves of ribwort (R) forage in a 35-day growth trial. Fecal samples were collected at the start (D0), 17 (D17) and 35 (D35) days after weaning and profiles of the microbial consortia were generated using terminal restriction fragment length polymorphism (T-RFLP). 454-FLX pyrosequencing of 16S rRNA gene amplicons was used to analyze the microbial composition in a subset of the samples already analyzed with T-RFLP. Results The microbial clustering pattern was primarily dependent on age of the pigs, but diet effects could also be observed. Lactobacilli and enterobacteria were more abundant at D0, whereas the genera Streptococcus, Treponema, Clostridium, Clostridiaceae1 and Coprococcus were present in higher abundances at D35. Pigs fed ribwort had an increased abundance of sequences classified as Treponema and a reduction in lactobacilli. However, the abundance of Prevotellaceae increased with age in on both the chicory and the ribwort diet. Moreover, there were significant correlations between the abundance of Bacteroides and the digested amount of galactose, uronic acids and total non-starch polysaccharides, and between the abundance of Bacteroidales and the digested amount of xylose. Conclusion This study demonstrated that both chicory and ribwort inclusion in the diet of newly weaned pigs influenced the composition of the fecal microbiota and that digestion of specific dietary components was correlated with species composition of the microbiota. Moreover, this study showed that the gut will be exposed to a dramatic shift in the microbial community structure several weeks after weaning. Background In order to maintain normal physiological functions in the digestive tract of pigs, a minimum level of fiber has to be included in the diet [1]. Moreover, by increasing the fiber level in the diet of weaned piglets, the pH in the hindgut is reduced [2] and the content of organic acids in the stomach and the ileum is increased [2,3]. These changes in the gut environment, induced by fiber inclusion, indicates a shift in dominating bacterial population which may impair the conditions for pathogenic bacteria and may be more beneficial for maintaining gut health [1,4]. Fiber properties (soluble vs. insoluble) and age of the pig will modulate the impact of fiber level on the gut environment [2]. Soluble fiber is well digested by both growing pigs and sows, whereas sows have a higher capacity to digest insoluble fiber [5]. Chicory (Cichorium intybus L.) and ribwort (Plantago lanceolata L.) are dicotelydenous herbs with a high content of uronic acid (80-90 g per kg dry matter) of which approximately 80 % is soluble. Uronic acid in dicotelydenous plants derives from galactosyluronic acid that is the building block in pectins [6]. Uronic acid has a high digestibility in forage crops fed to growing pigs [7,8]. Moreover, pectin substances from sugar beet pulp have been shown to influence the gut microbial ecosystem, in particular by increasing the fecal Lactobacillus counts [9], and is therefore a very interesting fiber component in piglet nutrition. We have previously shown that inclusion of chicory in the diet influenced the intestinal micro-environment and the microbiota in pigs [10][11][12]. For example, inclusion of chicory forage was associated with higher abundance of ileal lactobacilli and colonic butyrate producing bacteria [11]. In addition, chicory forage inclusion influenced the relative abundance of Prevotella, but the change in abundance was dependent on species of Prevotella [10,12]. We also found correlations between specific bacterial groups and short chain fatty acid (SCFA) profiles, which shows that inclusion of chicory is influencing the intestinal micro-environment. However, less is known about ribwort inclusion and its influence on the microbiota. Ribwort forage contains a range of bioactive and antimicrobial compounds that may influence the microbiota [13]. The recent technological development of the Next Generation Sequencing platforms has facilitated a deeper analysis of the gut microbiota composition, more recently referred to as "microbiome". The aim of this experiment was therefore to characterize the post weaning gut microbiome and to get a deeper understanding of how inclusion of chicory and ribwort forage in a cereal-based diet influences the microbiome in weaned piglets. Furthermore, we aimed to identify correlations between dietary components and the composition of the intestinal microbiome. Experimental setup The study included 19 5-wk old weaned and castrated male piglets (Swedish Landrace × Yorkshire) used in a growth trial. The pigs originated from five different litters and had a live weight of 11.7 kg (s.d. 0.8 kg) at the start of the experiment. The piglets were purchased from a herd free from diseases according to the A-list of International Office of Epizootics [14] and were housed individually in pens equipped with a rubber mat, urine drainage and no bedding. Piglets had ad libitum access to feed and water throughout the experiment, except for the first days when the feed allowance was restricted. The experimental diets comprised a cereal-based basal diet (B) and two diets composed to contain 80 and 160 g/kg air-dry forage made from vegetative shoots of chicory (C80, C160) and leaves of ribwort (R80, R160), respectively. The basal diet was composed of ground cereals (wheat, barley and oats), milled through a 5-mm screen, supplemented with protein, amino acids, mineral and vitamins to meet nutritional requirements of piglets (Table 1). In diets with chicory and ribwort inclusion, the cereal mixture was substituted with the herbs on an air-dry basis ( Table 1). The herbs where harvested at the vegetative stage (September) with a stubble height of c. 5 cm and dried with forced air at 30°C for a week and milled through a 5-mm screen before mixing with the other feed ingredients. The experiment was organized according to a randomized block design, with three replicates for the low inclusion level of forage, four replicates for the highest inclusion level of forage and five replicates for basal diet ( Table 2). Fecal samples were collected at the start of the experiment (D 0), after 17 d (D 17) and after 35 d (D35). The experiment was carried out at the Swedish University of Agricultural Sciences (SLU) and was approved by the ethical committee of the Uppsala region. Chemical composition and digestibility of diets Chemical composition of the experimental diets (Table 3) as well as the digestibility of the dietary components had been characterized previously [7]. The chemical analysis included quantification of total soluble and insoluble non-starch polysaccharides (NSP) and their constituent sugars including uronic acids. The digested amount of arabinose, xylose, mannose, galactose, glucose, uronic acids, and total NSP was based on the intake and digestibility of each component. Terminal-restriction fragment length polymorphism (T-RFLP) analyses DNA was isolated from fecal samples in triplicates according to the method described by Leser et al. 2002 [15]. The 16S rRNA genes were PCR amplified from each DNA extract using the general bacterial primers Bact-8 F (5′-AGAGTTTGATCCTGGCTCAG-3′) [16], 5′ end-labeled with 6-carboxyfluorescein (6-FAM), and 926r (5′-CCGTCAATTCCTTTRAGTTT-3′) [17] under conditions described elsewhere [18]. DNA product amounts and sizes were confirmed by agarose gel electrophoresis using GeneRuler 100 bp DNA ladder Plus (Fermentas Life Sciences, Burlington, Canada) as a size marker. PCR products were digested with restriction enzyme HaeIII and the resulting fragments were separated on an ABI 3700 capillary sequencer (Applied Biosystems, Foster City, CA). The sizes of the fluorescently labelled fragments were determined by comparison with the internal GS ROX-500 size standard (Applied Biosystems). The T-RFLP electropherograms were imaged using the Peak scanner software (Applied Biosystems) and relative peak areas of each terminal restriction fragment (TRF) were determined by dividing the area of the peak of interest by the total area of peaks, using 50 and 500 bp lower and upper threshold values, respectively. Data was normalized by applying a threshold value for relative abundance at 0.5 %, and only TRFs with higher relative abundances were included in the remaining analyses. Taxonomic analysis Sequences were checked for quality and sequences that were less than 200 bp in length, that contained incorrect primer sequences, or that contained more than 1 ambiguous base were discarded. Assignment of sequences to samples was based on the 4-bp barcode. Remaining sequences were then subjected to complete linkage clustering using the pyrosequencing pipeline at RDP-X using a conservative 5 % dissimilarity to define operational taxonomic units (OTUs) because of the short sequence length. The most abundant sequence from each OTU was selected as a representative sequence and was taxonomically classified by BLAST searching against a local BLAST database comprised of 269,420 bacterial 16S rRNA gene sequences longer than 1,200 bp with good Pintail scores from RDP v. 10.7. The OTU inherited the taxonomy (down to genus level) of the best scoring RDP hit fulfilling the criteria of ≥ 95 % identity over an alignment of length ≥ 180 bp. Statistical analysis To visualize time or diet related effects in composition of the microbiota, relative abundance values and sizes of T-RFLP fragments were analyzed with principal component analysis (PCA) using the software Canoco (version 4.5, Microcomputer Power Ithaca, NY, USA). For the 454 data, principal coordinate analysis (PCoA) based on Bray Curtis distances were used to monitor clustering pattern of the microbial architecture using the software PAST [20]. To identify specific taxa that correlated with diet or time, statistical analyses were performed using GLM in SAS (SAS Institute, Cary, NC, USA, version 9.1). Pearson correlation analysis was used to identify correlations between digested amount of dietary components and the abundance of microbial taxa. The level of significance was set at P < 0.05 and the Benjamini and Hochberg method was used to account for multiple comparisons, based on global P values of the variables compared [21]. Pig performance Herb inclusion affected (P < 0.05) the average daily feed intake during the experiment (day 0-35; Table 2), with lower intake for the diet (R160) with the highest ribwort inclusion than for the other diets [7]. Inclusion of chicory did however not impair feed intake compared with the basal diet. Moreover, as a consequence of the lower feed intake on the diet with the highest inclusion of ribwort, the daily weight gain was lower (P < 0.05) than for the other diets [7]. There was no negative impact on the daily weight gain of including chicory in the diet. T-RFLP analysis of the fecal microbiome Profiles of the microbial consortia in fecal samples were generated using T-RFLP. Principal component analysis was used to identify patterns in the microbiome that could be explained by factors such as time or diet effects. The PCA showed a clustering pattern that largely was dependent on age of the pigs (Fig. 1). All samples collected at weaning (D 0) clustered separately from the samples collected at D 17 and D 35. There was a large variation in microbial composition between individual pigs at weaning, and the samples were subsequently spread out along the first principal component (PC 1). No apparent clustering pattern of diet effects could be visualized in the PCA scatter plots (Fig. 1). Barcoded 454 pyrosequencing analysis of the fecal microbiome Pyrosequencing of 16S rRNA gene amplicons was used to analyze the microbial composition in a subset of the samples that had already been analyzed with T-RFLP for a more detailed view of the microbial composition. 16S data was obtained from nine pigs from samples collected both at D 0 and D 35 (Table 2). After quality filtering, 31,620 sequences were obtained, with an average of 1,757 sequences per sample (range 1,386-2,095). Analysis of the sequence data revealed a large individual variation between pigs but also that the fecal microbiome at weaning and 35 days after weaning was dominated by the same main phyla, primarily members of the Firmicutes (F) and Bacteroidetes (B) phyla. These were mainly dominated by the Lachnospiraceae (F), Ruminococcaceae (F), Lactobacillaceae (F), Streptococcaceae (F) and Prevotellaceae (B) families. In addition, a large fraction of the sequences could not be matched to the sequences in the public databases indicating presence of undescribed species. Development of the post weaning microbiome Principal coordinate analysis (PCoA) based on Bray Curtis distance metrics was used to visualize clustering patterns in the 16S data. The samples arranged into two clusters and in agreement with the T-RFLP data analysis the segregation of samples were associated with the age of the pigs (Fig. 2). Comparing samples at D 0 and D 35 revealed a maturation of the gut microbiota with dramatic changes in the relative abundance of certain genera. Lactobacilli and enterobacteria were more abundant in younger pigs (P < 0.05), whereas the genera Streptococcus, Treponema, Clostridium, Clostridiaceae1 and Coprococcus were present in higher abundances in older pigs (P < 0.05; Fig. 3). In agreement with the T-RFLP data analysis, the 16S data showed that individual pig samples collected at D 0 had a larger variation in the community structure than the samples collected at D 35 (Fig. 2). Diet dependent influences on the microbiome Despite the large temporal variation of the developing microbiota it was possible to identify changes that could be linked to inclusion of chicory or ribwort. As indicated earlier, the abundance of lactobacilli was reduced in samples collected at D 35. The reduction of lactobacilli was however significantly more pronounced in pigs fed the ribwort diet (P = 0.004; Fig. 4). Instead the pigs fed ribwort had a significantly increased abundance of sequences classified as Treponema (P = 0.011; Fig. 4). Another microbial group that was associated with the diet regime was Prevotellaceae. The abundance of Prevotellaceae decreased in animals fed the control diet whereas it increased in animals fed both the chicory and the ribwort diet (P < 0.001; Fig. 4). Correlations between digestion of dietary components and specific groups of microbes Pearson correlations were tested between abundance data from all microbial taxa from samples collected at D 35 and the digested amount of arabinose, xylose, mannose, galactose, glucose, uronic acid and total NSP from the same samples. We found a significant correlation between the abundance of Bacteroides and the digested amount of galactose and uronic acids (Table 4). In addition, the abundance of Bacteroides was also positively correlated with the digested amount of NSP, but the correlation did not reach significance (Table 4). Furthermore, the abundance of Bacteroidales was positively correlated with the digested amount of xylose (Table 4). Discussion The fecal microbiome changed dramatically in composition after weaning, regardless of diet, but inclusion of the different fiber sources had an impact on the development of the post weaning microbiome. Inclusion of ribwort had a larger effect on the post weaning microbiome compared to chicory (Fig. 4). The abundance of lactobacilli was lower in samples collected at weaning (D 0) compared with samples collected 35 days post weaning (Fig. 3). However, for pigs fed the diet including ribwort, the abundance of lactobacilli had decreased to a larger extent compared with the other diets (Fig. 4). This indicates that ribwort inclusion has a negative impact on lactobacilli in the gut. Both chicory and ribwort have a high content of uronic acids, which derives from galactosyluronic acid and is a building block in pectins [6]. Pectin of plant origin, such as sugar beet pulp, has been used as a fibrous feedstuff in pig diets and resulted in an increased lactic acid bacteria (LAB) population in the small intestine [22]. In addition, we have earlier shown that inclusion of chicory forage was associated with higher abundances of LAB, primarily in ileal digesta, to a lesser extent in colonic digesta [11] but not in fecal samples [10]. In the present study, the chicory feed did not impact the fecal lactobacilli compared with the control. It is therefore likely that the effect of chicory forage on lactobacilli occurs primarily in the small bowel. Our study showed that the abundance of Prevotella increased in pigs fed the chicory and ribwort diets compared to the control feed. Prevotella is one of the abundant bacteria found in the pig gut. This group of gram-negative bacteria is able to produce several xylanases, mannanases, β-glucanases, and corresponds to soluble xylan utilization, and is therefore likely important for biodegradation of complex sugars in the gut [23]. Rural African children and rural Papua New Guinea habitants, living on a fiber-rich diet harbor a gut microbiota rich in Prevotella spp. while this community is less abundant in European children and habitants in the United States, living on a 'Western' diet (typically high in animal protein, sugar, starch, and fat and low in fiber) [24,25]. This indicates that the abundance of Prevotella is influenced by the fiber content in the diet but the type of fiber is also important. For example, it was shown that ruminal Prevotella ruminicola and Prevotella bryanti responded in opposite directions to hay and grain-based diets [26]. In the current dataset, the abundance of Bacteroides was positively correlated with the digested amount of galactose and uronic acid. In addition, the abundance of sequences classified as Bacteroidales was correlated with the digested amount of xylose. Bacteroides and Prevotella are the major carbohydrate degrading organisms in the gut and it is therefore not surprising that these positive correlations were found. Uronic acid is extensively fermented in the colon, but utilization of uronic acid is restricted to few genera. Bacteroides have the ability to utilize uronic acid [27,28] as too do Faecalibacterium [11,29]. We could, however, not find a significant correlation between the abundance of Faecalibacterium and the digested amount of uronic acid. The pigs fed the highest inclusion of ribwort had a significantly lower feed intake and weight gain compared with pigs fed the other diets. However, it is not known if the reduced weight gain and feed intake influenced the Abbreviations: NSP non-starch polysaccharides microbiome. Neither is it possible to conclude to what extent the dietary influence in the microbiota structure was masked by the natural change in microbiota structure after weaning. The development of the post weaning microbiome was characterized by a dramatic shift in the bacterial composition with a marked reduction of lactobacilli and Enterobacteriaceae, and an increased abundance of the genera Streptococcus, Clostridium, Clostridiaceae1, Treponema, and Coprococcus. These bacterial groups are commonly detected in weaned pigs reflecting that the fecal microbiome in the pigs included in this study has a composition similar to what others have shown [30][31][32]. The dramatic change in the microbiome during weaning is in agreement with earlier studies in human infants [33,34], and in previous studies in pigs that have shown a shift from a Lactobacillus dominated microbial population towards dominance of Streptococcus [35,36]. In addition, the reduction in relative abundance of Enterobactericeae with increasing age was in agreement with earlier culturing data from the same animals [7]. Conclusion In conclusion, this study demonstrated that both chicory and ribwort inclusion as feed supplements in the diet of newly weaned pigs, influenced the composition of the fecal microbiome. The feed supplements were associated with a change in the abundance of Lactobacillus, Treponema and Prevotella. Furthermore, we showed that digestion of specific dietary components was correlated with the species composition of the microbiota. However, the most dramatic change in the microbiota was found when fecal samples collected 17 and 35 days post weaning were compared with samples collected at weaning and demonstrated that the gut will be exposed to a dramatic shift in the microbial community structure several weeks after weaning.

v3-fos

2017-07-04T20:54:19.966Z

2015-04-22T00:00:00.000Z

9472577

s2

Resistance to Sri Lankan Cassava Mosaic Virus (SLCMV) in Genetically Engineered Cassava cv. KU50 through RNA Silencing Cassava ranks fifth among the starch producing crops of the world, its annual bioethanol yield is higher than for any other crop. Cassava cultivar KU50, the most widely grown cultivar for non-food purposes is susceptible to Sri Lankan cassava mosaic virus (SLCMV). The objective of this work was to engineer resistance to SLCMV by RNA interference (RNAi) in order to increase biomass yield, an important aspect for bioethanol production. Here, we produced transgenic KU50 lines expressing dsRNA homologous to the region between the AV2 and AV1 of DNA A of SLCMV. High level expression of dsRNA of SLCMV did not induce any growth abnormality in the transgenic plants. Transgenic lines displayed high levels of resistance to SLCMV compared to the wild-type plants and no virus load could be detected in uninoculated new leaves of the infected resistant lines after PCR amplification and RT-PCR analysis. The agronomic performance of the transgenic lines was unimpaired after inoculation with the virus as the plants presented similar growth when compared to the mock inoculated control plants and revealed no apparent reduction in the amount and weight of tubers produced. We show that the resistance is correlated with post-transcriptional gene silencing because of the production of transgene specific siRNA. The results demonstrate that transgenic lines exhibited high levels of resistance to SLCMV. This resistance coupled with the desirable yield components in the transgenic lines makes them better candidates for exploitation in the production of biomass as well as bioethanol. Introduction Cassava (Manihot esculenta) is an important root crop in Africa, Asia and South America, providing energy for about one billion people. It is the 3 rd largest source of carbohydrates for human food in the world, a staple or subsidiary food for about a fifth of the world's population and raw material for starch based industries. Its flexible harvesting time, tolerance to adverse environmental conditions such as drought and poor soils, little requirement to agricultural fertilizers and high starch content make cassava one of the most attractive plants for starch production in future. In recent years, cassava has emerged as a potential biofuel plant, ranking among other high energy crops such as maize, sugarcane and sweet sorghum. Indeed, the annual yield of cassava-derived bioethanol was found to be higher than for any other crop, including sugarcane [1][2][3], and its bioethanol production has been increasing due to its economic benefits compared to other bioethanol production crops. Unfortunately, cassava production is being increasingly affected by cassava mosaic disease (CMD), resulting to losses estimated at 1.6 billion dollars [4]. CMD is caused by several cassava mosaic begomoviruses, which are transmitted, plant-toplant, exclusively by the whitefly Bemisia tabaci. The cassava bipartite begomovirus genome comprises two circular, single-stranded DNA components, which are DNA A and DNA B, and possess a segment of high sequence identity (*200 nucleotides in length) known as the common region (CR). The CR harbours the viral promoters, origin of replication and sequences involved in binding of DNA A-encoded replication associated protein (Rep), the only virus encoded product required for viral DNA replication [5]. DNA A encodes two overlapping virion-sense open reading frames (ORFs) AV2 and AV1, and at least four overlapping complementary-sense ORFs AC1, AC2, AC3 and AC4. These genes are involved in encapsidation, viral DNA replication and control of gene expression. AV1 encodes the coat protein gene (CP) and is the determinant of vector transmission in addition to its role in genome encapsidation. AC1 encodes a replication-associated protein (Rep), AC2 a transcriptional activator protein (TrAP) and also functions in the suppression of post-transcriptional gene silencing, and AC3 a replication enhancer protein (REn). AC4 plays a role as a suppressor of RNA silencing. DNA B encodes two gene products, BV1 and BC1, which encode the nuclear shuttle protein and the movement protein, respectively [6]. CMD is widespread in Africa and the Indian subcontinent [7]. African cassava mosaic virus (ACMV) was the first virus species found to be associated with CMD in Africa, although no fewer than seven begomovirus species are now recognized in Africa [8]. In the Indian subcontinent, Indian cassava mosaic virus (ICMV) has been shown to be associated with CMD [9]. Another species, Sri Lankan cassava mosaic virus (SLCMV), was identified in Sri Lanka and clearly linked to cassava mosaic disease in India [10]. ICMV and SLCMV are distinct among the viruses associated with CMD in Africa and are reported to cause serious cassava infection in India. Survey of cassava mosaic disease in India revealed that SLCMV is the most prevalent virus [11]. To date, a number of strategies to engineer CMD resistance in cassava have been reported mostly for ACMV [12]. For example, increased ACMV resistance in cassava has been developed in transgenic cassava plants expressing antisense RNA or dsRNA targeting the viral mRNAs of Rep (AC1), TrAP (AC2) and REn (AC3), or the viral untranslational common region [13][14][15]. Until now, no such report exists on the production of transgenic cassava plants resistant to SLCMV. SLCMV has recently become a major concern and is rapidly emerging as an important CMD prevalent in the Indian subcontinent, resulting in serious yield losses [11]. CMD is currently managed by multiplication and distribution of disease-free stem cuttings. It has been difficult to produce SLCMV-resistant cassava by conventional breeding because of high heterozygosity and inbreeding depression of elite cultivars or farmer-preferred landraces. As a result, new strategies to control SLCMV are desirable. Post-transcriptional gene silencing (PTGS) or RNA interference (RNAi) is a technology that offers significant potential to control plant viral pathogens. RNAi has been applied to generate resistance to African cassava mosaic virus [15], Cucumber mosaic virus, Zucchini yellow mosaic virus and Watermelon mosaic virus [16][17][18][19], Bean golden mosaic virus [20], Potato leaf roll virus, Potato virus Y and Potato virus X [21,22], Papaya ring spot virus [23] and Plum pox virus [24,25]. RNA interference (RNAi) is a conserved mechanism that recognizes double-stranded RNA (dsRNA) as a signal to trigger sequence-specific degradation of homologous mRNA. The key feature of RNAi is short dsRNA fragments known as "short interfering RNAs (siRNAs)" of 21-25 bp in length, which are produced by the cleavage of dsRNA by a ds-specific ribonuclease termed 'Dicer'. Once generated, the siRNA are then recognized by a ribonuclease complex known as the RNA-induced silencing complex (RISC) and used as a guide for the recognition and sequence-specific degradation of homologous mRNAs [26][27][28][29], resulting in post-transcriptional gene silencing (PTGS). Currently, the elite cassava variety, Thai cassava cultivar Kasetsart University 50 (KU50) one of the most important cassava cultivar in the world is grown by many farmers and biofuel industries in Asia under different names because of its high root yield and high root starch content with good germination and vigorous plant growth with wide adaptation [30]. Therefore, evaluation of its capacity for SLCMV resistance is of importance due to devastating impact of this virus on cassava production in the region. Unfortunately, engineering disease resistance in this cultivar has faced a major setback and difficulties largely due to lack of efficient and reproducible regeneration protocol. An important prerequisite for engineering plants for resistance to diseases is the availability of morphogenic culture that can be used in gene transfer techniques [31]. In this article, we report a simple, efficient, quick and reproducible regeneration protocol for cassava cultivar KU50 through somatic embryogenesis. This protocol allowed us to produce transgenic cassava lines that express dsRNA homologous to the region between the AV2 and AV1 of SLCMV. Transgenic lines obtained displayed high levels of resistance to SLCMV and agronomic performance in the transgenic lines was not affected in the presence of the virus. We show that the resistance is correlated with post-transcriptional gene silencing because of the production of transgenic specific siRNA. Plant regeneration in cassava Enlarged axillary buds ( Fig. 1, plate 2) were used for somatic embryo production and plant regeneration. When these were cultured on MSP, callus started 7 days after culture. Initially, most of the calli formed were soft and translucent (data not shown). After 2 weeks in culture on MSP medium in the dark, somatic embryos (SE), which had a globular appearance, were formed. Initially, the globular structures could not be separated easily from the originating tissue and the structures were fragile. Nevertheless, after additional 5 days in culture, distinct globular structures which closely resemble globular embryos in appearance were produced ( Fig. 1, plate 3). After 3 cycles of transfer of SE in the same medium at 2 weeks interval with constant removal of soft non embyogenic tissues, somatic embryos that developed torpedo stage were isolated from mother tissues and transferred to fresh medium of the same composition for further growth (Fig. 1, plate 4). After 4 weeks, the somatic embryos were transferred to MS2 supplemented with 0.5 mg/l BA and 0.5 mg/l IBA. Cotyledons appeared after 2 weeks of culture ( Fig. 1, plate 5). The cotyledons thus produced were transferred to hormone free MS medium and exposed to light for shoot and root development. After 4 weeks of culture under light condition, shoots and roots were produced (Fig. 1, plate 6). A summary of the main events is shown in Fig. 1. Also, the percentage of somatic embryos that produced shoots is shown in Fig. 2. Production of transgenic plants resistant to SLCMV RNAi construct and cassava transformation. In order to express virus-derived dsRNA in cassava, we produced a construct containing inverted repeat of 527 bp DNA fragment of SLCMV. The 527 bp fragment, which includes part of the AV2 (137-493 bp) and half of the AV1 (297-534 bp) spans from nucleotide 8-534. To ensure stability of the inverted repeat in Escherichia coli, the two DNA fragments were separated by a 278 bp cat 1 1 st intron spacer derived from castor bean catalase gene [32]. The entire cassette was cloned in the plant transformation vector, pEKH2IN2 yielding pEKH2IN2SLCMV (Fig. 3), with the SLCMV gene being driven by cauliflower mosaic virus (CaMV) 35S promoter. Somatic embryos were inoculated with Agrobacterium and plants were regenerated as described above. In order to avoid possible chimeric plants, the shoots produced were subcultured in selective rooting medium. After 3 rounds of subculture, the chimeric shoots completely bleached and died or produced shoots on the surface of the medium while only 10 produced roots in the medium. Eight plantlets out of the 10 rooted shoots were transgenic as transgenic plants was analyzed by northern hybridization by hybridizing total RNA with a DNA probe of SLCMV transgene. Our result shows that exception of line K3, which had high level expression, very little or no transgene transcript could be detected in the other transgenic lines tested. Since northern blots represent the steady state of the RNA concentration, but not the transcription rate; this could indicate that in these lines, the dsRNA became quickly degraded due to activation of PTGS [18]. No expression could be detected in the wild-type plants (Fig. 5C). Plant inoculation and symptom screening. After screening transgenic plants by Southern and northern hybridization for siRNA accumulation and phenotype comparison of in vitro plants, we selected plant lines that were positive for agroinoculation with infectious clone of SLCMV. Since the number of plants was few, six lines, 3 plants per line were used for inoculation. Except for transgenic line K3 which was susceptible to the virus, all other transformants displayed high levels of resistance (Table 1). Upon inoculation, mild mosaic symptoms began to appear on new emerging young leaves of the wild-type plants and transgenic line K3, 7 dpi ( Fig. 6, Table 1). The symptoms, which started as reduced chlorosis mostly close to the veins, quickly spread to the entire leaf and by 15 dpi, all the older leaves of the wild-type plant and most of the older leaves of line K3 have developed severe mosaic symptoms (Fig. 6). By 28 dpi, severe mosaic symptoms which included mosaic bleaching of leaves, leaf deformation and decrease in leaf size was observed in the control plant and transgenic line K3, whereas all the other transgenic lines (K4, K6, K7, K9 and K10) were free of symptom (Fig. 6). However, 40 days after inoculation, mild symptoms like reduced chlorosis, but not mosaic formation, leaf deformation or decrease in leaf size were observed in these transgenic lines (Table 1). These mild symptoms were completely obliterated 2 weeks later. This was further supported by the fact that the newly developed symptom-free recovered leaves had no viral-DNA accumulation as determined by PCR and RT-PCR compared with the symptomatic leaves of the wild-type and K3 transgenic plants. These observations clearly established that these transgenic lines displayed high levels of resistance to SLCMV. Since different leaves that emerged after inoculation usually showed a range of symptoms severity especially in the wild-type and susceptible transgenic line K3, we quantified disease severity per plant by evaluating the number of emerging leaves showing mosaic symptom at 45 dpi. Symptom severity was evaluated according to a standard scale of 0 (asymptomic) to 3 (severe mosaic, >76% of leaf area, leaf deformation) (Fig. 7). Based on the above scale, disease indices were calculated according to the formula shown in materials and methods. As shown in Table 1, all the emerging new leaves of the wild-type plants and transgenic line K3 developed a ranged of symptoms, from mild (grade 1) to severe (grade 3). In the wild-type plants, of the 42 leaves that were scored for the 3 plants, 21 had severe symptoms classified to be of grade 3, 12 leaves were classified to be of grade 2, while 9 were classified to be of grade 1 severity score (Table 1). Consequently, disease index in this plant was high (76.2%) and the plant was rated as being highly susceptible to the virus (Table 1). In transgenic line K3, among 48 leaves scored, 15 were found to present symptoms of grade 3 severity score, whereas 21 and 12 leaves had grade 2 and 1 symptoms, respectively. Disease index calculated for this line was 68.8%, hence the line was classified as being susceptible (S) to the virus. It is worth noting that disease severity in these plants increased with age of the leaves i.e. lower leaves had symptoms which were mostly of grade 3 severity score compared to upper leaves in which the symptoms were of grade 2 or 1. Compared to the wild-type and transgenic line K3, only a few leaves of the remainder of the transgenic lines presented mild symptoms classified to be of grade 1 severity score (Table 1). For example, in transgenic line K4, only 3 leaves out of the 63 leaves that were scored from the three plants had symptoms classified to be of grade 1. In these transgenic lines, disease indices were very low ranging from 1.5% in line K4 to 6.3% in line K9. Therefore, these transgenic lines were rated as having high levels of resistance (HR) to the virus. Next we determined whether agronomic performance of these plants might be affected in the presence of the virus. First, we compared the plant height of the inoculated transgenic plants and the mock inoculated plant at 60 dpi (Table 2). There were no differences between Disease rating is based on the calculated disease indices. Symptom severity score, the intensity of the disease on the leaf is expressed on a scale of 0-3 grades (0, no symptom; 1, mild/faint mosaic symptoms; 2, moderate mosaic symptoms; 3, severe mosaic symptoms, as shown in Fig. 7). Plants with a disease index of 0% were considered as immune, those with a disease index <25% as having high levels of resistance (HR), those with a disease index (Table 2). Compared to the mock inoculated control plant, the wild-type plant and the susceptible transgenic line K3 were significantly shorter (less than 60 cm). Second, we measured the yield of the plants which is an important aspect for biofuel industries. After taking the heights, the plants were uprooted and the number, length and weight of tubers were recorded. As shown in Fig. 8 and Table 2, the number of tubers in the wild-type and susceptible transgenic line K3 were significantly fewer (4 and 2, respectively) compared to the mock inoculated control plant and the resistant transgenic lines in which the number of tubers harvested per plant was 7. In fact, in line K9, up to 9 tubers were harvested per plant. Furthermore, there were no differences in length of tubers between the mock control plant and the resistant transgenic lines. However, in the weight of tubers, significant differences were observed. Tubers obtained from transgenic line K4 were noted to weigh more than those harvested from the other resistant transgenic lines and the mock inoculated (Table 2). Together, these results show that agronomic performance of the resistant transgenic lines was unimpaired after infection with the virus. We assessed the level of transmission of SLCMV to cassava by mechanical inoculation with infectious clone. Six out of the 7 Wild-type plants inoculated presented symptoms, which ranged from leaf curling, stunted growth and chlorosis, showing 85.7 percent transmission across two independent experiments (Table 3). High transmission efficiency of 71.4% was observed in Table 3). Accumulation of siRNA in transgenic plants. Before challenging the plants with SLCMV clone pSL7, northern analysis was carried out to detect SLCMV-specific siRNAs in transgenic and wild-type plants. The presence of siRNA is characteristic of PTGS and would indicate whether the PTGS response had been activated, especially in lines K4-K10 where transcript levels of the hairpin were either low or not detected. First, we screened the plants by PCR and RT-PCR to exclude a potential latent infection with SLCMV, which might result in virus-derived siRNA that are not of transgene origin. No SLCMV signal was detected in any of the lines tested (data not shown), indicating that no pre-induced PTGS effects are active in the transgenic plants. When northern blot was performed in the uninoculated transgenic plants, all transgenic lines, except line K3 were found to accumulate siRNAs signals of about 21-23 nt, homologous to the sense and antisense SLCMV sequences (Fig. 9A). No siRNAs were detected in the wild-type plants (Fig. 9A). Next, we probed for the presence of siRNA in uninoculated new leaves of transgenic and wild-type plants 60 days after challenge with SLCMV. All transgenic lines tested showed detectable levels of siRNA signals even in the susceptible transgenic line K3. Also, highly intense siRNAs signals were detected in the wild-type plant (Fig. 9 B). This result suggests that plant virus infection causes accumulation of siRNA in both susceptible and resistant phenotypes [17,18]. The presence of SLCMV siRNA in the resistant transgenic cassava lines after infection can be interpreted as a natural antiviral defense responses, that is, however, overcome by the virus in the wild-type plant and transgenic line K3. Screening of transgenic plants for presence of virus. PCR amplification (Fig. 10 A) and RT-PCR (Fig. 10B) were carried out to detect viral DNA 60 dpi in the same uninoculated new leaves analyzed for the presence of siRNA using coat protein specific primers. Viral DNA was not detected in new leaves of all the resistant transgenic lines (Fig. 10 A and B). On the contrary, strong signal of the CP gene were detected in new leaves of the inoculated wild-type plant and susceptible transgenic line K3 (Fig. 10 A and B). Discussion Regeneration of whole plants from cell culture systems is often the limiting step in the application of various biotechnological techniques to crop improvement. A prerequisite for genetic modification of cassava is a reliable regeneration system. Establishment of a regeneration system for elite cassava cultivar such as KU50 will open up the possibility for genetic manipulation of the cultivar and provide the information needed for handling and introduction of useful genes. Adventitious shoot regeneration via somatic embryogenesis is highly desirable as the process affords high multiplication rates and results in propagules which possess both root and shoot axes. Somatic embryos may develop from single cell and, dependent on the genetic stability of the regeneration system, plants with novel genotypes may be recovered [33]. In several cassava cultivars, apical meristem and young leaf lobes have been frequently used for regeneration [33][34][35][36]. However, using these tissues is time consuming, often requiring several steps including cycling of somatic embryos, use of liquid medium and other plant growth regulators such as NAA to produce cotyledonary embryos and regenerated plants are obtained after several months of culture initiation. For example, in KU50, Saleim et al. [36] reported regeneration from apical and lateral buds; however, plantlets were only produced after several weeks of cycling and upon transfer of cotyledons to medium containing BA, IBA and NAA. In our study, we used axillary buds to regenerate cassava plants via somatic embryogenesis. Plant regeneration was achieved within 3 months of culture initiation and there was no need to induce and maintain FEC in GD. Rather, somatic embryos were subcultured and maintained in MSP and after transfer to MS2 supplemented with 0.5 mg/l BA and 0.5 mg/l IBA, cotyledons were induced which later produced shoots on hormone free MS medium, approximately 80% of the cotyledons produced shoots (Fig. 2). We optimized our protocol for the cultivar and used it to produce transgenic plants showing high levels of resistance to SLCMV. This rapid and efficient protocol could be useful for other cassava cultivars. However, as different cultivars appear to have different responses to different culture media and explants, optimal conditions need to be established separately for each cultivar if this protocol is to be used. Cassava mosaic diseases can result in massive economic losses for industries using it for biofuel production, and also cause food and economic insecurity in countries where cassava is used as a staple food and cash crop. Therefore, attempts should be made to bring CMD under control in these regions. Unfortunately, control measures presently employed in infected regions are based on the chemical control of the vector population, with partial efficacy, environmental negative effect, elimination of natural enemies, and appearance of pesticide-resistant whitefly. Thus, producing disease resistant or tolerant varieties of cassava by genetic engineering is the best way to control the disease in the field. To date, considerable effort has been made by scientists to engineer cassava for resistance to African cassava mosaic virus by RNA silencing [13,14,35] using TMS60444. So far, such effort has not been applied to other cassava mosaic begomoviruses such as Sri Lanka cassava mosaic virus, and one of the most important cassava cultivar such as KU50 has not been engineered for resistance to CMD. In this study, we hypothesized that expression of dsRNA of a fragment of SLCMV in KU50 would lead to sequence-specific degradation of target mRNA interfering with viral replication and would reduce or prevent viral DNA accumulation and, consequently, appearance of symptoms. To achieve this, we produced a construct containing inverted repeat of 527 bp fragment of SLCMV. The DNA fragment contains a region encoding AV2 (137-493 bp) and half AV1 (297-527 bp). Among geminiviruses, amino acid sequences of AV1 (coat protein, CP) are fairly conserved [37] and known to be involved in the efficiency of virus infection. AV1 protein shares the same domain with AV2 (pre-coat protein), which together, they form a viral particle containing the sense fragment of Geminivirus DNA A. A recent report by Bull et al. [38] showed that AV2 of East African cassava mosaic Zanzibar virus (EACMZV) was necessary for infection in tobacco and cassava. The AV2 of Indian cassava mosaic virus (ICMV) has been shown to be involved in the cell-to-cell movement [39]. Furthermore, the AV2 protein of tomato leaf curl virus (ToLCV) and tomato yellow leaf curl virus (TYLCV) is shown to act as a potent suppressor of gene silencing activity. Silencing of AV2 gene of ToLCV by antisense RNA [40] and AV1/AV2 genes of ToLCV by artificial micro RNA [41] resulted to increased resistance to the virus in transgenic tobacco and tomato, respectively. Moreover, SLCMV DNA A has been reported to have properties of a monopartite begomovirus, which in the absence of DNA B, can induce upward leaf roll and vein swelling symptoms similar to those produced by monopatrtite begomovirus [10], indicating that the AV2 protein maybe involved in cell-to-cell movement. Therefore, we hypothesized that silencing of the AV1/AV2 genes would disrupt the encapsidation and the next round of virus infection, and would be a useful strategy to develop broad-spectrum resistance against CMD in cassava, and other begomoviruses where numerous distinct virus species/strain may cause disease in a particular crop. Using this construct, we demonstrated that transgenic cassava expressing 527 bp fragment of SLCMV in the form of an intermolecular intron-hairpin RNA displayed high levels of resistance to SLCMV infection compared to the wild-type plant. We show that resistance was acquired by RNA silencing through the production of transgene-specific siRNA. The present study and work reported elsewhere [40,41] suggests that AV1/AV2 could be targeted to confer resistance to geminiviruses. The use of siRNAs, an intermediate in the gene-silencing pathway, has become a powerful tool for specifically down regulating gene expression, and has been demonstrated successfully in a wide variety of cells and organisms [42]. It is one of the most important characteristics of RNA silencing and can be a reliable molecular marker that is closely associated with viral resistance in transgenic plants [18,21]. In this work, before transgenic plants were analyzed for siRNA accumulation, we analyzed the plants by PCR and RT-PCR to exclude a potential latent infection with SLCMV, which might result in virus-derived siRNA that are not of transgene origin. The absence of viral load in the transgenic and wild-type plants confirmed the absence of siRNA which in turn confirmed the absence of premeditated PTGS process. Of the transgenic lines analyzed for siRNA prior to challenge by the virus, one line, K3, did not produce detectable levels of siRNA and was susceptible to the virus. This indicates that RNAi mechanism was not activated in this line; hence mRNA was not degraded to siRNA. Although we did not check partial transgene deletion or rearrangement, their effect on the absence of siRNA accumulation in line K3 cannot be ruled out. It has been shown that the presence of siRNA prior to challenge by virus plays a vital role in the resistance of transgenic lines to the virus [18]. Plants that produced detectable levels of siRNA prior to inoculation were resistant to viral infections, whereas those in which siRNA could not be detected were susceptible. When cassava lines were challenged with the virus, we observed accumulation of SLCMV siRNA signals in all transgenic lines tested including the susceptible line K3 and the wild-type plants. Indeed, the signals were more intense in the wild-type plants and in line K3 than in the other transgenic lines. In the wild-type plant and line K3 in which siRNA signals were detected but the plants were susceptible to SLCMV infections, it is most likely that the virus was actively replicating despite PTGS, whereas in the transgenic plants, the dsRNA transgene provides an additional defence mechanism leading to plant recovery. In the susceptible plants, there seem to be a fragile balance between the plant and the virus: the plant suppressing the virus via PTGS (and possibly other mechanisms) and the virus responds by rapid replication and suppression of the host's silencing mechanism [43,44]. To overcome the plant defence mechanism, certain plant viruses encode proteins that suppress RNA silencing. In Sri Lankan cassava mosaic virus, AC4 proteins have been reported to block post-transcriptional gene silencing [45]. It is possible that AC4 proteins inhibited gene silencing by sequestrating siRNAs and blocking them from entering RISC, thereby preventing their use as a guide for the recognition and sequence-specific degradation of homologous mRNAs. AC4 probably suppresses the antiviral defense system in plants at the beginning of infection, resulting to plants developing symptoms rapidly after inoculation [46]. We observed different levels of siRNA accumulation in the transgenic lines before and after virus challenge. The reason for the variability remains to be elucidated. However, it had been demonstrated that the variability in siRNA accumulation is reminiscent of the variability when antisense genes had been introduced for gene suppression [47]. The different response of resistant transgenic plants to virus infection does not seem to depend on the accumulation of siRNA. For example, line K4, Fig. 9, the most resistant line, had low siRNA accumulation after virus challenge. Kalantidis et al. [18] reported that CMV-specific short RNAs increases with the copy number of the transgene. However, in our study, with the exception of line K6 which had 2 copies of the transgene, all the other transgenic lines had one copy each. Therefore, we do not know whether the production of short RNAs is coupled to a particular locus or influenced by environmental factors. The developmental stage of a leaf at the time of siRNA analysis may also play a role in the variability. More studies are required to clarify these assertions. Apart from transgenic line K3, which was susceptible to the virus (Table 1), the remainder of the tested lines developed symptoms in a few leaves at a much reduced level of severity (grade 1) with delayed appearance (more than 40 dpi). However, the plants quickly recovered as the symptoms completely disappeared 2 weeks later. Cassava plants can recover from mild symptoms but still carry virus load, which may be carried from one crop cycle to the next through the cuttings (stems) used as planting material since cassava is vegetatively propagated, or may be a source of inoculums by whiteflies. The propagation of plants that display no symptoms but carry a high virus load would be undesirable with regard to virus control under field conditions as such plants would serve as a source of inoculums for subsequent dissemination via whiteflies [48]. To confirm that the resistant lines do not contain virus load, they were analyzed for detecting viral DNA by PCR and RT-PCR. As no virus DNA was detected in these plants, it is likely that infected transgenic plants would be a poor source for spreading of the virus by whiteflies under field conditions. RNA-mediated resistance has advantages for environmental biosafety over protein mediated resistance as the potential risks of heterologous encapsidation and recombination of virus are diminished. The major drawback in RNA silencing is that it is usually highly sequence specific, and viruses having between 10-15% nucleotide diversity are mostly insensitive to the technology [49]. Sequence comparison of SLCMV used in this study and other begomoviruses show that SLCMV is more closely related to ICMV (DNA A, 84%; DNA B, 94% nucleotide identity) than African cassava mosaic virus (DNA A, 74%; DNA B, 47% nucleotide identity) [10]. Although we did not test our transgenic plants for resistance to other begomoviruses, it is most likely that the resistance gained here will be effective against other geminiviruses as the amino acid sequences of AV1 (coat protein, CP) are fairly conserved among geminiviruses. Furthermore, the resistance gained here will be more effective against ICMV than ACMV since the nucleotide sequence used for hairpin in the construct and the SLCMV strain used for infection share high homology with ICMV. In cassava, up to 90% of its starch is stored in the tubers, which makes them suitable for biofuel production. Therefore, high tuber yield is an important factor for bioethanol production in cassava. When cassava is attacked by CMD, there is reduced tuber yield in terms of number and size, many of them rotting, making them unsuitable for use for biofuel production. In this regard, we performed another round of inoculation and checked the agronomic performance of the plants in the presence of the virus. It was encouraging to see that, besides the absence of disease symptoms and virus load in the resistant transgenic plants, the agronomic performance of these plants was not affected by infection with the virus and the expression of SLCMV dsRNA did not intrinsically cause yield depression, as the plants presented similar growth when compared to the mock inoculated control plants and revealed no apparent reduction in the amount of tubers produced as well as weight of tubers (Table 2). This desirable yield components coupled with high levels of resistance to SLCMV in these transgenic lines makes them better candidates for exploitation in the production of biomass as well as bioethanol. In this study, since the number of replicates was low, we used mechanical inoculation with infectious clone to introduce SLCMV DNA into cassava. Cloned SLCMV DNA has been shown to be infectious to cassava by agroinoculation [50] and biolistic inoculation [11,51]. Here, we show that mechanical inoculation can be used to introduce SLCMV DNA to cassava, with variable degrees of infectivity. The efficiency of transmission observed here was seen to be similar to that reported earlier for SLCMV by agroinoculation [49] and for cassava brown streak disease (CBSD) by graft inoculation [52]. Altogether, this method, in addition to agroinoculation and biolistic approach, would be useful in screening large collections of cassava germplasm for SLCMV resistance. Production of SEs and regeneration Commercially important cassava cultivar KU50, which was provided from Genetic Resource Unit of CIAT, Cali, Colombia, was tested for its regeneration ability. The plant material was maintained as shoot cultures on MS2 (MS salts and vitamins [53] supplemented with 2% sucrose and 2 μM CuSO 4 ), solidified with 0.8% plant agar at 28°C with a 16-h photoperiod and subcultured at 8 week-intervals. All media supplements were added prior to adjusting the pH to 5.8 and autoclaving at 121°C for 15 min. For dark cultures, all plate cultures were sealed with parafilm and wrapped in aluminum foil. All cultures were maintained at a temperature of 28 ±2°C. The regeneration protocol is according to the method described by Bull et al. [54], but with significant modification. Nodal stem cuttings measuring about 10 mm were obtained from in vitro grown plants maintained in MS2. The tissues, which contained tiny axillary bud at each node, were cultured onto plates containing MS2 supplemented with 10 mg/l BA (MSB) for axillary bud enlargement. Six days later, enlarged axillary buds were isolated and transferred to plates containing MS2 supplemented with 12 g/l picloram (MSP). After 2 weeks in culture, somatic embryo structures (SEs) were produced on the axillary buds. Once the SE developed to torpedo stage, they were transferred to the same fresh medium (MSP) at 2 weeks interval for 6 weeks (3 cycles) for further growth. At each transfer, the soft non embryogenic tissues were removed. Four weeks later, the somatic embryos were transferred to MS2 supplemented with 0.5 mg/l BA and 0.5 mg/IBA for cotyledon production. To produce shoots and roots, the cotyledons were transferred to MS2 medium but without 2 μM CuSO 4 and exposed to light. Roots and shoots developed within 4 weeks in culture. Plant transformation RNAi vector construction. A DNA fragment (527 bp) of SLCMV segment A (KC424490) was isolated by RT-PCR using a pair of Deng's primers [55] ( Table 4). The DNA fragment has the highest homology to Sri Lanka cassava mosaic virus isolate Adivaran, encoding AV2 (137-493 bp) and half (297-527 bp) of AV1. The PCR product was purified and cloned into Gateway entry vector, pCR8/GW/TOPO (Invitrogen, Life Technology, Tokyo), which contains attL1 and attL2 recombination sites. The transformants were subjected to sequencing the targeted DNA fragment by using M13 primers and analyzed. The correct transformant containing the 527 bp fragment was subcloned in the sense orientation between the attB2 and attB1 recombination sites and in the antisense orientation between the attB1 and attB2 recombination sites on either ends of a 278 bp fragment of cat1-intron in the binary vector pEKH2IN2 (Nakamura et al. unpublished) by eLR clonase (Invitrogen, New Zealand) recombination reaction. The product was transformed into TOP10 chemical competent cells (Invitrogen, New Zealand) and selected on kanamycin-containing LB plates. Clones were verified by digestion with EcoRV. The plasmid, which contains marker genes for neomycin phosphotransferase (nptII) and hygromycin phosphotransferase (hpt), and the SLCMV gene being driven by cauliflower mosaic virus (CaMV) 35S promoter, was introduced into Agrobacterium tumefaciens strain EHA105 by triparental mating. Agrobacterium culture and plant transformation. Agrobacterium tumefaciens strain EHA105 carrying the binary vector pEKH2IN2SLCMV was cultured overnight on a reciprocal shaker (120 cycles/min) at 28°C in 50 ml liquid LB medium containing 50 mg/l kanamycin and 25 mg/l chloramphenicol. The bacterial suspension was centrifuged and then resuspended to final density of OD600 = 0.5 in inoculation medium, which was liquid MS2 containing 200 μM acetosyringone and incubated at room temperature for 1 h before inoculation. For axillary bud enlargement, nodal stem cuttings were cultured on MSB for 6 days. Thereafter, the enlarged axillary buds were isolated and cultured on MSP for 6 weeks with subcultures at 2 week-intervals for somatic embryo (SE) induction. The SEs were cycled again in the same medium for 4 weeks before being used for infection with Agrobacterium. These tissues were transferred to Erlenmeyer flasks containing Agrobacterium suspension for inoculation. The flasks were wrapped with aluminum foil and incubated on rotary shaker (R-20 min) at 80 cycles/min for 30 min. The tissues were retrieved by filtering, and placed on filter papers to remove excess bacteria. The SEs were then cultured onto plates containing MSP supplemented with 200 μM acetosyringone. The plates were wrapped with aluminum foil and co-cultivated at 24°C for 2 days and then exposed to light for another 2 days. Thereafter, the SEs were transferred to the MSP containing 20 mg/l meropenem and maintained at 28°C, dark for 1 week (pre-selection). After 1 week, the SEs were cultured on MSP containing 50 mg/l kanamycin and 20 mg/l meropenem for 2 weeks for maturation. If bacteria overgrowth was noted after co-cultivation, the tissues were washed three times with sterile distilled water containing 10 mg/l meropenem. For production of cotyledons, SEs were transferred to MS2 supplemented with 0.5 mg/l BA and 0.5 mg/l IBA and containing the same concentrations of antibiotics and exposed to light. Cotyledons were transferred to MS2 but without 2 μM CuSO 4 for shoot and root development. Regenerated plantlets having shoots and roots were excised and cultured in selective rooting medium, which was MS medium containing 3 g/l gelrite and 100 mg/l kanamycin. Putative transgenic shoots formed roots in the medium, while non-transgenic shoots developed roots on the surface of the medium. Therefore, shoots which produced roots in the medium were selected and micropropagated in vitro for subsequent molecular analysis and transfer to soil. Molecular analysis of transgenic plants. Genomic DNAs were extracted from young leaves of in vitro plants using a modified cetyltrimethylammonium bromide (CTAB) protocol [56]. Total RNA was isolated using Guanidine thiocyanate protocol [57] with slight modification. PCR, Southern and Northern analyses were carried out following standard protocols [58]. PCR amplification for the SLCMV was performed using primers specific to the SLCMV (SLCMV-5P and SLCMV-3P), whereas for nptII gene, the primers used were NPTII-5P and NPTII-3P (Table 4). For Southern blot, 15μg of the DNA was digested overnight with either HindIII, which cuts the T-DNA at two positions or XbaI, which cuts the T-DNA once, separated on a 0.8% agarose gel, transferred to a nylon membrane (Immobilon-Ny+ Transfer Membrane; Millipore Co, Billerica, MA, USA) and probed with SLCMV PCR-DIG labelled probe. The probe DNA fragment was generated from plasmid DNA pEKH2IN2SLCMV and labelled by PCR using DIG-2'-deoxyuridine 5'-triphosphate (DIG-dUTP) in the sense and antisense direction according to the supplier's instruction (PCR DIG probe synthesis kit, Roche Diagnostic GmbH, Boehringer Mannheim, Germany). Prehybridization (3 h) and hybridization (overnight) were carried out at 38°C and 42°C respectively, using high-SDS hybridization buffer containing 50% deionized formamide, 5 × SSC, 50 mM sodium phosphate (pH 7.0), 2% blocking solution, 0.1% N-lauroylsarcosine and 10% SDS. Post hybridization washes and detection using CDP star were performed according to the instruction manual of the DIG labelling and Detection System (Roche Diagnostics, Mannheim, Germany). For northern blot, 15 μg of the total RNA was denatured and separated on 1.5% agarose gel. Separated RNAs were transferred to nylon membrane, probed with a DNA probe of SLCMV gene and detected following the same procedure used in Southern blot analysis, with slight modification where necessary. Prehybridization (2 h), hybridization (overnight) and washing were performed at 50°C. Detection of short RNAs in selected transgenic lines before and after virus challenge. Total RNA was isolated as described above, and small RNAs were enriched from the total RNA by polyethylene glycol (PEG; MW 8000 ) as described by Smith and Eamens [59]. Thirty micrograms of small RNAs were electrophoresed on a 17% polyacrylamide gel containing 7 M urea and 10x TBE (Tris Borate EDTA). siRNAs were transferred to Immobilon-NY+ membrane (Millipore Corporation, Billerica, MA, USA) in a semi-dry cell (Semi-dry blotting apparatus NA-1512, Nippon Eido, Tokyo, Japan) for 1h at 10V/400mA and subjected to northern hybridization with a probe obtained by the in vitro transcription of the SLCMV gene in the antisense and sense orientation using T7 RNA polymerase from DIG RNA labelling Kit SP6/T7, Roche Diagnostic GmbH, Boehringer Mannheim, Germany. Briefly, 10 μg of plasmid DNA extracted from pCR8/GW/TOPO, was linearized by digesting with ApaI at 37°C for 3 h. The linearized plasmid was purified via phenol/chloroform extraction and ethanol precipitation. Then, 1 μg of the purified template DNA was mixed with 12 μl of DMPC water, 2 μl of 10x NTP labelling mix, 2 μl of 10x Transcription buffer, 1 μl of Protector RNase inhibitor and 2 μl of RNA polymerase T7. The mixture was incubated at 37°C for 2 h and 2 μl of 0.2 M EDTA (pH8.0) was added to stop the reaction. In order to improve the signal, the probe was hydrolyzed with carbonate buffer (60 mM sodium carbonate and 40 mM sodium bicarbonate), and incubating at 60°C for 5 h [60]. Prehybridization (30 min) and hybridization (overnight) were performed at 37°C. Posthybridization washes were performed with 2x SSC for 2 x 5 min at room temperature, followed by 0.1x SSC/0.2%SDS for 2 x 15 min at 50°C. siRNA signals were detected using CDP-star (Roche Applied Science), as described in the DIG system and DIG application manual (Roche Diagnostic GmbH, Boehringer Mannheim, Germany). Plant inoculation with SLCMV and symptom evaluation. Four week-old hardened transgenic and wild-type plants lines obtained from 3 generations of in vitro cuttings were mechanically inoculated twice with SLCMV clone pSL7 and maintained in the greenhouse at 22 ± 2°C, 60% relative humidity. Six lines, 3 plants per line were used for the assay. First, two completely opened young leaves were rubbed with carborundum (abrasive agent) to create wounds. The leaves were rinsed with 50 mM sodium phosphate buffer containing 0.4% sodium sulphite, pH 7.5. Then, SLCMV clone pSL7 was applied by rubbing each leaf several times back and forth using a cotton bud. Second, three days after the first inoculation, another young leaf was cut off at the node. The cut surface on the stem was rinsed with sodium phosphate buffer and the same concentration of viral clone was applied by rubbing several times. In parallel, mock control plants were inoculated with 50 mM sodium phosphate buffer only. The experiment was performed twice. Symptom development was assessed every alternate day but the final classification was recorded at 45 days post inoculation (dpi). The number of leaves per plant showing mosaic symptoms was recorded at 45 and 60 dpi. Also, the plant height, number, length and weight of tubers were recorded at 60 dpi. Disease symptom severity on fully expanded leaves was recorded at 45 dpi on a scale of 0-3 (0, no symptom; 1, mild chlorotic pattern over entire leaflets; 2, moderate mosaic pattern throughout the leaf, narrowing and distortion of the lower onethird of leaflets; class 3, severe mosaic, distortion of two thirds of the leaflets). Disease indices were calculated using the method described by [61] as follows: D:I ¼ ðn 1 þ 2n 2 þ 3n 3 Þ100 3ðn 0 þ n 1 þ 2n 2 þ 3n 3 Þ Where n is the number of leaves in each grade (0-3) with respect to the symptom severity score. Plants with a disease index of 0% were considered as immune, those with a disease index <25% as having high levels of resistance (HR), those with a disease index of 25.1-50.0% as being moderately resistant (MR), those with a disease index of 50.1-75.0% as susceptible (S), and those with a disease index of 75.1-100% as highly susceptible (HS). Determination of viral load on uninoculated new leaves by PCR and RT-PCR. Sixty days after infection, PCR and RT-PCR analyses were carried out to detect SLCMV cassava leaves. DNAs were extracted from new leaves that emerged from infected transgenic and wildtype plants using CTAB. Primers SLCMV-A-5P and SLCMV-A-3P (Table 4) were used to amplify a 700 bp fragment from SLCMV genome (DNA-A). For RT-PCR, total RNAs were extracted from new leaves that emerged from infected transgenic and wild-type plants using guanidine thiocyanate. The RNAs were treated with DNase and RT-PCR was performed using the Superscript III RNase H reverse transcriptase (RT) kit (Invitrogen). The cDNAs were then used as templates for the amplification of SLCMV-CP gene with the same pair of primers (SLCMV-CP-5P and SLCMV-CP-3P) used for PCR amplification. Also, PCR analysis of rice actin gene (RAc1; X16280) was performed as a control to check the quality of cDNA synthesized in the RT-PCRs using the primers RAc1-5P and RAc1-3P (Table 4). Statistical analysis Data on yield (length and weight of tubers) were subjected to analysis of variance (ANOVA) test using a completely randomized design (CRD). Means were separated by least significant difference (LSD) test at the 5% probability level. All computations were performed using SPSS 17.0 statistical package for Windows (SPSS, Inc., Chicago, IL, USA).

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Effects of Root Pruning on Germinated Pecan Seedlings . Root systems of pecan trees are usually dominated by a single taproot with few lateral roots, which are commonly thought to inhibit successful transplanting. This study aimed to evaluate early growth and root/shoot development of pecan seedlings in response to taproot pruning. Taproots of ‘Shaoxing’ seedling pecan trees were mildly (1/3 of the total length of the radicle removed) and severely (2/3 of the total length of the radicle removed) pruned at different seedling development stages shortly after germi- nation. At the end of the first growing season, top growth was measured and then trees were uprooted so that root system regrowth could be evaluated. The results showed that root pruning had no impact on increases in stem height or stem diameter. However, pruning the taproot could stimulate primary growth in taproot branches. Root weight and the number of taproot branches per tree increased with decreasing taproot length. This study indicated that severe root pruning when three to five leaves had emerged resulted in root systems with more taproot branches and the greatest root dry weight after one growth season, which may increase survival and reduce transplanting shock. Pecan ( Carya illinoinensis ) is a deciduous nut tree that is well adapted to loamy bottom land sites (Sparks, 2002). Most pecan seeds are normally germinated and grown in field nurseries for one season, budded the Pecan (Carya illinoinensis) is a deciduous nut tree that is well adapted to loamy bottom land sites (Sparks, 2002). Most pecan seeds are normally germinated and grown in field nurseries for one season, budded the second year, and then dug and sold as bare root trees. The root system predominantly consists of a taproot with weak lateral roots during the first year after pecan seed germination. The taproot will penetrate the soil up to 2 m unless stopped by a water table or an impervious layer by the first season's end. In contrast, lateral roots are typically limited and will not begin abundant development until the second year. Vertical roots develop from the primary lateral roots at least by the fourth year (Sparks, 2005). Pecan trees, in their native habitats, have been classified as a phreatophyte (a plant that characteristically roots to the water table) (Sparks, 2002). Failure to successfully transplant pecan trees is commonplace and could be a result of the lack of adequate lateral root formation. Newly planted trees may become established promptly, may make a semblance of growth for several years and finally become established, or may fail entirely and die (Laiche, 1980). Root pruning (Harris et al., 2001;Keever et al., 1986;Laiche, 1980;McCraw and Smith, 1998;Smith and Johnson, 1981;White and Payne, 1982) and growth regulator application (Matta and Storey, 1981) can influence top growth and root branching and therefore increase transplant survival. Previous research has focused on root pruning and transplanting of 2-year-old (McCraw and Smith, 1998) or 3-year-old (Smith and Johnson, 1981;Wood, 1996) pecan trees. Research has not been conducted to determine if pruning the roots shortly after germination stimulates lateral root formation. Similarly, little work has been attempted to consider the effects of taproot pruning in young pecan seedlings back to different lengths on root regeneration. The objective of this study was to determine if root pruning at different periods after seed germination affects pecan seedling root and shoot growth and to evaluate different degrees of taproot pruning on root initiation. Materials and Methods The test was established at Lvzhou Pecan Research Station, Nanjing, China (lat. 32.05°N, long. 118.77°E). Open-pollinated seeds of the Chinese selection 'Shaoxing' were used as seed stock to produce seedlings. 'Shaoxing' had a small nut of very good quality with 50% percentage fill. The seeds averaged 30.4 mm in length, 20.9 mm in width, and 5.4 g in weight. Seeds were collected on 7 Nov. 2012, air-dried for 7 d, and then packed in polyethylene bags and stored at 4°C before treatment initiation. The seeds were soaked in running cold water for 48 h and then stratified in moist sand at 5°C ± 2°C for 60 d beginning on 20 Feb. 2013, after which the seeds were transferred to a medium (5 peat: 3 vermiculite: 2 perlite by volume, Shanghai Jizhi Agricultural science and technology Co., Ltd., Shanghai, China) at 30°C in the greenhouse to initiate germination. On 3 May 2013, 640 seedlings at stage I ( Fig. 1-I) with a 1-to 3-cm emerging radicle were selected for the experiment and were individually placed 2 cm below the medium surface in each of the 15 · 30-cm containers filled with medium (5 peat: 3 vermiculite: 2 perlite by volume, Shanghai Jizhi Agricultural science and technology Co., Ltd., Shanghai, China). Four stages after stage I were selected for root pruning. At stage II ( Fig. 1-II), the embryo emerged; the hypocotyl was short with a crooked tip and was white to reddish, while the radicle extended to 5 to 8 cm in length. At stage III ( Fig. 1-III), acrospires that were small, tender, and reddish yellow emerged. The hypocotyl, turning reddish yellow to red-brown, became straight and grew rapidly to 10 cm. The radicle was delicate, extending to 10 to 13 cm. At stage IV ( Fig. 1-IV), small, light green euphylla emerged. The hypocotyl 3.3 ± 0.4 b 20.0 ± 1.9 a 4.9 ± 0.5 b V y 5.7 ± 0.5 a 22.4 ± 4.1 a 6.0 ± 1.1 a z Radicle was not pruned. y Root pruning with 2/3 of the total length of the radicle removed. x No. of taproot branches, stem height and stem diameter were investigated on 1 Sept. 2013. The data are shown as the mean value ± SE. w Means within a column were separated using Tukey's test. Means followed by the same letter are not significantly different at P # 0.05. We thank the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) and the Special Fund for Forest Scientific Research in the Public Welfare (201304711) for financial assistance. 1 Corresponding author. E-mail: [email protected]. turned yellowish-green, became hardened and extended to 15 cm. The taproot kept extending to 15 cm, the upper taproot was semilignified with a few fibrous roots, and the lower taproot was still tender. At stage V ( Fig. 1-V), three to five true leaves were visible. Shoot growth was slow, while the taproot kept extending from 17 to 20 cm. More fibrous roots emerged on both the upper and lower taproots. Expt. 1 was conducted to evaluate the effect of root pruning at different stages on pecan root and shoot growth. Treatments were randomly assigned to the developing seedlings: radicles were not cut, or 2/3 of the total length of the radicle was removed at stage II ( Fig. 1-II stage, containers were cut through the center with a razor blade. The medium was gently pushed aside to observe the radicles. Radicles were cut at the depth that was described. Containers were reattached with clear tape and then refilled with medium. The experimental design was a randomized block with four replications, and each replication consisted of 20 seedlings. On 1 Sept., the seedling height was measured from the soil line to the growing point, while the stem diameter was measured with vernier calipers at a point 2.5 cm above the soil line. The seedlings were separated from the soil, and the number of taproot branches was recorded. The roots were washed for 3 min under running water, spread in a thin layer of water (2-3 mm) on a transparent tray and scanned by an Epson Expression/STD 1600 scanner (Seiko Epson, Nagano, Japan). The images were analyzed using WinRhizo commercial software (Regent Instruments, Quebec, QC). The surface areas of coarse roots (main lateral, >2 mm in diameter at origin) and fine roots (<2 mm in diameter) were measured and recorded. Stems (all tissue above the substrate) and roots were labeled, separated, and over-dried (105°C) until they reached a constant weight, and then the dry weights were recorded. The data were subjected to analysis of variance, and where applicable, the means were separated by Tukey's test using Statistix (version 8.0; Analytical software, Tallahassee, FL). Results Root pruning had no effect on stem height or diameter at any stage except stage IV, in which the stem diameter was significantly smaller than that of seedlings that were pruned at other stages (Table 1). This study showed that the morphology of the root system and taproot branches were significantly affected by root pruning. All of the pruned seedlings produced branches, rather than a single taproot (Table 1). Root pruning at stages II, III, IV, and V on average produced 2.2, 3.0, 3.3, and 5.7 taproot branches, respectively, while nonroot-pruned seedlings kept only one single taproot (Table 1). Branches were generated at the cut after the taproot was pruned. The branches were tough, large-diameter roots that had reached 1 cm after 4 months of growth. In addition, a small compact fibrous root system was produced for all root-pruned seedlings. Both shoot and root dry weights were slightly increased by root pruning at stages II and III (Fig. 2). However, root pruning at stage IV significantly decreased the shoot dry weight, while root pruning at stage V significantly increased both shoot and root dry weights (Fig. 2). The total dry weight was affected by root pruning. Root pruning at stage IV significantly decreased the total dry weight; however, the total dry weight was significantly increased when the root was pruned at stages II and V. Seedlings that were root pruned at stage V achieved the highest total dry weight, which was 1.37 times that of non-root-pruned seedlings. In addition, root pruning had a significant influence on the surface area of both fine and coarse roots, which were two major components of the belowground system. Root pruning at stages II, III, IV, and V increased the surface area of fine roots by 35.0%, 59.4%, 91.0%, and 132.6%, respectively (Fig. 3). Root pruning at stages II, III, IV, and V increased the surface area of coarse roots by 87.2%, 72.4%, 15.1%, and 87.1%, respectively (Fig. 3). An additional experiment was conducted to evaluate the effect of two different degrees (mild and severe pruning) of radicle pruning on root generation. The results showed no significant difference between mild pruning May and were small, tender, and reddish yellow. Hypocotyl, which changed from reddish yellow to red-brown, became straight and grew rapidly to 10 cm. The radicle was delicate, extending to 10 to 13 cm. (IV) Euphyllas emerged on 23 May. Two small, light green euphyllas were visible. The hypocotyl turned yellowish-green, became hardened, and extended to 15 cm. The taproot continued extending to 15 cm, the upper taproot was semilignified with a few fibrous roots, and the lower taproot was still tender. (V) Euphyllas expanded from 23 May to 28 May. Three to five true leaves were visible. Shoot growth was slow, while the taproot continued extending to 17 to 20 cm. More fibrous roots emerged on both the upper and lower taproots. Fig. 2. Effect of root pruning at different development stages on first-year pecan seedling stem, root and total dry weight. Root pruning at each stage with 2/3 of the total length of the taproot removed. Means within a weight series were separated using Tukey's test. Means followed by the same letter are not significantly different at P # 0.05. and severe pruning on shoot dry weight, root dry weight, stem height, and stem diameter (Table 2). However, the root system was affected by these two different pruning strategies. The number of taproot branches increased with decreasing taproot length (Table 2). Similar variation was observed on the surface area of fine and coarse roots. The surface area value of both fine and coarse roots of the severe pruned seedlings was significantly higher than that of seedlings that were mildly pruned at any stage except stage IV, when severe root pruning resulted in a slight decrease in the surface area of coarse roots (Fig. 4). Additionally, mild root pruning did not significantly increase the surface area of fine or coarse roots compared with non-root-pruned seedlings. Discussion Conflicting reports exist on the effect of root number on the long-term performance of out-planted pecan trees. Root pruning of seedling trees at a depth of 15 cm 3 months after germination did not reduce tree growth in the nursery or increase the number of lateral roots or taproot branches or root quality (Laiche Jr, 1980). Laiche et al. (1983) reported that root pruning for 2-yearold seedlings at the time of transplant did not influence trunk height or weight, number of roots, or root weight. Similar results were reported by Wood (1996) for 3-year-old seedlings, although lateral roots proliferated at the base of the severed tap root. Other researchers have reported that taproot pruning stimulates top growth, root branching, and growth during the first 2 years after transplantation (McCraw and Smith, 1998). In a 2-year study, pecan trees with a taproot that was pruned to 20 or 25 cm in length regenerated roots better and with a greater survival rate than trees pruned to a 76-cmlong taproot (Smith and Johnson, 1981). Our data showed that root pruning shortly after germination had no effect on aboveground growth in the first year, but significantly increased the taproot branches. Additionally, similar to previously published findings (Harris et al., 2001;McCraw and Smith, 1998), the number of taproot branches increased with decreasing taproot length (Table 2). Further investigation would be required to evaluate whether these new root systems with more taproot branches would hold on or affect aboveground growth for longer periods of time. Early research (Fin er et al., 2011;Lynch et al., 2013;McCormack et al., 2013) indicated that fine-root dynamics control a flux of carbon from plants and into soil and mediate the potential uptake and cycling of nutrients and water in terrestrial ecosystems. Our data suggested that root pruning could increase the surface area of both fine and coarse roots compared with non-root-pruned seedlings. Additionally, severely root-pruned seedlings had more fine-root surface area than seedlings that were mildly root pruned. Future research efforts can focus on the No. of branches of tap roots y Shoot dry wt (g) Root dry wt (g) Stem ht (cm) y Stem diam (cm) y I N 1.0 ± 0.0 d x 5.2 ± 1.1 bc 7.9 ± 0.1 ab 22.8 ± 4.5 ab 6.1 ± 1.4 a III M 1.7 ± 0.5 c 5.3 ± 1.2 bc 8.5 ± 0.8 a 17.8 ± 1.9 b 5.6 ± 0.7 ab III S 3.0 ± 0.9 b 5.4 ± 0.6 bc 9.8 ± 0.6 a 19.6 ± 2.8 ab 5.7 ± 0.8 ab IV M 1.8 ± 0.4 c 5.5 ± 0.4 bc 9.9 ± 2.5 a 19.6 ± 4.2 ab 5.3 ± 1.2 ab IV S 3.3 ± 1.4 b 3.4 ± 0.6 c 5.8 ± 1.3 b 20.0 ± 2.0 ab 4.9 ± 0.5 b V M 1.8 ± 0.7 c 7.1 ± 1.3 ab 9.3 ± 2.0 a 22.9 ± 3.0 a 6.0 ± 0.9 a V S 5.7 ± 0.1 a 8.4 ± 2.5 a 9.6 ± 0.6 a 22.4 ± 4.1 ab 6.0 ± 1.3 a z N: radicle was not pruned. M: mild pruning with 1/3 of the total length of the radicle removed. S: severe pruning with 2/3 of the total length of the radicle removed. y No. of taproot branches, stem height, and stem diameter were investigated on 1 Sept. 2013. Stems and roots were separated and oven-dried (105°C) until a constant weight, and then dry weights were recorded. The data are shown as the mean value ± SE. x Means within a column were separated using Tukey's test. Means followed by the same letter are not significantly different at P # 0.05. Fig. 3. Effects of root pruning at different development stages on root surface area. I: root was not pruned; II, III, IV and V: root pruning with 2/3 of the total length of the taproot removed. Coarse roots: diameter >2 mm; fine roots: diameter <2 mm. Means within a surface area series were separated using Tukey's test. Means followed by the same letter are not significantly different at P # 0.05. Fig. 4. Effect of two different degrees (mild and severe pruning) of radicle pruning on root surface area. Control means that the root was not pruned. Mild pruning means that 1/3 of the total length of the radicle was removed. Severe pruning means that 2/3 of the total length of the radicle was removed. Coarse roots: diameter >2 mm; fine roots: diameter <2 mm. Means within a surface area series were separated using Tukey's test. Means followed by the same letter are not significantly different at P # 0.05. understanding of the fine-root dynamics of pecan trees. Shoot dry weight may comprise as little as 12% of the total dry weight of a 1-year-old pecan seedling (White, 1980). Some research has indicated that because pecan trees are pheratophytes, there is a low probability of altering the root: shoot ratio by fertilization (Conner, 2006;White, 1980). This growth pattern was vital to pecan trees in its native sites especially when pecan trees were restricted by the vigorous growth of more competitive sympatric species (Fletcher et al., 2012;Sparks, 2002). In this study, data indicated that seedlings at our experiment site produced more shoot growth that accounted for as much as 35% to 46% of the plant total dry weight. This difference could have been a result of soil differences, e.g., texture, aeration, or water holding capacity, as suggested by Smith and Johnson (1981). These determinations were beyond the scope of this experiment. In this study, our data showed that root pruning at stage IV had no benefit for seedling growth in terms of stem height, stem diameter, root dry weight, and shoot dry weight, although it could increase taproot branching. This indicated that stage IV may be a critical period, in which germinated pecan seedlings most likely cannot tolerate substantial root loss. For germinated seedlings, the cotyledons contain the stored food reserves of the seed. The cotyledon may be ephemeral, lasting only days after emergence, or may be persistent, enduring a year or more on the plant (Baraloto and Forget, 2007). As reported by Wetzstein et al. (1983), pecan seedling growth is dependent on cotyledonal lipids for the first 3 weeks after seed germination. We assume that as these reserves were depleted, seedlings could not obtain enough nutrients from the cotyledon during stage IV, which is presumed to be a transitional period when the first leaves begin to take over food production for seedlings by photosynthesis. Thus, taproot pruning at stage IV could be detrimental to seedling growth. Conclusions Generally, root pruning shortly after germination did not detrimentally affect the shoot growth of pecan seedlings, nor did it result in additional growth for the first year. However, pruning the taproot could stimulate the primary taproot branches, which may affect subsequent overall growth and may increase survival and reduce transplant shock. Severe root pruning with 2/3 of the total length of the radicle removed generated more taproot branches and achieved a higher surface area value for both fine and coarse roots than that of mild root-pruned seedlings. The ideal time to prune the taproot is at stage V when three to five leaves have emerged, which may encourage the highest production of taproot branches and achieve the highest root and shoot dry weight after one season's growth. Root pruning at stage IV, which has been assumed to be a critical period for germinated seedlings to wean off of nutrition absorption from the cotyledon, would have negative effects on seedling growth.

v3-fos

2017-05-27T23:55:48.774Z

2015-01-27T00:00:00.000Z

2678307

s2

Recharge and Groundwater Use in the North China Plain for Six Irrigated Crops for an Eleven Year Period Water tables are dropping by approximately one meter annually throughout the North China Plain mainly due to water withdrawals for irrigating winter wheat year after year. In order to examine whether the drawdown can be reduced we calculate the net water use for an 11 year field experiment from 2003 to 2013 where six irrigated crops (winter wheat, summer maize, cotton, peanuts, sweet potato, ryegrass) were grown in different crop rotations in the North China Plain. As part of this experiment moisture contents were measured each at 20 cm intervals in the top 1.8 m. Recharge and net water use were calculated based on these moisture measurement. Results showed that winter wheat and ryegrass had the least recharge with an average of 27 mm/year and 39 mm/year, respectively; cotton had the most recharge with an average of 211 mm/year) followed by peanuts with 118 mm/year, sweet potato with 76 mm/year, and summer maize with 44 mm/year. Recharge depended on the amount of irrigation water pumped from the aquifer and was therefore a poor indicator of future groundwater decline. Instead net water use (recharge minus irrigation) was found to be a good indicator for the decline of the water table. The smallest amount of net (ground water) used was cotton with an average of 14 mm/year, followed by peanut with 32 mm/year, summer maize with 71 mm/year, sweet potato with 74 mm/year. Winter wheat and ryegrass had the greatest net water use with the average of 198 mm/year and 111 mm/year, respectively. Our calculations showed that any single crop would use less water than the prevalent winter wheat summer maize rotation. This growing one crop instead of two will reduce the decline of groundwater and in some rain rich years increase the ground water level, but will result in less income for the farmers. Introduction Available water resource has become scarcer especially in arid and semi-arid regions, leading to mining of groundwater in many places [1]. Since agriculture is the largest water user and the increasing and more affluent population consumes more milk and meat products, one of the greatest challenges for the agricultural sector is to produce more food with less water [2]. This is especially critical in the North China Plain (NCP) where agricultural sustainability is threatened by the continued decline in the region's groundwater table. The North China Plain is the premier agricultural area in China where 61% of the nation's wheat, 45% of the maize, 35% of the cotton and 64% of the peanuts are produced [3]. In this area, crop productivity relies heavily on irrigation from groundwater because nearly all usable surface waters are stored in reservoirs for transfer to metropolitan areas [4][5][6]. Groundwater, and to a limited extent the city waste water downstream of large cities, are used for three to four flood irrigations per year with 300 mm or more water in total [7][8][9][10]. Using a large scale weighing lysimeter, Liu et al. [11] reported annual agricultural water consumption for the NCP of about 800 to 900 mm. This is much more than the regional precipitation which averages 480 mm/year (yr) [12]. As a result, crops are irrigated using groundwater as the only available source. The groundwater tables have fallen at a rate of 1m per year in the last 20 years which has led to severe land subsidence in some areas [13,14] and salt intrusion in areas near the coast. Earlier regional studies of irrigation efficiency in the North China Plain have used several methods to calculate recharge and evapotranspiration [8,[15][16][17][18][19][20][21][22][23][24][25][26][27]. Estimates of actual evapotranspiration (ET a ) of winter wheat varied widely with a low of 346 mm/yr [19] to a high of 737 mm/yr [25] and the ET a of summer maize from a low of 280 mm/yr [27] to a high 374 mm/yr [22]. Ma et al. [18], Liu et al. [21], Zhang et al. [22], Kong et al. [24] and Zhao et al. [28] used a soil water balance method to calculate ET a using precipitation and irrigation as input and neglecting deep percolation to below the soil profile. Thus in this method any deep percolation is counted within ET a . Other researchers accounted for recharge in their simulation models. Sun et al. [8] simulated recharge as a constant fraction of both irrigation and effective rainfall (e.g. Luangcheng County Water Policy and Integrated Water resources Management Office, 1993 [29]) for the period of 1999 to 2002 and found for the NCP a recharge of 25-37 mm under winter wheat in a period including 309-405 mm total irrigation and 347-402 mm precipitation. Ma et al. [27] quantified drainage out of the root zone with a simplification of Darcy's law, calculating a recharge of winter wheat at 5mm and 64 mm in 2007 (300 mm irrigation and 83 rainfall) and 2008 (210 mm irrigation and 186 rainfall), respectively. Liu et al. [26] calculated percolation from the root zone based on the relation between unsaturated water conductivity and soil moisture content at the bottom of the soil profile, and reported there was 1-18 mm percolation during the winter wheat growing season from 2008 to 2012 with irrigations totaling 226-304 mm, using a root zone was of 1.5 m. However, they did not report the recharge of other crops. Kendy et al. [15,16] validated a one-dimensional soil-water-balance model assuming that drainage from the soil profile was continuous to estimate areal recharge from winter wheat-summer maize and reported a recharge between 71-170 mm for the whole rotation from 1998 to 2001 under irrigation of 210-328 mm and annual precipitation of 347-402 mm. Using Kendy's model, Zhang et al. [17] simulated recharge amounts varying between 33-87 mm for winter wheat from 1998 to 2001 with 362-405 mm total irrigation and 53-134 mm precipitation in its growing season. Meanwhile, he also reported that recharge for summer maize was 127 and 12 mm in 2000 (126 mm irrigation and 348 mm precipitation) and 2001 (67 mm irrigation and 212 mm precipitation), respectively. Finally Hu et al. [12] indicated that, based on a combination of SWAT and MODFLOW models, a 39% reduction in irrigation pumping for winter wheat-summer maize would induce groundwater recovery and restoration to the pre-development hydrologic conditions of 1956 in about 74 years in the NCP. As a simplifying assumption, all of the above studies on irrigation efficiency assume either implicitly or explicitly that there is no surface runoff. To neglect surface runoff on the large scale in this area is justified. Since 1980, after the reservoirs were built to collect the river flow from the mountains for industrial and domestic water supply, rivers were dry except in the high rainfall years of 1988 and 1996 [30]. On a small scale, runoff is unlikely due to the high infiltration capacity of the soil and flat topography allowing water to stand in small puddles until it infiltrates or evaporates [12]. In the North China Plain there is no surface water available for irrigation and groundwater is the only source for irrigation. It is useful to know the net ground water use, namely the difference in irrigation water withdrawal and recharge. The excess of irrigation withdrawal above recharge year after year drives the cumulative groundwater level decline. Kendy et al. [15] found that on average, when growing both winter wheat and summer maize, net water use was about 125-212 mm per year from 1998 to 2001. (In this summary, positive values represent greater irrigation than recharge, which is a negative effect on the groundwater level.) Zhang et al. [17] showed net water uses of winter wheat-summer maize from 181-321 mm between 1998 and 2001 in the NCP. Sun et al. [8] reported net water use for winter wheat ranging from 230 mm to 251mm from 1999 to 2002 in the NCP. Sun et al. [31] calculated that the net groundwater use required for winter what-summer maize with reduced input of water and nitrogen under farmers' practice still surpassed 300 mm yr -1 in the NCP. Liu et al. [26] reported that the net water use in the growing season of winter wheat ranged from 226 mm to 292 mm from 2008 to 2012 in the NCP. Based on a root zone model, Ma et al. [27] reported the net water use for winter wheat by itself in the NCP was 146 mm in 2007 and 295 mm in 2008, respectively. However, the models were not directly validated leaving a large uncertainty about recharge and net water use amounts. The exception was the model of Kendy et al. [15,16] that was validated against observed soil moisture data for the winter wheat-summer maize rotation. They used lysimeter data published by Liu et al. [11] from the Luancheng experimental station site. While these cited reports are very helpful, crop rotation and longer term field research on the net water use and recharge of the staple crops in the NCP remains scare. Because of limited knowledge about recharge and net water use mentioned above in the NCP, an 11 year experiment was carried out that starting in October 2002 to study the moisture depletion patterns of six crops including winter wheat, summer maize, peanuts, cotton, sweet potato and ryegrass in five cropping systems. In this paper we analyze this experiment during which soil moisture content was measured in increments of 20 cm every 10 days to calculate the net water use of these crops as a function of crop rotation, irrigation schedule and precipitation. The overall objective of this study is to calculate the recharge and the net water use directly based on measured soil moisture content, pan evaporation, irrigation and precipitation for important crops in the North China Plain. Specifically, we will (i) quantify the deep percolation of the six crops from 2003 to 2013; (ii) re-express the difference between deep percolation and irrigation to infer groundwater table change; and (iii) calculate the net water use for the six crops from 2003 to 2013. Ethics Statement This field experiment was conducted in the Luancheng Agro-ecosystem station (37°50'N, 114°4 0'E, altitude 50 m) which is a long-term experimental site and belongs to the Chinese Academy of Sciences. This research was performed in cooperation with China Agricultural University. The farm operations of this experiment were similar to rural farmers' operations and did not involve endangered or protected species. This experiment was approved by China Agricultural University and the Chinese Academy of Sciences. Study site, soil and climate The Luancheng Agro-ecosystem station is one of 36 agricultural ecosystem stations in the Chinese Ecological Research Network (CERN). It is located in Luancheng County in Hebei Province. Its property and operation are representative of the agricultural production and climate conditions in the northern part of the North China Plain, where winter wheat-summer maize rotation is the main cropping system (Fig. 1). The water table in Luancheng County has been constantly declining since the 1970s, which fell from 11 m below the surface to about the current 42 m with an annual decline of approximately one m yr -1 . The experimental site has a warm temperate zone, semi-humid, monsoon climate. The annual mean air temperature is 12°C. The average annual rainfall over the last 20 years was 480 mm, with sharp yearly fluctuations and an erratic seasonal distribution. Generally, 60-70% of the yearly precipitation occurs from June to August. The monthly precipitation and averaged temperature are shown in Fig. 2. The frost-free period is about 200 days from April to October. The experimental site has a sandy loam in the surface layers, light/medium loam at a depth of 40-80 cm, and light clay below 80 cm. The soil profile properties are given in Table 1 [32]. The plow layer was about 0.2 m thickness, contained 11 g/kg of organic matter, 1g/kg of total nitrogen, 36 mg/kg of available phosphate, and 96 mg/kg of available potassium. The soil pH is 7.8 [33]. Experimental design and crop management In October 2002, five cropping systems were established on 15, 4 × 7.5 m plots in a randomized complete-block design with three replicates. Between two plots, there was a 1 m-wide zone without irrigation to minimize cross-plot effect. The five cropping systems were (1) winter wheat-summer maize (WS; 1-year cycle), (2) peanuts!winter wheat-summer maize (PWS; 2-year cycle), (3) rye-cotton! peanuts! winter wheat-summer maize (RCPWS; 3-year cycle), (4) sweet potato! cotton! sweet potato! winter wheat-summer maize (SpCSpWS; 4-year cycle), and (5) continuous cotton cropping (Cont C). Planting, harvesting, fertilizers and irrigation applied were the same for each crop independent of its rotation and according to local agronomic practices ( Table 2). Fertilizer N (primarily urea fertilizer) was broadcast prior to seedbed preparation and top applications of N, P and K fertilizer were made during the crop growth period. Data were analyzed up to October 2013. Data collection Average daily air temperature, precipitation and pan evaporation were obtained from an automatic weather station located 100m from the experimental plots. The groundwater table was measured about 400 m from the experimental plots at the Experimental Station's well. Soil volumetric moisture content was measured by a neutron probe (L520) at increments of 20 cm every 10 days to a depth of 180 cm. The top 20 cm soil moisture was measured by a thermogravimetric method because neutron probe measurement is inaccurate near the surface. Calculations and measurements Aquifers in the North China Plain are potentially recharged by deep percolation from excess precipitation and irrigation [12,15,34]. In order to calculate the cumulative percolation, we calculated the water balance of the top 180 cm for 10 day intervals between consecutive measurements of soil moisture content. Any water shortage in the top 180 cm after subtracting the estimated evapotranspiration by the crop is considered deep percolation which eventually becomes recharge to the groundwater. This assumes implicitly as in other studies within the North China Plain that surface runoff can be neglected [12,34], which was confirmed by direct observation. It also assumes that interflow is small because the horizontal hydraulic gradient is close to zero in the nearly flat alluvial plain. Finally, with the local groundwater table much deeper than 4 m below the ground surface, capillary rise is negligible [8]. Thus, by neglecting lateral flow and water moving upward from the groundwater, the water balance equation for the deep percolation between moisture measurements for each crop can be written as: Where the storage S is as measured in the top 180 cm of the soil profile; S (t-Δt) is the storage in the profile at the previous measurement time; Δt is the time between measurements which was usually 10 days; DP is the average daily percolation for the interval (mm/day); P is the daily precipitation (mm/day); I is the daily irrigation (mm/day); and ET a is the estimated daily actual evapotranspiration (mm/day). P, I and ET a were summed over Δt days. ET a was calculated with the FAO method [35], e.g. Where K c is the crop growth coefficient; P c is a pan coefficient that converts the evaporation from a pan to potential evapotranspiration from a well-watered, fully leafed crop; and ET p is the measured pan evaporation. The crop coefficients K c varys during the different growth stages of the crop [35]. Here, P c was equal to 0.7 which was the same as Kendy et al. [15] at the same site. K c was obtained from the study of Liu et al. [11] that determined values for the Luancheng Station site using lysimeters (S1 Table). In cases when the deep percolation in Eq. (1), DP, was computed to be negative, we assumed that the FAO method (which gives potential evapotranspiration from a very moist surface) overestimated the actual evapotranspiration. Then we reduced the ET a so that DP would become zero in Eq. (1). Net water use, NWU, by the crop from the perspective of the groundwater can be estimated based on DP and pumpage for irrigation. The meaning of a negative "use" is that storage in the aquifer has been reduced; a positive "use" means that aquifer storage increased Where n was the number of days from sowing till harvest. Statistical evaluation Analysis of variance (ANOVA) was carried out using Statistical Analysis System 9.3 [36] software, and differences were considered significant at the 0.05 level. Results and Discussion Deep percolation and evaporation The temporal distributions of precipitation and irrigation and the calculated percolation and evaporation during the period of 2003 to 2013 are presented in Fig. 3 for various crops in the SpCSpWS (sweet potato! cotton! sweet potato! winter wheat-summer maize) rotation. Analogous information for the other four cropping systems is provided in S1 Fig. It is obvious that intensive rains in summer generate more deep percolation than the smaller precipitation events and irrigation applications during the remainder of the year. These findings are consistent with Kendy et al. [15] at the same experimental station and Bradbury et al. [38] in Wisconsin U.S. By summing the water losses between the soil measurements, the percolation and ET a for each crop can be calculated with Equations (1) and (2) (Table 3). Results revealed that cotton had significantly more percolation (51-359 mm) than all other crops (P< 0.05), particularly when it was grown as part of the cotton monoculture (Cont C). The reason for the large percolation amounts was the extra irrigation water given to cotton compared to other crops. Liu et al. [39] reported the extra irrigation was needed to meet the water requirement of cotton if there was not much rain. The high standard irrigations, together with the high rainfall in 2004 that fell in a relatively short time period at the beginning of the planting season on relatively wet soil resulted in the greatest percolation of 359 mm under the cotton crop. The minimum percolation for cotton was 51 mm in the following year (2005), mainly because of poor rainfall in that year. Low soil moisture carried over from the preceding cotton in late 2004 also contributed. Irrigation, as mentioned before, was based on a schedule that did not consider soil moisture content. In general, percolation amounts under winter wheat and ryegrass were the least of all crops (in some cases there was no percolation), due to low rainfall (rain stopped generally in the beginning of October) and low initial soil moisture content in the soil profile ( Table 3). The long October-May non-precipitation winter wheat cultivation season relied on groundwater irrigation, which was the main reason behind saturated zone storage loss in this area. Some of the irrigation water that we applied would have built up in the soil in winter and spilled downward to the aquifer, but instead was transpired by the winter crops. Similarly to cotton, sweet potato had a relatively high percolation rate ranging from 25 mm to 136 mm. However, there was no percolation in the growing season of sweet potato in 2007, due to the poor precipitation and high evapotranspiration. Peanuts' growing season percolation ranged from 7 mm to 335 mm (Table 3). Summer maize had the annual average percolation of 44 mm/yr. However, Percolation for all crops was small in 2007 and 2010 because rainfall was scarce (Table 3). Our results in Table 3 indicate that percolation of water under regionally irrigated cropland is common. This is contrary to the assumptions made by some of the early investigators calculating the crop water use [18,22,24,25]. Therefore, in the next section we demonstrate that our predictions of percolation that recharges the groundwater are realistic and can represent the observed decline in the ground water tables in the North China Plain. Validation of deep percolation calculation In order to check the percolation calculation we re-express the difference between the calculated deep percolation and irrigation into infer the groundwater table change. Thus we compare our time series of calculated net water use with the time series of observed groundwater table change at the Luancheng experimental station. Fig. 4 shows the monthly observed water table at the experimental station along with our simulated values which will be explained shortly. The depth of the groundwater table d can be predicted as Where d is depth of the ground water in reference to the land surface at zero; R and I are the recharge and irrigation water withdrawn respectively in the period between the current time step, t, or the previous time step t-Δt, f is the fraction of the land under irrigation and η is the specific yield or drainable porosity. R, I and d are in meters. To calculate the recharge, since the groundwater table below the surface is at 30 m during the experiment period there is a notable time lag between when the water percolates out of the root zone and when it arrives at the groundwater. To estimate this time lag, we look at the ground water table historical behavior. We concentrate on a wet period starting with 1995 with annual rainfall of 510 mm/year; 1996 with 774 mm/year and then 1997 was dry with 272 mm/ year. The ground water table as shown in Fig. 4 peaked in 1997 and 1998 indicating that there is one year time delay and the effect is spread over two years. Since our model is not refined enough to predict the inter-annual variation of the ground water we use a yearly time step. Based on this the average annual recharge R is predicted as Where the subscript y is the year and DP is the annual averaged areal deep percolation. In order to calculate the annual averaged deep percolation DP in the area around the Luancheng experiment station we note that 90% of the area around the Luancheng experiment station is irrigated and 85% is managed under the winter wheat-summer maize rotation [31]. Thus by summing the deep percolation under winter wheat and summer maize (Table 3), we can obtain the annual percolation near the experiment station. In addition based on these observations we assign a value of 0.85 to f in Eq. (4). Since the amount of irrigation is known from table 2 (based on farmer's practices), the last parameter that need to be estimated is the specific yield in order to find the decline in ground water levels. Specific yield at the site has not been measured. Kendy et al. [15] assumed 0.2 and found a good fit between their computed deep percolation-irrigation and monitor well observations without considering the other factors above. Groundwater modeling literature covering the vicinity assumes 0.10-0.23 [40] and 0.12-0.18 values [12]. Standard texts often cite 0.2 for alluvial gravel and sand like that found beneath the Experiment Station. So we consider an 0.2 value to be reasonable. The predicted groundwater tables in our winter wheat-summer maize rotation are shown in Fig. 4 after the above calculation. It starts from the year of 2004. Due to this experiment initiated from October 2002, we set a percolation out of the root zone in 2002 the same as in 2003 by lack of a better estimate. As it can be seen in Fig. 4, the predicted annual average groundwater table follow the observed levels well, within the range of monthly variability of the observed water tables. Statistical measures indicate this as well with the root mean square error (RMSE) of 0.6418 m, the mean relative error (RE) of 1.35%, and Nash-Sutcliffe of 0.9633. These three criteria formula to quantify the deviation of the modelling results from the observed data were expressed in Ma et al. [27]. Shu et al., [41] reported among others that the excessive irrigation is generally assumed to be the key factor contributing to declining groundwater tables in the North China Plain. In contrary, especially Eq. (4) distinctly shows that the recharge nor the irrigation by itself are causing the decline of the ground water. It is the difference between the two that is responsible for rate that the ground water changes. Similarly recommendations to decrease the groundwater decline by either decreasing irrigation [12] or increasing the percolation [42] likely should be reconsidered. Net Water Use Exploring groundwater balance Eq. (4), there are two ways to reduce the aquifer depletion by reducing the net water withdrawal (and decreasing the net water use) or by decreasing the fraction of agricultural land (and minimizing the non-evaporation from cropping land). We next explore the choice of crop toward by minimizing the negative balance between irrigation, I, and recharge, R, using our experiment results. Thus to consider what crop is best for decreasing the reduction of groundwater, we calculated the net water use for each crop from the perspective of groundwater using Eq. (3) (Fig. 5). Negative values indicate that irrigation pumpage exceeded recharge, positive that recharge exceeded pumpage. From Fig. 5, the net water withdrawal of winter wheat was greatest among the tested crops with an average of 198 mm/yr in various crop rotations mainly due to the low precipitation in winter and continuous evapotranspiration for regular growth, drawing mostly upon 225 mm irrigation provided in winter wheat growing season. The ryegrass, winter cover crop, with irrigation of 150 mm in each growing season, also had high net water use with an average of 112 mm/yr due to ongoing evapotranspiration and low rainfall in the winter dry season. Under the same 150 mm irrigation, but in a wetter part of the annual weather cycles, sweet potato and peanuts had annual average net water use of 74 mm/yr and 32 mm/yr, respectively. Sweet potato had its highest net water use of 150 mm in 2007 due to the low growing season precipitation and no percolation. Peanuts in the PWS rotation had an extra recharge of 89 mm to the groundwater in 2013. The annual average net water withdrawal of summer maize from the groundwater reached 71mm/yr with the 105 mm irrigation, while in some years summer maize actually replenished the groundwater in the PWS rotation by returning 125 mm in 2004 and 48 mm in 2012. Cotton had the least annual average net water use of 14 mm/yr under its irrigation regime of 225 mm in each growing season. In wet years, cotton was the most likely crop to reverse the water extraction from the groundwater replenishing the aquifer by 18-134mm/yr (S2 Table). Overall, the annual average net water use decreased in the order of winter wheat > ryegrass > sweet potato > summer maize > peanuts > cotton (Fig. 5). Across all crops, the sharp yearly fluctuations and the erratic seasonal distribution of annual precipitation contributed to a wide variation in any crop's net water use. Our results are in agreement with Yang et al. [43] who estimated that the crop water requirement for five major crops (wheat, maize, cotton, fruit trees, vegetables) in NCP using crop models DSSAT and COTTON2K, and found winter wheat accounted for over 40% of total irrigation water requirement in the plain, while summer maize and cotton together accounted for 24% of the total irrigation water requirement. In order to find the relationship between net water use and rainfall and recharge, Fig. 6A plots the deep percolation (that eventually becomes recharge) versus the sum of precipitation and irrigation (P+I) over the growing season (from sowing to harvest) for each of the crops and for each of the years from 2003 to 2013. Although there is a general relationship in which the percolation increases with increasing P+I, there is a large variation between the various Groundwater Use for Staple Crops during 11 Years in North China Plain crops. The fit becomes much tighter in Fig. 6B when we take the duration of the growing period into account by dividing the total amounts in the growing season by the number of days of the growing period. Thus in Fig. 6B, we express the percolation versus P+I amounts by expressing the quantities in mm/day. Results reveal that there is a threshold, T, of around 3 mm/day. Above the threshold there is almost a linear relationship between P+I and percolation with a slope close to 1 (Fig. 6B). Below the threshold the percolation varies with the average percolation generally less than 0.75 mm/day with an average of approximately 0.2 mm/day. The equation for the line for T!3 mm/day in Fig. 6B can be written as Nothing that the threshold value is approximately equal to the average evapotranspiration during the growing season we can rewrite Eq. (6) as The simple results for estimating the amount of deep percolation per crop in Eq. (7) is based on regression of experimental results of percolation amounts determined from frequently measured moisture contents during the growing season and is therefore different from Eq. (1) that is based on theoretical considerations. To show that this Eq. (7) is valid for other places as well in the North China plain we plotted in Fig. 6A and 6B the result of these other studies. Zhang et al. [17] reported that the recharge of winter wheat ranged from 33-87 mm from 1998 to 2001 with the total P+I from 425 to 504 mm in its growing season and the recharge of summer maize ranged from 5-127 mm with the total P+I from 212-474 mm. Sun et al. [8] found that the recharge of winter wheat ranged from 25-37mm from 1999 to 2002 under the total P+I of 448-463 mm during the growing season. Liu et al. [26] demonstrated that the recharge of winter wheat ranged from 1-18 mm from 2009 to 2012 with the total P+I of 323-357 mm. Ma et al. [27] reported that the recharge of winter wheat was from 5 mm to 64 mm with water input (P+I) of 383 to 396 mm during the growing season from 2007 to 2009. These studies provide similar estimations of evapotranspiration and net water use for winter wheat and summer maize to our study in the same region. Our study, however, also consider the net water use by cotton, sweet potato, peanuts, ryegrass. Rewriting Eq. (7) and combine it with Eq. (4) we find that the change in water table can be written as It clearly shows that the ET term is the most important one in managing groundwater. Thus the only way to maintain yield and lessen the impact on groundwater is by reducing nonproductive evapotranspiration from crops in the area's agriculture. This is actively being pursued, such as breeding new drought resistant crop [44], increasing soil surface management (tillage [45]); soil nutrient management [46]; crop residue cover and mulching [47]; irrigation management [48,49]; Meanwhile, new alternative cropping systems were also recommended to develop [31,50]. In this study, the establishment of the relationship between recharge and precipitation plus irrigation and the estimation of the groundwater decline change provide a practical theoretical basis for improving irrigation regimes, reducing unproductive evaporation, and ultimately more effective utilization of the limited water resources in this area. Conclusions In the North China Plain, irrigation is often essential to achieve economically viable crop production. More accurate insights about seasonal aquifer recharge and net water use are prerequisites to calculating the groundwater balances at local, sub-watershed scales for effective management of scare water resources in this area. In this study, the recharge and net water use of six crops were quantified from 2003 to 2013 based on a long-term crop rotation field experiment using simple soil water balance monitoring. Results showed that the annual average net water use (recharge minus irrigation) was highest beneath winter wheat averaging 198 mm/yr, followed by ryegrass with 112 mm/yr, sweet potato with 74 mm/yr, summer maize with 71mm/year, peanuts with 32 mm/yr, and cotton with the lowest at 14 mm/yr. Moreover, the groundwater table prediction and the establishment of the relationship between percolation and precipitation plus irrigation provide an important perspective when searching for efficient irrigation regimes and sustainable water management policy. This study implicated that groundwater decline will be less by growing different crops that require less time to mature, evaporate less than the potential rate. In some years with above average rainfall this might even lead to an increase in groundwater tables.

v3-fos

2015-03-21T21:52:17.000Z

2015-04-01T00:00:00.000Z

16125527

s2

Close Relationship of Ruminant Pestiviruses and Classical Swine Fever Virus To determine why serum from small ruminants infected with ruminant pestiviruses reacted positively to classical swine fever virus (CSFV)–specific diagnostic tests, we analyzed 2 pestiviruses from Turkey. They differed genetically and antigenically from known Pestivirus species and were closely related to CSFV. Cross-reactions would interfere with classical swine fever diagnosis in pigs. P estiviruses are enveloped viruses within the family Flaviviridae that have a highly variable single-stranded positive-sense RNA genome of ≈12.3 kb (1). The genus Pestivirus comprises the established species bovine viral diarrhea virus (BVDV)-1, BVDV-2, border disease virus (BDV), and classical swine fever virus (CSFV), as well as a growing number of additional tentative Pestivirus species. CSFV is the causative agent for classical swine fever, which is notifiable to the World Organisation of Animal Health because it is highly contagious and can cause great loss of pigs (2)(3)(4). For a given country, CSFV-positive status severely diminishes international trade of pigs and pig products. Accordingly, because of cross-reacting antibodies, infections of pigs (nonruminants) with ruminant pestiviruses, which occasionally occur under natural conditions, can cause serious problems with regard to serologic diagnosis of classical swine fever (5). In Turkey, 2 pestiviruses, Aydin/04 and Burdur/05, have been isolated from a sheep and a goat with clinical signs of border disease (6). A detailed genetic and antigenic characterization revealed that these 2 isolates must be regarded as representatives of a new Pestivirus species that is closely related to CSFV and can cause serious diagnostic problems in established CSFV serology. The Study During 2004-2007, serum samples from 1,036 sheep and goats in Turkey were serologically screened for infection with pestiviruses of small ruminants. Of these, 11 serum samples from 7 sheep herds gave positive or doubtful reactions in the CSFV antibody-specific ELISA (HerdChek, IDEXX) and were subjected to commonly used virus neutralization testing (VNT) (7). VNT against the 2 established CSFV strains Alfort187 (genotype 1.1) and Diepholz (genotype 2.3) and against the BDV strains Moredun (genotype 1) and Gifhorn (genotype 3) revealed higher BDV titers in only 3 serum samples (Table 1). Equal or slightly higher titers against the CSFV reference strains became evident in 8 of the 11 serum samples, which came from 5 regions of Turkey. Further VNT analyses with the 2 previously obtained isolates, Aydin/04 and Burdur/05, demonstrated neutralizing antibody titers that were equal or higher than those against BDV and CSFV test strains. To elucidate the reason for strong serologic reactivity in CSFV assays, we genetically and antigenically characterized pestiviruses Aydin/04 and Burdur/05. The complete genome sequence of Aydin/04 was determined as reported previously (8). The genome sequence of Burdur/05 was determined by next-generation sequencing on an Illumina MiSeq platform (2 × 250-bp paired end run, 593,328 reads) as recently described (9). Template total cellular RNA was extracted from supernatant of sheep fetal thymus cells. Of all reads, 73.9% were found to be of host origin. Of the nonhost reads, 89.9% assembled into a single sequence contig encompassing the entire pestivirus Burdur/05 genome (coverage 196-fold). Sequence and phylogenetic analyses were performed with complete genome sequences and deduced amino acid sequences of new pestiviruses Aydin/04 (GenBank accession no. JX428945) and Burdur/05 (KM408491). For further analyses, reference sequences were obtained from GenBank ( Figure 1). Genetic distances were calculated by using the Kimura 2-parameter substitution model, and phylogenetic analyses were conducted by applying the neighbor-joining method as commonly used for CSFV phylogeny (11). With the same set of sequences, a grouping scan was performed by using the SSE platform (12). Comparison of the complete coding sequences of Aydin/04 and Burdur/05 revealed a genetic distance of 16.5%. Phylogenetic analyses based on deduced polyprotein sequences showed that isolates Aydin/04 and Burdur/05 form a distinct group located between CSFV and BDV ( Figure 1, panel A). Systematic antigenic characterization was performed by using cross-neutralization assays ( Table 2). For this purpose, CSFV and BDV reference strains for which homologous serum was available were tested by VNT as described (7). In general, neutralization of both isolates was more efficient when performed with different CSFV antiserum than with BDV antiserum. In addition, the Aydin-specific antiserum obtained from animal experiments neutralized the CSFV reference strains with titers higher than those for the BDV strains (Table 2). Because no experimental infection with Burdur/05 has been performed, Burdur/05specific antiserum was not available; however, close antigenic relatedness of both isolates was demonstrated by the high neutralization titers of the Aydin-specific antiserum for isolate Burdur/05 (Table 2). To quantify and to depict the antigenic relatedness, we calculated coefficients of antigenic similarity (R values) as described previously (13). An antigenic tree graphically displaying the R values clearly shows 2 distinct clades, one representing CSFV and the other comprising BDV strains (Figure 1, panel B). Furthermore, Aydin/04 is antigenically more closely related to CSFV than to BDV, but it also clearly differs from these 2 pestivirus species. Because of their close relationship to CSFV, it was of particular interest to determine the ability of these ruminant pestiviruses to infect pigs and induce clinical disease. Therefore, 3 clinically healthy and pestivirus uninfected weaner (6 weeks of age) piglets were inoculated with 1 × 10 6 50% tissue culture infectious doses of isolate Aydin/04 and given a booster of 3 × 10 7 50% tissue culture infectious doses 2 weeks later. Pigs showed no clinical signs of disease, no fever, no platelet or leukocyte depletion, and no viremia (data not shown). For all 3 animals, strong seroconversion was found (50% neutralizing titer of serum for homologus virus was 240-640 on postinoculation day 77). Conclusions Several new genetically diverse groups of pestiviruses have emerged in domestic livestock and wild animals, adding to the continuously growing list of approved and tentative pestivirus species (1). According to phylogenetic analyses of short partial genome sequences, 2 pestivirus isolates, Aydin/04 and Burdur/05, recently circulating in sheep and goat herds in different regions of Turkey, were classified as novel members of the BDV species (6). However, the data from this study demonstrate that these novel Aydin-like pestiviruses are representatives of a new pestivirus species, genetically and antigenically located between CSFV and BDV ( Figure 1). The genetic distance of 16.5% between these isolates indicates that distinct ruminant Aydin-like pestiviruses circulate in different regions of Turkey. For some genomic regions, both ruminant pestivirus isolates display an even higher similarity to CSFV than to BDV (Figure 2). The close genetic relatedness to CSFV is in line with the antigenic characterization by cross-neutralization assays as depicted in the antigenic tree (Figure 1, panel B). This finding is in contrast with findings for pestivirus isolates from Tunisia, another group of ruminant pestiviruses genetically closely related to CSFV but antigenically more closely related to BDV (14). The close antigenic relationship to CSFV explains the observed strong cross-reactivity of serum from sheep and goat in CSFV-specific ELISAs, even when the variable E2 protein is used as diagnostic antigen (Table 1). In routine diagnosis, questionable ELISA results are further investigated by VNT against CSFV and other pestiviruses (e.g., BVDV and BDV). Usually, VNT titers are highest for the homologous pestivirus species. Remarkably, even if representatives of the Aydin-like pestiviruses were included as test strains in the VNT, CSFV infection still could not be ruled out. Although these novel pestiviruses are the closest known relatives of CSFV, experimental infection of pigs with Aydin/04 did not result in detectable viremia and clinical signs. Nevertheless, these ruminant pestiviruses are candidates for a switch to porcine hosts after ongoing virus evolution, which would have severe consequences for serologic diagnosis of classical swine fever, affecting control and monitoring programs performed in many parts of the world. Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 21, No. 4, April 2015 Amino acid similarity of pestiviruses Aydin/04 and Burdur/05 to representative CSFV and BDV polyprotein sequences. The same CSFV and BDV polyprotein sequences as in Figure 1 were used for analysis. Grouping scan was performed with the SSE software platform as described previously, by using a window of 200 aa with 20-aa increments (12). For calculation of genetic distances, the Kimura 2-parameter model was applied. Borders of the mature viral proteins in the polyprotein of Aydin/04 are given below. BDV, border disease virus; CSFV, classical swine fever virus; C, core protein; E, envelope protein; rns, ribonuclease secreted; N pro , N-terminal autoprotease; NS, nonstructural protein; p7, protein p7.

v3-fos

2016-04-23T08:45:58.166Z

2015-03-01T00:00:00.000Z

18127807

s2

Protease and Hemicellulase Assisted Extraction of Dietary Fiber from Wastes of Cynara cardunculus The action of protease and hemicellulase for the extraction of fractions enriched in soluble fiber from bracts and stems of Cynara cardunculus was evaluated. Using a two-factor simplex design comprising protease amounts of 0–200 μL and hemicellulase amounts of 0–200 mg for 5 g of material, we explored the effect of a 5 h enzymatic treatment at 40 °C on the chemical composition and yield of the fractions isolated. The fractions contained inulin and pectin. In general, the protein, inulin, and polyphenol contents and also the yields were higher for fractions obtained from stems. The most marked effects were observed when enzymes were used at higher concentrations, especially for hemicellulase. The inclusion of a pre-heating step increased the yield and the inulin content for fractions isolated from bracts and stems and decreased the protein and polyphenol contents, and the galacturonic acid for bracts. These fractions, in general, contained the polyphenolic compounds monocaffeoylquinic acid, apigenin, and pinoresinol. Introduction The food industry controls the selection process, cleaning, and preparation of raw plant materials for further industrial processing [1], giving rise to remnants that could be reused, since they are a good source of dietary fiber and phytochemicals. According to Goñi and Hervert-Hernández [2], plant food waste contains more dietary fiber than its respective edible portions. For food companies, vegetable waste processing and its elimination represent important costs, often inaccurately evaluated by the companies themselves. The transformation of these wastes into products with higher added value allows them to reduce the cost of treatment and generates additional profits, contributing to the actual trend of sustainable development and environmental protection. Globe artichoke (Cynara cardunculus var. scolymus) is a species of thistle cultivated as a food. The edible portion of the plant consists of the flower buds before the flowers come into bloom. It is a perennial plant native to the Mediterranean region [3]. The ratio of edible fraction/total biomass produced by the plant is very low, being less than 15%-20% of the total plant biomass. This ratio decreases further if the contribution to the total biomass represented by offshoots, removed from the field by common cultural procedures, is also considered [4]. Cynara cardunculus is a rich source of bioactive phenolic compounds, and also inulin, other fibers, and minerals [5,6]. For this reason, it is considered a functional food. Vegetable tissues discarded at harvesting or after industrial processing constitute a valuable and renewable source of biopolymers and bioactive compounds. Upgrading of vegetable waste can not only reduce pollution but also add value to the commodity production. The obtention of valuable compounds from wastes contributes to their upgrading. The extraction, fractionation, and isolation of high added-value compounds from food wastes can be performed through different methodologies. According to Galanakis [7], among the numerous methodologies found in the literature, five distinct recovery stages can principally be observed: (1) macroscopic pre-treatment, which aims at the adjustment of the food waste matrix according to the water content, enzymatic activity, and permeability of the bioresource tissues; (2) macro-and micro-molecule separation by alcohol precipitation, the most popular method for the separation of smaller compounds from macromolecules; (3) extraction, which uses different methodologies according to the physicochemical characteristics of the target molecules; (4) isolation or clarification of the target compounds from co-extracted impurities; and (5) product formation (encapsulation or drying), the stage that attends to the target product stabilization. Inulin is a natural storage carbohydrate comprising a heterogeneous collection of fructose polymers. As human enzymes cannot digest fructans, they reach the colon and serve as a substrate for enterobacterial growth. Functioning as a prebiotic, inulin has been associated with enhancing the gastrointestinal and immune systems. In addition, it has been shown to increase the absorption of calcium and magnesium, influence the formation of blood glucose, and reduce the levels of cholesterol and serum lipids [8,9]. Diets containing fructans selectively stimulate bifidobacteria and make them the predominant species [10], producing an increased fecal content of short-chain fatty acids and a decreased concentration of tumor-promoting substances, such as ammonia [11,12]. Pectins are a type of soluble fiber commonly present in vegetal tissues. Pectic polysaccharides are bioactive macromolecules that consist mostly of polymers rich in galacturonic acid (GalA) and often contain significant amounts of rhamnose, arabinose, and galactose as well as another 13 different monosaccharides. The pectin network must be partially disrupted to enable extraction from the cell wall biopolymer network through the use of calcium-chelating agents, diluted alkali, diluted acid, or cell wall degrading enzymes. It has been suggested that enzymatic digestion is an environmentally friendly method of extraction that contributes to the sustainability of the process involved [13]. Fruits and vegetables are rich in polyphenols with antioxidant activity. These compounds may be classified into different groups as a function of the number of phenol rings that they contain and of the structural elements that bind these rings to one another. They are present in plant tissues associated to polysaccharides. These molecules have demonstrated several biological effects, as tested in vitro or ex vivo: they can inhibit the proliferation of cancer cells, reduce vascularization, exert antiviral activity, protect neurons against oxidative stress, stimulate vasodilatation, and improve insulin secretion [19,20]. The objective of this study was to investigate the action of protease and hemicellulase as well as of a short heat pre-treatment on the extraction of fractions enriched in soluble fiber from residues (bracts and stems) of artichoke (Cynara cardunculus) industrialization, with the purpose of contributing to their utilization through the sustainable obtention of added value products that can be used in the food industry. Results and Discussion Bracts and stems of artichokes purchased in a local market were dried obtaining a powder enriched in cell wall material (CWM). From the latter and by means of ethanol and heating, the alcohol insoluble residue (AIR) was prepared. The yield of AIR was 63 g/100 g CWM for stem and 78 g/100 g CWM for bracts. As can be observed in Tables 1 and 2, in general, the protein, inulin, and polyphenol contents and also the yields were higher for fractions obtained from stems. The galacturonic acid content and, in some cases, the total carbohydrate content were higher for fractions obtained from bracts. With respect to fractions isolated from bracts, it can be observed that: (a) total carbohydrates tended to increase for some treatments when hemicellulase was present at levels of 100-200 mg and (b) proteins and polyphenols tended to decrease when hemicellulase or both enzymes were present. With respect to fractions isolated from stems, it can be observed that: (a) total carbohydrates tended to increase for some treatments when hemicellulase was present at levels of 100-200 mg; (b) for the higher enzyme additions (runs 2, 3, and 4), polyphenol content tended to decrease; and (c) the yield increased with enzyme presence. Hemicellulase (H) is a group of cell wall degrading enzymes such as xylanases, mannases, and arabinases, which can remove hemicellulose substituents and hence weaken the hemicellulose-cellulose network; the one used in the present research has side-cellulase activity according to providers. Protease (P) can degrade extensin, rich in hydroxyproline and present in the cell wall, contributing to cell wall weakening. Consequently, enzymes assayed can alter in a diverse way the cell wall, determining the different characteristics of the fractions obtained. Fissore et al. [16] treated 10 g of artichoke CWM with 250 mg of hemicellulase at pH 5.2 (30 °C, 20 h) and observed that the use of hemicellulase increased the yield and the content of total polyphenols but decreased the content of inulin for both bracts and stems. Furthermore, when hemicellulase was used to isolate pectin from butternut [27], it was observed that the use of this enzyme caused higher yield, higher carbohydrate and protein content, and less galacturonic acid content when compared to a fraction isolated with no enzyme addition. When the fractions obtained from AIR in the present work are compared to those isolated by Fissore et al. [16] from CWM of artichoke, it can be observed that in the former case, fractions contained less protein, less inulin, and more galacturonic acid. Although AIR preparation allowed for concentration of the carbohydrates, eliminating small sugars and other alcohol soluble components, it is possible that protein and inulin have been lost during the heat treatment with ethanol for obtaining AIR, determining the differences observed. The statistical analysis of the results was performed for bracts and for stems through a regressional analysis and a Pearson correlation. Regressional Analysis of the Design The regressional analysis of the results showed that for fractions isolated from bracts, no significant effects of protease and/or hemicellulase concentration were detected in relation to galacturonic acid, inulin, total polyphenol contents, and yield. For carbohydrate content a positive but only slightly significant (p: 0.0314) effect of hemicellulase (H) was observed with a polynomial model: Y = 85.591 + 9.968 H; also, the R 2 of the model was low (0.419). For protein content, a negative and slightly significant effect of hemicellulase (p: 0.0412) was observed, with a low R 2 (0.386) and the following polynomial model: For fractions isolated from stems, no significant effects of enzymes were detected for protein and galacturonic acid contents or for the yield. For carbohydrate content a positive and significant effect of hemicellulase (p < 0.001; R 2 : 0.722) was observed and the polynomial model was Y = 78.2273 + 6.5622 H. The inulin content showed a negative and slightly significant effect of hemicellulase with a polynomial model Y = 16.6891-3.5215 H (p: 0.0382), with a low R 2 (0.396). For polyphenols, a negative effect of protease was observed; the association occurred through the quadratic term (p: 0.0476 and R 2 : 0.533) and the polynomial model was Y = 11.9468-0.6693P-3.2018 P 2 . Pearson Correlation of the Results The correlation between data was analyzed through the Pearson product moment coefficient [28] for bracts and stems. The Pearson product moment correlation coefficients (PPMCC) range from −1 (negative dependence) to +1 (positive dependence), and measure the strength of the linear relationship between the variables evaluated. When evaluating each pair of variables, it was observed that for bracts (pairs of data used: 10), carbohydrates-hemicellulase (PPMCC: 0.6766; p: 0.0317), and polyphenols-proteins (PPMCC: 0.8584; p: 0.0015) were significantly (p < 0.05) and positively correlated. For stems (pairs of data used: 9), carbohydrates-hemicellulase (PPMCC: 0.8308; p: 0.0055), proteins-protease (PPMCC: 0.8110; p: 0.0080) and inulin-hemicellulase (PPMCC: 0.8167; p: 0.0072) were significantly correlated (p < 0.05) and the coefficient was negative for the last pair. These results show that hemicellulase is linearly related to the content of carbohydrates in the fractions and that protease is related to the content of proteins. We also observed a linear relationship between polyphenol and protein contents, a fact that might be ascribed to protein-polyphenol interactions that were previously reported [29][30][31] and can be responsible for their joint extraction. Analysis of the Fractions Isolated through Treatments 1-4 and Study of the Effect of a Pre-Heating Step on Their Yield and Composition From the data in Tables 1 and 2, it could be concluded that the most marked effects were observed when enzymes were used at their higher assayed concentrations. Consequently, treatments 1-4 were further investigated including a heating step previous to the enzymatic treatments with the aim of increasing their yield [6,16]. Results obtained are shown in Tables 3 and 4. Fractions obtained from stems showed, in general, a higher yield and higher protein (when protease is present) and polyphenol (when enzymes are present) content than those obtained from bracts. Table 3. Composition of fractions isolated from bracts of Cynara cardunculus after a pre-heating step. Tables 3 and 4 were analyzed through ANOVA to evaluate the effect of the different enzymatic treatments involved and Tukey's post hoc test was used to evaluate the specific systems that presented different chemical characteristics with treatment. It can be observed that the use of enzymes produced significant changes in chemical composition (carbohydrates, proteins, galacturonic acid, inulin, polyphenols) of fractions isolated from both tissues. Data reported in The same analysis when heat pre-treatment was not applied was performed for data reported in Tables 1 and 2 (Runs 1-4) and results are reported in Table 5. It can be observed that the use of enzymes produced significant changes in chemical composition (total carbohydrates, proteins, galacturonic acid, inulin, polyphenols) for all the fractions evaluated except for stems, for which galacturonic acid was not significantly (p > 0.05) affected by enzymatic treatment. Table 5. One-way ANOVA for the evaluation of the effect of enzymatic treatment for fractions isolated from bracts and stems of Cynara cardunculus (Runs 1-4 of Tables 1 and 2). The statistical comparison of results reported in Tables 1 and 3 and in Tables 2 and 4 allowed us to conclude that the inclusion of a pre-heating step increased the yield and the inulin content for fractions isolated from bracts and stems and decreased the protein, polyphenol, and galacturonic acid contents for bracts. It is known that below temperatures of ≈50 °C, part of the inulin does not dissolve completely [32]. Most likely, the application of a heat pretreatment at 70 °C helped to increase inulin solubility and its concentration in the extract, from which fractions are insolubilized by means of ethanol. According to Lutz et al. [33], the total phenolic content of different cooked vegetables varies depending on the treatment applied. They may decrease up to 50% due to antioxidant breakdown and leaking into the water, may increase due to a higher accessibility, or may remain unchanged. Ruiz-Cano et al. [6] studied the effect of thermal treatment on the composition of six artichoke byproducts and observed that thermal treatment had a negative effect on the protein content, probably due to the loss of soluble proteins; also, the total phenolic content varied widely as a function of thermal treatment. Williams et al. [34] showed that the levels of phenolics and other bioactive compounds decreased when some vegetables were thermally treated. Concerning the evaluation of the effect of heat and enzymatic treatment, two-way ANOVA (Table 6) showed that the application of heat did not have the same effect for all enzymatic treatments, revealing the existence of interactions between both treatments except for total carbohydrate content in stems (p > 0.05). Polyphenol Identification The study of the phenolics present in the different fractions isolated from artichoke bracts and stems with a pre-heating step was performed using HPLC-DAD-ESI-QTOF-MS operated in negative ionization mode. For the identification, UV spectrum and MS data were used, together with the interpretation of the observed MS spectra in comparison with those spectra found in the literature. Figure 1 gives the HPLC-DAD chromatograms of the fractions obtained after a pre-heating step. As can be observed in Tables 7 and 8, some peaks could not be identified. In all fractions a compound was identified with a mass-to-charge ratio (m/z) of 353.09, in accordance with the molecular formula C16H17O9 corresponding to monocaffeoylquinic acid. Another compound with an m/z of 515.12 (molecular formula: C25H23O12), which corresponds to dicaffeoylquinic acid, was observed in Fraction 3, obtained from bracts [35]. These hydroxycinnamic derivatives have been reported previously by Schütz et al. [36] who found that the monocaffeoylquinic acids were the major compounds in a total of 13 Cynara scolymus commercial preparations (six medicinal, one fresh plant juice, and seven dietary supplements). Pandino et al. [37][38][39] also observed that the globe artichoke cultivars "Tondo di Paestum" and "Violetto di Sicilia" were high in caffeoylquinic acids and that, regardless of the cultivar, individual polyphenols were preferentially accumulated in specific parts of the plant, presumably related to their role. In particular, the floral stem was the best source of caffeoylquinic acids, mainly chlorogenic acid (5-O-caffeoylquinic acid) and 1,5-di-O-caffeoylquinic acid. With regard to lignans, at 17.6 min three derivatives of pinoresinol not completely separated through HPLC were detected in all fractions with the exception of Fraction 2, obtained from the stems. The detected m/z of 357.13 corresponds to the molecular formula C26H31O11 and C28H33O12 and the m/z 151.04 and 136.02 correspond to the molecular formula C20H21O6. According to During et al. [40], plant lignans can be absorbed and metabolized in the small intestine, and pinoresinol has a strong anti-inflammatory action on human intestinal Caco-2 cells, possibly in relation to its furofuran structure and/or its intestinal metabolism. Concerning flavone derivatives, an apigenin glucuronide was detected in all the fractions through the fragmentation pattern observed in the MS spectrum, which shows a ion at m/z 269.0462 that corresponds to the molecular formula C21H17O11 [41]. Lombardo et al. [42] studied different varieties of globe artichoke and reported that the receptacles are an interesting source of apigenin derivatives, mainly apigenin-7-O-glucuronide, and that inner bracts are the richest part in total apigenin among all plant parts analyzed. Navarro Núñez et al. [43] noted that the flavonoid apigenin improves the efficacy of aspirin in the inhibition of platelet aggregation. Experimental Section Artichokes were purchased in a local market. The flower head was separated into heart, bracts, and stems. Bracts and stems were cut in small pieces and dried in a convection oven (85 °C, 2.5 h, air rate: 0.5 m/s). The dried product was ground in a domestic grinder (Wemir E909, Buenos Aires, Argentina) to obtain a powder enriched in cell wall material (CWM). Preparation of the Alcohol-Insoluble Residue (AIR) According to Martín-Cabrejas et al. [44], 100 g of CWM were suspended in 350 mL of 80% (v/v) ethanol solution, mixed and then boiled for 30 min under stirring. The residue obtained was then boiled once with 350 mL of 80% (v/v) ethanol solution for 15 min and twice with 250 mL of 80% (v/v) ethanol solution for 15 min. The insoluble residue was separated and washed with 100 mL of 80% (v/v) ethanol and finally with 96% (v/v) ethanol. Between each ethanol treatment, the suspension was filtered and the solvent was discarded. The material was left overnight under a lab hood to eliminate the ethanol and the free ethanol product was freeze-dried (Stokes freeze-drier, Stokes Company, Philadelphia, MA, USA) after freezing at −18 °C. The product was then milled (Wemir E909, Argentina) and stored at −18 °C under a vacuum into heat-sealed Cryovac (polyvinyl chloride-polyvinylidene chloride copolymer) bags until usage. Isolation of the Fractions Since pectin is known to be unstable at pH above 5 when exposed to elevated temperatures [21], it was decided to test enzyme performances at a pH of ≈5, and at a temperature not higher than 50 °C. We also took into account that inulin is stable at pH 5-7 in the temperature range 20-70 °C [22] and its sensitivity to the temperature and acidity of enzyme activities [23][24][25][26]. These facts and the results of preliminary assays determined that the assays were performed at a temperature of 40 °C for 5 h at a pH of 5.2. An amount of 5.00 g of AIR obtained from artichoke stem or bracts was digested in 500 mL of sodium citrate buffer (0.05 M, pH 5.2) with 0.01% sodium azide (w/v) and the adequate quantity of enzyme (range of protease concentration: 0-200 μL; range of hemicellulase concentration: 0-200 mg). Hydrolysis was performed with constant stirring (ARE magnetic stirrer, Velp, Usmate, Italy) at 450 RPM for 5 h at 40 °C. The system was filtered through glass fiber filter and two volumes of ethanol 96% (v/v) were added to the supernatant to precipitate the soluble fiber. After filtration through a glass fiber filter, the solid residue was freeze-dried under the conditions previously described. A pre-heating step was also assayed, for some selected treatments. This step was performed for 5 min at 70 °C under stirring and was followed by cooling to 40 °C. The system was maintained under constant stirring for 5 h either without or with addition of enzymes. Enzymes used were: (A) Hemicellulase H2125 (SIGMA, St. Louis, MO, USA): Hemicellulase from Aspergillus niger with side cellulase activity. One unit will produce a relative fluidity change of 1 per 5 min, using locust bean gum as substrate at pH 4.5 at 40 °C. This enzyme is named herein as H; (B) Protease P1236 (SIGMA, St. Louis, MO, USA): This enzyme is Neutrase ® 0.8 L, a protease from Bacillus amyloliquefaciens with side endo-proteolytic activity. It has an activity of 0.8 Anson unit/g (Au/g). One Anson unit is defined as the amount of enzyme that digests urea-denatured hemoglobin under specified conditions (25 °C and pH 7.5) at an initial rate such that an amount of trichloroacetic acid (TCA)-soluble product is liberated per minute that gives the same color with the Folin-Ciocalteu Phenol reagent as one milliequivalent of tyrosine. This enzyme is named herein as P. Experimental Design In order to find the effect of the factors (protease and/or hemicellulase concentration) on yield and chemical composition of fractions obtained from stem and bracts of Cynara cardunculus, a design was used [45]. The levels of enzyme concentrations were arranged as a two-factor simplex design projected from a star and box central composite design (CCD). A two-factor simplex design was chosen over a full factorial design because the former needs 11 treatments, including triplicate central points, in order to cover five different values for each variable over the experimental space. The minimum full factorial design to test curvature would also require 11 treatments, but spanning only three different data values for each variable. The central composite design tests a fraction of all possible combinations of treatments while ensuring it is statistically appropriate. In a two-simplex design the alpha values of the star points have a range of [−sqrt(2)/2; +sqrt(2)/2], instead of [−sqrt(2); +sqrt (2)], as in a conventional CCD. This difference allowed us to set the real enzyme concentrations at zero for the lowest levels of the box part of the design. On the other hand, a conventional CCD would have required "negative" enzyme concentrations for the star points. Statistical Analysis The data shown in the tables correspond to means and their standard deviations (n = 3). The regression and ANOVA models were analyzed according to Montgomery [45]. Pearson's product-moment correlations between variables were also evaluated. Statistical analyses were performed with R version 3.0.2 (R Core Team, 2013, Vienna, Austria) and Statgraphics Centurion XV (02/15/06 version, 2007, Statpoint Inc, Herndon, VA, Canada) using a critical p value of 0.05. Yield Yield was calculated as g of product obtained per 100 g of AIR used. Chemical Analyses Deionized water was used for all assays. All determinations were performed in triplicate. Determination of Cellulose, Lignin, Non-Cellulosic Polysaccharides, and Protein in CWM and AIR Hydrolysis of cellulose and non-cellulosic polysaccharides was performed according to Ng et al. [46]. From the supernatants, non-cellulosic carbohydrates and uronic acids were determined. From the residues, lignin and cellulose were determined. Total carbohydrate content was determined by the phenol-sulfuric method [47], and protein content was determined according to Lowry et al. [48]. Uronic acid content was determined spectrophotometrically by the method reported by Filisetti-Cozzi and Carpita [49]. Determination of Carbohydrates The total carbohydrate content was evaluated according to the colorimetric method of Dubois et al. [47], using phenol-sulfuric acid and measuring the absorbance at 490 nm. Fructose was used as standard. Protein Analysis The protein content in the samples was determined by the assay of Lowry et al. [48], using bovine serum albumin (BSA) as standard. Determination of Uronic Acids The technique for uronic acids reported by Filisetti-Cozzi and Carpita [49] was used adding sulfamic acid to the samples to suppress the browning of neutral sugars released and heating with a mixture of sulfuric acid and tetraborate. Determination of Inulin The determination was performed according to a modification of the method proposed by the AOAC 999.03 and AACC 3232 [50,51]. For this purpose, an enzymatic kit (Fructan Assay Procedure, Megazyme, Ireland) was used to determine fructans. Determination of Total Polyphenols Total polyphenols were assayed using a Folin-Ciocalteau reagent [52]. Results are expressed as gallic acid equivalents (GAE) in g/100g. Characterization of Polyphenols for Fractions Isolated with Enzymatic Treatment The isolated fractions (0.4 g) were extracted using methanol (4 mL) and with the help of ultrasound treatment for 45 min at room temperature. Then, the samples were placed on a shaker for 48 h at 25 °C. The extracts were filtered through a 0.45-μm syringe filter. Polyphenol analysis was conducted with a Waters HPLC consisting of a vacuum degasser, binary pump, column heater, and diode-array detection (DAD) system. The column used was a 150 mm × 4.6 mm i.d., 5 μm particle size, C18 XBridge from Waters (Dublin, Ireland) with a C18 security guard column. Analysis was performed at 40 °C. Monitoring was performed at 320 nm and the diode-array detector was set at an acquisition range from 210 to 800 nm. For HPLC-MS, separation was performed on an Agilent 1200 Series. This instrument was equipped with a Phenomenex Luna, C18 column (100 × 2.00 mm, 3 μm). The mobile phases and the gradient program were the same as previously described for HPLC-DAD. The flow rate was set at 0.20 mL/min throughout the gradient. The HPLC system was coupled to a Quadrupole-Time-of-Flight mass spectrometer (micrOTOF-Q II, Bruker Daltonik GmbH, Bremen, Germany), an orthogonal accelerated Q-TOF mass spectrometer, equipped with an electrospray ionization source (ESI), which was used in a negative ion mode with nitrogen as the collision gas. The spectra were acquired over a mass ranging from m/z 50 to 1000. The optimum values of the ESI-MS parameters were: capillary voltage, +3.5 kV; drying gas temperature, 200 °C; drying gas flow, 7.0 L/min; set nebulizer, 51 psi; and collision RF, 150 Vpp. Conclusions The use of an enzymatic (protease, hemicellulase) treatment performed at 40 °C for 5 h, allowed us to obtain fractions enriched in soluble dietary fiber from the alcohol-insoluble residue of artichoke bracts or stems. The technique is an environmentally friendly method of extraction that contributes to improving the sustainability of the industrialization process. The yield and chemical composition of fractions were influenced by the tissue used and the level of hemicellulase and protease; the higher levels assayed were the more effective ones for yield or carbohydrate content increases. In general, hemicellulase showed a more marked effect than protease and exerted a positive effect in the carbohydrate content of the fractions. The application of a heat treatment prior to enzyme action contributed to the increase in yield and inulin content and decreased the protein and polyphenol content of the fractions. In general, interactions between enzymatic and heat treatments were observed for the higher enzyme concentrations used. These fractions, in general, contained the polyphenolic compounds monocaffeoylquinic acid, apigenin, and pinoresinol. It can be concluded that the isolation procedure proposed can provide fractions enriched in soluble fiber from waste products of artichoke industrialization; the combination of heat and enzymes forms a useful tool for expanding the portfolio of fractions with diverse content of protein, inulin, pectin, and polyphenols, determining different nutritional, biological, and technological functionalities for these fractions. wrote the manuscript as part of her CONICET grant; Marcelo Soria assisted in the statistical design and evaluation; and Ana M. Rojas collaborated in the analysis of some results.

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The Potential of Some Non-Conventional Vegetable Oils in Biodiesel Applications 3919 | P a g e J u l y 1 6 , 2 0 1 5 The Potential of Some Non-Conventional Vegetable Oils in Biodiesel Applications Abolanle Saheed Adekunle*, John Adekunle Oyedele Oyekunle*, Basirat Adeola Tijani, Wasiu Oladotun Makinde, Olaoluwa Ruth Obisesan, Muibat Olabisi Bello, Iyabo Oluremi Olabanji, Ojo Oluwaseyi Samson 1 Department of Chemistry, Obafemi Awolowo University, Ile-Ife, Nigeria [email protected], [email protected], [email protected], [email protected], [email protected], [email protected] 2 Centre for Energy Research and Development Obafemi Awolowo University, Ile-Ife, Nigeria. [email protected] 3 Department of Pure and Applied Chemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Oyo State, Nigeria [email protected] INTRODUCTION Climate change is currently a serious global environmental concern. Conferences upon conference have been held by various stakeholders on the way to arrest the phenomenon. Anthropogenic factors have been identified as the main cause of global warming, which is responsible for the adverse change in climate due to continuous emission of greenhouse gases (CH4,CO2,NOx) into the atmosphere from burning of fossil fuel (mainly from petroleum) [1][2][3]. However, world energy demand is increasing geometrically as evidenced in increased need of fuel for transportation, industrial as well as domestic operations. Hence, the war against climate change and its attendant environmental pollution and global warming resulting from the use of petroleum fuels remains unsuccessful [4]. Biodiesel is a non-petroleum based fuel that consists of mixture of alkyl esters derived from either the transesterification of triglycerides (TGs) or the esterification of free fatty acid (FFAs) with low molecular weight alcohol. Biodiesel can be used in conventional compression ignition-engines, which need almost no modification. Biodiesel can also be used as heating oil and as fuel [5,6]. The flow and combustion properties of biodiesels are similar to petroleum based diesel and thus can be used either as substitute for diesel fuel or more commonly in fuel blend. Modern biofuels have been reported as a promising long term renewable energy source which has potential to address both environmental impacts and security concerns posed by current dependence on fossil fuels [7][8][9]. Considering the rate at which the world petroleum-based energy demand is increasing as well as the decrease in world's reserve of petroleum, it has been widely reported that not less than ten major oil fields from the twenty largest world oil producers are already experiencing decline in oil reserve [10]. Recently published data also revealed a total of 29 major oil producing countries already experiencing declining oil reserves from the years 2005-2007 [10]. Thus, it has become imperative to source for an alternative renewable fuel such as biodiesel from non-conventional seed oils and other agricultural waste products [3,11,12]. The fruits and seeds from which the non-conventional oils are obtained are available in large quantities but remain either underexploited or unexploited and are allowed to waste due to poor storage system and delay in converting them into important uses for economic gains as it is done for sunflower oil, groundnut oil, soybean oil, etc. Previous studies [13] had shown that these non-conventional oils possessed certain physico-chemical properties that suggest their use either for edibility or industrial applications. To the best of our knowledge, there is paucity of literature on the physical and chemical properties of the resultant biodiesels obtained from the crude and refined forms of these oils. This therefore brought about the motivation of the present study to determine the physico-chemical properties of biodiesels made from the nonconventional oils and highlight the possible benefits of such biodiesels on a large scale basis. The study also compares the biodiesel properties of the non-conventional oils with that of palm kernel oil (conventional seed oil) and commercially available petroleum-based diesel. The blend properties of the biodiesel and petroleum-based diesel were also studied and discussed. MATERIALS AND REAGENTS Matured fruits of Persea americana (Avocado pear), Irvingia gabonenses (Dica nut) and Darcryodes edulis (Native pear) and palm kernel seed used in this work were obtained from local markets in Ile-Ife, Osun State, Nigeria. Commercially available petroleum-based diesel (Diesel motor oil SAE 40 API CF/SF manufactured in Nigeria by African Petroleum PLC) was also obtained for comparative experiments. Other materials include agate mortar and pestle, a batch reactor (500 mL round bottom flask), mechanical stirrer, magnetic stirrer, 120 mL plastic bottle; 100 mL beakers; Metler electronic balance; n-hexane; water bath; NaOH; Wheaton soxhlet extractor; and 99.5% methanol. Oil Extraction and Biodiesel Production Fruits of Persea americana (PA), Dacryodes edulis (DE) and Irvingia gabonensis (IG) collected for the experiments were washed, and the flesh separated from the seeds. Both the flesh and the seeds were air dried and later oven dried at 50 o C for 3 hours. From a previous study by Akanni et al. [13], the oil contents of 50.14, 5.13, 58.09, 17.28 and 70.41% were reported for PA flesh, PA seed, DE flesh, DE seed and IG seed, respectively. Thus, the present study was focused on oils extracted from PA flesh, DE flesh and IG seed because of their respective high percentage oil composition. The dried flesh and seeds were pulverized using a mechanical grinder. Oil was extracted from the milled sample using n-hexane according to the methods of the Association of Official Analytical Chemists [14]. The extracted oils were represented as PAO, DEO and IGO for Persea americana oil, Dacryodes edulis oil and Iirvingia gabonensis oil, respectively. Palm kernel oil (PKO) was extracted under the same condition to serve as a control and for comparative study. The extracted oil was stored in a sealed plastic bottle for further study. Biodiesel was produced from the extracted oils and the commercially obtained palm kernel oil using methanol in the presence of NaOH as catalyst following the method already described in literature [15][16][17]. The transesterification reactions were carried out batch wise at a 6:1 methanol to oil molar ratio, 1% catalyst to oil and 65 o C reaction temperatures. These variables were chosen since they have been found to give optimal yields of methyl ester from seed oils [18]. A batch reactor (500 mL) was charged with 240 g palm kernel oil and heated to the desired temperature in a water bath. Accurately weighed 40g methanol and optimal weight of NaOH (1% by weight of oil) were mixed and heated in a separate container to the desired temperature before being added to the reactor contents. The mechanical stirrer at a stirring speed of 400 rpm was started immediately the mixture was added to the batch reactor. The reactions were performed for 4 hours, and afterwards the reactor and its contents were cooled down under convective air current. The J u l y 1 6 , 2 0 1 5 separation of the fatty acid methyl ester (FAME) and the glycerine phase was carried out by means of a separating funnel. The percentage conversion of the different oils to biodiesel was calculated as: Physico-chemical Properties of the Biodiesel The physico-chemical properties of the biodiesels were determined using the standard methods of the Association of Official Analytical Chemists [14]. Parameters analyzed were relative density, kinematic viscosity, surface tension, cloud point, smoke point, acid value (AV), % free fatty acid (%FFA) and iodine value (IV). The density and viscosity at 30oC, 400C and 60oC were measured using a 25 mL specific gravity bottle and a 50 mL PSL ASTM-IP viscometer. The smoke, flash, cloud and pour points were determined using the American Society for Test and Material (ASTM) standard methods as described by Salvatore (2003) [19]. RESULTS AND DISCUSSION The results of the biodiesel analyses compared with that of petroleum based biodiesel (PBD) are presented in Tables 1-4. The biodiesel yield obtained (Table 1) for PKO (91%), IGO (94%), and PAO (96%), compared favourably with 96.5% set by the International Standards (American Society for Test and Material -ASTM 900 and European Norm -EN 14214), while the 82% yield obtained for DEO agreed closely with the set standard. The percentage biodiesel yield obtained was favourable suggesting low free fatty acid (FFA) content of the oils. It has been observed that the amount of FFA contents of oil greatly determine the conversion of crude vegetable oils into biodiesel, hence the conversion efficiency decreases considerably if FFA content is greater than 3% [20]. Earlier, Akanni et al. [13] had reported acid values of 2.607, 6.10 and 6.726 mgKOH/g sample, corresponding to %FFA of 1.31, 3.07 and 3.38% for IGO, PAO and DEO, respectively. These values are within the 3% expected for crude vegetable oils that would produce very high biodiesel yield as obtained in this work. The acid values obtained in this study for the biodiesels are within the range 0.935-2.230 mgKOH/g, while the %FFA ranged from 0.46 % in PKOD to 1.120% in PAOD ( Table 1). The decrease in both the acid value and the %FFA of the biodiesel relative to that of their crude vegetable oils further confirmed the successful modification of the free fatty acids in the raw oils to the fatty esters in their respective biodiesel. Similarly, the acid and the %FFA values for commercially available PBD analyzed under the same conditions were 1.980 and 0.993% respectively. Palm kernel oil diesel (PKOD) and IGOD had approximately half these values, while the acid values and %FFA of PAOD and DEOD agreed closely with that of PBD. This implies that the %FFA and acid values of the nonconventional oils biodiesels produced met the minimum requirements for their potential applications as source of fuel. The iodine value ranged between 9.64 meq/kg for DEOD and 16.52 meq/kg for PKOD ( Table 1). The values obtained for PAOD, PKOD agreed with 15.00 meq/kg obtained for PBD under the same condition, and 12-18 meq/kg reported in literature for palm kernel biodiesel [21]. The 9.64 and 10.07 meq/kg recorded for DEOD and IGOD respectively were closer to 12 meq/kg for PKD reported in literature (Mittelbach and Schober, 2008).Therefore, the results obtained in this study showed that the produced biodiesel could favourably compete with PKOD and PBD as alternative fuel material for energy generation. High iodine values of biodiesel have been associated with fuel polymerization and formation of deposit in heated internal combustion engine. It has also been linked with decreased oxidation stability that could lead to degradation products or deterioration of the lubricating property, and some inhibition of engine operation [22]. The pour and cloud points analyses in the characterization of biodiesel is very important for they determine the suitability of the fuel for large storage and pipeline distribution [23]. Pour point is the lowest temperature at which the fuel can still be moved, before it becomes gelled. The cloud point on the other hand is the temperature at which small solid crystals are first visually observed as the fuel is cooled. The cloud and pour points of the produced biodiesel were found to be higher than that of PBD ( Table 1). The difference in value was more significant for IGOD (cloud point 31 o C; pour point 29 o C). Palm kernel oil diesel (PKOD), PAOD and DEOD had values close to that of PBD, with PAOD pour point (-6 o C) occurring very close to that of PBD (≥-10 o C). However, the higher cloud and pour points of IGOD might be due to the high fatty acid content of its oil since higher proportions of saturated fatty acids accounts for higher pour point of biodiesel [24]. These properties of IGOD could limit its application as fuel in diesel engine except the oil is improved upon by refining processes. The result therefore suggests that PKOD, DEOD and PAOD can be potential materials in biofuel applications, while IGOD needs further processing before it can be suitable for similar applications. It is evident from Table 1 (Table 1). Flash point determines the safety of fuel during its handling and storage. It is the lowest temperature at which the vapours above the fuel become flammable. The flash point, therefore, specifies the temperature to which a fuel needs to be heated for spontaneous ignition of the vapour and air above the fuel to occur [24]. The results in this work agreed with that of other workers on biodiesel produced from various oil-bearing seeds as well as domestic waste vegetable oil where it was reported that biodiesel has a flash point that is considerably higher than petroleum-based diesel [24,20]. This means that the fire hazard associated with transportation, storage and utilization of biodiesel produced from the non-conventional oils in this study is much less than that of petroleum-based diesel. Table 2 presents the physico-chemical properties of the biodiesel used in this study when blended with the petroleumbased diesel (PBD) at different biodiesel/PBD ratio. This experiment was limited to PAOD and DEOD since I. gabonensis oil congeal readily at room temperature and its biodiesel applications could be limited because of IGOD high cloud and pour points respectively. On the other hand, PKOD blend with petroleum diesel had been studied and reported to impact positively on its bio fuel properties [25]. (Table 1) got reduced to 80 and 90 o C respectively at the blend ratio 40:60 (Table 2). In the same vein, PAOD and DEOD smoke points which were initially 105 and 90 o C (Table 1), had their smoke points reduced to 65 o C at the blend ratio 40:60 ( Table 2). The improved values of cloud, pour, flash and smoke points of the biodiesels due to their blend with PBD is represented pictorially in Figures 1 and 2 below. Similar trend was observed for the chemical parameters of the biodiesels in their blends with PBD. For example, PAOD and DEOD acid values which are initially 2.230 and 2.170 mgKOH/g are now reduced to 1.255 and 1.824 mgKOH/g respectively at blend ratio 10:90 with PBD. Lower acid values were obtained at other blend ratio studied. Lower values were also obtained for the %FFA due to the biodiesel blend with PBD (Table 2, Fig. 3). The iodine value dropped for J u l y 1 6 , 2 0 1 5 PAOD from 16.0 meq/Kg to its lowest value (12.4 meq/Kg) at 40:60 blends, while no significant change was observed for the iodine value of DEOD at all the blend ratio studied. The economic implication of this result lies in the fact that the fuel potential of these biodiesels can be complemented with that of petroleum base diesels thereby reducing the present over dependence and high cost of purchasing petroleum based diesel. Tables 3 and 4 present the effects of temperatures on the density and viscosity of the biodiesels and their blends. Density has been described as one of the most important parameters of fuel since certain performance indicators like heating value and cetane number are correlated with it [20,26,27]. At 30 o C, all the biodiesels used in this study had density values higher than that of the PBD (0.850 g/cm 3 ) under the same experimental conditions (Table 3), and 0.850 g/cm 3 standard set for petroleum based diesel [28]. The implication of the high density of the biodiesel is that there will be delivery of a slightly greater mass of fuel especially for fuel injection equipment that operates on a volume metering system [29]. However, the density values for the biodiesel decreases with increase in temperature (Table 3). Effect of temperature on the viscosity of the biodiesel is presented in Table 3. The viscosity values range from 5.59 to12.71 mm 2 /s. The viscosity of IGOD cannot be determined at room temperature because of the congealed nature of the oil. The viscosities values obtained in this work are too high compared with that of the PBD (4.03 mm 2 /s) obtained under the same experimental conditions. Darcryodes edulis oil diesel (DEOD) viscosity value of 5.59 mm 2 /s fell within the ASTM standards (1.9 -6.0 mm 2 /s) for biodiesel [30]. Viscosity is a measure of the internal flow resistance of a liquid. Viscosity affects injection lubrication and fuel atomization [20]. High viscosity fuel has the tendency of forming engine deposits. Although high kinematic viscosity biodiesel when used in engines can help to lubricate the engine parts which may be an advantage to users [31], but the disadvantages also need to be carefully weighed. In order to take care of the limitation due to the high density and viscosity of the biodiesel recorded in this work, the density and the viscosity of their blends at different ratios with PBD was carried out at different biodiesel/PBD ratios (10:90, 20:80, 30:70 and 40:60), and the result is presented in Table 4. This experiment was limited to PAOD and DEOD biodiesels due to the reason already provided earlier. It was observed from Table 4 that for the entire ratio investigated, the biodiesel density was positively improved upon. For example at 30 o C, PAOD density decreased from 1.105 (Table 3) to 0.852 g/cm 3 at the blend ratio 10:90 (Table 4). Similarly, DEOD density decreased from 0.860 (Table 3) to 0.854 g/cm 3 at the blend ratio 10:90 (Table 4). Thus, the density values obtained for the biodiesel and their blends fell within the recommended specified limits of 875 -900 kg/m 3 [30] and 860 -900 kg/m 3 [32] for biodiesel fuels, and by other international standards [27]. Therefore, the biodiesels and their blends possessed the potentials that can be utilized as automobile diesel fuel and thus, reduce over dependence on the petroleum based diesel alone. Similarly, all the ratios gave an improved viscosity for the biodiesel/PBD blend. The obtained viscosity values fell within the ASTM (1.9 -6.0 mm2/s) and EN (3.5 -5.0 mm 2 /s) set standards, with biodiesel/PBD blend ratios 10:90 and 20:80 giving the best viscosity values that perfectly satisfied the fluidity requirements of an alternative biodiesel fuel. The improved viscosity and density values of the biodiesels due to their blend with PBD is summarized in Figure 4 below. CONCLUSION It was established from this work that some non-conventional oils such as Irvingia gabonensis, Dacyodes edulis and Persea americana oils found in Ile-Ife, Nigeria are potential raw materials for the production of biodiesel based on their excellent percentage biodiesel yields which compared favourably with that of palm kernel oil biodiesel produced under the same conditions. Results obtained from this study indicated that Dacryodes edulis oil diesel (DEOD) and Persea Americana oil diesel (PAOD) had good biodiesel yields of 82% and 96% respectively. Their very good biodiesel qualities were supported by their fuel properties such as acid value, iodine value, pour point, cloud point, smoke and flash point that closely agreed with that of a commercially obtained petroleum-based diesel (PBD) investigated under the same experimental conditions, and with the international standards set for biofuels. Though, Irvingia gabonensis oil gave very high biodiesel yield (94%), but its oil congealed readily at room temperature and its biodiesel application could be limited because of IGOD high cloud and pour points respectively. The oil can be further refined to remove gumming and unsaponifiable materials so that its biofuel potential can be maximized. The results of DEOD and PAOD blend with PBD at different biodiesel/petroleum diesel ratios confirmed a significant improvement in their biodiesel properties, such as acid value, iodine value, pour point, cloud point, smoke point, flash point, density and viscosity respectively at every blend ratio investigated, with best results obtained mostly at 30:70 and 40:60 biodiesel/PBD ratio. The production of biodiesel from these non-conventional oil sources could proffer solutions to several problems of non-renewability of petroleum resources and overdependence on petroleum based diesel. It is recommended that the non-conventional oilseeds should be investigated further for their full economic potentials.

v3-fos

2016-05-12T22:15:10.714Z

2015-08-12T00:00:00.000Z

16603907

s2

Impact of Selection for Digestive Efficiency on Microbiota Composition in the Chicken Objectives Feed efficiency and its digestive component, digestive efficiency, are key factors in the environmental impact and economic output of poultry production. The interaction between the host and intestinal microbiota has a crucial role in the determination of the ability of the bird to digest its food and to the birds’ feed efficiency. We therefore investigated the phenotypic and genetic relationships between birds’ efficiency and the composition of the cecal microbiota in a F2 cross between broiler lines divergently selected for their high or low digestive efficiency. Methods Analyses were performed on 144 birds with extreme feed efficiency values at 3 weeks, with feed conversion values of 1.41±0.05 and 2.02±0.04 in the efficient and non-efficient groups, respectively. The total numbers of Lactobacillus, L. salivarius, L. crispatus, C. coccoides, C. leptum and E. coli per gram of cecal content were measured. Results The two groups mainly differed in larger counts of Lactobacillus, L. salivarius and E. coli in less efficient birds. The equilibrium between bacterial groups was also affected, efficient birds showing higher C. leptum, C. coccoides and L. salivarius to E. coli ratios. The heritability of the composition of microbiota was also estimated and L. crispatus, C. leptum, and C. coccoides to E. coli ratios were moderately but significantly heritable (0.16 to 0.24). The coefficient of fecal digestive use of dry matter was genetically and positively correlated with L. crispatus, C. leptum, C. coccoides (0.50 to 0.76) and negatively with E. coli (-0.66). Lipid digestibility was negatively correlated with E. coli (-0.64), and AMEn positively correlated with C. coccoides and with the C. coccoides to Lactobacillus ratio (0.48 to 0.64). We also detected 14 Quantitative Trait Loci (QTL) for microbiota on the host genome, mostly on C. leptum and Lactobacillus. The QTL for C. leptum on GGA6 was close to genome-wide significance. This region mainly includes genes involved in anti-inflammatory responses and in the motility of the gastrointestinal tract. Introduction Feed efficiency is the major component of both economic profitability and environmental impact of poultry production. It has been shown that when birds are fed a challenging diet (for their hardness and viscosity characteristics) their digestive efficiency has a significant role in feed efficiency, and that is highly heritable [1]. After 8 generations of divergent selection on digestive efficiency, we obtained two genotypes of chickens with 30 to 40% difference between good digesters (D+) and poor digesters (D-). In a preliminary study, Gabriel et al. [2] showed that the composition and homogeneity of microbiota varied widely between these two lines, which suggests that the genetics of the host influence the composition of its microbiota. This difference in microbiota composition is not surprising as biotopes of the digestive tract have probably been modified between these two lines due to differences in anatomy of the gastrointestinal tract and digestive physiology [3]. Moreover, the microbiota is in constant interaction with the host and has been shown to influence several major functions such as the immunological, physiological and nutritional status of birds [4,5]. Several factors originating from the host can impact its microbiota, such as those due to digestive physiology (turnover of the intestinal epithelium, quantity of mucus, motility of gut, gut secretions), the nutrient composition of the bowel which depends on the composition of the diet and on the bird's capacity to digest feed, and the presence of antibacterial compounds of the immune system [6]. Several studies have suggested the existence of the influence of the host's genetics on the composition of the chicken microbiota as it differs between individuals [7,8], between lines selected on growth or digestive efficiency [2,4,[9][10][11][12] and between birds within a genotype with high or low feed or digestive efficiency [9,11,13]. A few studies have gone further than group comparisons, to propose estimates of genetic parameters, genetic or phenotypic correlations between growth performance and microbiota composition or QTL detection for microbiota. Heritability of the quantity of 16S rRNA copies has been estimated in only two studies on high and low body weight chicken lines [4,10]. Despite the relatively low numbers of birds (60 to 132 chickens per study), they indicated that some species or genera such as Lactobacillus spp. or Streptococcae seem to be heritable and correlated with body weight. However, no correlation with feed or digestive efficiency was available, and these studies relied on fecal samples, the composition of which varies widely within a day due to emptying of the ceca [14]. However, studies performed in mammals have indicated that the host's genetics influence its digestive microbiota [15]. The aim of our study was therefore to provide a complete set of information on the genetic basis of the host's influence on microbiota composition through i) comparison of microbiota composition between high and low efficiency groups to establish how far selection on digestive efficiency affected microbiota composition, ii) estimation of phenotypic and genetic relationships between feed efficiency, digestive efficiency and microbiota composition to estimate which proportion of microbiota composition is due to the overall genetic background of birds and iii) Quantitative Trait Loci (QTL) detection of microbiota composition to identify regions in which a variation of the DNA sequence will affect microbiota composition, through a modification of the environment provided to bacteria (e.g., physico-chemical conditions, nutrient concentrations, immune system activity, . . .). As previous studies showed that the difference in microbiota composition between efficient and non-efficient birds was greater in cecal content than in other intestinal compartments [2,11,16], we focused our study on this specific digestive segment. Animals and rearing All animal care and experimental procedures reported in this paper were in accordance with French and European regulations concerning animal experimentation, including authorizations to experiment on live birds no. 37 Data were collected on chickens from a F2 population obtained by crossing two mediumgrowth broiler lines divergently selected on their high (D+) or low (D-) digestive efficiency determined by metabolizable energy corrected to zero nitrogen retention at 3 weeks (AMEn) [1]. The divergent selection experiment started from a pure male line from the SASSO breeding company, used as the father of the medium-growth crossbred commercial chickens. The F2 population, created to detect the QTLs for digestive efficiency, has been described in Tran et al. [17]. Before crossing, the D+ and D-populations presented wide differences in feed and digestive efficiency (30 to 40%) [18,19]. Using an F2 population instead of the initial divergent lines allowed us to compare efficient and non-efficient birds in a population with a common genetic background. Five males and fourteen females per line (D+ and D-) were used as F0 grand-parents. Males of the D+ and D-lines were mated respectively to females from the D-and D+ line to produce the F1 generation (half D+×D-and half D-×D+). Six F1 sires (3 D+×D-and 3 D-×D+) were mated to sixty F1 females of the reciprocal cross (i.e., D+×D-females for D-×D+ males, D-×D+ females for D+×D-males) to produce a total of 864 F2 birds (male and female). The F2 birds were reared in 4 batches (between January and June 2009) on the floor from hatching to 8 d to allow normal development of intestinal microbiota and subsequently transferred to individual cages in three rearing cells until slaughter at 23 d to measure feed and digestive efficiency. Birds were fed a diet similar to the diet used during the selection experiment [17], including 52.5% Rialto wheat and 6% soybean oil, 3110 kcal.kg -1 DM and 21.1% CP. Clinacox (0.02%) was used as anticoccidial agent, as it has a limited effect on the development of intestinal microbiota [20,21]. Phenotypes Birds were weighed at 0, 9, 14, 17, 20 and 23 d. Their feed intake was individually recorded between 9 and 14 d, 14 and 17 d, 17 and 20 d and between 20 and 23 d. A balance trial with a total collection of excreta was performed between 20 and 23 d to measure fecal digestive efficiency traits as AMEn, coefficients of fecal digestive use of dry matter, starch, lipids and proteins (CDUDM, CDUS, CDUL, CDUP). These digestive efficiency traits were determined through near infrared spectroscopy following the method of Bastianelli et al. [22]. Due to time constraints, it was not possible to select birds used for microbiota study on their digestive efficiency. Instead, the subsample of 144 birds used for microbiota determination were selected on their feed efficiency between 17 and 20 d, as feed efficiency and digestive efficiency had been previously shown to be strongly genetically correlated (-0.70, [1]). The mean values of feed efficiency, estimated through the feed conversion ratio (FCR, i.e. the ratio of feed intake to weight gain) were 1.41±0.05 in the low FCR group (FCR_L) and 2.02±0.04 in the high FCR group (FCR_H), respectively. Initial and final body weight of birds in the 2 groups were similar (Table 1), as could be expected from the absence of genetic correlation between AMEn and body weight. Microbiota determination Previous studies in these chicken lines showed that the greatest difference in microbiota composition between D+ and D-was in the cecal content [2]. This study was therefore focused on this digestive segment. At 23 d, after 2h30 of feeding following 8 hours' fasting, birds were killed by pentobarbital injection, and their ceca immediately removed. Ceca were opened and their content gently removed in order to obtain only the content and not the mucosa, frozen in liquid nitrogen and stored at -80°C until further processing. Microbial DNA was then extracted from cecal samples using the QIAamp DNA mini-kit (QIAGEN, cat#51306). We used a combination of the methods of Yu et al. [23] and Stanley et al. [11]. Briefly, 25 mg of cecal content were transferred to a tube with lysis buffer [11] and sterile zirconium beads. Samples were homogenized at maximum speed (Frequency 30.sec -1 ) Retsch MM301 for 3 min, followed by heating at 70°C for 5 min. Following centrifugation (5 min, 16 000 g, 4°C), a second extraction step was carried out. The two supernatants were pooled for the DNA purification step. Proteinase K was added and the sample was heated at 70°C for 10 min to remove proteins. Ethanol was then added and the sample was purified using a QIAamp column as described by the manufacturer. The sample was eluted in Tris-EDTA buffer AE (Qiagen). DNA quantity and quality were measured on a Nanodrop spectrophotometer. 16S rDNA was quantified by qPCR to determine the number of copies of the main bacterial groups in the chicken gut within the Firmicutes phylum (lactobacillus genus, Lactobacillus salivarius and Lactobacillus crispatus species, Clostridium coccoides and Clostridium leptum groups) and within the Proteobacteria phylum (Escherichia coli). The primers used for Lactobacillus were those described by Walter et al. [24] and Heilig et al. [25] for forward and reverse primers, respectively. The primers used for L. crispatus, L. salivarius, C. leptum, C. coccoides and E. coli were those proposed by De Backer et al. [26], Harrow et al. [27], Matsuki et al. [28], Matsuki et al. [29] and Huijsdens et al. [30], respectively. Reactions were run in triplicate in 384 well plates in a final volume of 10 μl. The EpMotion 5070 liquid handling robot (Eppendorf, Le Pecq, France) was used to distribute the master mix and DNA to the 384 well plates. The L. salivarius reaction consisted of 5 μl of TaqMan Universal PCR 2 × Master Mix (Applied Biosystems, Courtaboeuf, France), 0.2 μl of both 10 μM primers (Eurogentec, Angers, France) and minor groove binder probe (Applied Biosystems), 1.9 μl of nuclease-free water and 2.5 μl of template DNA at the appropriate dilution. Amplification was carried out with a Light Cycler 480 (Roche, Meylan, France) as follows: 10 min at 95°C, followed by 45 cycles of denaturation (10 s at 95°C), annealing (30 s at 60°C) and extension (30 s at 72°C). Reactions for the other bacterial groups consisted of 5 μl of Light Cycler 480 SYBR Green I Master Mix (Roche, Meylan, France), 0.5 μl of 10 μM primers (Eurogentec), 1.5 μl of nuclease-free water and 2.5 μl of template DNA at the appropriate dilution. The cycling conditions were as follows: 10 min at 95°C, then 45 cycles of denaturation (10 s at 95°C), annealing (20 s at 60°C) and extension (30 s at 72°C). Following amplification, melting curve analysis was included in order to assess the specificity of the amplified product. Reference clones EF445158 and EF445150 [31] were used to generate the standard curves for the quantification of C. leptum and C. coccoides, respectively. The copy number for each reaction was calculated from the standard curves and determined by the second derivative maximum method [32]. Results are presented as number of 16S rDNA copies expressed per gram of fresh sample ( Table 2). As preliminary studies showed that the Bacteroides genus was not detected in F0 birds from D+ and D-lines [2], this group was not included in the present study. Markers and genotyping All F0, F1 and F2 birds were genotyped with a dedicated Illumina Infinium custom array including 6,000 single nucleotide markers (SNP) markers chosen for their informativity in our design and for their distribution across the genome [33]. The markers presenting deviations from the Hardy-Weinberg equilibrium within families, inconsistent genotyping relative to pedigree or genetic map information or poor quality of markers were discarded from the analysis in order to reduce the risk of erroneous results [33]. Finally, 3,379 markers were used. The genetic map was deduced from the physical position of the SNP markers and from the genetic consensus reference map published by Groenen et al. [34]. This set of markers covers 3,099.1 cM. Statistical analyses Phenotypic analyses. We first tested whether the composition of microbiota (count of each category or ratio of counts between categories) and digestive efficiency parameters were different between the feed efficiency groups. Due to their non-normal distributions, raw bacterial counts were log-transformed before analysis and the ratios calculated with the log-transformed counts of each category. The analysis of variance was performed with the GLM procedure of SAS/STAT Version 9.4 and model 1: where y ijklmn is the performance of animal n (N = 144), μ the general mean, H i the fixed effect of hatch i (i = 1 to 5), S j the fixed effect of sex j (j = males or females), C k the fixed effect of rearing cell k (N = 3), RC l the fixed effect of the raw of cage within the cell (N = 3), G m the fixed effect of FCR group (FCR_H, FCR_L), and e ijklmn the residual pertaining to animal n. In order to determine which microbiota characteristics might be related to digestive efficiency, we carried out multifactorial correspondence analysis with the SPAD 7.0 software. For each trait of microbiota and digestive efficiency, we determined three categories with equal frequencies, i.e. the third with the lowest values, the third with the median values and the third with the highest values (noted L, M and H, respectively). The analysis was performed using microbiota as active traits (i.e. contributing to construction of axes) and projecting digestive efficiency categories on the graph. The impact of active variables was assessed through their relative contribution to each axis. A t-test was then performed to determine whether digestive efficiency traits were significantly associated with composition of microbiota. Genetic analyses. In order to estimate both heritability of microbiota traits and their genetic correlations with digestive efficiency, we added an animal genetic effect into the model used for the analysis of variance (model 1) and estimated genetic parameters with VCE 6.0.2 software [35]. The pedigree used to construct the relationship matrix included 1571 animals. [37,38] with interval mapping based on maximum likelihood estimations [39]. This model does not make assumptions on the number of QTL alleles segregating in the design. The traits were analyzed separately. Depending on preliminary analysis of variance, data were pre-corrected for fixed effects of batch (4 levels), sex (2 levels), rearing cell (3 levels) and cage row (3 levels). QTL analyses were performed by comparing the hypothesis of one QTL (H1) versus no QTL (H0) to test the segregation of a QTL on each linkage group. For chromosome Z, separate analyses were performed for males and females. For each trait on each chromosome, the significance threshold at the chromosome-wide level was calculated from the results of 5,000 simulations of performance under the null hypothesis. For the most significant QTLs, 20,000 simulations were made to derive the genome-wide p-value (P G ) from the chromosome-wide p-value (P C ) using an approximate Bonferroni correction: where r is the ratio of the length of a specific chromosome to the length of the genome considered for QTL detection, as in Tilquin et al. [40]. Confidence intervals for QTLs (95%) were estimated using the LOD drop-off method as proposed by Lander and Botstein [39]. The significance of the QTL effects within each sire family was tested using a Student test, by assuming an equal distribution of the QTL alleles in the progeny. A QTL effect was retained as significant for Student test p-values <0.05, and the corresponding sire families were assumed to segregate for this QTL. These familial substitution effects were estimated in families found to significantly segregate for the QTL. Differences between groups and multifactorial analysis The main differences in digestive and feed efficiency and in microbiota composition between the FCR_L and FCR_H groups are presented in Tables 1 and 2, respectively. Differences in FCR between the two groups were due to higher feed intake in FCR_H, as no difference of initial of final body weight was observed. Due to the incomplete genetic correlations between FCR and digestive efficiency, the difference in digestive efficiency between the two groups (17.3%) was lower than the expected 30 to 40% [18,41]. Differences between the two groups for the coefficients of fecal digestive use of starch, lipids and proteins were similar to differences previously observed between the D+ and D-lines [42], the difference being lower for proteins (10.4%) and higher for lipids (37.7%). Differences between the two FCR groups regarding microbiota composition are shown in Table 2. The groups mainly differed by higher counts for Lactobacillus, L. salivarius and E. coli in the FCR_H group (+24.6%, +58.4% and +50.7%, respectively) than in the FCR_L group. These variations in some bacterial groups resulted in differences in equilibrium between bacteria. As L. salivarius but not L. crispatus differed between FCR_H and FCR_L, their ratio to Lactobacillus was also different between the two groups, with relatively more L. salivarius and less L. crispatus in less efficient birds (P = 0.03 and 0.06, respectively). The ratios of clostridia to lactobacillus and to E. coli were also higher in efficient than in less efficient birds (P<0.02). The association between the composition of cecal microbiota and feed conversion ratio in chicken has already been reported by Torok et al. [16] and Stanley et al. [11]. In the latter study, contrary to our study, a higher L. crispatus count was associated with poor efficiency, but their study was based on a very different genotype and diet, which might explain the difference in results. The phenotypic association between microbiota composition and digestive efficiency was seen with the multifactorial analysis (Table 3, Fig 1). It first illustrated that the first factor of variation in microbiota composition was E. coli, as together E. coli and the ratio of E. coli to Lactobacillus, L. crispatus, C. leptum and C. coccoides represented 52.9% of the variability on the first axis. The second axis reflected the equilibrium between Lactobacillus, L. crispatus and clostridia, with 70.5% of the variability of the axis explained by Lactobacillus, C. leptum, the ratios of L. crispatus to Lactobacillus, C. leptum and C. coccoides and the ratio of C. coccoides to Lactobacillus. All traits of digestive efficiency were significantly associated with these two axes, better digestive efficiency being associated with a lower E. coli count, and thus higher ratios of other bacteria types to E. coli. On the second axis, better digestive efficiency was also associated with lower Lactobacillus and C. leptum counts, higher ratios of C. coccoides and L. crispatus to Lactobacillus and a lower ratio of C. leptum to Lactobacillus. These associations between digestive efficiency and microbiota composition are consistent with literature reports. Indeed, it was shown in previous studies that E. coli and Lactobacillus were more frequent in the chicken ceca when birds were fed a wheat and barley diet, leading to a lower AMEn, than when they were fed a corn diet leading to a higher AMEn [43,44]. The digestive microbiota in the ceca is dependent on the characteristics of this biotope such as the nature and quantity of available substrate and transit time. It has previously been reported that the transit time is much shorter in D-than in D+ birds [45]. This implies that D + birds have more time to absorb nutrients in the intestine, which promotes the development of bacterial species able to survive in harsh conditions, whereas the development of bacteria able to proliferate fast is favored in D-birds with shorter transit times. The quantity and nature of nutrients in the ceca indicate that cecal function is more developed in D+ than in D-birds, the former having heavier cecal weights and cecal content than the latter [45]. This may contribute to the better capacity of the FCR_L birds in our study to extract energy and nitrogen from the diet, which thus leads to a higher AMEn and a lower quantity of nitrogen available to be used by bacteria in uric acid fermentation. Moreover, the relationship between cecal digestive microbiota and feed efficiency may be explained in part by the large number of bacteria present in this digestive segment and by their high metabolic capacity to produce volatile fatty acids by fermentation, which provides an additional energy source for birds [46]. The development of cecal bacteria is also influenced by the nature of the substrates that come both from the end of the small intestine and from the retro-peristaltic flux from the cloaca, the latter including urinary products. Undigested compounds from the ileum in our FCR_H and FCR_L groups were probably different as a consequence of their difference in the digestion of proteins, starch and lipids. Moreover, urinary compounds mainly composed of uric acid may also differ between the two groups [47]. Cecal contents may thus be relatively rich in protein and uric acids in FCR_L birds, and conversely relatively rich in starch in FCR_H birds. These different conditions may be responsible for the different bacterial development, for example the positive relationship between digestive efficiency and the C. coccoides to Lactobacillus ratio might partly be due to the ability of Clostridium spp. to utilize uric acid [48]. On the other hand, the relationship between digestive efficiency and microbiota composition may be due to the effects of microbiota on its host. The cecal digestive microbiota may have an effect on digestive physiology via its production of metabolites such as butyrate, secretion of neuroendocrine hormones and its interactions with the nervous system that innervates the gastrointestinal tract or via neuropeptides [49][50][51][52]. Another contribution of cecal microbiota to fecal digestibility is its contribution to the fecal biomass. However, in the case of the D + and D-lines, this contribution is probably minor as D+ animals with the highest fecal digestibility appeared to have more developed cecal microbiota [2]. Heritability Heritability of microbiota composition reflects the proportion of this composition that can be attributed to the genetics of the host. As they were calculated on a low number of animals, the genetic parameters presented in Table 4 have to be taken as indicative values. Heritability estimates were generally low. However, among the bacterial groups or ratios that differed between FCR_H and FCR_L birds, the ratios of L. crispatus, C. leptum and C. coccoides to E. coli presented significant heritability estimates (between 0.16 and 0.24). E. coli and the ratio of E. coli to Lactobacillus presented similar heritability estimates but, due to higher standard error estimates, they were not significant. By comparing the composition of fecal microbiota in lines selected for high or low body weight, Zhao et al. [4] and Meng et al. [10] also found that microbiota differed between the two lines and that several species presented heritability. As in our study, they found that L. salivarius was not heritable. The presence of significant heritability for some microbiota components and of genetic correlations between microbiota and digestive efficiency is consistent with the expected effects of host genetics on microbiota. By selecting more and less efficient birds, we first changed the quantity of undigested nutrients in the ceca that are used as growth substrates by bacteria. Moreover, several earlier studies on these lines showed that the biotope had been considerably modified in the small intestine, which also affected the conditions of microbiota development. Indeed, we showed that acid secretions and bile acid secretions [17], gut motility [45] and the structure of the intestinal epithelium [18,53] were very different between the two lines. All these parameters may explain an indirect effect of host genotype on microbiota through modification of the microbiota biotope [4]. Finally, the presence of several QTLs for digestive and feed efficiency which are located on GGA16, that also carries the major histocompatibility complex, highlights the fact that the birds' immune system had probably been affected during the selection process, which would also directly affect the relationship between host and bacteria. Both positive and negative genetic correlations were found between digestive efficiency and microbiota composition. As for phenotypic correlations, we found negative genetic correlations between Lactobacillus and starch and protein digestibility, and between E. coli and digestibility of dry matter and lipids. The negative correlation between Lactobacillus and starch digestibility Digestive Efficiency and Microbiota in Chicken may be due to the fact that the ceca of FCR_H group contain more undigested starch that can be used by lactobacillus in fermentation in the ceca, thus favoring its development [54]. Similarly, the negative correlation between digestibility of lipids and E. coli, L. crispatus/E. coli or C. coccoides/E. coli may be due to the negative effect of E. coli on lipid digestibility in the small intestine. A greater amount of E. coli decreases the digestibility of lipids and thus increases the quantity of undigested lipids in the ceca, that can in turn be used by E. coli for its growth in this segment [55,56]. This negative relationship between fecal lipid digestibility and the presence of E. coli in the ceca has already been reported by Rodriguez et al. [43]. The negative correlation may also originate from the effects of bacteria on the host, through the production of unfavorable metabolites, their secretion of neuroendocrine hormones and their interactions with the enteric nervous system [52]. However, not all relationships between microbiota and digestive efficiency were negative. Indeed, several positive correlations were observed between AMEn and C. coccoides and the C. coccoides to Lactobacillus ratio. This may be explained by the caloric extraction from undigestible polysaccharides by this Clostridium spp. which may increase energy available to the host [6]. The positive genetic correlations between protein digestibility and the ratio of C. leptum to lactobacillus (and C. coccoides to Lactobacillus although not significant) could be explained by the ability of Clostridium spp. to metabolize amino acids [57] and to degrade uric acid into Table 4. Heritability (± standard errors) of microbiota composition and genetic correlations (± standard errors) between microbiota composition and digestive efficiency. ammonia that can be used by the host to synthesize amino acids [58]. Clostridium spp. and Lactobacillus may also be involved in regulation of the digestive physiology via the production of beneficial active biological compounds [59,60]. QTL for microbiota We detected a total of 14 QTLs that influence the composition of the microbiota (Table 5). They were all significant only on the chromosome-wide scale. However, the QTL for C. leptum count on chromosome 6, which was significant in all six sire families, was quite close to the genome-wide significance level (P = 0.09). For 10 of these 14 QTLs, C. leptum and lactobacillus were involved. This higher frequency of QTL in these two groups is consistent with their frequency in cecal microbiota in this study [61]. Moreover, Clostridium spp. are able to degrade the non-starch polysaccharides of wheat [62,63], and it is thus possible that our selection on digestive efficiency with Rialto wheat specifically affected these bacteria. The effects of these QTLs were quite high, which is partly due to the fact that we used birds with extreme FCR values for detection. Several of these QTLs co-localized with QTLs for other traits detected in the same experiment. First, co-localizations were found with the anatomy of the gut, such as intestine and particularly ileum weight and length (with QTLs 2, 7, 13 and 14 [17,64]) and proventriculus weight (with QTLs 4 and 6, [17]). Secondly, QTLs 6 and 8 co-localized with the QTL for breast yield [64]. Finally, QTLs for L. crispatus and L. crispatus to C. coccoides ratio co-localized with a QTL for feeding behavior (unpublished data). The QTL for C. leptum count on chromosome 6 was close to genome-wide significance, and we therefore looked for potential candidate genes in this region. Relevant genes present in this region are mainly linked to the inflammatory response of the intestine, which is consistent with previous results in mammals showing the contribution of host genetics to the digestive microbiota community [15]. Indeed, most of the genes shown to have an impact on the composition of gut microbiota are components of the immune system. In this study, candidate genes appeared in the Toll-Like Receptor (TLR) and the transforming growth factor β (TGF-β) pathways. This is consistent with the role of intestinal bacteria in the stimulation of immune system development and induction of a continuous anti-inflammatory response in the host [61,65]. The TLR receptors present in the intestinal epithelium are able to recognize molecular patterns present in microbial cell walls and are the first line of defense in the immune response of the host to microbes. They have also been shown to be involved in the control of microbiota in mice [66]. They activate transcription factor NFκB, that in turn regulates the expression of genes of both innate and adaptive immunity, including inflammatory cytokines [67,68]. Most commensal bacteria, including C. leptum, are able to limit the immuno-regulatory NFkB pathway by their production of butyrate [6,69]. The genes linked to NFκB in our QTL zone were i) DMTB1 which activates NFκB and has been shown to limit intracellular invasion by Salmonella enterica [70], ii) C6H10ORF46, the neddylation of which can be reduced by bacteria, which in turn blocks the NFκB pathway [69], iii) GRK5 the expression of which inhibits the expression of NFκB [68], and iv) PRDX3 which interacts with MAP3KIA to regulate expression of NFκB [71]. TGF-β is a cytokine involved in the secretion of interleukin 17 (IL-17) by Th17 and Treg cells which contribute to the inflammatory process in the intestine [72], and its production is stimulated by the presence of C. leptum [6,73]. Within the TGF-β pathway, our QTL zone contained i) HTRA1 which inhibits signals from TGF-β family members [74], ii) RAB11FIP2 which is involved in the limitation of inflammatory responses to commensal bacteria through its action of compartmentalization of Toll-Like receptors [75], iii) ADAM12 which limits the production of IL-17 by Th17 cells [72], and iv) C10ORF88 which is also involved in the secretion of IL-17 by Th17 cells through its effect on vitamin D metabolism [76]. Vitamin D also regulates the innate immune response to microbiota [77]. In addition, the PSTK gene within the QTL for C. leptum (GGA6), which contributes to the selenocysteine secretion pathway, is used by bacteria to fix selenium, a trace element that has Digestive Efficiency and Microbiota in Chicken an anti-apoptotic function in the colonic crypts and contributes to the integrity of the intestinal mucosa [78]. This gene is also involved in the regulation of calcium metabolism which is required for normal early muscle development, which is also consistent with the fact that this QTL co-localizes with a QTL for breast yield found in the same experiment [64]. Finally, our QTL region for C. leptum on GGA6 also includes genes involved in the regulation of intestinal motility such as VMAT2 and BAG3, which to our knowledge has not been reported before. BAG3 is expressed in the muscular layer of the intestine and has a probable function in the regulation of motility of the intestine [79]. VMAT2 is a transporter of catecholamines such as dopamine and norepinephrine that affect both immunity and motility of the intestine and have been shown to be stimulated by the presence of Clostridium spp., including C. leptum [6]. This is also consistent with our previous results on the D+ and D-lines showing wide differences in transit times between the two lines, particularly in the ceca [45], and this factor may be involved in modification of digestive microbiota (including clostridia), as has been reported in the mouse [80]. Conclusion Our study clearly demonstrates the existence of genetic control by the host of its microbiota, and the link between host genetics, microbiota composition and feed and digestive efficiency. Lactobacillus, C. leptum and E. coli were identified as the most important factors in this interaction. Moreover, the equilibrium between the different categories of bacteria is also an important element of this interaction. The QTL for C. leptum on chromosome 6 indicates that the inflammatory response of the gut and the motility of the digestive tract are the most probable processes involved. Transcriptomic analyses are underway to confirm the involvement of these candidate genes in determination of microbiota.

v3-fos

2015-06-01T23:46:22.000Z

2015-05-19T00:00:00.000Z

15434217

s2

Genetic (co)variance of rainbow trout (Oncorhynchus mykiss) body weight and its uniformity across production environments Background When rainbow trout from a single breeding program are introduced into various production environments, genotype-by-environment (GxE) interaction may occur. Although growth and its uniformity are two of the most important traits for trout producers worldwide, GxE interaction on uniformity of growth has not been studied. Our objectives were to quantify the genetic variance in body weight (BW) and its uniformity and the genetic correlation (rg) between these traits, and to investigate the degree of GxE interaction on uniformity of BW in breeding (BE) and production (PE) environments using double hierarchical generalized linear models. Log-transformed data were also used to investigate whether the genetic variance in uniformity of BW, GxE interaction on uniformity of BW, and rg between BW and its uniformity were influenced by a scale effect. Results Although heritability estimates for uniformity of BW were low and of similar magnitude in BE (0.014) and PE (0.012), the corresponding coefficients of genetic variation reached 19 and 21%, which indicated a high potential for response to selection. The genetic re-ranking for uniformity of BW (rg = 0.56) between BE and PE was moderate but greater after log-transformation, as expressed by the low rg (-0.08) between uniformity in BE and PE, which indicated independent genetic rankings for uniformity in the two environments when the scale effect was accounted for. The rg between BW and its uniformity were 0.30 for BE and 0.79 for PE but with log-transformed BW, these values switched to -0.83 and -0.62, respectively. Conclusions Genetic variance exists for uniformity of BW in both environments but its low heritability implies that a large number of relatives are needed to reach even moderate accuracy of selection. GxE interaction on uniformity is present for both environments and sib-testing in PE is recommended when the aim is to improve uniformity across environments. Positive and negative rg between BW and its uniformity estimated with original and log-transformed BW data, respectively, indicate that increased BW is genetically associated with increased variance in BW but with a decrease in the coefficient of variation. Thus, the scale effect substantially influences the genetic parameters of uniformity, especially the sign and magnitude of its rg. Background Uniformity of traits depends on an individual's sensitivity to perturbations in its internal environment and of unknown local micro-environmental factors [1][2][3]. Additive genetic variance in uniformity is defined as the genetic heterogeneity of the residual variance for a trait [4][5][6]. Accordingly, less sensitive genotypes have offspring that are more uniform and show a smaller within-family residual variance. In animal production, uniformity is often a desired character because: (1) it indicates phenotypic robustness and (2) it aids in producing homogeneous animal stocks and uniform food products. Generally, aquatic animals exhibit considerable heterogeneity in growth performance. Large variation in body weight (BW) among individuals reduces fish welfare and decreases the sustainability of the aquaculture industry [7]. A common practice to reduce heterogeneity in growth performance is regular grading during rearing, where heterogeneous fish schools are size-sorted into more homogeneous groups that are harvested at different times. However, these procedures reduce overall profit at the farm scale because labor and farming costs increase and the price of smallsized fish is lower. Another solution would be to select animals for uniformity of growth performance, provided that some genetic variance exists for this trait. Rainbow trout, Oncorhynchus mykiss (Walbaum 1792), is an economically important aquaculture species, and breeding programs distribute improved material across continents [8]. Producers worldwide of rainbow trout regard growth performance and its uniformity as two of the most important traits to be improved by selective breeding [9]. When rainbow trout from a single breeding program are introduced into various production environments, a genotype by environment (GxE) interaction on growth performance and its uniformity may occur, which hampers genetic improvement of these traits across multiple environments. However, to our knowledge, GxE interaction on uniformity of growth performance in rainbow trout has not been studied. In Finland, rainbow trout is farmed in sea and in inland freshwater environments. The nucleus of the Finnish national breeding program is located inland, where breeding candidates are kept in fresh water, while their sibs are performance-tested in the Baltic Sea, where most largescale commercial production takes place. To reduce the risk of disease infections, sea-tested individuals and their eggs or milt are not transported from the sea test station back to the nucleus. Genetic parameters for uniformity of BW in rainbow trout have been studied only in the nucleus environment [10], using the additive model described by Mulder et al. [11]. The statistical methods applied for genetic analysis of uniformity of BW have, however, evolved rapidly in recent years. Rönnegård et al. [12] introduced a double hierarchical generalized linear model (DHGLM), which has the advantage of accounting for the non-normal distribution of squared residuals. Therefore, in this study, genetic parameters for uniformity of BW that were previously estimated in the nucleus environment were confirmed by using multivariate DHGLM, and uniformity of BW was studied on fish from both the freshwater nucleus and sea test stations. For many morphological traits, a positive correlation between mean and variance is expected, i.e. the variance increases with the mean, which is referred to as a scale effect [13]. When trait variation is scaled by the mean trait value, e.g. by logtransforming the data, the resulting log-transformed variance quantifies the variation that does not depend on the scale effect [13,14]. Thus, the aims of this study were: (1) to quantify the genetic variance of harvest BW and its uniformity and the genetic correlation between these traits for sibs reared in the freshwater breeding nucleus and in the seawater production environment, and (2) to investigate the degree of GxE interaction on uniformity of BW for these two environments. Finally, we also log-transformed the data to investigate whether genetic variance in uniformity of BW, GxE interaction on uniformity of BW, and the genetic correlation between BW and its uniformity were influenced by the scale effect, micro-environmental sensitivity, or both. Data The data used in this study originated from the Finnish national breeding program [15,16]. All procedures that involved animals were approved by the animal care committee of the Finnish Game and Fisheries Research Institute (FGFRI). The breeding nucleus (defined as the breeding environment or BE) was located on the FGFRI fish farm located in Tervo (Central Finland). Siblings of the breeding candidates were tested in commercial sea cages (defined as the production environment or PE) located in the Baltic Sea. Phenotypic data comprised 53 638 records on BW at tagging from four year classes and belonged to two subpopulations, i.e., 1996/1999 and 1997/2000, which were measured for both environments. For each year class, the number of sires and dams and the number of recorded offspring are in Table 1. Both subpopulations were established from the parents of year class 1993. Sires and dams were mated using either paternal nested or partial factorial mating designs. Each year class consisted of 94 to 197 full-sib families established from the mating of 37 to 95 sires with 79 to 129 dams. After hatching, fingerlings from the same full-sib family were maintained in one or more family tanks until they reached a body size suitable for individual passive integrated transponder (PIT) tagging (i.e. at a mean BW of approximately 50 g). During tagging, full-sibs from each family were randomly sampled and divided into two or three batches that were reared either in BE or PE. When the fish were 2 years old, they were individually weighed, denoted by BW BE in g for BE and BW PE for PE. For BE, sex and sexual maturity status were recorded based on external sex characters, whereas for PE, since fish were slaughtered, sex and maturity were identified based on the morphology of the gonads. In total, 22 175 and 20 865 individual records were available for BW BE and BW PE , respectively (Table 1). Average BW BE and BW PE (standard deviation, SD) estimated from the raw data were equal to 1094 (364) and 1050 (335) g, respectively. Statistical analysis We used DHGLM for statistical analysis [12,14,17], which uses a log-link function to account for the nonnormal distribution of squared residuals. The models were run for two transformations for the data. First, observed BW were standardized to a mean of 0 and variance of 1 to rescale the original data, which facilitates convergence. Second, observed BW were log-transformed to account for the scale effect. Log-transformation is one way to reduce dependency of variance on mean, since the log-variance represents a parameter that is similar to the coefficient of variation [13]. Both standardized and logtransformed data were modelled using the following multivariate sire-dam DHGLM in ASReml [18,19]: where G is 4×4 sire-dam (co)variance matrix, and A is the numerator relationship matrix. Q(Q v ) is the incidence matrix of random effects common to full-sibs (family tank prior to communal rearing and non-additive genetic effects) other than additive genetic effects, and c(c v ) is the vector of solutions for the effect common to full-sibs, is a scaling variance that was expected to be 1, since W contains the reciprocal of the individual residual variances. The multivariate sire-dam DHGLM was fitted iteratively, with updating of ψ and the diagonal elements of W Ej and W v,Ej until the log-likelihood converged [19]. Calculation of estimates of genetic parameters The estimated additive genetic sire-dam variance com- In the sire-dam model, the estimated variance component for sires was set equal to the variance component for dams and equal to one quarter of the additive genetic variance σ 2 , and the estimated variance component for uniformity of BW σ 2 u v was equal to one quarter of the genetic variance for uniformity of BW. Therefore, additive genetic variance components estimated for BW σ 2 a À Á and for uniformity of BW σ 2 a v were equal to 4σ 2 u and 4σ 2 u v , respectively. Phenotypic variance σ 2 c is the variance component for the effect common to full-sibs and σ 2 e is the residual variance of BW, which in a sire-dam model includes one half of the additive genetic variance plus the random environmental variance. Therefore, σ 2 u was multiplied by 2 to calculate σ 2 p . Heritability for BW (h 2 ) was calculated as σ 2 a =σ 2 p and for uniformity of [20] and Appendix). Similarly, the common environmental effect for BW (c 2 ) was calculated as σ 2 c =σ 2 p and for uniformity of BW The genetic coefficient of variation for uniformity of BW (CV a v ) was calculated as . Three genetic correlations (r g ) were calculated based on the additive genetic covariance divided by the product of the two corresponding additive genetic standard deviations: (1) between BW and its uniformity within an environment, (2) for one trait (BW or its uniformity) in BE versus PE, i.e. to quantify genetic re-ranking between environments, and (3) between BW in one environment and its uniformity in the other environment. Approximate standard errors of variance component estimates were calculated with ASReml following Fisher et al. [21]. Approximated standard errors of h 2 v and c 2 v are not available in ASReml and to our knowledge have not been derived. Comparison with an additive model We also used an additive model that refers to the "iterative bivariate model" described in Mulder et al. [11], to analyze part of the data for BW and its uniformity using the log-squared residuals, as described in [10,11]. In that analysis, we included only the data from BE and we report only the genetic correlation between BW and its uniformity. Our aim was to verify whether or not the genetic correlation estimated by the additive model was consistent with that estimated by the DHGLM when the scale effect on uniformity of BW was accounted for by log-transformation of BW. Genetic variation of BW and its uniformity Using standardized data, additive genetic variances for BW were similar for BE and PE (0.140 to 0.143). Heritability estimates for BW (h 2 ) were also similar and moderate for BE (0.258) and PE (0.221) ( Table 2). Heritability estimates for uniformity of BW h 2 v À Á were low and of similar magnitude for BE (0.011) and PE (0.010). Using log-transformed data, additive genetic variances in BW were proportionally lower for both environments (0.013 to 0.015) than with standardized data. All estimates of genetic variance for uniformity of BW were greater than their standard errors (SE). Using log-transformed data, estimates of h 2 for BW in BE and PE were slightly lower (0.12 to 0.17) than with standardized data, and the esti- for uniformity of BW in BE (0.024) was slightly higher than with standardized data, whereas h 2 v À Á in PE (0.010) was similar to that obtained with standardized data. While estimates of h 2 v À Á were low, genetic coefficients of variation CV a v for uniformity of BW estimated with standardized data were equal to 21.1% for BE and 19.0% for PE, which indicated a high genetic potential for response to selection relative to the mean. The CV a v for uniformity of BW estimated with log-transformed data was equal to 29.6% and 17.4% for BE and PE, respectively, which supports the existence of genetic differences for uniformity of BW beyond the scale effect. Estimates of common environmental effects on BW, c 2 , ranged from to 0.02 to 0.03 for both environments, which suggests that a small amount of phenotypic variation was due to separate full-sib tanks before communal rearing and to non-additive genetic effects. The estimate of c 2 v for uniformity of BW ranged from 0.004 to 0.005 when estimated based on standardized data and from 0.019 to 0.021 when estimated with log-transformed data. Genotype by environment interaction Using standardized data, the estimate of r g of BW between BE and PE was equal to 0.70 ± 0.06, which means that a low degree of re-ranking occurred between environments (Table 3), while slightly greater re-ranking (r g = 0.56 ± 0.20) was found for uniformity of BW between BE and PE. Using log-transformed data, the estimate of r g of BW between BE and PE was equal to 0.66 ± 0.06, which was similar to that obtained with standardized data. In contrast, the estimate of r g of uniformity of BW between BE and PE was close to 0 (-0.08 ± 0.33), which indicates that, after accounting for the scale effect, the ranking of breeding values for uniformity of BW between BE and PE was independent. Genetic correlation between BW and its uniformity With standardized data, the estimate of r g between BW and uniformity of BW was lower in BE (0.30) than in PE (0.79). However, with log-transformed data, the estimates of r g between BW and uniformity of BW in the two environments were similar but negative (-0.83 in BE and -0.62 in PE). For transformed data, the magnitude of these estimates was greater than the estimates of r g between BW BE and its log-squared residuals from the additive model (-0.40 ± 0.05). As for genetic correlations within one environment, estimates of r g between traits measured in different environments depended on whether standardized or logtransformed data were used (Table 3). With standardized data, the estimates of r g between BW BE and uniformity PE (0.49) and between BW PE and uniformity BE (0.46) were similar. Conversely, r g estimated with log-transformed data was negative but of similar magnitude between BW BE and uniformity PE (-0.42) and between BW PE and uniformity BE (-0.31). Genetic variation for uniformity of body weight Heritability for uniformity of BW estimated with standardized data was low for both environments (<0.02). After log-transformation, estimates of h 2 and c 2 for BW were lower in both environments, whereas estimates of h 2 v and c 2 v for uniformity of BW were higher in BE but lower in PE. The estimates of h 2 v for uniformity of BW obtained in this study are in line with those previously reported for rainbow trout h 2 v ¼ 0:024 À Á [10] and for terrestrial animals such as snail [22], broiler chickens [11,23,24], mice [25], and pigs [26] ( h 2 v ¼ 0:028 : min = 0.006 and max = 0.047; reviewed by Hill and Mulder [6]). These h 2 v estimates are low partly because the Table 2 Estimates of variance components and genetic parameters of body weight at harvest and its uniformity measured under breeding and production environments, with or without log-transformation of the data where σ 2 e is the residual variance for body weight; σ 2 a and σ 2 av = additive genetic variance for body weight and its uniformity, respectively; σ 2 c = common environmental variance; CV av = coefficient of additive genetic variance for uniformity σ av =σ 2 ; h 2 = heritability for body weight; c 2 = common environmental effect due to full-sib tanks; h 2 v = heritability for uniformity; c 2 v = same as c 2 but for uniformity of body weight. Table 3 Estimates of the genetic correlation (r g ) and standard errors between body weight at harvest (BW) and its uniformity, within and between environments and with or without log-transformation of the data heritability is defined at the level of a single observation and estimating a breeding value for variance based on a single observation will be inaccurate. In addition, uniformity of BW can be affected by multiple environmental factors that reduce heritability estimates [27]. In fact, finding low heritabilities with high CV a seems to be a general observation for traits that are closely related to fitness, such as fecundity and age at sexual maturity [27]. Although we found low estimates of h 2 v for uniformity of BW, its CV a v was high in both environments (21.1% in BE and 19.0% in PE), which indicates a high potential for genetic gain in response to selection for increased uniformity relative to the mean [5,27,28]. The CV a v estimated in this study are in the lower range of those reported previously for uniformity of BW in rainbow trout (0.374) [10], Atlantic salmon (0.417) [14], and terrestrial animals ( CV a v = 40.6%; min = 30.0% and max = 58.0%) [6,11,[22][23][24][25][26]. The CV a v estimated with standardized BW data can be explained by both the scale effect and additive genetic effects of micro-environmental sensitivity. As expected, when the scale effect was accounted for by log-transformation of BW, the additive genetic variance of uniformity of BW decreased. Yet, after log-transformation, CV a v estimates remained high, which indicates that genetic variation for uniformity of BW is scale independent. Previous studies have reported a similar phenomenon by comparing transformed and untransformed data for BW in Atlantic salmon [14] and for litter size in rabbits and pigs [29]. Studies on uniformity commonly use transformed data to reduce non-normality of the data. For example, squared residuals were log-transformed in the additive model applied in [10,11], and a Box-Cox transformation was used in the Bayesian approach of [10,23,28,29]. It is likely that such transformations also removed part of the scale effect from the data, which influences the genetic parameters of uniformity, as evidenced by the current and previous studies [14,29]. The definition of uniformity before and after logtransformation is not the same. From a biological point of view, uniformity of log-transformed BW may be more relevant because the scale effect is accounted for and thus the actual genetic variation for environmental canalization can be quantified. However, for a fish farmer, uniformity at the observed scale may be more relevant because it corresponds to the real range of fish sizes that are processed by the industry. Variance at the observed scale can be selected for directly, whereas log-transformed variance can be controlled either by direct selection, or by selecting on an index with appropriate weights on mean BW and observed variance. In the sire-dam mixed DHGLM that we applied, the squared residuals that were used as phenotypic observations of uniformity included both the Mendelian sampling term and the true residual that remained unexplained by the systematic fixed effects, the random additive genetic effects, and the non-genetic random effects. The animal mixed DHGLM, assumes that the residual is free of Mendelian sampling variance [14]. However, applying this model may create biased genetic parameters for uniformity [30] and thus requires that repeated records from the same individuals are used to minimise the bias of genetic parameters [12]. A reduction in phenotypic variation of animal traits is beneficial for animal production. However, selection for uniformity in livestock is in its initial phase of development. In rabbits, selection for uniformity of birth weight was implemented successfully and resulted in improved survival rate of baby rabbits without reducing mean birth weight [31]. To our knowledge, selection for uniformity has not been implemented yet in fish breeding. It has been stated that selection for uniformity is not relevant when the profit function based on mean values of a trait is linear [28], which is the case for growth performance or body weight. However, it is arguable that uniformity per se has both an economic and a noneconomic value [32]. In aquaculture, a more uniform growth pattern reduces the mortality of smaller fish [33]. During the grow-out period, the size of feed pellets is increased as the mean BW of a fish school increases. Thus, a uniform growth pattern allows most fish to adapt to changes in pellet size. Uniformity of growth may also partially reduce negative social interactions between fish and thus the development of behavioural dominance hierarchies [34,35], which further improves fish welfare. Moreover, it has been suggested that uniformity of growth performance reduces the need for size-grading and thus, improves the efficiency of fish production [36]. Therefore, while the economic value of uniformity remains to be calculated, simultaneous selection for BW and its uniformity is expected to yield direct and indirect profitable prospects. Direct selection for uniformity of a trait should be carried out if this trait is economically important and can be recorded at an acceptable cost. The methods investigated in this study can also be extended to other trait types. For example, reducing the variation in carcass quality traits that have intermediate optimum values such as fillet color, fillet lipid content and body shape, has economic value, i.e. fillet color and fillet lipid content should not be too low or too high, and body shape should not be too thin or too round. Considering the breeders equation ΔG = ir IH σ a [3], response to selection is determined by three factors: selection intensity (i), accuracy of selection (r IH ), and the genetic standard deviation (σ a ) or CV a when ΔG is relative to a trait mean. We found that the CV a v for uniformity of BW was high, which indicates that substantial genetic response to selection relative to the mean can be expected. To minimize sampling variance of the estimates of σ a v , phenotypes on a large number of relatives are required. Based on the equation in Hill and Mulder [6], the optimal family size to estimate variance components for uniformity of BW is 85 for full-sibs when using average h 2 estimates of 0.145 for log-transformed BW and a CV a v of 23.5% for log-transformed uniformity of BW (Table 2). In livestock, e.g., for dairy cattle, information is mainly available from half-sibs, for which the optimal design is 190 half-sibs for the same input parameters. With respect to the r IH , accuracies of sib selection for a trait with a h 2 v of 0.014 and c 2 v of 0.012 (average values from Table 2) are equal to 0.234, 0.300, 0.364, and 0.412 for full-sib family sizes of 40, 80, 160, and 300, respectively. When the values of h 2 v and c 2 v reported by Janhunen et al. [10] are used, accuracies increase slightly and the required family sizes decrease. With the accuracies of sib selection above, it is possible to calculate expected changes in uniformity of BW. Using a proportion of 10% of selected animals (selection intensity = -1.755), a CV a v of 0.211 in BE (Table 2), genetic gain was calculated following Mulder et al. [5]. Residual variance of BW (as a percent of the trait mean) decreased by -9%, -11%, -13%, and -15%, for full-sib family sizes of 40, 80, 160, and 300, respectively. For many aquaculture species, it is possible to have large families. However, the challenge is that breeding candidates are from the offspring generation and their selection accuracy is lower than that of their parents. Progeny-testing schemes are effective to increase the accuracy of selection for traits with low heritability, including uniformity [5,28], but have not gained popularity in aquaculture breeding. In aquaculture breeding schemes, sib-testing is considered to be more feasible because large sib groups increase selection accuracy and generation intervals are shorter than in progeny-testing schemes. The most suitable designs to improve uniformity in aquaculture are still to be developed. Another approach to increase the accuracy of sib selection is to use genomic selection [37,38], which can theoretically increase accuracy of selection without progeny testing. Genotype by environment interaction To the best of our knowledge, this is the first study on GxE interaction on uniformity of BW in rainbow trout. The main production environment for Finnish rainbow trout is in the Baltic Sea. PE and BE differ considerably in terms of water temperature, salinity, length of growing season, feeding practice, and type of cage culture (sea cages vs. earth-bottomed raceways). With standardized data, moderate re-ranking of families for uniformity of BW was found (r g = 0.56), which indicates that uniformity of BW shares a certain degree of genetic background in each environment. When scale effects and microenvironmental sensitivity simultaneously influence uniformity of BW, the magnitude of re-ranking for uniformity of BW is only slightly smaller than for BW (0.62 to 0.70). This was surprising, given that the two environments analyzed differed greatly, and that standard deviations of individual BW, measured as squared residuals, are influenced by many unspecific abiotic and biotic environmental factors, as well as by developmental perturbations during the two years of growth. However, when the scale effect was accounted for by log-transformation, the genetic correlation between uniformity of BW in BE and PE decreased to -0.08. This shows that the scale effect may be the main factor that causes the moderate positive correlation between uniformity of BW in the two environments, and that uniformities estimated with standardized versus log-transformed data are genetically distinct traits. Log-transformed uniformity is more greatly influenced by micro-environmental sensitivity than by scale effects. The genetic correlation of -0.08 between uniformities of BW in BE and PE was the lowest genetic correlation reported for any trait across these two environments, but had a high standard error (0.33). The high sampling variance of the r g may be explained by the low h 2 v for uniformity of BW in both environments, but also by the fact that standard errors of genetic correlations tend to increase with decreasing magnitude of genetic correlations [39]. If the aim is to increase genetic response in uniformity of BW in both environments, an optimized selection strategy that accounts for the GxE interaction on uniformity and uses sib performances in both environments is recommended [40][41][42]. Uniformity of BW in the nucleus environment and in the production environment should be considered as two different traits and should be included separately in a selection index. In a situation where two or more environments are equally important, it might be possible to establish a separate breeding program for each environment to maximize response to selection for uniformity in each environment [43]. Nevertheless, establishing an additional breeding program is very costly and may not be possible in many cases. Genetic correlation between body weight and uniformity In addition to the degree of re-ranking of families for uniformity in the two environments, the scale effect drastically affected the genetic correlation between BW and its uniformity. Genetic correlations of 0.30 and 0.79 were found between BW and its uniformity in BE and PE, respectively, but these values switched to -0.83 and -0.62 after the scale effect was accounted for by logtransformation. A similar change in sign was observed for correlations between BW in one environment and its uniformity in the other environment. The data obtained for BE were also analyzed using the additive model, which used log-squared residuals [11]. This resulted in a genetic correlation of -0.40 between BW and its uniformity, which is closer to the genetic correlation estimated after log-transformation in the DHGLM. On the whole, the genetic correlation estimated between BW and its uniformity was unfavourable when untransformed BW data were used but favourable when log-transformed BW data were used. Hence, selection for BW increases the variance of BW, but decreases the coefficient of variation (CV) for BW because the increase in variance of BW is smaller than expected if the CV for BW remains constant or decreases. It may be argued that due to increased growth rate, farmers can harvest fish earlier rather than at an increased BW. Hence, the genetic gain in BW or growth (e.g. g/day) is expressed as lower age rather than higher weight at slaughter. In that case, it is still unknown whether genetic variation in uniformity of BW changes since fish are slaughtered at a younger age. We observed a change in the magnitude and sign of genetic correlations between BW and its uniformity after data transformation, which agrees with other studies. Sonesson et al. [14] reported that the Pearson correlation between estimated breeding values of BW and its uniformity in Atlantic salmon changed from 0.42 with untransformed data to -0.17 with log-transformed data. Several studies on livestock species have reported negative genetic correlations between BW and its uniformity ( r g = -0.36: min = -0.81 and max = -0.11) [6,11,[22][23][24]. Yang et al. [29] estimated the genetic correlation between the mean and variance of litter size in rabbits and pigs using a model with Markov chain Monte Carlo (MCMC) sampling, which simultaneously estimated the model parameters and the Box-Cox transformation parameters. They compared genetic correlations before and after Box-Cox transformation and found that they changed from -0.73 to 0.28 for rabbit data and from -0.64 to 0.70 for pig data. Moreover, while the genetic trends across four successive generations showed that growth rate increased across generations by selection, no correlated genetic change in uniformity of growth rate was found during the same period, when uniformity was estimated based on log-transformed data (residual variation scaled by the trait mean). Estimates of genetic correlations between BW and its uniformity obtained in our study using the DHGLM and an additive model were of the same sign (-0.157) as in Janhunen et al. [10] but more negative. Thus, it is likely that selection for increased BW based on the genetic parameters estimated here, will result in a favourable correlated trend for logtransformed uniformity. Originally, it was suggested that mass selection for an increase in the mean of a trait may result in increased environmental variance because the selected extreme individuals may also have the highest micro-environmental sensitivity, even if there is no genetic correlation between the mean of the trait and its uniformity [4,5]. However, to test this hypothesis, it is necessary to consider whether the data on the trait is log-transformed or not. In other words, it is important to be explicit whether analysis of uniformity (or micro-environmental sensitivity) concerns the combined effect of scale and true micro-environmental sensitivity, or only the latter. Conclusions We found a high potential for response to selection for uniformity of BW in rainbow trout relative to the mean and that uniformity of BW is a genetically different trait in breeding and production environments. We recommend that, in practice, aquaculture breeding programs use sib testing when the aim is to improve uniformity across environments. A large number of relatives will aid in obtaining a sufficiently high accuracy of selection for uniformity of BW. When using log-transformed harvest BW, we found a negative genetic correlation between BW and its uniformity, which indicates that selecting for increased BW and more uniform fish is possible. The scale effect substantially influences the genetic parameters for uniformity of BW, especially the sign and magnitude of the genetic correlations between BW and its uniformity and uniformity between environments. environmental variance for the additive model can be calculated as: a v þ σ 2 c v ¼ σ 4 e;exp exp 2σ 2 a v ;exp exp 2σ 2 The product of equation (2) is a combination of σ 2 a v and σ 2 c v . Under the assumption that the ratio of σ 2 av σ 2 av þσ 2 cv is equal on both the additive and exponential scales, subsequently σ 2 a v is calculated as: and for common environmental effects: The heritability for environmental variance h 2 v À Á can be calculated as: Similarly, the ratio between common environmental effects c 2 v À Á can be calculated as: For these equations, it is assumed that genetic and common environmental correlations between mean and variance are 0; otherwise the denominator would be slightly higher with the exponential model (not shown). However, the effect of this simplifying assumption is negligible. The equations were verified with Monte Carlo simulation and following the same assumptions as in Mulder et al. [5].

v3-fos

2018-04-03T05:22:52.403Z

2015-04-07T00:00:00.000Z

14392907

s2

Rye Affects Bacterial Translocation, Intestinal Viscosity, Microbiota Composition and Bone Mineralization in Turkey Poults Previously, we have reported that rye significantly increased both viscosity and Clostridium perfringens proliferation when compared with corn in an in vitro digestive model. Two independent trials were conducted to evaluate the effect of rye as a source of energy on bacterial translocation, intestinal viscosity, gut microbiota composition, and bone mineralization, when compared with corn in turkey poults. In each experiment, day-of-hatch, turkey poults were randomly assigned to either a corn or a rye diet (n = 0 /group). At 10 d of age, in both experiments, 12 birds/group were given an oral gavage dose of fluorescein isothiocyanate dextran (FITC-d). After 2.5 h of oral gavage, blood and liver samples were collected to evaluate the passage of FITC-d and bacterial translocation (BT) respectively. Duodenum, ileum and cecum gut sections were collected to evaluate intestinal viscosity and to enumerate gut microbiota. Tibias were collected for observation of bone parameters. Broilers fed with a rye diet showed increased (p<0.05) intestinal viscosity, BT, and serum FITC-d. Bacterial enumeration revealed that turkey poults fed with rye had increased the number of total lactic acid bacteria (LAB) in all three sections of the gastrointestinal tract evaluated when compared to turkey poults fed with corn. Turkey poults fed with rye also had significantly higher coliforms in duodenum and ileum but not in the ceca, whereas the total number of anaerobes increased only in duodenum. A significant reduction in bone strength and bone mineralization was observed in turkey poults fed with rye when compared with corn fed turkey poults. In conclusion, rye evoked mucosal damage in turkey poults that increased intestinal viscosity, increased leakage through the intestinal tract, and altered the microbiota composition and bone mineralization. Studies to evaluate dietary inclusion of selected Direct-Fed Microbial (DFM) candidates that produce exogenous enzymes in rye fed turkey poults are currently being evaluated. Introduction The intestinal epithelium constitutes the largest and most important barrier against external environmental agents and has three critical functions: 1) To prevent the entry of harmful intraluminal microorganisms, antigens, and toxins; 2) To enable the selective translocation of dietary nutrients and electrolytes into circulation; and 3) To tolerate the beneficial microbiome [1][2][3][4]. Inappropriate immunological reactions against food compounds, such as lactose or gluten, can lead to the breakdown of oral tolerance and the development of intestinal immune disorders in humans [5][6][7][8][9][10][11][12][13][14][15][16] and several investigators have described how the composition of the diet, also has a tremendous impact in digestibility and gut health of [17][18][19]. Thousands of years of evolution shaped the digestive system of the jungle fowl and wild pig to deal with the dietary ingredients they encounter in an efficient manner. More recently, throw intensive genetic manipulation, nutrition and health programs we have modified the biology and growth potential of production animals. Today, modem commercial monogastric animals diets contain 2 or 3 ingredients that may constitute >75% of intake. Corn is usually the main source of energy in poultry diets, but at times it is difficult to formulate least cost diets using corn, therefore, unconventional grains have to be used. Specifically, rye-based diets versus traditional corn-based diets, were different cereals are used as principal source of energy. The inclusion of rye in poultry diets has been fraught with problems, principally related to the production of sticky droppings, malabsorption syndrome, elevated feed conversion and intestinal bacterial overgrowth [20][21][22]. The endosperm cell wall of rye and wheat is comprised mainly of highly branched arabinoxylans which increase the viscosity of the digesta [23]. Elevated viscosity reduces digestibility and performance by interfering with the movement of particles and solutes across the intestinal lumen [24] favoring intestinal bacterial overgrowth [22]. The purpose of the present study was to evaluate the use of rye on bacterial translocation (BT), intestinal viscosity, microbiota composition, and bone mineralization when compared with a traditional cereal (corn) in turkey poults. Animal source, diets and experimental design In order to show that the same or similar results can be achieved independently, two independent experiments were conducted in the present study. In each experiment, forty turkey poults were obtained from a commercial hatchery (Cargill Gentry, AR, USA), randomly assigned to 2 groups (n = 20 turkey poults), and placed into isolator chambers in a controlled age-appropriate environment with unrestricted access to feed and water for 10 days. Turkey poults received either a corn or rye diet meeting the nutritional requirements of poultry recommended by National Research Council [25]. Diets were antibiotic-free (Table 1). All animal handling procedures were in compliance with Institutional Animal Care and Use Committee (IACUC) at the University of Arkansas. Specifically, the IACUC approved this study under the protocol #11047-"Evaluation of direct fed microbials and prebiotics in poultry". At ten days of age, in both experiments, 12 turkey poults in both treatment groups were randomly selected, and given an oral gavage dose of fluorescein isothiocyanate dextran (FITC-d; 2.2mg/mL/bird; MW 3,000-5,000 Da; Sigma Aldrich Co., St. Louis, MO). After 2.5 h they were humanly killed using carbon dioxide asphyxiation method. Blood samples were collected from the femoral vein for measuring leakage of FITC-d. Liver was collected to evaluate BT. Duodenal, ileal, and cecum gut sections were collected to enumerate bacteria. For intestinal viscosity, 5 turkey poults from each group ere humanly killed and intestinal digesta were individually collected. Additionally, tibias were collected for bone parameters as describe below. Viscosity Total intestinal digesta contents were collected from Meckel's diverticulum to the ileocecocolonic junction. For viscosity analysis, approximately 1.5 g (wet weight) of the fresh digesta was immediately placed in a microcentrifuge tube and centrifuged at 12,000 x g at 4°C for 5 min. The supernatant fluid was collected and stored on ice until viscosity measurement was determined using a LVDV-I Brookfield digital cone-plate viscometer fitted with a CP-40 spindle (Brookfield Engineering, Middleboro, MA). The analyzed samples and the viscometer cup were maintained at 40°C during viscosity measurement. Viscosity was measured in centipoise (cP = 1/100 dyne s/cm 2 ) and the results were reported as log 10 cP. Bacterial translocation Briefly, the right half of the liver was removed from each turkey poults, collected in sterile bags, homogenized, weighed and 1:4 wt/vol dilutions were made with sterile 0.9% saline. Ten-fold dilutions of each sample, from each group were made in a sterile 96 well Bacti flat bottom plate [11,26,27]. Serum determination of FITC-d Blood was kept at room temperature for 3 h and centrifuged (1,000 x g for 15 min) to separate the serum from the red blood cells. FITC-d levels of undiluted serum were measured at excitation wavelength of 485nm and emission wavelength of 528nm (Synergy HT, Multi-mode microplate reader, BioTek Instruments, Inc., Vermont, USA). Fluorescence measured was then compared to a standard curve with known FITC-d concentrations. Gut leakage for each bird was reported as μg of FITC-d/mL of serum. Enumeration of bacteria Whole duodenum, ileum, and both ceca were aseptically removed, separated into sterile bags, and homogenized. Samples were weighed and 1:4 wt/vol dilutions were made with sterile 0.9% saline. Bone parameters Bone parameters were measured according to the methods as described by Zhang and Coon, [28]. Tibias from each turkey poults were cleaned of attached tissues. Bones from the left leg were subjected to conventional bone assays and tibia from the right leg was used to determine breaking strength. The bones from left tibia were dried at 100°C for 24 h and weighed again. The samples were then incinerated in a muffle furnace (Isotemp muffle furnace, Fisher Scientific, Pittsburgh, PA) at 600°C for 24 h in crucibles. Finally, the content of calcium and phosphorus in the tibia was determined using standard methods [29] and were reported as percentage of dry matter. The right tibial diaphyses from individual birds were cleaned of adherent tissues, the periosteum was removed, and the biomechanical strength of each bone was measured using an Instron 4502 (Norwood, MA) material testing machine with a 100 kg Load Cell. The bones were held in identical positions and the mid-diaphyseal diameter of the bone at the site of impact was measured using a dial caliper. The maximum load at failure was determined using a three-point flexural bend fixture with a total distance of 30 mm between the two lower supporting ends. The load, defined as force in kilograms per square millimeter of crosssectional area (kg/mm 2 ), represents bone strength. The rate of loading was kept constant at 20 mm/min collecting 10 data points per second. The data were automatically calculated using Instron's Series IX Software (Norwood, MA). Statistical analysis All data were subjected to one-way analysis of variance as a completely randomized design using the General Linear Models procedure of SAS [30]. Data are expressed as mean ± standard error. Significant differences among the means were determined by using Duncan's multiple-range test at p<0.05. Results The evaluation of body weight, intestinal viscosity, serum FITC-d, and liver BT in turkey poults fed with a corn diet or a rye diet of Experiment 1 and 2 are summarized in Table 2. A significant (p<0.05) reduction in body weight was observed in turkey poults fed with rye as compared with corn in both experiments. However, turkey poults fed with rye showed an increase in intestinal viscosity which was associated with elevated (p<0.05) serum FITC-d, and an increase in BT of Enterobacteriaceae to the liver ( Table 2). Total bacterial counts in duodenum, ileum, and ceca of neonatal turkey poults fed with a corn or rye diet in Experiment 1 and 2 are summarized in Table 3. In both trials, turkey poults that were fed with rye had a significant increase in the number of total LAB that were observed in duodenum, in ileum, and ceca when compared with turkey poults fed with corn. In these turkey poults, a significant increase in the total number of coliforms was also observed in duodenum and ileum but not in cecum, whereas, an increase in total number of anaerobes was observed only in the duodenum ( Table 3). The results of the evaluation of bone breaking strength and bone parameters in neonatal turkey poults fed with corn or rye in Experiments 1 and 2 are summarized in Table 4. Significant increases in tibia diameter, tibia breaking strength, tibia ash, and calcium and phosphorus percentages were observed in turkey poults that fed corn when compared with turkey poults that fed the rye diet (Table 4). Discussion Feeding cereals high in non-starch polysaccharides (NSPs) leads to increased feed conversion ratios and lower body-weight gain [31][32][33]. In addition, high NSPs diets have also been associated with Necrotic Enteritis (NE), a multi-factorial disease caused by Clostridium perfringens that is probably the most important bacterial disease in terms of economic implications in turkey poults [24,34,35]. Since poultry has little or no intrinsic enzymes capable of hydrolyzing these NSPs, exogenous xylanases as additives are used in an attempt to reduce this anti-nutritive factors [21,23,36]. Several mechanisms of action of NSPs on nutrient absorption have been described that include an increased digesta viscosity, thickening of the mucous layer on the intestinal mucosa, epithelial cell apoptosis, inflammation in response to the dysbacteriosis caused by a higher soluble NSPs content [30,[37][38][39], and the nutritional and economic consequences of mounting an inflammatory response in poultry is inversely related to body-weight gain and overall performance [22,40]. In the present study, turkey poults fed with rye showed an increase in intestinal viscosity, elevated BT of Enterobacteriaceae, and increased serum FITC-d ( Table 2). These changes were also associated with significant bacterial overgrowth when compared with turkey poults fed with corn (Table 3). It is important to mention that the total bacterial counts were evaluated on selective media and using standard microbiological procedures that are known to severely under-represent the true microbiological diversity. Nevertheless, it provides interesting results that justify further exploration using metagenomics analysis. Variations in the composition of the microbiome within different segments of the alimentary tract are influenced by the environment, by the diet, and by the host [41][42][43][44]. Alterations in gut permeability are associated with BT in the portal and/or systemic circulation in several types of leaky gut syndromes leading to systemic bacterial infections [26,45]. Similarly, FITC-d is a large molecule (3-5 kDa) which does not usually leak through the intact gastrointestinal tract barrier. However, when conditions disrupt the tight junctions between epithelial cells, the FITC-d molecule can enter circulation as demonstrated by an increase in trans-mucosal permeability associated with chemically induced disruption of tight junctions by elevated serum levels of FITC-d after oral administration [46]. The significant reduction in bone strength and mineralization (Table 4) confirmed previous studies that have shown that high NSPs diets in poultry or gluten intolerance in humans, are also associated with malabsorption of minerals and fat-soluble vitamins [13,[47][48][49][50][51]. Performance of rye-fed birds can be improved markedly by dietary supplementation with exogenous xylanase [21,52,53]. Previously, we have reported that dietary inclusion of selected Direct-Fed Microbial (DFM) candidates that produce exogenous enzymes (protease, phytase, lipase, xylanase and cellulose) in high NSPs diets significantly reduced both viscosity and Clostridium perfringens proliferation when compared with control diets without the DFM in vitro [27,54,55]. Together, they represent a step towards the application of nutrigenomics in the context of a chicken model. The incorporation of one or more nutrigenomics techniques (in particular, assessment of the microbiome) will provide a better understanding of how dietary food components can affect physiological functions and the fundamental cellular and molecular mechanisms implicated in the digestive process of high NSPs diets in chickens. In conclusion, rye evoked mucosal damage in turkey poults resulting in increased intestinal viscosity, increased leakage through disruption of epithelial tight junctions in the intestinal tract, and altered the microbiota composition and bone mineralization. Studies to evaluate dietary inclusion of selected DFM candidates that produce exogenous enzymes in rye fed turkey poults are currently being evaluated. Author Contributions Conceived and designed the experiments: GT JL VK. Performed the experiments: GT JL VK XH. Analyzed the data: GT. Contributed reagents/materials/analysis tools: BH. Wrote the paper: GT JD VK XH. Gave to the manuscript the format requested, made orthographic and concordance reviews, and made the changes requested by the reviewers: GT JK VK BH XH.

v3-fos

2015-09-18T23:22:04.000Z

2015-07-09T00:00:00.000Z

17555427

s2

Air Quality in Alternative Housing Systems May Have an Impact on Laying Hen Welfare. Part I—Dust The new legislation for laying hens in the European Union put a ban on conventional cages. Production systems must now provide the hens with access to a nest, a perch, and material for dust bathing. These requirements will improve the behavioral aspects of animal welfare. However, when hens are kept with access to litter, it is a concern that polluted air may become an increased threat to health and therefore also a welfare problem. This article reviews the literature regarding the health and welfare effects birds experience when exposed to barn dust. Dust is composed of inorganic and organic compounds, from the birds themselves as well as from feed, litter, and building materials. Dust may be a vector for microorganisms and toxins. In general, studies indicate that housing systems where laying hens have access to litter as aviaries and floor systems consistently have higher concentrations of suspended dust than caged hens with little (furnished cages) or no access to litter (conventional cages). The higher dust levels in aviaries and floor housing are also caused by increased bird activity in the non-cage systems. There are gaps in both the basic and applied knowledge of how birds react to dust and aerosol contaminants, i.e., what levels they find aversive and/or impair health. Nevertheless, high dust levels may compromise the health and welfare of both birds and their caretakers and the poor air quality often found in new poultry housing systems needs to be addressed. It is necessary to develop prophylactic measures and to refine the production systems in order to achieve the full welfare benefits of the cage ban. Introduction The welfare of laying hens is of great concern to the European Commission, citizens, and the egg industry [1,2]. The council directive 1999/74/EC put a ban on conventional cages in EU from 2012. The directive improves laying hen welfare, especially their freedom to express behavioral priorities such as laying eggs in a nest, dust bathing, and perching in enriched cages; and, in addition, wing flapping and mobility in loose housing systems. There is no doubt that such allowances have a positive effect on vital aspects of animal welfare in laying hens. These welfare benefits are well documented in several scientific studies summarized by EFSA [1]. Canada and the United States are also considering a transition away from battery cages [3,4]. However, the approved systems currently available for intensive large-scale egg production may have negative side effects that cause other welfare problems, like increased risk of feather-pecking and cannibalism, especially within non-cage systems [1]. Another important challenge and the theme of two review articles in the current special issue on poultry welfare is the aerial environment. This first article reviews the effects of air quality on the welfare of laying hens with regards to airborne dust. In order to discuss the effects of aerial pollutants on the welfare of poultry, an introduction to the concept of animal welfare is given. The aim is to ease the understanding of why different aspects of welfare are valued differently by different people. Thereafter a brief description of specific features of the avian respiratory system is given to better understand the effects of air pollutants. The effects of ammonia in poultry houses are discussed in Part II: "Air Quality in Alternative Housing Systems May Have an Impact on Laying Hen Welfare. Part II-ammonia" in this journal [5]. Where little research has been published regarding laying hens, we refer to research done on other types of poultry, mainly broilers. The Concept of Animal Welfare The Brambell Committee was one of the first to suggest a definition of animal welfare. This definition later became known as "the five freedoms": freedom (1) from hunger and thirst; (2) from discomfort; (3) from pain, injury, or diseases; (4) to express normal behaviors; and (5) from fear and distress [6,7]. The World Organization for Animal Health (OIE) has adopted the following definition: "Animal welfare means how an animal is coping with the conditions in which it lives. An animal is in a good state of welfare if (as indicated by scientific evidence) it is healthy, comfortable, well nourished, safe, able to express innate behavior, and is not suffering from unpleasant states such as pain, fear, and distress. Good animal welfare requires disease prevention and veterinary treatment, appropriate shelter, management, nutrition, humane handling, and humane slaughter/killing" [8]. According to Dawkins [9], assessment of animal welfare should be directed at answering two questions: Are the animals healthy? Do they get what they want? Depending on how animal welfare is understood, the underlying values of the interpreters, the selection of indicators to study, and how differing and even contradicting evidence is weighed may result in different conclusions regarding animal welfare [10,11]. Regarding laying hens, a main challenge is that increasing environmental complexity to improve the hens' possibility to express motivated behaviors could result in health problems and, consequently, reduce welfare. In this special edition on poultry welfare, we describe the effects of dust (reported here) and ammonia [5] on laying hen welfare, and we have focused on health implications and behavioral studies related to the aerial environment in furnished cages and different loose housing systems. Anatomy of the Avian Respiratory System The structure of the avian respiratory system is unique among vertebrates [12]. Research on the effects of air quality in mammals can therefore not be directly applied to poultry. Birds have small lungs that do not change volume during breathing and nine large air sacs that act as bellows to ventilate the lungs, while not directly participating in gas exchange [12]. The functional anatomy of the avian respiratory system is very effective, allowing for gas exchange in the lungs both during inhalation and exhalation. Birds can breathe through either the nares or the mouth. The trachea has complete cartilaginous rings, in contrast to the incomplete rings of mammals, which are connected with a collapsible membrane. This is considered an important feature of the mammalian cough, an effective mechanism for clearing debris from the upper airway. It is uncertain whether the complete rings of the bird reduce the effectiveness of coughing for clearing the passageways, but birds are observed to cough [13]. Each of the primary bronchi enters the lung, and exits caudally into an abdominal air sac. Each primary bronchus gives rise to four groups of secondary bronchi. Numerous tertiary bronchi (parabronchi) branch off within the lung [14]. Gaseous exchange occurs in tiny air capillaries that form extensive networks interconnecting the parabronchi, and there are no dead-end structures comparable to the alveoli of mammals [13]. The transparent walls of the air sac are composed of a network of elastic fibers with some collagen. The air sacs have systemic arterial supply but are poorly vascularized [13,15]. Categories, Sources, and Composition of Dust Exposure to dust is commonly found to be greater in poultry houses compared to other animal productions [16][17][18][19]. Dust is composed of small particles. The finer particles may easily be suspended in air. The size of dust particles is often defined in terms of inhalable, thoracic, and respirable dust [20,21]. This description is based upon its ability to reach the different parts of mammalian lungs. Using these definitions, a respirable particle has a diameter of less than 4 [21] or 5 µm [20] and may pass all the way down to the alveoli. Thoracic particles (5-10 µm) may pass the larynx and be found in the bronchioles. Inhalability decreases gradually with increasing particle diameter. Inhalable particles are usually considered to be bigger particles with diameters up to 100 µm. Inhalable particles may accumulate in the nostrils and in the nasal cavity. In intensive animal production housing, the respirable fraction typically represents 5% to 10% of the inhalable particles [20]. It is debatable to what extent these definitions are valid for poultry. Early investigations of the anatomy and mechanisms of the avian respiratory system used soot to determine the unidirectional gas flow through the lungs [22,23]. The soot particles were deposited first in the caudal portion of the respiratory system, thus being respirable. In 1982, these findings were confirmed using particles with a diameter of 0.45 µm [24]. Later investigations in poultry have determined that dust particles with a diameter from 3.7 to 7 µm settle in the anterior portions of the respiratory tract and thus are inhalable [25]. Smaller particles (1.1 to 0.091 µm) may be found equally throughout the respiratory tract, including the lungs and the air sacs [25], and can be described as respirable for poultry. Based on this, respirable dust has a smaller diameter in birds compared to mammals. Corbanie et al. [26] performed experiments to determine the effect of age on how far particles of different sizes penetrated the respiratory system in broiler chicks. In 2-and 4-week-old chicks, particles with a size of 5 and 10 µm, respectively, were too large to reach the lungs and air sacs. The difference found here is probably due to the differing size of the airways. However, in day-old chicks particles up to 20 µm were found to reach the lungs and air sacs. A possible explanation for this apparent contradiction is that the young chicks breathe through their mouths initially and therefore do not benefit from the filter effect of the nares. This would also be a relevant situation in hot conditions where birds pant with their mouths open in order to dissipate heat. Dust in the poultry house is of both organic and inorganic origin, with birds and their sheddings being the main source [27]. The inorganic dust originates from building materials such as concrete, metal, mineral or fiberglass insulation, or material such as soil particles brought into the house by the fresh air supply. In a study of a broiler facility, calcium from the feed was found to be the most common inorganic dust component [28]. Magnesium, copper, iron, lead, and zinc were other feed or cage components found in the airborne dust. However, in general, publications considering dust in animal housing have focused on organic dust. Included in the organic dust of poultry houses are feather and skin particles, feed components, dried fecal matter, molds, fungi, bacteria and bacterial endotoxins, and viruses [29]. Koon et al. [30] found that the organic dust from caged layers consisted of two distinct types of particulate matter. The bulk of the matter was flat, flaky, and cellular in structure, with a diameter from 1 to 450 µm, some containing droplets of oil, and was identified as skin debris and feed particles. The other matter was long, cylindrical particles with nodes and internodes, identified as broken feather barbules. Both types of dust contained electrostatic charges, causing them to clump and form aggregates. The dust contained approximately 92% dry matter, of which 60% was crude protein, 9% fat, 4% cellulose, and the rest ash and hydrocarbons. Airborne particulates, referred to as bioaerosols, including bacteria, endotoxins, viruses, and fungi, are also present in poultry houses [31,32], with dust often acting as a mechanical vector. Bacteria include non-pathogenic and dead bacteria. Gram-positive bacteria are more widely represented than Gram-negative in dust. Most authors have measured the total number of cultivable microorganisms and less often quantify and identify the genus and species [33]. The main microorganism genera identified are, for bacteria: Bacillus, Clostridia, Corynebacterium, Enterobacter, Flavobacterium, Pseudomonas, Staphylococcus, and E. coli; and for fungi: Cladosporium, Penicillium, and Aspergillus are the most common, but Alternaria, Fusarium, Geotrichum, and Streptomyces can also be present [20, 34,35]. A number of the constitutive parts of microorganisms are found in dust. These include cell membrane peptidoglycans and other peptides (proteases, heat-shock proteins, etc.) as well as endotoxins from Gram-negative bacteria and mycotoxins from fungi [20, 36,37]. An experimental study by Michel et al. [38] found low levels of mycotoxins such as tricothecene B, deoxynivalenol, and zearalenone in suspended dust. The likely source of the mycotoxins was feed, ingested and excreted in droppings. Dust and Dust Components in Different Housing Systems An overview of the literature regarding specific dust levels and dust components found in various housing systems for laying hens is summarized in Table 1. The papers mostly report respirable dust rates ranging from 0.1 mg/m 3 in conventional cages to a maximum of 1.19 mg/m 3 in aviaries. Floor housing represents intermediate figures (0.37-0.848 mg/m 3 ). Dust levels are apparently similar in furnished and conventional cages. This could be explained by litter not always being provided in furnished cages, as witnessed in field studies [39]. Reported levels of total and inhalable dust vary, even within the same system category, depending on the study. The level of total dust is found to be higher in floor systems compared to cages (e.g., around 12 mg/m 3 in floor systems and 2.4 mg/m 3 maximum in cages). Endotoxins are reported in very variable levels and comparison across studies is difficult due to the use of different units of measure (ng/m 3 or EU/m 3 ). Nevertheless, endotoxin levels, as dust levels, appear to be more important in alternative systems compared to cage systems. The same trend is seen for bacteria, with a specific increase in aviaries. To sum up, dust levels and the bioactive components of dust are generally found to be much higher in loose housing systems compared to cages. Only two studies [40,44] have compared conventional and enriched cages, and they found no significant difference between these two cage systems. However, in one of the two studies [40], no litter was available for the hens in the cage. Factors Affecting Dust Levels The amount of airborne dust in a hen house depends upon the animals' access to litter, its quality, and the birds' activity level. These factors are greatly influenced by the housing system [17,46,47,52,53]. Furthermore, the concentration of suspended dust decreases in direct proportion to the height above the floor [52]. As a result, floor-raised birds are exposed to the highest concentrations of dust in the room, much higher than those experienced by the poultry workers. Houses where broiler chickens are housed with access to litter have higher numbers of both respirable (<5 µm) and larger particles suspended in the air compared to keeping them on a netting floor [30,52]. Studies indicate that housing systems where laying hens have access to litter-especially floor housing systems and aviaries-consistently have higher concentrations of suspended dust and its components compared to cage systems where hens have little or no access to litter [38][39][40][41]43,[45][46][47]53,54]. This is as expected, considering the fact that a large proportion of the dust in loose housing systems originates from the litter. Peaks of dust concentrations are measured during times when the birds are very active, because their activity raises settled dust [55]. In aviary systems dust levels have been shown to be significantly higher in the afternoon than in the morning, owing to the hens' dust-bathing behavior [47,56,57], and also after the light is turned on [41]. In general, laying hens are more physically active at higher light intensities [41,58]. Similarly, the feeding system and management may influence bird activity, and therefore affect the concentration of suspended dust. Schierl et al. [59] found that levels of suspended endotoxins had a diurnal variation, with daytime concentration being 14 times that of nighttime. The authors attributed this to animal activity when feeding. Poultry species, breed, and age affects activity. Consequently, suspended dust concentrations are usually low in broiler chicken flocks (relatively inactive birds), and higher in pullet loose-rearing (more active) and in guinea fowl (very nervous and active) [60]. The activity of the stockperson also plays a role in the suspension of dust [38,61]. Another important factor affecting dust levels is the relationship between temperature, humidity, and activity. Both in cages and in loose housing systems, average aerial dust concentrations have been found to be positively correlated with indoor air temperature and negatively to relative humidity [41]. Koon et al. [30] found that the quantity of dust produced by caged layers was low at 10˝C (50˝F), increased to a high level at 16 and 21˝C (60 and 70˝F), and then decreased as the temperature approached 38˝C (100˝F). The authors suggested that this was caused by increased bird activity at the medium temperature. For broilers kept on litter, there was, on the contrary, a distinct decline in dust production for birds kept at 32˝C (90˝F) compared to 16 and 24˝C (60 and 75˝F); the authors attributed this to an increase in absolute humidity (the relative humidity was the same at all temperatures) [30]. Also, according to Grub et al. [62], dust production by layers on litter is a function of e.g., air moisture. The finding that dust levels dropped as air moisture increased appears to support this conclusion with regards to floor systems, but this was not the case in barren cages [30]. An explanation for this discrepancy might be that dust in litter systems contains absorbent particles from wood shavings, which when moist will cause aggregation and settling. Dust levels may also be affected by the use of ventilation to maintain a precise temperature inside the house [38]. The aerial concentration of bacteria decreases in the summer [45], probably because of the increased ventilation rate. Practical experience indicates that the dust-reducing effect of ventilation varies between buildings, and that commonly used air-mixing ventilation systems may not be able to reduce dust levels significantly (Nimmermark, pers. comm.). Gustafsson and von Wachenfelt [63] reported that the type of litter material to some extent affected dust levels in loose housing systems; gravel resulted in higher dust levels compared to chopped straw, peat, and wood shavings. Dust bathing behaviors in furnished cages were more frequently seen in baths with sawdust than with sand [64]; however, no publication was found on the effects of various types of litter and litter management in furnished cages in relation to air quality. Health Dust may have direct and indirect negative health effects and, thus, affect welfare [65]. Airborne microorganisms are frequently attached to dust particles. These microorganisms may be directly pathogenic or release toxins, meaning that dust in a poultry house may serve as a pathogen disseminator in addition to making the animals more susceptible to normally non-or low-pathogenic microorganisms. According to Wolfe et al. [66], dust increased the number of turkey condemnations at slaughter due to infections of the air sacs. Broilers raised on litter were also observed to have a higher incidence of lung damage ascribed to infection than that of broilers raised on netting floors [52]. Microorganisms following non-respirable dust clogging up the birds' head may cause infections in the nares and upper respiratory tract [52]. Many of the organic dust particles are antigenic and can activate both the innate and the adaptive immune systems. This antigenicity may result in an inflammation of the exposed areas. Antigens and allergens that can induce allergic reactions include mites, pollen, fungi, and even components of animal origin in the farm environment [36,67,68]. Human and animal studies have demonstrated that exposure to organic dust can sensitize the lungs and may lead to hypersensitivity reactions [37,69] and respiratory diseases. Dust may impair lung clearance mechanisms and depress immune response to infection [69][70][71][72]. Michel and Huonnic [46] found pulmonary lesions of parabronchitis at the end of laying period to be more extensive and severe in birds in aviaries than in caged hens. This was thought to be a result of the differing dust concentrations, with respective maximum levels of 31.6 mg/m 3 and 2.3 mg/m 3 . Riddell et al. [72], found that when comparing warm (27˝C) and cool (16˝C) poultry houses, more than 50% of the broiler chickens in warm rooms had microscopic lesions in the bronchi of their lungs, whereas fewer than 5% of chickens in cold rooms had such lesions. Large dust particles were visible in some of the lesions. The increased incidence of lung lesions in chickens from warm rooms was interpreted to be due to mouth-breathing rather than being a result of the higher dust levels in the air of these rooms. The mouth-breathing allowed the dust to penetrate deeper into the respiratory system by bypassing the natural filtration of the sinuses. Dust might make the respiratory system more susceptible to even non-pathogenic microorganisms. Oyetunde et al. [73] showed that normally harmless E. coli had pathogenic effects on the respiratory system of four-week-old chicks when combined with sterile dust with a mean concentration of 101 mg/cm 3 to 103.72 mg/cm 3 . Interestingly, despite the fact that Madelin and Wathes [52] found a higher load of dust and microorganisms in litter houses, and also a higher incidence of lung damage and living microorganisms present in the broilers' lungs at necropsy, there was no significant effect on mortality. Actually the birds raised on litter tended to have lower mortality. More air sac lesions and even lower mortality was found for turkeys kept on litter [74]. Behavior No studies have been found describing the effects of dust on poultry behavior. However, it cannot be ruled out that birds, like humans, experience discomfort when dust clogs the upper respiratory passages and causes irritation of the eyes and nose. Production Whereas high production does not necessarily imply good welfare, reduced production may indicate a welfare problem [65]. Only one study has been found dealing with the effect of dust on production parameters. Madelin and Wathes [52] found significantly better food utilization in broiler chickens kept on litter compared to a netting floor, despite a higher load of dust and microorganisms in litter houses. Discussion The alternative housing systems for laying hens undoubtedly provide the animals with resources highly important to their welfare, as reviewed by EFSA [1]. For example, access to litter is of utmost importance for hens to display motivated behaviors such as dust bathing or scratching. At the same time, access to litter is also a classical example of the dilemma arising when solving a welfare concern, e.g., by allowing motivated behaviors, may give rise to other welfare problems, e.g., due to poor air quality. The challenge is to keep the welfare benefits of the alternative systems while avoiding other welfare problems. This paper offers a review of the available literature on potential animal welfare challenges related to dust in the housing systems for laying hens that became compulsory in 2012. There is considerable evidence that providing laying hens with litter material increases the amount of suspended dust in the poultry house. Not surprisingly, a high dust level in the new systems is also a concern for the health of poultry workers [41]. Large litter areas and high activity levels contribute to generally high levels of suspended dust in loose housing systems. There are very few studies that have looked at dust levels in furnished cages, but in general, dust levels seem to be lower in these than in loose housing systems and comparable to those in conventional cages. There are several possible explanations for this: the activity level of the birds is lower in cages than in loose housing systems, it is common (and legal) to restrict birds' access to the dust bathing area to prevent misplaced eggs, and not all farmers renew the dust bathing material regularly, if at all. In addition, studies have revealed that dust bathing behavior in enriched cages is often disrupted [75] and a large proportion (30%) of the birds never enter this compartment [65]. In some litter box designs, the litter is displaced from the compartment during dust bathing, resulting in the litter not being available for the next bird. This may be one explanation for the lower dust levels in furnished cage systems. This has led to the question of whether the furnished cages as they are designed and managed do fulfill the individual bird's dust bathing motivation. This illustrates the need for system refinement. The literature review shows that dust levels are sometimes high, also the inhalable and respirable fractions. This is also the case for pollutants attached to dust particles such as bacteria, endotoxins, fungi, and mycotoxins. Sensitization or depression of the immune function and even lesions in the respiratory system, as a result of exposure to dust, have been demonstrated. The intensity of the experienced discomfort caused by dust is difficult to evaluate. Although the discomfort may not be very severe, the duration of exposure is relevant to animal welfare and should be considered, especially considering the longer life span of laying hens compared to meat poultry. Thus, health problems that have been documented in broiler chickens and turkeys may be an even greater welfare problem for laying hens. The benefits and drawbacks of the system in question should not be considered inherent and unchangeable. Rather, the superior aspects of each system and the cause of the major problems in that system should be assessed and understood. In this respect, it is interesting to note that environmental enrichment (litter versus netting floor) led to reduced mortality and enhanced productivity despite the documented pathological changes in the respiratory system [53]. This illustrates the complexity of the interactions between animals and their environment. The new legislation requiring access to a nest, litter, and perches has a profoundly positive effect on vital aspects of animal welfare in laying hens [1], in particular when emphasizing the behavioral aspects of animal welfare. Nevertheless, there is an immediate need to solve the challenges regarding the aerial environment in order to safeguard the intended welfare benefits of the recent ban on conventional cages. In order to introduce effective preventive measures against dust, there is a need for more knowledge of housing design, technical systems for ventilation and dust removal, litter material that produces little dust, and management routines. The large variation found within systems regarding levels of dust and its components indicate that improvements are within reach. For example, by spraying water with 10% rapeseed oil over the manure storage bins, dust concentration was reduced by 30%-45% [65]. Zheng et al. [76] showed that spraying slightly acidic electrolyzed water in an experimental aviary laying-hen housing chamber significantly reduced airborne culturable bacteria. On the other hand, the treatment did not succeed in reducing airborne particulate matter. Nevertheless, this is a promising technique for alleviating the adverse health impacts of bioaerosols in aviary laying-hen housing systems for both animal and workers. Ogink et al. [59] showed that spraying water in aviary air decreased the level of fine dust but enhanced ammonia emissions and odor. In conclusion, the use of aerosolized water (or solutions) should be investigated and refined as a possible method for the reduction of dust emission in laying hen systems. Conclusions In two articles we have reviewed the available literature on potential welfare challenges related to high levels of dust (reported here) and ammonia (reported in Part II) in the alternative housing systems. There are gaps in knowledge on how laying hens react to dust, gases, and bioaerosols in the short and long term, what levels they find aversive and/or that impair health, as well as any additive or synergistic effects of dust and gases. The findings of Oyetunde et al. [73] show that there may be a substantial synergism in the effects of the various components that reduce the air quality. The uniqueness of the avian respiratory system means that studies conducted on mammals cannot readily be transferred to poultry. To find durable solutions to improve hen welfare in the new housing systems, the aerial environment has to be addressed. There is an urgent need for basic as well as applied research to reduce levels of dust and aerial pollutants in hen housing systems that are designed to increase welfare by allowing motivated behaviors in more complex environments. Thus, multi-criteria approaches that include information regarding hen health and behavior should be employed.

v3-fos

2016-05-18T16:11:46.681Z

2015-12-23T00:00:00.000Z

10587277

s2

Nutritional value of high fiber co-products from the copra, palm kernel, and rice industries in diets fed to pigs High fiber co-products from the copra and palm kernel industries are by-products of the production of coconut oil and palm kernel oil. The co-products include copra meal, copra expellers, palm kernel meal, and palm kernel expellers. All 4 ingredients are very high in fiber and the energy value is relatively low when fed to pigs. The protein concentration is between 14 and 22 % and the protein has a low biological value and a very high Arg:Lys ratio. Digestibility of most amino acids is less than in soybean meal but close to that in corn. However, the digestibility of Lys is sometimes low due to Maillard reactions that are initiated due to overheating during drying. Copra and palm kernel ingredients contain 0.5 to 0.6 % P. Most of the P in palm kernel meal and palm kernel expellers is bound to phytate, but in copra products less than one third of the P is bound to phytate. The digestibility of P is, therefore, greater in copra meal and copra expellers than in palm kernel ingredients. Inclusion of copra meal should be less than 15 % in diets fed to weanling pigs and less than 25 % in diets for growing-finishing pigs. Palm kernel meal may be included by 15 % in diets for weanling pigs and 25 % in diets for growing and finishing pigs. Rice bran contains the pericarp and aleurone layers of brown rice that is removed before polished rice is produced. Rice bran contains approximately 25 % neutral detergent fiber and 25 to 30 % starch. Rice bran has a greater concentration of P than most other plant ingredients, but 75 to 90 % of the P is bound in phytate. Inclusion of microbial phytase in the diets is, therefore, necessary if rice bran is used. Rice bran may contain 15 to 24 % fat, but it may also have been defatted in which case the fat concentration is less than 5 %. Concentrations of digestible energy (DE) and metabolizable energy (ME) are slightly less in full fat rice bran than in corn, but defatted rice bran contains less than 75 % of the DE and ME in corn. The concentration of crude protein is 15 to 18 % in rice bran and the protein has a high biological value and most amino acids are well digested by pigs. Inclusion of rice bran in diets fed to pigs has yielded variable results and based on current research it is recommended that inclusion levels are less than 25 to 30 % in diets for growing-finishing pigs, and less than 20 % in diets for weanling pigs. However, there is a need for additional research to determine the inclusion rates that may be used for both full fat and defatted rice bran. Background With the increased global production of livestock, dairy, and poultry, the demand for feed is also increasing and co-products from the tropical food industries are increasingly used in diets fed to pigs. These co-products include copra meal and copra expellers, palm kernel meal and palm kernel expellers, and rice bran. Global production of palm kernel and copra products is relatively modest compared with the production of soybean meal and canola meal [1] and availability of these ingredients is often geographically dependent. However, in some areas, these ingredients are the most abundant and least expensive sources of energy and amino acids (AA) that are available to the local swine industry [2] and it is, therefore, important that information about the nutritional value of each ingredient is available. It is also recognized that copra-, palm kernel-, and rice co-products have certain specific attributes including AA profile, fatty acid profile, and composition of fiber that are unique to these ingredients and special attention to these attributes is needed. The objective of this review, therefore, is to provide information about the composition and recommended use of copra-and palm kernel products and of defatted and full fat rice bran when fed to pigs. The review is primarily based on literature published in peer-reviewed journals and feed composition tables. Although attempts were made to mainly include data that have been published since 1990, on a few occasions, it was necessary to include older data because of a lack of newer data for some of these ingredients. With the exception of ingredient tables, non-peer-reviewed literature was not used because of the uncertainty of the quality of this information. Copra meal and copra expellers The coconut palm (Cocos nucifera) is widely distributed throughout the tropics with major production in Indonesia, The Philippines, India, and in some African and Central American and South American countries. World production of copra meal and copra expellers is approximately 2,000,000 metric tons [1]. Copra meal is produced by expeller extracting or solvent extracting the oil from dried coconut kernels. Copra meal is sometimes referred to as coconut meal or coconut oil meal. Although its protein content is less than that of conventional ingredients commonly used as protein sources, copra meal represents the largest quantity of locally available feed protein in many tropical areas, such as countries in Central America, some African countries, and some countries in South East Asia. Variations in the nutrient composition of copra meal are mainly a function of the differences in residual oil concentration. The residual oil in copra meal and copra expellers contains 50 to 70 % medium-chain, saturated fatty acids (lauric acid and myristic acid), which can lead to firmer carcass fat when high levels of copra meal are used in the diet [3,4]. Thus, the deposition of lauric acid and myristic acid is three to five times greater in the backfat of pigs fed 30 % copra meal compared with pigs fed 10 % copra meal [3]. Quality problems such as rancidity and aflatoxin contamination may be an issue in copra meal, which may cause reduced feed intake and in some cases reduced feed efficiency of pigs [5]. Quality problems may be attributed to the high moisture content of copra during drying and storage [6]. Copra meal and copra expellers contain between 10 and 16 % crude fiber and approximately 47 % total dietary fiber [7]. Concentrations of β-mannans, galactomannans, arabinoxylogalactans, and cellulose are relatively high [8,9] and the water binding capacity of copra meal is much greater than that of palm kernel meal or palm kernel expellers [7]. Water binding capacity is an estimate of the amount of water that a fiber can absorb and hold after an external force has been applied to it via centrifugation. High water binding capacity will usually result in reduced feed intake of animals because of swelling in the intestinal tract. The relatively high concentrations of fermentable fiber in copra-and palm kernel ingredients may result in increased needs for dietary Thr because dietary fiber increases the endogenous losses of AA, and therefore increases the loss of Thr [9]. Protein levels of copra meal and copra expellers typically range from 20 to 26 % ( Table 1). The concentration of gross energy in copra meal is greater than in corn, but because of the high concentration of fiber in copra meal and copra expellers, concentrations of digestible energy (DE) and metabolizable energy (ME) are less than in corn [10,11]. Copra meal and copra expellers contain between 0.50 and 0.58 % total P [10,12,13], but less than one third of the P is bound to phytate. The standardized total tract digestibility (STTD) of P, therefore, is relatively high in copra meal and copra expellers (Table 2; [12,13]). However, if microbial phytase is included in the diets, the STTD of P will increase [13]. The quality of the protein in copra meal is less than that of soybean meal and palm kernel products with Lys only being 1.91 % of total crude protein (CP) and total indispensable AA being 33.92 % of total CP. However, one specific characteristic of copra protein is that it is high in Arg and Arg is almost 10 % of total CP and the Arg:Lys ratio is almost 5:1 ( Table 3). The standardized ileal digestibility (SID) of AA in copra meal and copra expellers fed to pigs ranges between 43 and 81 % [11,[14][15][16]. The SID of Lys in copra meal is also variable, ranging from 51 [15,17] to 73 % [10], but the SID of all other indispensable AA is greater than that of Lys indicating that the sources of copra meal used in these experiments may have been heat damaged because heat damage will reduce the digestibility of Lys more than that of other AA [18][19][20]. The SID of Lys in copra expellers was reported at only 40 % [16], which was much less than for other indispensable AA indicating that this source was also heat damaged. The differences in AA digestibility among experiments may also be due to differences in nutrient composition, drying procedures, oil extraction procedures, and the degree and duration of heat processing that is used during oil extraction [21]. Overall, the SID of protein and indispensable AA in copra expellers is less than in soybean meal, but similar to those in palm kernel meal (Table 4; [11]). Copra meal and copra expellers may be included in diets fed to growing and finishing pigs by up to 30 % without affecting growth performance [22], but negative effects of increasing levels of copra meal in the diet have been reported [4,14,23]. However, Thorne et al. [3] demonstrated that copra meal can be used by up to 50 % in growing-finishing diets if diets are supplemented with synthetic AA or proteins with higher quality. Results with copra meal have been improved if diets either were semi-purified diets or if they were formulated based on digestible AA rather than based on crude protein [3]. In diets fed to weanling pigs from 2 wk post-weaning, performance was linearly reduced if copra meal was included in the diet and pigs fed diets containing 15 % copra meal gained approximately 1 kg less over a 3-wk period than pigs fed a control diet without copra meal [7]. This result was obtained even though diets were balanced for digestible AA and ME. It is possible that it is the high fiber concentration and the high water binding capacity of the fiber in copra meal that resulted in the pigs eating less and therefore gaining less weight because of the increased gut fill that is associated with consuming diets with high water binding capacity. However, References [9,10,15] gain to feed ratio was also reduced over the 3-wk feeding period if copra meal was used. It is, therefore, recommended that less than 15 % copra meal is used in diets fed to weanling pigs. Palm kernel meal and palm kernel expellers Global production of palm kernel meal and palm kernel expellers has increased from approximately 5 million metric tons in 2005 to almost 7 million metric tons in 2012 [1]. The reason for this increase is the increased demand for palm oil, which is often used in the biodiesel industry. Produced mainly in Southeast Asia and Africa, the oil palm fruit (Elaeis guineensis) yields palm oil extracted from the fleshy, outer mesocarp that surrounds the nut and palm kernel oil extracted from the kernel within the inner, hard shelled nut [24]. Prior to oil extraction, the outer shell of the kernel is cracked open, separated, and subjected to steam conditioning. Mechanical extraction by screw pressing is the most common process in oil extraction from palm kernels, which results in production of palm kernel expellers. However, sometimes oil is removed via solvent extraction, and the resultant co-product is called palm kernel meal. The nutrient concentration of palm kernel meal and palm kernel expellers depends on the method of oil extraction, the species of the palm nut, and the amount of shell remaining in the meal [25]. Palm kernel expellers have a residual oil concentration of 6 to 8 %, whereas solvent-extracted meals contain 1 to 2 % residual oil (Table 1; [26,27]). The concentration of crude fiber in palm kernel meal ranges between 7 and 20 % [28], depending on the amount of shells and fruit removed from the palm kernel. More than 81 % of the total carbohydrates in palm kernel meal are in the form of non-starch polysaccharides [29], mainly as β-(1,4)-D-mannans [30,31]. Palm kernel meal also contains high amounts of lignin, which may be a result of contamination of nut shells [32], which contributes to its grittiness and fibrous texture. However, water binding capacity in palm kernel meal and palm kernel expellers is less than in copra meal [7]. Because of the high concentration of insoluble dietary fiber, the energy in palm kernel meal and palm kernel expellers is poorly digested by pigs and concentrations of DE and ME in palm kernel meal and palm kernel expellers is less than 75 % of that in soybean meal and corn (Table 1; [10,11]). However, energy digestibility in diets containing palm kernel expellers may be increased by 2 to 3 percentage units if betamannanase is added to the diet [32] because betamannanase may help digesting some of the D-mannans in palm kernel expellers. The concentration of P in palm kernel meal and palm kernel expellers is between 0.5 and 0.65 % [10,12,13]. However, between 60 and 75 % of total P is bound to phytate and the STTD of P in palm kernel meal and palm kernel expellers is, therefore, between 35 and 50 % (Table 2; [10,12,13]). Because of the relatively high concentration of phytate in palm kernel products, the STTD of P can be increased to between 60 and 75 % if microbial phytase is added to the diets [13]. As a consequence, the supply of digestible P from palm kernel meal and palm kernel expellers is similar to that of soybean meal if microbial phytase is added to the diet [13]. Relative to other oilseed meals, palm kernel meal has the lowest protein concentration ranging from 14 to 21 % [11,26]. Palm kernel protein has a low concentration of Trp and a relatively high concentration of Arg, which is approximately 10 % of the CP (Table 3; [11,33]). However, the Arg:Lys ratio is around 4:1 (Table 3) and as is the case with copra co-products, the supply of Arg is much greater than if other feed ingredients are used. The high concentration of Arg may suppress the digestibility of Lys because Arg and Lys compete for the same transporter in the enterocytes [34,35]. However, making sure that diets are sufficient in digestible Lys may minimize the negative effect of high concentration of Arg. In general, the standardized ileal digestibility of AA in both palm kernel meal and palm kernel expellers is less than in soybean meal, but not different from copra meal (Table 4; [11,36,37]). Palm kernel meal and palm kernel expellers are not always well-accepted by pigs [38,39] and if included by more than 20 % in the diet, palm kernel meal negatively affects growth performance and carcass quality of growing finishing pigs [40,41]. It is, however, possible that if diets are formulated to be equal in standardized ileal digestible indispensable AA, pigs will be able to perform better on diets containing palm kernel meal and palm kernel expellers. Finishing pigs have greater tolerance for palm kernel meal than nursery pigs [28]. In experiments with weanling pigs, it was observed that if diets are formulated to contain similar concentrations of digestible AA and ME, feed conversion rates may be maintained if up to 15 % palm kernel meal or palm kernel expellers are included in the diets [7]. However, average daily gain may be slightly reduced if palm kernel products are used, which may be a result of reduced bulk density of the diet and increased water binding capacity [7]. Full fat rice bran and defatted rice bran The global production of rice (Oryza sativa) exceeds 700 million metric tons per year and rice is the most produced cereal grain in the world after maize and wheat [42]. Rice is produced primarily for human consumption and is the main carbohydrate source in human diets in many countries in the world. The largest rice producing countries are China and India followed by Indonesia, Vietnam, and Thailand [42]. Annual production of rice in the United States is around 9 million metric tons, but the United States is the 5 th largest exporter of rice after Thailand, India, Vietnam, and Pakistan. The main objective of producing rice is to produce polished white rice that is used for human consumption. However, paddy rice contains approximately 20 % hulls that mainly consist of lignin and silica, and therefore, has very low nutritional value [43]. As a consequence, rice has to be de-hulled before consumption. Removal of the hulls results in production of brown rice that contains the bran layers, the germ, and the endosperm. Further processing is needed to remove the bran layers and endosperm and this results in production of rice bran, which may be used for animal feeding. After the bran has been removed, rice goes through several polishing steps before the final product, polished rice, is produced [44]. On a quantitative basis, rice bran is approximately 10 % of the total weight of paddy rice, which means that approximately 70 million metric tons of rice bran is produced annually and is available for animal feeding. There are other co-products produced from rice including brewers rice and rice mill feed, but these products are produced in much smaller quantities. Rice bran includes the pericarp, the aleurone, and the subaleurone layers of rice, but depending on the type of milling, fractions of the endosperm may make up 20 to 25 % of the bran product [45]. Rice bran, therefore, may contain up to 30 % starch [10,46]. The concentration of ether extract in rice bran varies between 14 and 24 % depending on the variety of rice that was grown and the type of milling used [10,46,47]. However, because of the high concentration of lipase in rice bran, the fat may quickly peroxidize and become rancid [45,48]. As a consequence, rice bran needs to be stabilized by use of heat treatment such as extrusion to deactivate the lipase and thus reduce the risk of oxidation [49]. Alternatively, the fat may be removed from rice bran using solvent extraction to produce defatted rice bran with a concentration of fat of 2 to 4 %. Therefore, both full fat rice bran and defatted rice bran are available for animal feeding. Full fat rice bran contains 20 to 30 % neutral detergent fiber and the concentration of CP is approximately 15 % [10,46,47]. Values for DE in full fat rice bran have been reported between 3,000 and 3,100 kcal per kg and values for ME are approximately 100 kcal less than the DE values (Table 5; [10,46]). Concentrations of neutral detergent fiber and CP in defatted rice bran are 10 to 15 % greater than in full fat rice bran because removal of the fat concentrates other nutrients in the bran. However, DE and ME values in defatted rice bran are much less than in full fat rice bran and values between 2,100 and 2,200 kcal per kg have been reported [10,46]. The concentration of P is greater in rice bran than in most other plant ingredients and values between 1.6 and 2.2 % have been reported [10,46,50]. Between 70 and 90% of the P is bound in phytate, and the STTD of P in rice bran, therefore, is relatively low (Table 5; [50,51]). However, addition of 1,000 units/kg of microbial phytase will increase the STTD of P in rice bran by 15 to 50 % [51]. The biological value of rice protein is high and the standardized ileal digestibility of most AA in polished rice is greater than in most other cereal grains except wheat [52]. The protein in rice bran also has a relatively high concentration of Lys, Met, Trp, and Thr (Table 6). However, the SID of AA in both full fat and defatted rice bran is considerably less than in polished rice and for most indispensable AA, values between 70 and 85 % have been reported (Table 6; [10,47]). There are relatively few reports on effects of including rice bran in diets fed to weanling, growing, or finishing pigs. However, inclusion of 10 % rice bran in diets fed to weanling pigs improved feed conversion rate by almost 10 % because of increased colonic concentrations of bifidobacteria [53]. A balanced microbial community with a large presence of the beneficial bacteria is critical for weanling pigs to maintain their intestinal health. The prebiotic effect of rice bran was likely related to arabinoxylan oligosaccharides in this ingredient [54,55]. However, it is not known what the maximum inclusion rate is. For growing and finishing pigs, reduced growth performance has been reported for inclusion of 30 % full fat rice bran [56]. Inclusion of 10 % full fat rice bran in diets fed to growing pigs had no influence on the growth performance compared with pigs fed a corn-soybean meal control diet [50]. In finishing diets, inclusion of 20 % full fat rice bran improved performance compared with pigs fed defatted rice bran [57], and it has been suggested that the maximum inclusion rate of defatted rice bran in diets fed to growing-finishing pigs is 20 % [58]. It is, however, possible, that the reduced performance of pigs fed the defatted rice bran simply is an effect of the reduced metabolizable energy in the defatted rice bran. If that is the case then it is expected that the reduction in growth performance observed for pigs fed defatted rice bran can be avoided if diets are formulated to be isocaloric. However, to our knowledge, research to test this hypothesis has not been reported.

v3-fos

2018-11-20T00:35:52.212Z

2015-07-20T00:00:00.000Z

21558177

s2

Control of Listeria monocytogenes on Alternatively Cured Ready-to-Eat Ham Using Natural Antimicrobial Ingredients in Combination with Post- Lethality Interventions Ready-to-Eat (RTE) meat and poultry products manufactured with natural or organic methods may be at greater risk for Listeria monocytogenes growth, if contaminated, than their conventional counterparts due to the required absence of preservatives and antimicrobials. Thus, the objective of this study was to investigate the use of commercially available natural antimicrobials in combination with post-lethality interventions for the control of L. monocytogenes growth and recovery on alternatively-cured RTE ham. Antimicrobials evaluated were cranberry powder (90 MX), vinegar (DV), and vinegar and lemon juice concentrate (LV1 X). Post-lethality interventions studied included high hydrostatic pressure at 400 MPa (HHP), lauricarginate (LAE), octanoic acid (OA), and post-packaging thermal treatment (PPTT). Viable L. monocytogenes on modified Oxford (MOX) and thin agar layer (TAL) media were monitored through 98 days of product storage at 4 ± 1°C. The post-lethality treatments of HHP, OA, and LAE significantly reduced initial viable L. monocytogenes numbers compared to the control, regardless of the antimicrobial ingredient used in the formulation while PPTT did not. Only when used in combination with DV and LV1 X did HHP, OA, and LAE exhibit sustained suppression, of L. monocytogenes recovery and growth throughout refrigerated storage. As a result, the use of natural antimicrobial ingredients such as DV and LV1 X in combination with post-lethality interventions such as HHP, LAE, and OA represents an effective multi-hurdle approach that could be instituted by manufacturers of organic and natural processed meat and poultry products for L. monocytogenes control. Control of Listeria monocytogenes on Alternatively Cured Ready-to-Eat Ham Using Natural Antimicrobial Ingredients in Combination with PostLethality Interventions Introduction The popularity of natural and organic foods has been increasing for several years, and has led to noticeable market growth of these food categories [1,2]. In 2013, for example, organic foods in the United States experienced a 13% increase in sales compared to the previous year [3]. Similar increases are expected to continue in the future in spite of the price premiums typically associated with these products [4]. Natural and organic meat products, in particular, have accounted for a significant part of that growth. Stringent regulations that govern the production of natural and organic foods have prevented the use of certain traditional ingredients. For instance, in the manufacture of natural and organic processed meat products, such as boneless ham and frankfurters, the direct addition of nitrite or nitrate, curing ingredients used in the manufacture of such products, and that have strong antimicrobial properties, are not permitted. Additionally, lactate and diacetate, antimicrobials commonly found in ready-toeat (RTE) meat and poultry products, and that is effective inhibitors of pathogens such as Listeria monocytogenes, are not permitted in the manufacture of natural or organic meat products. Thus, RTE meat and poultry products manufactured under uncured, natural, or organic methods are sometimes termed "alternatively cured" or "naturally cured". The requirements for these products suggest that they are likely to be at a greater risk than their conventional counterparts for growth of L. monocytogenes if contamination occurs, and previous reports have supported this concern as well [5][6][7]. The use of natural antimicrobials or post-lethality interventions in the manufacture of natural and organic meat products has beenstudied by several researchers and meat processors alike [8][9][10][11]. The United States Department of Agriculture Food Safety Inspection Services (USDA-FSIS) defines a post-lethality treatment as "…a lethality treatment that is applied or is effective after post-lethality exposure. It is applied to the final product or sealed package of product in order to reduce or eliminate the level of pathogens resulting from contamination from post-lethality exposure" [12]. High hydrostatic pressure processing (HHP), for example, is one such post-lethality intervention that takes place after the product has gone through the lethality or cooking step [12,13]. Other examples of post-lethality interventions include sprays or solutions such as lauric arginate (lauramide arginine ethyl ester or LAE) and octanoic acid (sometimes referred to as caprylic acid or OA) as well as post-packaging thermal treatment or pasteurization, all of which can be applied to the finished product. The USDA-FSIS lists lauric arginate as a safe and suitable ingredient for the production of meat and poultry products, and allows up to 44 mg/kg (ppm) (± a 20% tolerance) by weight of the product to be applied to the inside of a package as a processing aid [14]. When used at this level, lauric arginate is considered a processing aid, would not have to be declared on the label of the product, and could be used in the manufacture of uncured, no-nitrate-or-nitrite-added (alternativelycured), RTE natural or organic meat and poultry products. Similarly, the USDA-FSIS also allows for octanoic acid to be used as a processing aid if applied to the surface of an RTE meat and poultry product at a rate not to exceed 400 mg/kg octanoic acid by weight of the final product [14]. Octanoic acid is a saturated (C 8:0 ) fatty acid (pK a 4.89) naturally found in coconut oil and bovine milk [15]. While natural sources of antimicrobials could potentially replace chemical preservatives as a means to address L. monocytogenes [10,16,17], it has also been shown that the anti listerial properties of antimicrobials can vary as a result of the fat content of the food [18] and other variables including protein content, pH, a w , and other ingredients added. Thus, there is significant concern for the potential recovery and growth of sub lethally injured and uninjured L. monocytogenes during the storage life of alternatively-cured RTE ham and frankfurters that do not include the antimicrobial agents normally used in conventional cured meats. Such concerns highlight the need for a combination of antimicrobial hurdles to be investigated and, eventually, implemented in order to fully address L. monocytogenes control in natural and organic RTE meat and poultry products. Previous work in our laboratory [19] demonstrated that postlethality interventions such as HHP, OA, and LAE can deliver an initial lethality for L. monocytogenes, but survivors will grow in processed meats following the treatment. Secondly, we have also observed that natural antimicrobials such as vinegar and vinegar and lemon juice concentrate can impart a bacteriostatic effect on this pathogen, thus suppressing subsequent growth, but without reducing the initial population. Consequently, the objective of this study was to assess the commercially available natural antimicrobial ingredients that are currently allowed for natural and organic meat and poultry products when used in combination with post-lethality interventions to both reduce the initial contaminating population, and subsequently inhibit the recovery and growth of any L. monocytogenes survivors. We hypothesized that a combination of treatments that achieves both initial lethality and sustained suppression of growth of survivors would effectively improve the overall control of L. monocytogenes on alternatively-cured processed meat products. Manufacture of hams Thirteen ham formulations (twelve experimental and one control formulation) were manufactured at the Iowa State University Meat Laboratory using inside (gracilis and semimembranosus) ham muscles. The formulations consisted of 18.14 kg of ham insides, 3.66 kg water, 0.50 kg salt, 0.30 kg sugar and 74.84 g celery powder plus the selected antimicrobials. The ham muscles were obtained from a local processor and frozen prior to use to ensure uniformity of raw materials. The ham muscles were tempered to -2°C, then coarse ground through a grinder plate with 9.53-mm-diameter holes (Biro MFG Co., Marblehead, OH). Nonmeat ingredients (water, salt, sugar) were added and mixed with ground ham muscles at 26 rpm for 2 min using a double action, paddleand-ribbon mixer (Leland Southwest, Fort Worth, TX). Pre-converted (nitrate converted to nitrite) celery powder (Veg Stable 504, Florida Food Products, Inc., Eustis, FL) containing 1.5% (wt/wt) nitrite was used as the natural, alternative source of nitrite. All products were formulated to contain 50 mg/kg (ppm) ingoing natural nitrite to represent the reduced ingoing nitrite concentration that is typical of many natural and organic processed meat products. Control hams were formulated without antimicrobials or post-lethality interventions to best represent the natural and organic hams currently produced. Three commercially available natural antimicrobial ingredients were evaluated in this study; cranberry powder (90 MX; Ocean Spray International, Middleboro, MA), buffered vinegar (DV; WTI Ingredients, Inc., Jefferson, GA), and buffered vinegar and lemon juice concentrate (LV1 X; WTI Ingredients, Inc.) (wt/wt). Each ingredient was added at a concentration (1.0%, 1.0%, 2.5%, respectively) recommended by the respective supplier. The pH of 10% solutions (w/v) of the 90 MX, DV, and LV1 X ingredients were 3.89, 5.87 and 5.57 respectively. The hams and appropriate ingredients were mixed, then reground using a grinder plate with 6.35 mm diameter holes and stuffed into a 50 mm diameter impermeable plastic casing (Nalobar APM 45, Kalle USA, Gurnee, IL) using a rotary vane vacuum stuffer (RS 1040 C, Risco USA Corp., South Eaton, MA). All samples were then placed in a single-truck smokehouse (Maurer, AG, Reichenau, Germany) and heated to an internal temperature of 71.1°C. The hams were then placed in a 0°C cooler overnight to stabilize. The next day (day 0 of the experiment), the hams were sliced into approximately 12.0 mm thick slices using a hand slicer (SE 12 D, Bizerba, Piscataway, NJ), placed into barrier bags (B2470, Cryovac Sealed Air Corporation, Duncan, SC; oxygen transmission rate of 3-6 cc/m 2 , 24 h at 4°C, 0% RH; water vapor transmission rate of 0.5-0.6 g/0.6 m 2 at 38°C (100% RH, 24 h), and vacuum-sealed (UV 2100, Multivac, Inc., Kansas City, MO). Hams for physicochemical analyses were placed in boxes, transferred to a holding cooler in the Iowa State University Meat Laboratory and stored at 4 ± 1°C until analyses were conducted. Hams for microbial analyses were placed in boxes with vacuum packaged ice, transferred to the Iowa State University Microbial Food Safety Laboratory in the Food Science and Human Nutrition Department for subsequent inoculation, and stored at 4 ± 1°C for the duration of the experiment. Two complete independent replications of the entire experiment were performed. Product analyses Proximate analysis was conducted for moisture, fat, and protein of homogenized control and treatment formulations on day 0 using AOAC methods 950.46, 960.63, and 992.15, respectively [20][21][22]. Samples were prepared in duplicate for each ham formulation. Product pH was measured by placing a pH probe (FC20, Hanna Instruments, Woonsocket, RI) into homogenized (KFP715 food processor, Kitchenaid, St. Joseph, MI) samples from the control and treatments that were prepared by first blending the ground ham with distilled, de-ionized water in a 1:9 ratio, and then measuring the pH with a pH/ion meter (Accumet 925 pH/ion meter, Fisher Scientific, Waltham, MA). Calibration was conducted using phosphate buffers of pH 4.0, 7.0, and 10.0. Duplicate readings were taken for each product formulation on day 0. Available moisture was determined using a water activity meter (AquaLab 4 TE, Decagon Devices Inc., Pullman, WA). Samples were cut into small pieces, placed in disposable sample cups, covered, and allowed to equilibrate to room temperature (5-10 min). Measurements were obtained on day 0 and were performed in duplicate for the control and all treatments. Calibration was performed using 1.00 and 0.76 sodium chloride water activity standards. Residual nitrite concentration was determined utilizing AOAC method 973.31 [23]. Samples from each treatment were frozen at -20 ± 1°C on day 0 and evaluated in duplicate at a later date. L. monocytogenes strains Scott A NADC 2045 serotype 4b, H7969 Protect-M contains approximately 10.0% lauricarginate (v/v). A 2.5% Protect-M solution (v/v) was prepared by mixing Protect-M with sterile de-ionized water at 4 ± 1°C. Based on the ham slice surface area measurements, the LAE solution was aseptically dispensed into the bag containing the ham slice (7.19 × 10 -3 ml per cm 2 ) and vacuum-sealed. PPTT was conducted by immersing packages of ham in water at 71.0 ± 1.0°C water for 30 s using a water bath (Isotemp-228, Fisher Scientific). Seven packages were immersed as a group so that water temperature would not change by more than 1.0°C. Water temperature was monitored throughout the process. Packages were held in heated water for the prescribed length of time and then placed on ice immediately to chill before placement in refrigerated storage. Microbial analysis Microbial analysis of ham samples for viable L. monocytogenes was conducted on days 1, 14, 28, 42, 56, 70, 84, and 98 of storage. On the appropriate day, two packages for each treatment were removed from the holding cooler, opened aseptically, and their contents placed inside a sterile Whirl-Pak stomacher bag (Nasco, Ft. Atkinson, WI). Fifty (50.0) ml of sterile BPW was added to each bag, and the bags shaken by hand for approximately 30 s. The rinse solution from each ham sample was then serially diluted (10-fold) in BPW to obtain pre-determined dilutions of the samples according to the sampling day. One ml (for undiluted rinsate, divided into three ~0.33-ml aliquots plated on three separate plates) or 0.1 ml of the appropriate dilution was surfaced plated on modified listeria selective agar (Oxford, MOX)(Difco, Becton Dickinson). The dry ingredients used to manufacture the MOX were 42.5 g of Columbia agar base (Difco, Becton Dickinson), 15.0 g of lithium chloride (Difco, Becton Dickinson), 1.0 g of esculin hydrate (Sigma-Aldrich, St. Louis, MO), and 0.5 g of ferric ammonium citrate (Difco, Becton Dickinson) per liter of de-ionized water. Additionally, an aliquot of 1.0 ml (for undiluted rinsate, divided into three ~0.33-ml aliquots plated on three separate plates) or 0.1 ml of the appropriate dilution was surface-platedon thin agar layer medium base (TAL) that was made according to Kang and Fung [24]. Within 48 h before use, MOX plates to be made into TAL were aseptically overlaid with 7.0 ml of sterile tryptic soy agar (Difco, Becton Dickinson) held at 55°C to facilitate the even distribution of the molten agar. Each sample was plated in duplicate. All inoculated plates were incubated in an inverted position at 35°C for 48 h, after which time they were removed from the incubator, and colonies typical of L. monocytogenes were enumerated. The populations (CFU per ml) were averaged and then converted to log 10 CFU per g using the average weight of the sliced ham from the two replications of the experiment (n=40). The detection limit of our sampling protocols was ≥0.30 log 10 CFU per g based on a sample weight of 25.0 g. Statistical analysis The overall design of the experiment was a factorial design. The generalized linear mixed models (GLIMMIX) procedure of Statistical Analysis System (version 9.3, SAS Institute Inc., Cary, NC) was used for statistical analysis. L. monocytogenes growth data were analyzed for treatment effects within day. Day and treatment x day interactions were also analyzed. The effects of each post-lethality intervention were analyzed separately for each natural antimicrobial ingredient studied. Likewise, the effects of each natural antimicrobial ingredient were analyzed separately for each post-lethality intervention studied. Where significant effects (P<0.05) were found, pair-wise comparisons between the least squares means were computed for each day using Tukey's honestly significant difference adjustment. serotype 4b, H7962 serotype 4b, H7596 serotype 4b, and H7762 serotype 4b were obtained from the Iowa State University Microbial Food Safety Laboratory in the Food Science and Human Nutrition Department. These strains were selected because each has been isolated from cases of food-borne disease outbreaks. Each strain was cultured separately in tryptic soy broth supplemented with 0.6% yeast extract (TSBYE) (Difco, Becton Dickinson, Sparks, MD) for 24 h at 35°C. A minimum of two consecutive 24 h transfers of each strain to fresh TSBYE (35°C) were performed prior to each experiment. The cells were harvested by centrifugation (10 min at 10,000 × g and 4°C) in a Sorvall Super T21 centrifuge (American Laboratory Trading, Inc., East Lyme, CT). The supernatant was discarded and the pelleted cells were resuspended in 30.0 ml of sterile buffered peptone water (BPW) (Difco, Becton Dickinson). The total concentration of the five-strain mixed culture was approximately 10 9 CFU per ml based on the washed cell suspension. Two serial dilutions (100-fold each) of the cell suspension were prepared in BPW to give a final inoculum concentration of approximately 10 5 CFU per ml. This diluted five-strain mixed culture was used to inoculate the ham samples. While in the Microbial Food Safety Laboratory, each packaged sample was reopened and the surface of the product was aseptically inoculated with 0.2 ml per package, using the diluted five-strain mixed culture of the pathogen. The viable cell concentration at inoculation was approximately 10 3 CFU per g of ham slice. The bags were then vacuumsealed using a model A300/52 vacuum packaging machine (Multivac, Inc.) and stored at 4 ± 1°C for the duration of the experiment. Post-lethality interventions Four post-lethality interventions were evaluated in this study; high hydrostatic pressure (HHP), octanoic acid (OA), lauricarginate (LAE), and post-packaging thermal treatment (PPTT). Ham slices from each formulation were randomly assigned to these post-lethality interventions. All post-lethality interventions were applied to the product within two hours following inoculation on day 0 of the study. The HHP parameters were 400 MPa, 4 min dwell time at 12 ± 2°C initial fluid temperature of the pressurization fluid. The 400 MPa HHP treatment was utilized for this study rather than the more common 600 MPa that is used for commercial products to allow a measurable number of the organisms to survive so that the effects of the antimicrobials in combination with HHP could be assessed. Inoculated samples were transported to the High Pressure Processing Laboratory at the Iowa State University Food Science and Human Nutrition Department and subjected to HHP treatment using a FOOD-LAB 900 Plunger Press system (Standsted Fluid Power Ltd., Standsted, UK). The pressurization fluid was a 50.0% propylene glycol (GWT Koilguard; GWT Global Water Technology, Inc., Indianapolis, IN) and 50.0% water solution (v/v). The average rate of pressurization was 350 MPa per min and depressurization occurred within 7 s. Adiabatic heating of the pressurization fluid was 4.6°C ± 0.8°C/100 MPa. Octanoic acid (Octa-Gone; Eco Lab, Inc., Eagan, MN) was applied according to the manufacturer's recommendations. Octa-Gone contains approximately 3.6% octanoic acid (v/v). A 23.4% Octa-Gone solution (v/v) was prepared by mixing Octa-Gone with sterile deionized water at 4 ± 1°C. Based on average surface area measurements obtained as previously described, the OA solution was aseptically dispensed into the bag containing the ham slice (0.0186 ml per cm 2 ) and vacuum-sealed. Lauricarginate (Protect-M; Purac America, Lincolnshire, IL) was also applied according to the manufacturer's recommendations. Results and Discussion The mean weight of the ham slices was 24.57 ± 0.64 g, while the mean diameter, height, and surface area were 4.72 ± 0.06 cm, 1.31 ± 0.01 cm, and 54.51 ± 1.13 cm 2 , respectively (data not shown; n=40 for all measurements). These ham slice dimensions were used to calculate ham slice surface area for LAE and OA treatment volumes of 0.39 and 1.01 ml per package, respectively. The dosages of each compound were calculated according to the respective manufacturer's recommendations as previously described. These dosages resulted in LAE and OA treatment concentrations of 39.82 and 343.03 mg/kg (ppm), respectively. Physicochemical traits Physicochemical characteristics of the hams can be found in Table 1. All treatments exhibited significantly lower a w values than the control treatment (P<0.05). The DV and LV1 X treatments, in turn, resulted in significantly lower a w values when compared to the 90 MX treatment (P<0.05). Final product pH was also affected by natural antimicrobial compound added. The pH of the control treatment was not significantly different from that of the DV treatment (P>0.05), but did significantly differ from both the LV1 X and the 90 MX treatments (P<0.05). These differences in pH most likely resulted from the presence of acidic compounds in the natural antimicrobial compounds utilized. Cranberry has been reported to contain phenolic acids and exhibit a high titratable acidity [25]. Xi et al. [16] obtained similar pH results when using different ingoing levels of cranberry powder in a cooked meat model system and in frankfurters [17]. Similarly, the vinegar and vinegar and lemon juice concentrates used in this study also contain acidic compounds, such as acetic and citric acid, and can be expected to result in the observed lower pH in products made with those ingredients. No significant differences in protein % and moisture % were found between the treatments (P>0.05). Fat %, however, was significantly lower in the 90 MX treatment compared to both the DV and LV1 X treatments (P<0.05). Although some of these differences were statistically significant, the differences were very small and were not expected to affect the results of this study. The residual nitrite concentration found in the 90 MX treatment was lower (P<0.05) than that of the control and DV treatments. No significant differences between all other treatments were detected (P>0.05). Although all ham formulations were manufactured with 50 mg/kg (ppm) natural nitrite on an ingoing basis, the highest residual nitrite concentration observed in all of the treatments on day 0 of the study was 36.01 mg/kg (ppm) (control treatment). This indicates that part of the ingoing nitrite was depleted in curing and other reactions that took place, as expected, during product manufacture. Honikel [26] reported that as much as 65% of the ingoing nitrite can be depleted during product manufacture. Similarly, Xi et al. [17] reported that as much as 75% of the ingoing nitrite can be depleted during the manufacture of frankfurters. Factors such as product pH, cooking temperature, and addition of reducing agents have been long recognized as important factors affecting residual nitrite concentrations in meat systems [27]. Thus, the significant (P<0.05) decrease in pH brought about by the natural antimicrobial ingredients used in this study, especially cranberry powder, was expected to influence residual nitrite concentrations. Viable Listeria monocytogenes populations The growth mediums used, MOX and TAL, did not significantly differ (P>0.05) within treatment on any given day, indicating that, under the conditions of this study, the use of the TAL technique offered no significant advantage compared to using a traditional medium such as MOX. Thus, the discussion about viable L. monocytogenes populations as affected by treatment is limited to the results obtained using MOX. The ham formulations included controls that were manufactured without antimicrobials or post-lethality treatments to provide comparison to the treatment combinations. The 400 MPa HHP treatment used in combination with all of the natural antimicrobial ingredients studied resulted in a significant (P<0.05) reduction in viable L. monocytogenes populations on day 1 when compared to the control treatment (Figure 1). More specifically, the HHP treatment resulted in populations that were 2.25, 1.99, and 1.67 log 10 CFU per g lower (P<0.05) on day 1 when combined with 90 MX, LV1 X, and DV, respectively, and relative to the control treatment. The differences in log 10 CFU per g reductions observed on day 1 in the different treatments subjected to HHP, however, were not significant (P>0.05) compared to each other, indicating that the three antimicrobial ingredients used did not influence the bactericidal properties of the HHP treatment applied. These results confirm the bactericidal properties of HHP at 400 MPa against L. monocytogenes. However, only when combined with DV or LV1 X was the initial reduction in viable L. monocytogenes achieved by 400 MPa HHP sustained throughout the duration of the study. The combination of 400 MPa and 90 MX resulted in an increase in the L. monocytogenes populations after day 70 that reached about 5 log 10 CFU per g by the end of the study. Damage to the cell membrane seems to be the likely mode of action for HHP, and it has been reported that damage to bacterial cell membranes can be extensive, often resulting in cell death [28,29]. Changes in membrane permeability, scarring around the cell wall, separation of the cell wall from the membrane and protein denaturation, as well as damage to transport systems have also been reported in HHP-treated microbial populations [30,31]. Thus, it is likely that the bacteriostatic effect observed in the HHP treatments combined with ingredients such as vinegar or vinegar and lemon juice concentrate was a result of the migration of growth inhibitory compounds present in these ingredients into the bacterial cells. As a result, the use of HHP at 400 MPa in combination with DV or LV1 X represents a promising multiple-hurdle approach for addressing the potential presence of L. monocytogenes in processed meats, andfor inhibiting the potential recovery and growth of those cells that remain viable over the refrigerated storage of the products. Further, it appears that the use of these antimicrobials may permit reduced HHP pressure of 400 MPa as an alternative to the higher 600 MPa that is currently used in commercial applications where HHP is used alone. Reduction of pressure used in the HHP process would increase product throughput for the process and result in lower maintenance cost, both of which are important in determining total cost of the treatment [32,33]. Combining OA with the natural antimicrobial ingredients evaluated in this study ( Figure 2) yielded similar patterns to those obtained when combining HHP with the same ingredients in terms of viable L. monocytogenes populations observed. Significant (P<0.05) reductions in initial viable L. monocytogenes populations were observed when OA was combined with each of the natural antimicrobial ingredients evaluated after day 1 and compared to the control treatment. On day 1, compared to the control treatment, the L. monocytogenes populations were lower by 2.67, 2.52, and 2.33 log 10 CFU per g when OA was combined with 90 MX, DV, and LV1 X, respectively. Burnett et al. [34] concluded that octanoic acid solutions acidified to pH 2.0 or 4.0, and applied to RTE meat and poultry, resulted in L. monocytogenes log reductions ranging from 0.85 to 2.89 log 10 CFU per sample. The pH of the working solution of OA used in the current study was 3.01. It has been reported that the main mechanism by which medium and short chain fatty acids achieve microbial inactivation is through the diffusion of undisocciated acids across the bacterial cells and the subsequent intracellular acidification [35]. Thus, it is likely that the bactericidal effects of OA on L. monocytogenes follow that mechanism. Sustained inhibition of L. monocytogenes recovery and growth compared to the control was exhibited by treatments that combined OA with DV or LV1 X (P<0.05) but not with 90 MX (P>0.05), which resulted in an increased population by over 6 log 10 CFU per g after 98 days. Previous work in our laboratory [19] showed that OA, when applied alone to naturally-cured frankfurters and RTE ham using similar protocols, exerted an initial bactericidal effect on L. monocytogenes but failed to inhibit the organism's recovery and growth over the refrigerated life of the products. Thus, the use of OA in combination with DV or LV1 X, similar to the effect of HHP, represents a necessary multiple-hurdle approach for L. monocytogenes in alternatively-cured processed meats. The effects of using lauricarginate in combination with natural antimicrobial ingredients on viable L. monocytogenes populations are shown in Figure 3. Again, on day 1 of the study, LAE in combination with DV, 90 MX, and LV1 X resulted in 2.67, 2.37, and 2.16 log 10 CFU per g reductions, respectively, in viable L. monocytogenes populations (P<0.05) compared to the control but which were not different (P>0.05) from each other. Similar to patterns observed when combining HHP and OA with the specified antimicrobial ingredients, sustained inhibition of the recovery and growth of L. monocytogenes was only observed when LAE was combined with the DV or LV1 X ingredients. When LAE was used in combination with the 90 MX ingredients, on the other hand, significant (P<0.05) increases in viable L. monocytogenes populations were observed from day 0 to day 14 of the study, with the increase reaching more than 7 log 10 CFU per g by 56 days and after. These findings are similar to other reports that found lauric arginate will exert a bacteriostatic effect on the pathogen only when used in combination with lactate or diacetate [36,37]. Consequently, the combination of a LAE post-lethality intervention with DV or LV1 X, much like combining HHP and OA post-lethality interventions with those same natural antimicrobial ingredients represents another promising multiple-hurdle approach. For the PPTT treatment, no significant reduction in viable L. monocytogenes populations was observed in any of the products with PPTT (P>0.05) when compared to the control treatment ( Figure 4). The PPTT treatment has been shown to be a potentially effective postlethality treatment [38], but in the current study, a longer heating time or a higher final temperature probably would have been necessary for the products to achieve significant population reduction under the conditions used. Conclusions As evidenced by our results, the use of high hydrostatic pressure at 400 MPa, octanoic acid, or lauric arginate as post-lethality interventions when used in combination with vinegar or vinegar and lemon juice concentrate represent effective multiple-hurdle approaches to control L. monocytogenes if post-processing contamination occurs in alternatively-cured RTE ham. These combination treatments inhibit the potential recovery and growth of those cells that might survive initial lethality treatments and that might remain viable during the refrigerated storage of the products. It should be noted that previous studies have shown that these post-lethality interventions will reduce the initial bacterial population but will not affect subsequent growth of survivors. Further, the antimicrobial ingredients used in this study did not affect initial population numbers but provided for suppression of subsequent growth. Thus, the combination of the appropriate post-lethality treatment with an effective bacteriostatic ingredient is necessary to assure control of L. monocytogenes on natural and organic ready-to-eat processed meat products. While these treatments did not independently achieve and sustain reduction of L. monocytogenes populations during product storage, the combination of these hurdles provides a means for manufacturers of natural and organic processed meat and poultry products to achieve control of L. monocytogenes.

v3-fos

2016-05-12T22:15:10.714Z

2015-06-25T00:00:00.000Z

8780637

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Post-Heading Heat Stress in Rice of South China during 1981-2010 Frequent extreme heat events are the serious threat to rice production, but the historical trend of heat stress associated with phenology shift and its impact on rice yield over a long period are poorly known. Based on the analysis of observed climate and phenology data from 228 stations in South China during 1981-2010, the spatio-temporal variation of post-heading heat stress was investigated among two single-season rice sub-regions in the northern Middle and Lower Reaches of Yangtze River (S-NMLYtz) and Southwest Plateau (S-SWP), and two double-season early rice sub-regions in the southern Middle and Lower Reaches of Yangtze River (DE-SMLYtz) and Southern China (DE-SC). Post-heading heat stress was more severe in DE-SMLYtz, west S-NMLYtz and east S-SWP than elsewhere, because of rice exposure to the hot season during post-heading stage. The spatial variation of post-heading heat stress was greater in single-season rice region than in double-season early rice region due to the greater spatial variation of heading and maturity dates. Post-heading heat stress increased from 1981 to 2010 in most areas, with significant increases in the east of double-season early rice region and west S-SWP. Phenology shift during 1981-2010 mitigated the increasing trends of heat stress in most areas, but not in west S-SWP. Post-heading heat stress played a dominated role in the reduction of rice yield in South China. Grain yield was more sensitive to post-heading heat stress in double-season early rice region than that in single-season rice region. Rice yield decreased by 1.5%, 6.2%, 9.7% and 4.6% in S-NMLYtz, S-SWP, DE-SMLYtz and DE-SC, respectively, because of post-heading heat stress during 1981-2010, although there were some uncertainties. Given the current level and potential increase of post-heading heat stress in South China, the specific adaptation or mitigation strategies are necessary for different sub-regions to stabilize rice production under heat stress. Introduction With the intensification of climate change, short episodes of extreme high temperature events become more and more frequent around the world [1][2][3]. High temperature above the Sites and data selection The study areas included 14 major rice production provinces or municipalities in South China as proposed by the Ministry of Agriculture in China in 2009 (http://www.agri.gov.cn). We excluded the regions where rice planting was impossible (northwestern Sichuan with accumulated temperature !10°C less than 2000°CÁd) or where no heat stress occurred (most areas of Yunnan where the historical maximum temperature as 33.5°C) (Fig 1A). Rice cultivation in this area accounts for about 81% of planting area and provides 84% of rice production in China. The sown area of rice in recent 5 years (2008-2012) is 1,727,000 hectares (ha) on average in the whole study region, ranging from 107,000 ha in Shanghai (SH) to 4034,000 ha in Hunan (HN) (National Bureau of Statistics of China). According to the ecological regionalization of rice in China, four rice planting sub-regions were classified across the whole study region, including two single-season rice planting regions, the northern Middle and Lower Reaches of Yangtze River sub-region (S-NMLYtz) and the Southwest Plateau sub-region (S-SWP), and two double-season early rice planting regions, the southern Middle and Lower Reaches of Yangtze River sub-region (DE-SMLYtz) and the Southern China sub-region (DE-SC) ( Fig 1B). In the double-season rice planting regions, only heat stress during the early rice season was analyzed in this study, because normally no heat stress after heading was observed during the late rice season [30]. 228 weather stations including 105 single-season rice planting sites and 123 double-season early rice planting sites were selected to calculate heat stress indices (Fig 1B). Historical daily maximum temperature data at each weather station in the study region from 1981 to 2010 were obtained from the Chinese Meteorological Administration (CMA). Rice phenological dates at 192 weather stations in South China from 1981 to 2010 were obtained from the Agrometeorological experimental stations (AES) operated by CMA and the provincial-level meteorological administrations. Phenological dates for the other 36 stations without an AES were replaced with the phenological dates of the best-fitted nearby AES [31]. during 1981-2010. Large differences of heading and maturity dates were observed at different stations. The maximum differences due to spatial variation in heading dates were 56 days and 35 days, and in maturity dates were 78 days and 34 days, for single-season rice and double-season early rice planting regions, respectively. The annual trends of heading and maturity dates during 1981-2010 at each station were showed in Fig 3. Negative trends were observed at 49.1% and 52.8% stations for heading and maturity dates, with 5.7% and 17.1% stations of significant (p < 0.05), respectively. Positive trends, almost as frequent as negative trends, were significant at 7.9% and 11.0% stations for heading and maturity dates, respectively. Overall, there were no consistent annual trends at all stations, and phenological dates were spatially and temporally varied among different stations. Therefore, the observed heading and maturity dates in each year from 1981 to 2010 were used at each station. The observed datasets from AES also included the information of rice grain yield, cultivar characteristics and management practices at each station. Grain yield data from 1981 to 2010 were used for evaluating the effects of post-heading heat stress on rice grain yield. Local rice cultivars were planted and generally switched every 3-5 years. Crop management practices at each AES were generally same as or a little better than the local traditional practices. Data analysis Description of heat stress indices. The threshold temperature of heat stress (T h ) was differed among different cultivars, plant organs and developmental phases, and 35°C was used as T h for the estimation of heat stress on rice grain yield in South China (S1 Fig). In our study, three heat stress indices were calculated with the historical daily maximum temperature (T max ) dataset and the observed phenology dataset in each year at each weather station from 1981 to 2010. The calculation of heat stress indices was summarized in Table 1, in which the accumulated days of heat stress (ADHS) measured heat stress duration, and the heat stress intensity (HSI) measured the magnitude of heat stress. Moreover, an index named heat degree days (HDD) [31][32][33] was used to evaluate the comprehensive effects of duration and intensity of heat stress. It was calculated as follows: : where h and m are heading and maturity dates, respectively; T maxi is the daily maximum temperature on day i; T h indicates the threshold temperature of heat stress; HD i indicates the heat degree days on day i, and HDD indicates the accumulated HD i from heading to maturity. Spatio-temporal variation of heat stress indices. All the heat stress indices were calculated annually at each station with actual heading and maturity dates obtained from AESs. The average value of each index at each station during 1981-2010 was determined to show the spatial variation of post-heading heat stress in the study region. The display of spatial characteristics for heat stress was analyzed in the software of ArcGIS 9.3 (Esri, Inc.), with the interpolation method of inverse distance weighting (IDW). In order to detect the general temporal change from 1981 to 2010, annual trends of heat stress indices (Tr) at each station were calculated by fitting the time series of each index over 1981-2010 with linear regression. Effects of phenology shift on trends of heat stress. Since heat stress indices were calculated with daily maximum temperature and the actual phenological dates at each station in each year, annual trends of heat stress indices (Tr) were therefore affected both by the change of maximum temperature, and by phenology shift during 1981-2010. In order to obtain a general response of heat stress to phenology shift, trends of heat stress indices only affected by the change of maximum temperature (Tr mxt ) should be quantified and excluded. For this purpose, heat stress indices in each year were recalculated with the fixed phenological dates (i.e. the average heading and maturity dates from 1981 to 2010 as showed in Fig 2) at each station, and their trends were then fitted with linear regression. Thus, the difference between Tr and Tr mxt generally represented the effects of phenology shift on annual trend of heat stress (Tr phe ) from 1981 to 2010. Tr, Tr mxt and Tr phe were analyzed at each station of the sub-region. Tr and Tr mxt of all the stations in each sub-region were compared by a paired t-test (p<0.05 and p<0.01) to determine whether their differences (i.e. Tr phe ) were significant. Effects of heat stress on rice grain yield. The year-to-year variation of climatic and grain yield data were both derived from the first-difference method which was commonly used to estimate the effects of climate change on crop grain yield [31,34]. In order to exclude the variation of management and other non-climatic factors on rice grain yield variation, the first-difference yield was normalized with the average yield of previous three years (Eq 3) as proposed by Iizumi et al. [35]: where ΔY i is the normalized first-difference yield (ranges 0-1) in year i; Y i and Y i-1 are the observed yield in year i and year i-1; Y iÀ3:iÀ1 indicates the average yield from year i-3 to year i-1, and the same Y iÀ3:iÀ1 was used in the first four years. The index of growing degree days (GDD) was commonly used to estimate crop yield response to temperature variation in previous studies [36,37], and it reflected the effective accumulated temperature during the crop growth season. However, the importance of heat stress effects was emphasized as well in recent years [10,38,39], because of the obvious increasing hot days during crop growth. Therefore, the statistical model for grain yield variation in response to temperature variation was preliminarily proposed as Eq (4): where GDD (°CÁd) is calculated by the accumulation of daily average temperature above 10°C (the base temperature for rice growth) between heading and maturity [40]. ΔGDD i and ΔHDD i are the year-to-year variation of GDD and HDD (without normalization). β parameters are regression coefficients, and ε indicates the random error. β 1 and β 2 represent the sensitivities of grain yield to the variation of GDD and HDD, respectively, which are expressed as the percentage of grain yield changes since ΔY i is the normalized year-to-year grain yield. For the further determination of main temperature variables affecting yield variation, a partial correlation analysis was used to investigate the relationship between ΔY i and the year-toyear variation of temperature variables (ΔGDD i and ΔHDD i ) among different sub-regions with all the stations. This method analyzed the correlation between ΔY i and ΔHDD i (or ΔGDD i ) with the common variance between ΔHDD and ΔGDD removed. Temperature variables with the correlation coefficients of statistical significance (p<0.05) were considered as the main factors affecting yield variation in each sub-region. Corresponding temperature variables were eventually included in the statistical model to estimated yield variation. The sensitivities of grain yield (β 1 and β 2 ) to temperature variables were investigated at each station of four sub-regions. Because of the limited observed samples for rice yield from 1981 to 2010 at each station, a bootstrap resampling method was used to estimate the uncertainty of samples [28,37]. A total of 1000 bootstrap resamples was performed and the median value was used as the final regression coefficients of statistical model at each station. The sensitivities of grain yield at sub-region scale were estimated with the average values of all stations in each sub-region. The total contribution of post-heading heat stress to yield variation (as a percentage) in rice from 1981 to 2010 at each sub-region was obtained by multiplying the sensitivity of grain yield to HDD (i.e. β 2 in Eq (4)) with the variation of HDD during 1981-2010 at sub-region scale [28,37]. The later was estimated by the linear trend of HDD from 1981 to 2010 (i.e. Tr). Statistical processing was performed with SPSS 18.0 (SPSS Inc.) and R program (R Core Team, 2014). Significance was tested with two-tailed t-test at p<0.05 and p<0.01. Spatial variation of post-heading heat stress in South China Distinct spatial variation of post-heading heat stress was showed in the study region from 1981 to 2010, based on the observed phenological date of each year at each station (Fig 4). The spatial variation for the average values during 1981-2010 of each heat stress index indicated that the post-heading heat stress was more serious in the central areas of the study region, including east S-SWP and west S-NMLYtz in single-season rice region and DE-SMLYtz in double-season rice region, than in the other areas. Moreover, larger spatial variation of heat stress was observed in the single-season rice region (S-SWP and S-NMLYtz), with obvious east-west spatial difference, than that in the double-season early rice region. The average value of ADHS after heading during 1981-2010 in east SWP, west S-NMLYtz and DE-SMLYtz could be up to 10.4 days (d), 4.2 d more than that in the other parts of the study region. The average HSI after heading in the central areas of the study region was 36.4°C, 0.9°C higher than that in the other areas. The average HDD after heading in east S-SWP and DE-SMLYtz was about 14.5°CÁd, three times higher than that in S-NMLYtz and DE-SC, and nearly six times the value in west S-SWP. The areas with the most serious heat stress in the single-season rice region and double-season early rice region were Chongqing (CQ) municipality in S-SWP and Zhejiang (ZJ) province in DE-SMLYtz, where the ADHS after heading were up to 11.2 d and 10.6 d, the HSI after heading were up to 36.5°C and 36.3°C, and the HDD after heading were up to 28.6°CÁd and 24.3°CÁd on average during 1981-2010 (Fig 4). Temporal trends of post-heading heat stress from 1981 to 2010 From 1981 to 2010, post-heading heat stress in rice increased in the study region except for some areas in the northeast (Fig 5). The post-heading heat stress decreased in east S-NMLYtz from 1981 to 2010, including Jiangsu (JS) province and most northern areas of Anhui (AH) province, and the average reduction for ADHS in east S-NMLYtz was about 0.06 dÁy -1 , and for HDD was 0.10°CÁdÁy -1 . Nevertheless, there was an obvious increase for post-heading heat stress in the east of double-season early rice region and in west S-SWP (most in northwest Sichuan province) of singleseason rice region. This suggested that despite generally being a cooler area (annual average temperature during 1981-2010 was about 10.8°C), west S-SWP had an increasing occurrence for post-heading heat stress. ADHS showed an uptrend of 0.12 dÁy -1 in the east of the doubleseason early rice region, and of 0.05 dÁy -1 in west S-SWP. The increasing trends of HSI in the east of the double-season early rice region and in west S-SWP were 0.042°CÁy -1 and 0.040°CÁy -1 , respectively. Trends for HDD were more than 0.2°CÁdÁy -1 both in west S-SWP and in the east of double-season early rice region. Effects of phenology shift on temporal trends of heat stress indices during 1981-2010 Phenology shift affected the temporal trends of post-heading heat stress obviously in the whole study region from 1981 to 2010, with generally similar trends among ADHS, HSI and HDD (Fig 6). Combined with the findings from Figs 5 and 6, phenology shift from 1981 to 2010 mitigated the increasing trends of post-heading heat stress in most central areas of South China (at 83.2% stations), while accelerated the increasing trends of post-heading heat stress in west S-SWP and Fujian (FJ) province of southeast DE-SMLYtz. In particular, the decreasing trend of post-heading heat stress was observed in east S-NMLYtz (mostly in Jiangsu (JS) province) (Fig 5), and phenology shift during 1981-2010 continually accelerated this decreasing trend (Fig 6). Because HDD was the comprehensive index that evaluated both heat stress duration and intensity, Table 2 analyzed the effects of phenology shift on temporal trends of post-heading heat stress using HDD index at different sub-region scales. Owing to phenology shift, the increasing trends of post-heading heat stress decreased significantly in S-NMLYtz (from 0.042°CÁdÁy -1 to 0.031°CÁdÁy -1 ), DE-SMLYtz (from 0.590°CÁdÁy -1 to 0.323°CÁdÁy -1 ) and DE-SC (from 0.249°CÁdÁy -1 to 0.178°CÁdÁy -1 ), while did not mitigate in S-SWP (p = 0.842). Overall, the effects of phenology shift on the temporal trend of post-heading heat stress were significant in the whole study region, with higher significant level in double-season early rice region. The impact of heat stress on rice grain yield Correlation between rice grain yield and temperature variables. Table 3 was the partial correlation analysis on the relationship of ΔHDD and ΔGDD with ΔY. Significant negative correlations were observed between ΔY and ΔHDD among four sub-regions in South China, suggesting obvious grain yield loss due to the increase of post-heading heat stress from 1981 to 2010. The variation of post-heading GDD only affected yield variation in S-SWP, and the significance level of the correlation between ΔY and ΔGDD (p = 0.029) was less than that between ΔY and ΔHDD (p = 0.000). These results indicated that post-heading heat stress was more important for rice grain yield variation among the four sub-regions during 1981-2010, as compared with effective accumulated temperature. Sensitivity of grain yield to the increasing temperature. Yield variation due to the increasing temperature was estimated both by considering GDD and HDD (type Ⅰ) , and by considering only HDD (type Ⅱ) during the post-heading stage. Table 4 showed that there was no obvious improvement for determination coefficients (R 2 ) of the statistical model of type Ⅰ in S-NMLYtz, DE-SMLYtz and DE-SC, as compared with that of type Ⅱ, suggesting yield variation in these sub-regions was mainly affected by post-heading heat stress. However, yield variation in S-SWP was affected both by heat stress and by effective accumulated temperature during post-heading stage, as indicated by the change of R 2 between the two types of statistical models. These results were consistent with the partial correlation analysis between rice grain yield and temperature variables (Table 3) Contribution of post-heading heat stress to yield variation from 1981 to 2010. The total contribution of post-heading heat stress to rice yield variation at each sub-region from Table 3. Partial correlation analysis on the relationship of ΔHDD and ΔGDD with ΔY in each sub-region of South China. Sub-region Temperature variable Partial correlation coefficient P value Table 4. Regression coefficients and determination coefficients (R 2 ) of statistical model for grain yield in response to temperature variables (per unit). Effect of phenology shift on the trend of heat stress Climate change significantly affected agricultural production in recent years [41,42]. Phenology shift was recognized as the most direct response to climate warming [43,44]. The increasing temperature during the past 2-3 decades are expected to accelerate phenological development in rice [27,45], but cultivar improvement by breeding efforts have partially offset the phenology acceleration at most sites in China [28,40,46]. Temporal trends in phenological dates at all stations of South China confirmed above conclusion, since phenology acceleration was only observed at about half of the stations (Fig 3). However, previous studies seldom estimated the contribution of phenology shift to the trend of heat stress during the past few decades. Taking the spatio-temporal variation of phenological dates into consideration, our study indicated that phenology shift in rice mitigated the increasing trends of heat stress in the central areas of South China (Fig 6), where severe post-heading heat stress commonly occurred from 1981 to 2010 (Figs 4 and 5). This interesting finding suggested that breeding efforts (or (Table 2). This was probably attributed to the less effects of heat stress on rice productions in two single-season rice sub-regions, and thus breeding target was not focused on, especially in west S-SWP (Fig 4). Although phenology shift mitigated the uptrend of heat stress at temporal scale, the spatial variation of phenological dates directly affected the distribution and magnitude of post-heading heat stress among different regions. For example, severe post-heading heat stress was observed in east S-SWP and west S-NMLYtz, because the period from heading to maturity was about from early August to early September in east S-SWP, and from mid-July to mid-August in west S-NMLYtz, respectively, when were the hotter part of the year (Fig 2). The long exposure of high temperature during post-heading reproductive phase could cause severe heat stress in rice. Therefore, considering the spatio-temporal variation of phenological dates is important for the analysis of the magnitude of heat stress, otherwise different conclusions might be drawn. Spatial and temporal variation in post-heading heat stress South China spans about 24°longitude and 15°latitude with a warm and humid climate in rice growing season. Rice planted in South China is subject to various types of climate, and thus the spatial variation of heat stress is obvious over the whole rice production region. During 1981-2010, post-heading heat stress was more serious in the central areas of South China where double-season early rice widely planted. The spatial variations of post-heading heat stress generally reflected the differences of each sub-region in response to climate warming. Phenology variation is one of the main factors affecting the spatial differences of heat stress among sub-regions. The severe heat stress in DE-SMLYtz and east S-SWP was mainly due to the exposure of reproductive phase after heading to the hotter part of summer season. Similarly, more spatial variation of post-heading heat stress was observed in single-season rice region because of the greater variation of heading and maturity dates, than that in double-season early rice region (Fig 2). With or without phenology shift, temporal trends of post-heading heat stress in rice both increased in most areas of South China from 1981 to 2010, especially in west S-SWP and in the east of double-season early rice region (Fig 5 and Table 2). These results indicated that postheading heat stress would become more severe if the trends persisted in the future. In particular, more attentions should be paid to the sub-region in SWP, where a high level of heat stress in the east (Fig 4) and an increasing trend of heat stress in the west were observed (Fig 5). Therefore, rice planted in S-SWP in the near future might suffered the potential threaten of post-heading heat stress. Although the trend of post-heading average temperature changed little from 1981 to 2010 for rice in DE-SC (S1 Table), the warmer area in South China, post-heading heat stress still increased significantly (Table 3). This suggested that post-heading heat stress would be a considerable increase with climate warming in the general warm areas of South China in the future. Quantification of the effect of temperature variables on grain yield Climatic warming in the last two or three decades has had great impacts on crop production across the world [34,40,47]. Previous studies paid more attentions to the effects of average temperature of growing season on grain yield [28,42]. However, little was known about the influence of heat stress on crop production. With the increasing variation of temperature under climate warming, the effect of hot days during crop growth was emphasized recently [28,38], and some studies even considered it as the main variable determining grain yield in statistical models [10]. In our study, possible impacts of effective accumulated temperature and heat stress on rice grain yield were preliminarily considered in Eq (4), and model selection was then performed by analyzing the significance of the correlation between yield variable and temperature variables (Tables 3 and 4). Generally, HDD was more appropriate than ADHS and HSI to estimate yield variation together with GDD during post-heading stage of rice in South China, as the R 2 of the regression equations indicated (Table 4, S2 Table and S3 Table). Moreover, no matter which heat stress indices were used, significant correlations between heat stress indices and yield variation were found in our study. These results demonstrated the relative importance of post-heading heat stress for rice grain yield variation in South China during 1981-2010. With a warming climate in South China, temperature during post-heading stage was considered as the main climatic factor affecting rice yield in this study. Other factors such as CO 2 , solar radiation, precipitation might also play vital roles on grain yield in field conditions [31,47]. Empirical equation for yield estimation with multiple variables or considering time-varying effects of equation parameters would achieve high determination coefficients. However, exploring the most appropriate statistical equation for yield estimation was beyond the focus of this study, and our study emphasized the dominated role that heat stress played on rice yield in South China since 1980s. Till now, the accurate quantification of the independent effect of heat stress on grain yield from other variables (e.g. average temperature, maximum temperature, precipitation) is difficult with statistical model because of the complex effects among them. As an alternative, the process-based crop model makes it possible to isolate the effects of different climate factors on grain yield formation [38]. However, the poor predictions and high systematic errors of process-based crop models under heat stress were reported in many studies [20,33,48]. Recently, the process-based sub-model for phenology simulation under heat stress was improved [48], while more validations are still needed with the field experiment dataset under heat stress [49]. Future study will pay more attention to evaluate the impact of heat stress on grain yield with the improved process-based crop models. Uncertainties in the effects of heat stress on rice grain yield An uncertainty for the effects of heat stress on rice grain yield might be from the selection of high temperature threshold. The actual value of high temperature threshold during post-heading reproductive phase is impossible to be determined at different stations for various rice cultivars. In order to select the optimal high temperature threshold in the whole study region, the method of leave-one-out cross validation (LOOCV) was used to find the minimized mean square errors for grain yield predictions among different temperature thresholds (range from 30°C to 38°C with an interval of 0.2°C) (S1 Fig). Results showed that the 35°C was the optimal high temperature threshold in rice in South China for the two types of statistical models. In addition, since there was great uncertainty in yield variation at a single station from 1981 to 2010 (Fig 7), the effects of post-heading heat stress on rice grain yield was eventually estimated at sub-region scale (Fig 8). Generally, our results suggest that the historical increase of post-heading heat stress has resulted in the reduction of rice grain yield in most rice cultivation regions of South China from 1981 to 2010, averagely 3.9% and 7.4% in the single-season rice region and double-season early rice region, respectively (Fig 8). With these percentages, rice production in South China during 1981-2010 reduced 6.73×10 7 t and 8.89×10 7 t in single-season rice region and double-season early rice region because of historical post-heading heat stress, respectively, according to the statistical planting area at provincial level (National Bureau of Statistics of China). Targeted adaptation strategies Recent studies have emphasized that more attentions should be paid to the increasing temperature variation under heat stress [39,50]. Our results showed that there was clear spatio-temporal variation in post-heading heat stress during rice growing season across South China. Consequently, the specific adaptation or mitigation strategies should be suggested for each sub-region. Serious post-heading heat stress during 1981-2010 was observed in west S-NMLYtz and east S-SWP of single-season rice region, where rice growth between heading and maturity was exposed to the highest temperature environment in a year (in mid-July and mid-August) (Fig 2A and 2B). Therefore, besides the improvement of cultivar heat resistance, the adjustment of sowing date in rice would be very important to avoid the occurrence of postheading heat stress. Furthermore, although there was less heat stress in west-SWP (mostly in Sichuan, SC), great increasing trend of heat stress was observed from 1981 to 2010 (Figs 4 and 5). With a large sown area (Fig 1A), SC provides the largest production of single-season rice in China. Nevertheless, there was no superiority for the agricultural practice (e.g. irrigation areas) in SC (S2 Fig), and phenology shift from autonomous breeding did not mitigate the increasing trend of post-heading heat stress in most areas of SC (Fig 6). Therefore, rice yield per unit enhances less in SC since 1980s as indicated by the observations at AES stations (S2 Fig) and previous study [26]. These results suggest that the progress of agricultural practice (e.g. irrigation) changes little in most areas of SC from 1981 to 2010. In contrast, though little heat stress in Jiangsu (JS) (the second producer of single-season rice), the progress of agricultural practice contributes a lot to rice production [51]. Hence, the improvement of management practices to mitigate the effects of heat stress will benefit the stabilization of rice yield in SC in the future. During 1981-2010, double-season early rice region experienced severe post-heading heat stress in most areas, such as the two largest producers, Hunan (HN) and Jiangxi (JX) provinces ( Fig 1A). With crop rotation of early rice and late rice, the light and temperature resources can be efficiently used in double-season rice planting region. Though cultivar changes with the phenology shift partly decreases the uptrend of heat stress (Fig 6 and Table 2), more efforts on breeding are still emphasized. Cultivars with heat-resistance or heat-escape traits are suggested to be widely planted in double-season early rice region, because heat stress might persist in most areas according to current uptrends (Fig 5). Conclusion Large spatial and temporal variations of post-heading heat stress in rice were observed in South China, with differences among four sub-regions. The spatial variation of heat stress was greater in the single-season rice region than the double-season early rice region. China, as compared with the effective accumulated temperature during post-heading growth season. Despite some uncertainties, post-heading heat stress averagely decreased rice production by 3.9% and 7.4% in single-season rice region and double-season early rice region, respectively. Rice production across South China was affected by the post-heading heat stress since 1980s, and the specific adaptation or mitigation strategies are needed for different sub-regions to ensure food security under climate change. Table. Regression coefficients and determination coefficients (R 2 ) of statistical model for grain yield in response to HSI and GDD. (DOCX)

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Evaluation of Herbicide Efficacy, Injury, and Yield in White Lupin ( Lupinus albus L.) White lupin is of increasing interest in the southeastern United States (US) as a winter le‐ gume cover crop or as mid-winter forage for ruminants. White lupins are poor weed competitors during early establishment, making effective weed control necessary; howev‐ er, only three herbicides are currently registered for use in lupin. An experiment was con‐ ducted at two Alabama sites in 2007 and 2008 to evaluate herbicide efficacy provided by ten preemergence (PRE) and nine postemergence (POST) herbicides as well as lupin in‐ jury and yield. Overall, PRE applied herbicides, particularly imazethapyr, linuron, and flumioxazin, caused less crop injury than POST herbicides while providing ≥ 86% control of annual bluegrass, corn spurry, heartwing sorrel, henbit, and lesser swinecress six weeks after application. Grass-active herbicides, fluazifop and sethoxydim, provided greater than 95% of annual bluegrass control without causing unrecoverable lupin dam‐ age. Imazethapyr applied POST controlled shepherd’s purse (96% to 98%), cutleaf eve‐ ning-primrose (81% to 96%), and wild radish (71% to 99%) without lupin injury. POST- directed spray applications of glyphosate and flumioxazin provided good weed control of corn spurry (80% to 98%) and winter vetch (71% to 95%) but caused significant crop injury due to drift. In general, grain yields were only reduced with the use of chlorimur‐ on, diclosulam, glyphosate, and thifensulfuron. This research suggests there are several herbicides not currently registered that could be beneficial for use in US lupin produc‐ tion. Introduction Conventional agriculture depends on synthetic nitrogen (N) fertilizers and herbicides for high crop performance [1]. Alternative N sources are available in the form of leguminous crops such as Lupinus spp. White lupin is of major interest in the southeastern US because new cultivars exhibit differential vernalization requirements similar to wheat (Triticum aestivum L.) and can be utilized as mid-winter forage. White lupin has been utilized in the southeastern US as a livestock feed, for human consumption and as a winter cover crop in conservation agriculture [2,3]. Since its introduction in the 1930s, until the 1950s the US lupin production reached over 1 million ha; however, production declined with the loss of government support, cold-weather damage to seed nurseries, and the increased availability of inorganic fertilizers [3][4][5]. Lupinus spp. are poor weed competitors during early establishment since canopy development is slow, facilitating light penetration and subsequent weed seed germination and yield loss due to competition. Lupin reaches maximum vegetative growth during flowering when it can successfully compete with newly emerging weeds [6]. Effective weed control is necessary to ensure lupin success under competition with weed species for water, nutrients, and light [6,7]. Previous research has been conducted to compare the effectiveness of herbicides on weed control and potential for crop injury in lupin. A successful preemergence (PRE) herbicide treatment resulting in no crop damage is pendimethalin alone, or in combination with metribuzin [8,9]. Pendimethalin use in white lupin provided 100% control of Russian thistle (Salsola tragus L.) and prostrate knotweed (Polygonum aviculare L.) [10]. The use of PRE applied metolachlor and alachlor, primarily in mixes with other herbicides, successfully controlled annual grasses and some broadleaf weed species greater than 90% in spring-type white lupin [11,12]. Additionally, metolachlor, alone or mixed with linuron, did not cause white lupin injury [13]. Knott [8] found that lupin are especially sensitive to postemergent (POST) herbicides. Fluazifop, as a POST application, provided ≥98% control of wheat (Triticum aestivum L.), triticale (x Triticosecale Wittm ex A. Camus), and annual ryegrass (Lolium multiflorum Lam.) without causing injury to the lupin crop [8,14]. POST application of imazethapyr provided good weed control but resulted in 15% to 24% crop injury and yield reduction [13]. Similarly, Penner et al. [12] found that the use of imazethapyr, as either PRE or POST, caused crop damage of 35% to 60%. Hashem et al. [15] showed that interrow weed control in narrow-leaf lupin provided by paraquat plus diquat increased yields compared to glyphosate alone, glyphosate plus metrabuzin, and glyphosate followed by paraquat plus diquat. Currently, only three herbicides are registered for use in lupin: S-metolachlor, carfentrazoneethyl, and glyphosate [16]. Therefore, the objective of this experiment is to investigate the use of chemical weed management practices in white lupin and evaluate their effect on weed control, crop injury, and lupin grain yield. Materials and methods Experimental treatment and design. A two-year experiment was established at two test sites on the E.V. Smith Research and Extension Center of the Alabama Agricultural Experiment Station in October 2007 and 2008, respectively. The experiment was a 2 (year) x 2 (location) x 3 (cultivar) x 4 (block) x 24 (weed control) factorial treatment arrangement. The experiment design was a randomized complete block design (r = 4) nested within each year x location x cultivar combination. The weed control factor had 20 levels: one nontreated control, ten PREapplied herbicides, and nine POST-applied herbicides ( Table 1). The two locations of the experiment were the Field Crops Unit (FCU), near Shorter, AL (32.42 N, 85.88 W) and the Plant Breeding Unit (PBU), Tallassee, AL (32.49 N, 85.89 W). At FCU, the experiment was established on a Compass soil; a coarse-loamy, siliceous, subactive, thermic Plinthic Paleudults with a loamy sand surface structure. At PBU, the experiment was conducted on a Compass Soil: a fine-loamy, mixed, semiactive, thermic Typic Hapludults with a sandy loam surface structure. The three cultivars used in the experiment were AU Homer (a high-alkaloid, indeterminate cover crop type), AU Alpha (a low-alkaloid, indeterminate forage type), and ABL 1082 (a lowalkaloid, determinate grain type experimental cultivar). Statistical analysis. We used generalized linear mixed models procedures as implemented in SAS 4 PROC GLIMMIX to analyze weed control data. This tool is flexible in the analysis of data with nonnormal distribution and unbalanced designs. Violations of normality and homogeneity of variance issues are often encountered when including a nontreated control treatment or percent control data with a large range. Weed control data were modelled using a binary distribution function or arcsine transformed data. Crop injury data were modelled using arcsine transformed data and then analyzed with a normal distribution function. All treatment factors and their interactions were considered fixed effects except the block factor and its interaction with the various treatment factors. Statistical significance was declared at Dunnett's P < 0.1. Results and discussion Weed control. Over the course of the two-year study, 14 weed species were observed. Not all species were present in all environments; therefore, weed control is presented for only those species that appear at both sites in each year of the study. At the first rating after planting, in both years, the following PRE herbicides provided greater than 90% control of all rated weed species when compared to the nontreated included: S-metolachlor 5 /linuron 6 mixture, metri-buzin 7 , diclosulam 8 , flumioxazin 9 , and imazethapyr 10 ( Table 2). Linuron and S-metolachlor alone provided greater than 90% control in most instances except for henbit (Lamium amplexicaule L.), which was controlled by linuron at 86%, as well as lesser swinecress [Coronopus didymus (L.) Sm.] and heartwing sorrel (Rumex hastatulus Baldw.), which were controlled by S-metolachlor at 86% and 88%, respectively ( Table 2). The mixture of S-metolachlor/linuron has been used previously in lupin study, even though linuron is not labeled for use in white lupin production in the southeastern US [17,18]. In this study, at both early weed and late weed ratings, this mixture provided greater than 70% control of all rated weed species. Pendimethalin 11 provided good early season control of all weed species at the 0.5X, 1X, and 2X rate with the exception of lesser swinecress and heartwing sorrel, which were controlled less than 50% by the 0.5X and 1X rates. In 2007, the second weed rating (22 weeks after planting) conducted after POST herbicide applications revealed PRE applied herbicide weed control to be greater than nontreated controls at both FCU and PBU for each rated weed species except for cutleaf evening-primrose (Oenothera laciniata Hill). At PBU, pendimethalin (0.5X rate) provided only 14% weed control and at FCU, cutleaf evening-primrose control was only 23% with the 1X rate of pendimethalin (Table 3). Less than 50% control was achieved for this weed species with the 2X rate of pendimethalin as well as S-metolachlor. The following POST applied herbicides provided greater than 50% control of all rated weed species included: fluazifop 12 , chlorimuron 13 , and imazethapyr. With the exception of black medic (Medicago lupulina L.) and crimson clover (Trifolium incarnatum L.), which were controlled by less than 70% (data not shown), imazethapyr controlled all broadleaf weed species by more than 80%. Ivany and McCully [13] evaluated various herbicides for use in sweet white lupin, they also showed that imazethapyr applied PRE and POST provided good broadleaf weed control (80% to 91%). Sethoxydim 14 provided good control for all weed species except for cutleaf evening-primrose, which was less than 50% at both sites. The grass weed species, annual bluegrass (Poa annua L.), was successfully controlled by the POST-applied grass active herbicides sethoxydim and fluazifop which is in agreement with previous research evaluating grass control in lupin [14,19]. Thifensulfuron 15 did not provide greater weed control than the nontreated for cutleaf evening-primrose at FCU (15%) and provided less than 50% control of this species at PBU (31%) as well as corn spurry (Spergula arvensis L.) at FCU (43%) ( Table 3). Corn spurry control was also less than 50% for fomesafen 16 at both FCU (22%) and PBU (37%) and 2,4-DB at FCU (39%). Glyphosate 17 and flumioxazin, which were both POST-directed spray applications, provided good weed control of all rated weeds at both locations (Table 3). and cutleaf evening-primrose. At PBU, pendimethalin at the 0.5X rate and full rate did not provide better control of shepherd's purse than the nontreated (Table 4). Similar results were seen at both PBU and FCU for all rates of pendimethalin in cutleaf evening-primrose control with 10% to 12% control with the 0.5X rate, 6% to 23% control with the 1X rate, and 8% to 18% control with the 2X rate. Control of corn spurry at both locations was also lacking for several POST herbicides including: fluazifop (6% to 7%), fomesafen (14% to 19%), 2,4-DB (5% to 6%), and sethoxydim (7% to 45%) (Table 4). Fluazifop, 2,4-DB, and sethoxydim also did not increase control of shepherd's purse compared to the nontreated at PBU with 32%, 21%, and 36% control, respectively. The clove/cinnamon oil mixture achieved poor control of shepherd's purse (29%) and cutleaf evening-primrose (14%) at PBU. Crop injury. Two-way interactions (herbicide-cultivar and location-herbicide) were significant; therefore, injury ratings are presented by location and cultivar. Injury ratings presented here as the mean crop injury was taken after the POST herbicide applications. PRE-applied herbicides in 2007 resulted in no significant increases in crop injury in comparison to nontreated, with a few exceptions. Metribuzin caused increased white lupin injury (4.45) at FCU in cultivar AU Alpha; pendimethalin at the 2X rate resulted in increased injury (3.95) at FCU for the same cultivar ( (9.43 to 10.00), regardless of cultivar or location; therefore, they were discontinued in 2008 (Table 5). Thifensulfuron and chlorimuron were initially included in this study since they are registered for use in soybean; however, research has shown variable phytotoxicity among soybean cultivars for both herbicides [21,22]. Research conducted by Knott [8] suggests that sulfonylurea herbicides such as metsulfuron cause variable crop injury in white lupin, ranging from limited to severe when applied at the normal field rate. Flumioxazin, as a POST-directed spray, caused significant crop injury at each location for each cultivar (4.50 to 7.84). Significant injury resulted from the use of fomesafen at FCU regardless of cultivar; however, increased injury was not observed with this herbicide at PBU. Glyphosate also resulted in increased lupin injury at FCU for ABL 1082 (6.30) and AU Alpha (5.89) ( Table 5). Glyphosate is registered for POST-directed application in lupin in the US [16]; however, herbicide drift can easily cause significant crop injury. This was the most likely cause of lupin injury in our study. Injury from POST flumioxazin applications may also be attributed to drift since PRE applications of this herbicide did not result in increased crop injury in most cases; although, in drier soil conditions, increased phytotoxicity of flumioxazin has been observed in other crops. This could pose a risk for increased lupin damage [23]. Fluazifop (0.50 to 3.81), 2,4-DB (0.06 to 0.75), sethoxydim (0.26 to 2.28), and imazethapyr (0.94 to 4.45) did not result in increased lupin injury over the nontreated (Table 5). Crop injury in 2008 resulted in less overall lupin injury than in 2007. PRE applied herbicides did not cause significant injury in comparison to a nontreated at either location for any of the cultivars except for diclosulam (5.26 to 9.00), which caused unacceptable injury, regardless of location or cultivar (Table 6). Diclosulam, which is applied either preplant incorporated (PPI) or PRE, is registered in soybean [Glycine max (L.) Merr.] and peanut (Arachis hypogaea L.) with little injury to either crop [24,25]. Lupin injury from PRE applications of diclosulam was significant for each cultivar included in the experiment. POST-applied herbicides did not increase crop injury over nontreated except for glyphosate (4.49 to 7.76) and fomesafen in AU Alpha at both locations (3.22 to 3.48) and in AU Homer at PBU (4.00) ( Table 6). Crop injury from fomesafen was noted in both years of the study with inconsistent injury for each cultivar. In other crops, such as soybean and dry beans, previous research has reported negligible fomesafen injury regardless of cultivar [26,27]. In this study, however, it is evident that fomesafen can produce significant injury to lupin. Grain yield. Mean grain yields (kg ha-1) were much higher for all three cultivars in 2008 as compared to 2007 ( Table 7). The grain type cultivar ABL 1082 yielded highest of the three cultivars in both years. The interaction of treatment and cultivar was statistically significant. (Table 7). Two POST-applied herbicides, thifensulfuron and chlorimuron, had no measurable yields in 2007. In 2008, glyphosate was the only POST-applied herbicide that caused significant yield losses of 1700 kg ha -1 . (Table 7). In 2007, none of the PRE-and POST-applied herbicides reduced yield. However, the POST herbicides, thifensulfuron and chlorimuron, yielded 218 kg ha -1 and 0 kg ha -1 , respectively. In 2008, diclosulam, with a mean grain yield of 210 kg ha -1 , was the only PRE herbicide that reduced mean grain yield of this cultivar. Similarly, glyphosate, with a mean grain yield 735 kg ha -1 , was the only POST herbicide that caused significant yield reduction in 2008. AU Homer. The nontreated control had a mean grain yield of 555 kg ha -1 in 2007 and 1219 kg ha -1 in 2008 ( Table 7). None of the PRE and POST herbicide treatments significantly reduced or increased yield as compared to the control in 2007. In 2008, none of the PRE or POST herbicide applications, with the exception of PRE diclosulam (548 kg ha -1 ), yielded lower than the nontreated control. Experiments conducted by Payne et al. [4] in the Pacific Northwest showed a maximum white lupin yield of 2128 kg ha -1 , but this yield is not stable. In our study, yield within each cultivar varied greatly between years depending on the treatment. The grain-type cultivar ABL 1082 had the highest mean grain yield, followed by the forage-type cultivar AU Alpha and the covercrop-type cultivar AU Homer. In this experiment, diclosulam, thifensulfuron, chlorimuron, and glyphosate caused major grain yield losses. AU Homer appears to be the least sensitive to herbicide-induced yield reductions, since neither thifensulfuron nor chlorimuron reduced grain yield. Ivany and McCully [13] stated that POST applications of imazethapyr caused severe crop injury and yield loss in sweet white lupin. The results of this study did not confirm their findings. Neither the PRE nor the POST imazethpyr applications caused significant crop injury or subsequent yield reduction. This could be due, in part, to the use of different cultivars than those used by Ivany and McCully [13]. In general, PRE herbicide applications included in this study, excluding diclosulam, could be used in lupin without posing a significant risk of crop injury. Previous observations by Dittman [28] agree with findings that PRE herbicides may cause less lupin injury than POST herbicide options. Certain POST herbicides, such as thifensulfuron, chlorimuron, and fomesafen, are not viable herbicide options for use in lupin. Other POST options, like fluazifop, 2,4-DB, sethoxydim, and imazethapyr, may offer additional options for weed control in lupin without increasing crop injury. The results of this experiment show that good weed control can be achieved by using a broad spectrum of herbicides that are currently not registered for use in US lupin production such as imazethapyr, flumioxazin, and linuron. With glyphosate and S-metolachlor, which are registered for use in lupin in the US, good weed control in lupin is possible; however, the use of a limited number of active ingredients can potentially increase resistance development in weed species in these systems. Based on these results, it is necessary to expand the number of registered herbicides for use in US lupin production.

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High prevalence and diversity of bovine astroviruses in the faeces of healthy and diarrhoeic calves in South West Scotland Highlights • Faeces from calves and adult cattle were examined by PCR for astrovirus (AstV).• Genotypically varied AstV were detected in faecal samples from 74% of calves.• AstV was detected in only 15% of faecal samples from adult cattle.• There was no association between presence of AstV and diarrhoea in calves.• AstV was associated with the presence of rotavirus Group A in calves. Introduction Diarrhoea in dairy and beef calves is very common and causes substantial morbidity and mortality through dehydration, metabolic acidosis and electrolyte depletion. Approximately half of the mortality in dairy calves up to 1 month old has been attributed to diarrhoea (Brickell et al., 2009). Diarrhoea in calves has many causes including infectious agents. The four pathogens most often associated with the disease are the protozoal parasite Cryptosporidium parvum, the viruses rotavirus and coronavirus, and enterotoxigenic strains of the bacteria Escherichia coli (Cho and Yoon, 2014). Other viral pathogens which have a less well defined association with calf diarrhoea include bovine torovirus, bovine calicivirus and bovine astrovirus. Astroviruses (AstV) are single stranded, positive-sense, nonenveloped RNA viruses of the family Astroviridae. The family is divided into the two genera Mamastrovirus and Avastrovirus based on their mammalian and avian host species, respectively. Astroviruses have long been recognised as an important cause of paediatric diarrhoea in human infants (reviewed in (Moser and Schultz-Cherry, 2005)); however, their role in enteric disease in other species is less clear. A diverse range of AstVs have been detected in faecal samples from diarrhoeic (Englund et al., 2002;Snodgrass et al., 1979;Toffan et al., 2009;Xiao et al., 2013) and healthy animals (Luo et al., 2011;Ng et al., 2013;Reuter et al., 2011;Tse et al., 2011) from a wide variety of species; however, their presence has only been convincingly linked with enteritis in mink and turkeys (Behling-Kelly et al., 2002;Englund et al., 2002). Further studies are required to define the role of AstV as a causative agent of diarrhoea in other species. AstV displays a high degree of sequence variability. In humans, for example, there are currently four identified species that can be further subdivided into numerous serotypes and subtypes. These serotypes and subtypes have been found, in some situations, to differ in their virulence (Caballero et al., 2003Holtz et al., 2011. There have also been reports that particular AstVs differ in their tissue tropism with some being associated specifically with Contents lists available at ScienceDirect Veterinary Microbiology j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / v e t m i c neurological disease in humans (Quan et al., 2010), mink (Blomstrom et al., 2010), and cattle (Bouzalas et al., 2014;Li et al., 2013). Infections of cattle with AstV were first described in 1978 (Woode and Bridger, 1978). Early studies suggested that these viruses were non-pathogenic in calves upon challenge (Bridger et al., 1984) but could exacerbate disease when calves were coinfected with rotavirus (Woode et al., 1984). Recent studies have described detection of AstV at a low prevalence in the faeces of adult cattle in Hong Kong (Tse et al., 2011) and calves in Korea (Oem and An, 2014). The latter study re-raises the potential pathogenic role of these viruses as detection was restricted to diarrhoeic samples. In order to examine the prevalence, diversity and disease associations of bovine AstV we analysed faecal samples from healthy calves, diarrhoeic calves and healthy adult cattle from farms in South West Scotland. Sampling design Seventy faecal samples from calves with a clinical history of diarrhoea were received by SAC Consulting: Veterinary Services for routine diagnostic investigation of neonatal enteritis between 27th November 2012 and 25th January 2013. All calves were under 4 weeks old and from 36 different dairy farms in South West Scotland. Control samples were obtained from 45 healthy calves from 5 dairy farms in South West Scotland with no reported calf diarrhoea at the time of sampling. Faecal samples were collected from 20 adult cattles over 2 years old with no evidence of diarrhoea from 3 farms. All control samples were collected at the time of defaecation and not per rectum. Samples and nucleic acid extraction Faecal samples were collected and suspended in 1 ml of RNAlater (Ambion) and stored at 4 C for a maximum of 2 days prior to processing. Particulate material was removed by centrifugation for 5 min at 13,000 Â g. Nucleic acids were extracted from 120 ml of faecal supernatants using an AllPrep DNA/RNA Mini Kit (Qiagen) and recovered in 30 ml of nuclease-free water. Reverse transcription (RT) and polymerase chain reaction (PCR) cDNA was synthesised from 6 ml of recovered RNA using Superscript III reverse transcriptase (Life Technologies) with random hexamer primers. The bovine AstV RNA dependent RNA polymerase (RdRp) PCR was performed using a previously described protocol (Chu et al., 2008) but with the BoAst3561as primer (5 0 -CCYTTRTTMABRWADGCRAACTCAAA-3 0 ) in place of the The tree was constructed using representative AstV sequences from humans (HuAstV), pigs (PoAstV), rodents (MoAstV), cattle (BoAstV), mink (MiAstV) and deer (CcAstV). Squares on each node represent the total number of clones matching each unique sequence from scouring calves (red), healthy calves (blue) and healthy adults (green). Nodes representing sequences derived from three individuals determined as having mixed infections are marked *, + and #. The BoAstV sequences with red node labels are from viruses detected in association with neurological disease. The evolutionary history was inferred using maximum likelihood methods. The optimum maximum likelihood models (lowest Bayesian information criterion score and typically greatest maximum likelihood value) for the nucleotide sequence alignment was first determined and used reverse primer in the second round of amplification. The rotavirus Group A (RVA) nested PCR was performed using primers designed based on an alignment of mammalian RVA segment VP1 sequences from 15 human, 3 equine, 2 porcine, 2 simian, 1 feline, 1 ovine, 1 antilopine and 4 bovine viruses (GenBank accession numbers NC011507,JF990805, JF693169, JF693103, HQ657138, JN013987, HQ657160, JF693158, JF693114, JF693180, JF693125, JF693191, JF693136, JF693147, JF693081, JN903527, JN903528, JN872865, X76486, M32805, EU636924, FJ422131, GU827406, FJ031024, FJ495126, JN831220, JF693059, JF693026 and DQ838640). Reactions were performed using GoTaq DNA polymerase (Promega) and primers RotaA_19_OS (5 0 -ATGGGGAAGTAYAATCTAATCTTGTCAG-3 0 ) and RotaA_467_OAS (5 0 -TCYARCCARAACATRACTGCATTTAA-3 0 ) in the first round and RotaA_47_IS (5 0 -AATATYTRTCATTYRTWTA-TAAYTCRCAATC-3 0 ) and RotaA_368_IAS (5 0 -TCAGAHGTTA-TYTTRTTRTTYTCATAATC-3 0 ) in the second round. First round reactions were performed using 2 ml of cDNA as template under the following conditions: initial denaturation at 94 C for 60 s and 30 cycles of 30 s at 94 C, 30 s at 50 C and 60 s at 68 C. Second round reactions were performed using 5 ml of first round template under the following conditions: initial denaturation at 94 C for 60 s and 40 cycles of 30 s at 94 C, 30 s at 50 C and 60 s at 68 C. PCR amplicons were ligated into pGEM-T Easy (Promega) according to manufacturer's instructions and these ligation reactions were used to transform DH5a chemically competent E. coli which were plated on LB/agar plates supplemented with 100 mg/ml ampicillin, 0.5 mM IPTG and 80 mg/ml X-gal. Positive clones were identified using PCR with primers specific for the M13F (5 0 -GTAAAACGACGGCCAG-3 0 ) and M13R (5 0 -CAGGAAA-CAGCTATGAC-3 0 ) sites located on opposite sides of the multiple vector cloning site. Plasmid-containing colonies were picked from LB/agar plates and resuspended in 15 ml of LB broth, 1 ml of which was added to GoTaq (Promega) PCR master mix. Reactions for screening clones were performed under the following conditions: initial bacterial lysis/denaturation for 2 min at 94 C, 30 cycles of 18 s at 94 C, 30 s at 50 C and 60 s at 72 C and a final extension of 5 min at 72 C. Direct sequencing of positive colony amplicons was carried out using BigDye Terminator v3.1 (Applied Biosystems) according to manufacturer's instructions with the M13F primer. Sequencing reactions were read by Edinburgh Genomics. Sequence analysis Cloned amplicon sequences, with vector nucleotides removed, were analysed and aligned with published AstV genome sequences using SSE v1.1 (Simmonds, 2012). Phylogenetic trees were constructed using maximum likelihood methods as implemented in the MEGA 6.0 software package (Tamura et al., 2013). Statistical analysis Statistical analysis was carried out in the R statistical environment version 3.1.2 (R Core Team, 2014). Univariable associations were estimated using the cc function in the epicalc package (Chongsuvivatwong, 2012). A Mantel-Haenszel adjusted odds ratio controlling for the presence of RVA was estimated using the epi.2by2 function in the epiR package (Stevenson et al., 2014). The multivariable model was estimated using a Firth adjusted logistic regression model and the logistf function in the package of logistf package (Heinze et al., 2013) to deal with low counts for certain covariate patterns. Nucleotide sequence accession numbers The nucleotide sequences of AstV amplicons were submitted to GenBank under the accession numbers KR138595-KR138670 and KR187112-KR187175. Epidemiological investigations do not reveal a statistical association between diarrhoea and AstV in faeces of calves in South West Scotland. In order to investigate the role of AstV in calf diarrhoea we compared the presence of AstV in faecal samples from healthy calves and diarrhoeic calves. The presence of AstV was tested for using a nested RT-PCR which amplifies the AstV RNA dependent RNA polymerase (RdRp) gene. Faecal samples were collected from 45 healthy calves from 5 dairy farms with no reported calf diarrhoea at the time of sampling and 70 calves with clinical signs of diarrhoea from 36 dairy farms. Faecal samples were also collected from 20 adult cattles with no recent history of diarrhoea. AstV was detected in a high proportion of both healthy and diarrhoeic calves (29 out of 45 (64.4%) and 56 out of 70 (80.0%), respectively). In contrast to the results from calves, AstV was uncommon in older cattles from the herds examined, being detected in only 3 out of 20 adult cattles (15.0%) none of which had signs of diarrhoea ( Fig. 1(a)). We also investigated the presence of rotavirus Group A (RVA), a common cause of calf diarrhoea (Dhama et al., 2009), by analysing the faecal samples from healthy and diarrhoeic calves for RVA using PCR directed against highly conserved sequences in the RVA segment VP1. RVA RNA was detected in 8 out of 45 healthy calves (17.8%) and 54 out of 70 diarrhoeic calves (77.1%) (Fig 1(a)) revealing, as expected for this well characterised enteric pathogen (Castrucci et al., 1994;Holland, 1990), an association between RVA and diarrhoea. A simple univariable analysis looking for statistical associations between variables of interest and the presence of diarrhoea initially suggested that AstV was also strongly associated with diarrhoea in the study samples ( Fig. 1(b)). However, AstV was also found to be strongly associated with RVA ( Fig. 1(b)), which could therefore be acting as a confounding factor. Indeed, after adjusting for the presence of RVA using a Mantel-Haenszel adjusted odds ratio the relationship between AstV and diarrhoea was no longer statistically significant ( Fig. 1(b)). To examine this further a multivariable model was developed to estimate the association between AstV and diarrhoea after adjusting for both RVA and animal age using a Firth logistic regression model (Table 1). The model suggests that adult animals have a lower odds of having diarrhoea (OR = 0.53; 95% CI 0.004-0.459) and that animals with RVA presence have $15 (OR = 14.6: 95% CI 5.80-41.2) times the odds of having diarrhoea compared to those without. After for phylogenetic reconstruction. This was the Tamura-Nei model with a gamma (g) distribution. Bootstrap support of branches (500 replications) is indicated. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) adjusting for age and the presence of RVA there was no statistically significant association with the presence of AstV (p-value = 0.855). We also tested for any evidence of a statistical interaction/effect modification between the two viruses but this was not significant and not included for simplicity. Importantly, the multivariable model is in agreement with the Mantel-Haenszel adjusted odds ratio, revealing that after adjusting for RVA and age, there is no statistically significant association between diarrhoea and AstV. Variation in the genotype of astrovirus in the faeces of calves There is evidence that certain lineages of human AstV exhibit greater virulence (Caballero et al., 2003Holtz et al., 2011. In order to determine if particular bovine AstVs are differentially associated with calf diarrhoea, amplicons from AstV PCRs selected to represent all positive farms and a variety of amplicon intensities were cloned and sequenced. A total of 209 individual clones from 48 amplicons (1-8 clones per amplicon from 28 diarrhoeic calves, 17 healthy calves and 3 healthy adults) were sequenced. Primer sequences were trimmed and a 220 nucleotide region equivalent to nucleotides 3316-3535 in the bovine AstV sequence HQ916313 was used for further analysis. 76 unique sequences were identified from the 209 clone sequences analysed. Phylogenetic analysis of these sequences revealed the presence of three distinct viral lineages (Fig. 2) with varying degrees of relatedness to previously described AstV from cattle, deer and pigs. The overall diversity of clones from healthy and diarrhoeic calves was similar with comparable numbers of clones from these two sample sets in the three viral lineages identified. The sequences in each of the three groups were diverse, with those classified as lineage 2 showing the highest variability with a mean pairwise nucleotide divergence across the analysed region of 18.1% compared to 11.9% and 6.2% in lineages 1 and 3, respectively. Pairwise distances between lineages were 30.0% (lineage 1 vs 2), 23.3% (lineage 1 vs 3) and 28.8% (lineage 2 vs 3). While the majority of AstV clones from a single individual contained identical or closely related sequences, there were three cases (Fig. 2, nodes marked *, + and #) where sequences of multiple lineages were cloned from a single individual's PCR amplicon indicating concurrent infection with multiple, diverse AstVs. Overall, many different AstVs were found in the faeces of calves; however, no association of a particular lineage with calf diarrhoea was identified. In the 21 clones that were sequenced from 5 RVA PCR amplicons, a pairwise nucleotide divergence of <1.2% over the 261 nucleotides amplified (322 nucleotide amplicon size minus primers) was found, as is to be expected with a highly conserved target region. All sequenced amplicons clustered phylogenetically with R2 genotypes (data not shown). Astrovirus persistence The temporal dynamics of AstV infection were examined by sequential sampling of three calves with diarrhoea from a single farm to determine if a change in AstV lineage correlated with clinical deterioration or improvement. Two calves (calves A and B) died from diarrhoea during the study while the third calf (calf C) survived. All 3 individuals remained AstV PCR positive over the sampling time. The relationship between the most prominent viruses detected at each time point was determined by phylogenetic analysis of 4-15 clones per sample (Fig. 3). In calf B, viral sequences detected at initial sampling and at time of death (15 days after initial sampling) were highly similar differing in, at most, 1 out of 223 nucleotides. Calf A, however, showed a complete change from detecting lineage 3 sequences on initial sampling (15 out of 15 clones) to detection of lineage 1 sequences at time of death (8 out of 8 clones). Calf C survived throughout the sampling period. No significant change was seen in viral sequences detected from samples on the 29th November, 17th December and 20th December with all being within lineage 3 and differing at most by 5 out of 223 nucleotides. However, from the sample taken on the 28th of December, lineage 1, 2 and 3 sequences were detected, demonstrating a clear mixed infection. From the sample collected on the 10th of January only lineage 2 sequences were detected. Overall these results show marked variation in the AstVs in the faeces of a single animal over time, with different AstVs present at different times and presence of multiple AstV lineages at the same time. In the three animals examined no temporal link was found between a change in AstV and the outcome of disease. Discussion Experimental studies have shown that inoculation of gnotobiotic calves with AstV does not result in clinical disease (Woode and Bridger, 1978;Woode et al., 1984); however, the situation on the farm where multiple pathogens are invariably present is less clear. Here we report a high prevalence of genetically varied astroviruses in faecal samples from both healthy and diarrhoeic calves in South West Scotland. No association between diarrhoea and presence of AstV was detected, neither was there an association between diarrhoea and specific AstV genotypes. This suggests that AstV were not an important cause of diarrhoea in our case animals. The finding is in contrast to the well-characterised enteric pathogen RVA which was found to be significantly associated with diarrhoeic calves in our study. Our findings are similar to recent studies of porcine AstV which found a high prevalence of AstV in swine faeces (Xiao et al., 2013), and no association of AstV presence with diarrhoea (Zhang et al., 2014). However, our findings are in contrast to a recently reported screen of bovine faeces from Korean cattle where bovine AstVs were detected at a much lower prevalence and only in samples from diarrhoeic calves (9 out of 91 diarrhoeal calves and none of the 24 non-diarrhoeal samples tested were positive by PCR (Oem and An, 2014)). It is possible that different PCR design may explain the difference since during optimisation of the AstV PCR in our study we found that the use of primers designed specifically for bovine AstV strains resulted in more sensitive and reproducible detection of AstV from bovine faeces compared to use of pan-AstV primers (data not shown). We examined age stratification of bovine AstV and found that AstVs were significantly more likely to be found in calves than adults, suggesting the younger animals are more susceptible to infection. A low level of detection in adult cattle was also reported by Tse et al. (2011) where only 5 of 209 samples from adult cattle were found to be positive for AstV. This age stratification is similar to reports from human medicine where AstV diarrhoea occurs predominantly in children (Afrad et al., 2013) and reported disease outbreak tend to be in children (Dalton et al., 2002;Li et al., 2010) and the elderly (Lewis et al., 1989), suggesting that protection against AstV is acquired after an initial infection and later wanes. However, the specific immune responses activated upon AstV infection and the level of protection they afford are not yet completely understood in either humans or veterinary species. Sequencing of the RNA dependent RNA polymerase gene of the bovine AstV species found in Scottish cattle revealed several highly divergent lineages within the Mamastrovirus genus. By sequencing sequential samples from the same animals, we have shown AstV infection to be highly dynamic with different AstVs present in the same animal concurrently and sequentially. It is unclear whether this absence of genotypic consistency is due to constant reinfection with viruses from different lineages, differential shedding of certain lineages over time or detection of non-infecting viruses acquired through dietary contamination. Our ability to classify the Fig. 3. Phylogeny of unique AstV clones as inferred from partial RdRp sequences (equivalent to nucleotides 3316-3535 of the bovine AstV sequence HQ916313). The tree was constructed using representative AstV sequences from humans (HuAstV), pigs (PoAstV), rodents (MuAstV), cattle (BoAstV), mink (MiAstV) and deer (CcAstV). Nodes with different symbols represent clones collected on different dates from four calves as indicated by the key. The evolutionary history was inferred using maximum likelihood methods. The optimum maximum likelihood models (lowest Bayesian information criterion score and typically greatest maximum likelihood value) for the nucleotide sequence alignment was first determined and used for phylogenetic reconstruction. This was the Tamura 3-parameter model with a gamma (g) distribution. Bootstrap support of branches (500 replications) is indicated. viral sequences detected was restricted by the limited size of the screening amplicons; however, further characterisation of complete genomes from these viruses will better inform classification and investigate the potential for recombination given the detection of concurrent infection with multiple AstV lineages. The use of the more specific PCR in this study compared to the published pan AstV assay (Chu et al., 2008) may have resulted in a restriction of viral lineages detected although the diversity of sequences reported here and obtained in an initial screen of these samples with the published assay was comparable (data not shown). Importantly, no sequences identified in the initial screen were shown to cluster with the recently described bovine neurotropic AstV (marked with red node labels in Fig. 2) (Bouzalas et al., 2014;Li et al., 2013) indicating that this lineage of viruses may have a more restricted prevalence or different tissue tropism. We investigated co-infection of AstV with a common viral enteric pathogen-RVA. Co-infection with AstV and other enteric pathogens has been reported previously in calves (Oem and An, 2014;Woode et al., 1984) and humans (Afrad et al., 2013;Li et al., 2010), and our study found that presence of AstV and RVA in calf faeces were strongly associated. We were unable to determine if this association is causal, for example if AstV presence predisposes calves to RVA infection or vice versa, or the clinical significance of the association for example if AstV potentiates the severity of diarrhoea caused by RVA, as has been reported experimentally (Woode et al., 1984). Definitive determination of bovine AstV as an enteric pathogen, either singly or in combination with another pathogen such as RVA, would require viral isolation and experimental infections under natural conditions. However, our study, with the important inclusion of age and geographically matched controls, found no evidence that detection of AstV, or even specific AstV lineages, in the faeces of calves is associated with diarrhoea. Conflicts of interest None

v3-fos

2017-06-26T09:27:29.969Z

2015-06-10T00:00:00.000Z

11571587

s2

Comparative transcriptomics analysis reveals difference of key gene expression between banana and plantain in response to cold stress Background Banana and plantain (Musa spp.) comprise an important part of diets for millions of people around the globe. Low temperature is one of the key environmental stresses which greatly affects the global banana production. To understand the molecular mechanism of the cold-tolerance in plantain we used RNA-Seq based comparative transcriptomics analyses for both cold-sensitive banana and cold-tolerant plantain subjected to the cold stress for 0, 3 and 6 h. Results The cold-response genes at early stage are identified and grouped in both species by GO analysis. The results show that 10 and 68 differentially expressed genes (DEGs) are identified for 3 and 6 h of cold stress respectively in plantain, while 40 and 238 DEGs are identified respectively in banana. GO classification analyses show that the majority of DEGs identified in both banana and plantain belong to 11 categories including regulation of transcription, response to stress signal transduction, etc. A similar profile for 28 DEGs was found in both banana and plantain for 6 h of cold stress, suggesting both share some common adaptation processes in response to cold stress. There are 17 DEGs found uniquely in cold-tolerance plantain, which were involved in signal transduction, abiotic stress, copper ion equilibrium, photosynthesis and photorespiration, sugar stimulation, protein modifications etc. Twelve early responsive genes including ICE1 and MYBS3 were selected and further assessed and confirmed by qPCR in the extended time course experiments (0, 3, 6, 24 and 48 h), which revealed significant expression difference of key genes in response to cold stress, especially ICE1 and MYBS3 between cold-sensitive banana and cold-tolerant plantain. Conclusions We found that the cold-tolerance pathway appears selectively activated by regulation of ICE1 and MYBS3 expression in plantain under different stages of cold stress. We conclude that the rapid activation and selective induction of ICE1 and MYBS3 cold tolerance pathways in plantain, along with expression of other cold-specific genes, may be one of the main reasons that plantain has higher cold resistance than banana. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1551-z) contains supplementary material, which is available to authorized users. Background Low temperature is one of the key environmental stresses that many plants have to cope with during their life cycle, which can influence growth, development, as well as the yield, quality, postharvest life, and geographic distribution of crop plants [1,2]. Cold stress can be classified as chilling (0-15°C) and freezing (<0°C) stresses. Generally, plants from temperate regions have the capacity to cold acclimate, that is, to develop increased freezing tolerance after being exposed to low, nonfreezing temperatures [3], but many important crops, such as rice, maize, soybean, cotton, and tomato, which originated in the tropics and subtropics, lack the cold acclimation mechanism and are sensitive to chilling stress [4]. Moreover, different varieties of the same species can also exhibit a high degree of genetic variability for cold tolerance [5][6][7]. In conventional crop cross-breeding, the cold-tolerant varieties are usually used as the main resource for increasing the cold tolerance of cultivars [8]. However, the lack of detailed knowledge of molecular mechanisms responsible for cold stress limits the potential for crop improvement. Investigation of gene expression profiles in response to cold stress will shed light on the sensing and regulatory networks for cold acclimation in plants and provide an effective approach to select targeted candidate genes for manipulation and/or cross-breeding of agronomic plants [8]. Musa spp. (including Banana and Plantain), which originated in the tropics are giant perennial herbaceous monocots. They are vital staple food in many African countries and the most popular fruit in industrialized countries [9]. Musa spp. exhibits a high degree of genetic variability for cold tolerance, with banana (Musa spp. Cavendish; AAA Group) being more cold sensitive than plantain (Musa spp. Dajiao; ABB Group). When the temperature drops to 8°C, banana growth is arrested, injury is inflicted [10], and irreversible damage often occurs with temperatures below 12°C [11]. In milder cases of cold injury, the fruit can be harvested, but its ripening process is abnormal. In contrast to the Cavendish "dessert" banana, the plantain species, Dajiao has superior cold tolerance, enabling it to tolerate temperatures of 0-4°C [12], and has been proposed as a potential germplasm resource of cold tolerance in banana breeding [10]. Although Musa spp. appear to lack a cold acclimation mechanism, transgenic plantain constitutively overexpressing the Arabidopsis transcription factor DREB1B/ CBF1 becomes highly tolerant to cold by increasing SOD activities, decreasing MDA content and the electrolyte leakage rate. Meanwhile the growth rates of these transgenic plants are severely retarded under normal growth conditions [13]. In the herbaceous monocot rice (Oryza sativa), which also originated in the tropics, a novel MYBS3-dependent pathway has recently been identified as essential for cold tolerance. MYBS3 was found to repress the CBF-dependent cold signaling pathway. Molecular evidence indicates that the sequential expression of CBF and MYBS3 provides two complementary mechanisms for conferring cold tolerance, with the CBF-mediated process initiating the immediate cold shock response and the MYBS3-mediated system adjusting the long-term cold adaptation in rice [14]. Recently, a new quantitative trait locus COLD1 was identified, which interacts with G protein to activate the Ca 2+ channel for low temperature sensing that confers chilling tolerance in japonica rice, compared with cold-sensitive indica rice. Overexpression of COLD1 jap significantly enhances chilling tolerance, whereas rice lines with deficiency or downregulation of COLD1 jap are sensitive to cold stress [15]. In the past decade, some physiological responses to cold stress were analyzed, comparatively, between banana and plantain [16], and another cold-resistance related plantain MpRCI (Rare cold-induced gene) has been identified, that enhances low temperature resistance when heterologously expressed in transgenic tobacco [17]. Through the traditional map-based cloning and transgenic methods, one can identify some key stress-related genes. But it's generally tedious and time-consuming, especially for fruit trees which have a relatively long juvenile phase. In recent years, advances in novel highthroughput sequencing technologies, such as Solexa/ Illumina RNA-Seq (RNA sequencing) and digital gene expression (DGE) has provided an opportunity to explore cold resistance and signaling-associated genes in different species by denovo assembly or mapping, facilitating rapid identification and analysis of many transcriptomes [18]. Transcriptome research has become an effective means to investigate the gene expression patterns of fruit trees in the growth and development process and under various stresses, which has been reported in tropical and subtropical fruit trees, such as litchi [19,20], mango [21], papaya [22], citrus [23] and grape [24] etc. Our quantitative proteomic analysis reveals that molecular mechanisms for the higher cold resistance found in plantain are associated with increased redox potential characterized by adapted ROS scavenging capability, reduced ROS production, decreased lipid peroxidation, and cell wall stabilization [10]. Gene expression under cold stress is very sensitive and it depends on the species, the temperature and the length of exposure to low temperature [5][6][7]. Although several important clues are suggested from intensive proteomic research of coldtolerance plantain and comparing those results with functional gene analysis conducted in other plants, a comprehensive differential transcriptome analysis in response to cold stress between banana and plantain has not been reported and remains unknown. In this study, plantain collected from a subtropical region of China with high cold-tolerance was used to investigate responses to cold stress at the transcriptional level. A cold-sensitive species, banana was examined as a control. A well-established whole genome transcriptome analysis method, based on RNA-Seq, and incorporating real time-PCR, was utilized to screen the differential transcripts associated with cold tolerance between banana and plantain. Our study provides a broad picture of the banana and plantain cold-responsive transcriptomes, with a new insight to cold-tolerance molecular mechanisms of plantain under cold stress. Results Phenotypes and electrolyte leakage of banana and plantain to cold stress To accurately evaluate the tolerance of plantain, we compared the physiological changes of plantain versus banana in parallel during cold stress. A significant phenotypic difference is that the banana leaves drooped after 6 h of cold treatment and the second and third leaves from the top displayed severe necrosis and wilting symptoms after 48 h of cold treatment at 10°C, while plantain leaves remained normal ( Figure 1A and B). The relative leakage increased from 12.0 to 33.9% in banana leaves, and from 14.6 to 28.0% in plantain leaves respectively after 6 h of cold treatment. After 48 h of cold stress, the leakage of plantain leaves decreased to the basal level, but the leakage of banana leaves still increased and the damage was not alleviated ( Figure 1C). These observations suggest that the seedlings of plantain leaves had adapted to the cold stress to some extent after 6 h of treatment and appeared to protect the membrane from further damage, suggesting that some important cold-tolerant genes, such as the early signal transduction genes of plantain, may work at the beginning 6 h of cold treatment. Both phenotypic response and relative leakage of plantain support the notion that plantain once again, has stronger cold tolerance than banana. RNA-Seq and alignment of unique reads to banana reference genome The raw data quality assessment of banana and plantain libraries with control and cold treatment are shown in Additional file 1: Table S1. For banana, after filtering out low quality reads, raw reads containing 'N' and adaptor sequences, 12 Multiple mapped clean reads in each library were excluded from further analysis. Finally a total of 5.14 M to 7.55 M uniquely mapped clean reads were used for subsequent analysis. The distribution of unique reads with chromosome '+/−' chain and splice/non-splice in each library were counted and are shown in Table 1. For plantain, after filtering out low quality reads, raw reads containing 'N' and adaptor sequences, 13.94 M to 16.20 M clean reads were generated from four biological replicates of 0, 3 and 6 h cold treated libraries, respectively (Table 1). Clean reads were aligning to banana reference genome database. There are also about 60% of plantain clean reads mapped to the reference genome. Finally a total of 5.04 M to 5.94 M uniquely mapped clean reads were used for further analysis. The distribution of unique reads with chromosome '+/−' chain and splice/non-splice in each library were counted and are shown in Table 1. Differential expression profiling of cold stress between banana and plantain To comprehensively investigate the differences in gene expression between cold-sensitive banana and coldtolerant plantain in response to cold stress, we performed comparative transcriptome analysis using the aligned reads (above). After 3 h of cold stress, a total of 40 (33 upand 7 down-regulated), 10 (9 up-and 1 down-regulated) cold-responsive genes were identified in banana and plantain, respectively (Table 2, Figure 2, Additional file 2: Table S2 and Additional file 3: Table S3) with the threshold of 0.05 for Corrected P-value and 1 for log2 base of foldchange. Out of the 40 DEGs, 33 cold-responsive genes (26 up-and 7 down-regulated) were exclusively identified in banana, whereas 3 cold-responsive genes (2 up-and 1 down-regulated) were uniquely observed in plantain. The remaining 7 genes (all up-regulated) were commonly regulated by cold stress in both banana and plantain. After 6 h of cold stress, a total of 238 (195 up-and 43 downregulated), 68 (54 up-and 14 down-regulated) coldresponsive genes were identified in banana and plantain, respectively (Table 2, Figure 2, Additional file 2: Table S2 and Additional file 3: Table S3). Out of the 238 DEGs, 188 cold-responsive genes (149 up-and 39 down-regulated) were exclusively identified in banana, whereas 18 coldresponsive genes (8 up-and 10 down-regulated) were uniquely observed in plantain and 50 genes (46 up-and 4 down-regulated) were commonly regulated by cold stress in both banana and plantain. The small number of coldresponsive genes identified in cold-tolerant plantain suggests that some inherent adaptation and regulation mechanisms may be attributed to the cold tolerance in plantain. Functional classification of cold stress-related DEGs The functional classification of DEGs in banana and plantain was further examined to explore the pattern of transcriptome regulation that occurs during cold stress. Genes matching well-characterized proteins or proteins with putative functions were grouped using the gene ontology (GO) and summarized in Additional file 4: Table S4 and Table 3. The majority of DEGs identified in this study are in the categories regulation of transcription, response to stress, transport, protein modification, nucleosome assembly, cell wall organization and biogenesis, signal transduction, oxidation reduction, RNA modification, cell redox homeostasis, etc. No obvious difference of GO classification was observed for those DEGs from either banana (Additional file 4: Table S4) or plantain (Table 3), despite the fact that few DEGs in each GO category were identified in plantain than in banana. Validation of the DEGs by quantitative RT-PCR analysis Plantain leaves showed significant phenotypic difference from banana after 3 h cold treatment at 10°C, we suspect that early response genes of plantain are closely associated with its cold resistance, thus 10 DEGs of plantain identified in this study after 3 h cold treatment and 2 critical cold-response homologous genes in arabidopsis ICE1 and rice MYBS3 were selected for quantitative RT-PCR analysis. Two additional extended time points for 24 and 48 h of cold stress were also measured in parallel with initial 0, 3 and 6 h cold stressed samples in both banana and plantain. The primers of selected genes are listed in Additional file 5: Table S5. 25S ribosomal RNA gene was used as reference gene for data normalization according to Van den Berg et al. [25]. The quantitative RT-PCR results from banana and plantain are shown in Figure 3. The expression profiles of all 12 detected genes show the same trend and consistent results between the RT-PCR and the Solexa-sequencing methods. For 24 and 48 h of cold stress, 6 out of 10 DEGs displayed the same down regulation in both banana and plantain, including GSMUA_Achr7G05900_ 001 (Dehydration-responsive element-binding protein 1D), GSMUA_Achr9G07610_001 (Probable cytosolic iron-sulfur protein assembly protein 1), GSMUA_Achr6 G32910_001 (Zinc finger CCCH domain-containing protein 33), GSMUA_Achr7G26580_001 (UDP-glucose 6-dehydrogenase), GSMUA_ Achr3G04360 _001 (Ethylene-responsive transcription factor RAP2-13), GSMUA_ Achr3G23000_001 (Calcium-binding protein KIC). However, 4 of them showed opposite changes between banana and plantain, including GSMUA_Achr6G25670_001 (U-box domain-containing protein25), GSMUA_Achr8G21550_001 (Ethylene insensitive 3-like 1 protein), GSMUA_ Achr2G 13410_001 (Zinc finger protein 1) and GSMUA_Achr 3G05220_001 (Probable xyloglucan endotransglucosylase/ hydrolase protein 23). Strikingly, there is a remarkable difference of ICE1 and MYBS3 expression profile between plantain and banana in response to cold stress. The ICE1 was significantly down-regulated (decreased by 4-fold) under cold stress at early stage (3 h) in banana, but its decrease (by~5-fold) didn't appear until at 24 h in plantain ( Figure 3K). Although the MYBS3 was down-regulated similarly at early stage by 9-fold and 4-fold in banana and plantain respectively, at 6 h of cold stress ( Figure 3L), it can be recovered much quickly in plantain than banana. With the extended cold stress, the plantain MYBS3 was rapidly recovered to the level of 41% (at 24 h) and 75% (at 48 h), while the banana MYBS3 was further decreased to 4% at 24 h and then recovered to 24% at 48 h of cold stress. The considerably different expression profiles of the two important transcriptional factors with a remarkable time delayed response in banana versus plantain suggest that the specific time course-based expression of ICE1 and MYBS3 in plantain might be related to its cold tolerance. Discussion and conclusions In our previous study on the temporal responses of plantain to cold stress using quantitative proteomics analysis, we have revealed that antioxidation mechanisms contribute to cold tolerance in plantain at the global proteome level [10]. However, due to the limitation of current technologies in overcoming the issue of the wide dynamic range in proteomics samples, quantitative proteomics analysis often misses the detection of many low abundance proteins, yielding only 10-30% proteome coverage for any given non-model species. Obviously this will reduce the number of low abundance proteins identified during global functional studies. Given the above consideration and to focus on the molecular mechanisms involving low abundance genes on the cold-tolerance of plantain, a comparative transcriptomics analysis of cold-sensitive banana and cold-tolerant plantain was conducted by RNA-Seq and real time RT-PCR with time course of cold treatment. After 48 h of cold stress at 10°C for banana and plantain seedlings, both phenotype and electrolyte leakage analyses clearly indicate that plantain seedlings exhibited a more robust cold tolerance than banana seedlings ( Figure 1). It is this phenotypic difference in the cold response between banana and plantain that provides an excellent model system allowing us to study differential gene expression in response to cold stress, as well as to elucidate the potential different cold responsive mechanisms between banana and plantain. RNA-Seq analysis shows that 10 and 68 DEGs are identified for 3 h and 6 h of cold stress respectively in plantain, while the equivalent DEGs are 40 and 238 being identified in banana (as shown in Figure 2), indicating banana is much more sensitive to cold stress than plantain. GO classification analysis shows the majority of DEGs identified in this study belong to the following 11 categories: regulation of transcription, response to stress, transport, protein modification, nucleosome assembly, cell wall organization and biogenesis, signal transduction, oxidation reduction, RNA modification, cell redox homeostasis, etc. Since there is no difference of GO classification found between banana (Additional file 4: Table S4) and plantain (Table 3), it suggests that cold stress appears to have a broad range of impacts on cellular activities. However, when we further performed the pathway analysis for some specific DEGs either found uniquely in plantain particularly or detected at variable cold stress time points in both banana and plantain, we found that many DEGs and their associated pathways are likely to be involved in cold-tolerance of plantain. Below we discuss intensively some of the important pathways and their possible mechanisms associated with the observed cold tolerance in plantain. ICE1 and MYBS3 pathways ICE gene was initially identified and isolated from Arabidopsis thaliana. The function of AtICE1 is to activate gene expression of C-repeat binding factor (CBF3) to enhance the cold resistance of Arabidopsis [26]. In Oryza sativa, three novel MYB proteins (MYBS1, MYBS2 and MYBS3) containing one highly conserved DNA-binding domain mediate sugar and hormone regulation by promoting gene expression of alpha-amylase [27]. Recent studies reveal that MYBS3 is also involved in adaptation of cold stress in rice. Compared to the ICE1, MYBS3 functions particularly in late stage of plant for adaptation of cold stress. For example, transgenic rice overexpressing MYBS3 can resist cold stress at 4°C for a week [14]. In the early stage of cold response, the transient activation of αAmy3 expression by CBF allows hydrolysis of reserved starch to meet the immediate need for a carbon source and energy to combat the cold shock, while the subsequent suppression of αAmy3 expression by MYBS3 allows rice to conserve carbohydrates until regrowth is allowed at elevated temperatures [14]. In this study using RNA-Seq analysis for 0, 3, and 6 h of cold stressed samples, although both ICE1 and MYBS3 genes were detected, neither was identified as DEG. This is not surprising, because ICE1 requires activation, which is regulated by post-translational modifications via phosphorylation and sumoylation of the SIZ1 gene [28,29]. Thus, ICE1 is likely not regulated at the transcriptional level. Since MYBS3 plays a role in cold adaptation at late stage of plant (See figure on previous page.) Figure 3 Relative mRNA levels of 12 DEGs in banana and plantain seedlings were determined by quantitative RT-PCR analyses. Six-leaf stage seedlings were incubated at 10°C for the indicated time. Transcript abundances of genes encoding dehydration-responsive element-binding protein 1D (A), ethylene insensitive 3-like 1 protein (B), probable cytosolic iron-sulfur protein assembly protein 1 (C), zinc finger protein 1 (D), U-box domain-containing protein 25 (E), zinc finger CCCH domain-containing protein 33 (F), UDP-glucose 6-dehydrogenase (G), probable xyloglucan endotransglucosylase/hydrolase protein 23 (H), ethylene-responsive transcription factor RAP2-13 (I), calcium-binding protein KIC (J), transcription factor ICE1 (K) and MYBS3 (L) from both banana and plantain were determined and compared across the time course of cold stress. Data represent means ± SD in four replicates (n = 4). The different lowercase letters labeled above columns indicate a significant difference at p ≤ 0.05 between the columns by Duncan's test using SPSS statistical software (version 16.0, SPSS Inc. Chicago, IL). The columns with the same letters mean no significant difference (p > 0.05) between each other. growth, MYBS3 is expected not present in early time points from cold stressed samples. In fact, we did identify both genes by RNA-Seq analysis at a low level with relatively large variation across the 4 replicate samples. Given the well-known functions of both ICE1 and MYBS3 genes in plant resistance to cold stress, we decided to use quantitative RT-PCR for assessing their changes with the extended time points at 24 and 48 h of cold stress in this study. The results indicate that although there is no significant change of ICE1 in plantain at 3 and 6 h cold stress, both an upstream gene: GSMUA_Achr9P04380_ 001(MpSIZ1, 68% homology with arabidopsis SIZ1) and a downstream gene: GSMUA_ Achr7 G05900_001 (CBF) in an ICE1-CBF-COR pathway, were up-regulated (Additional file 6: Figure S1; Figure 3A). Since the ICE1-CBF-COR is a well-known pathway involved in plant cold-tolerance [30], the up-regulation of CBF is therefore, expected to facilitate the cold-tolerant pathway. A 3.5-fold increase of COR47 protein found in our proteomics analysis of plantain for 6 h under cold stress at 8°C [10] supports this observation with the ICE1-CBF-COR pathway being activated in response to the cold stress in this study. Interestingly, at 24 h of cold stress, both plantain ICE1 and CBF were down regulated. Meanwhile, the MYBS3 gene had almost completely recovered (from early down-regulation in response to the cold stress), which may offset the down-regulated ICE1-CBF-COR pathway as a means of sustaining the cold resistance. In banana, however both ICE1 and MYBS3 were significantly decreased under cold stress. The CBF response to cold stress in banana is significantly slower than that in plantain, until 6 h of cold stress, when the banana CBF gene was up-regulated, only to go down again at 24 h of cold stress. Consistently, the time delayed response of MYBS3 gene to the cold stress was also observed in banana. However, at 48 h of cold stress, the banana MYBS3 gene appeared recover from its initial cold suppression. Based on the observation of slow response to the cold stress in banana for both ICE1 and MYBS3 as the two critical transcriptional factors responsible for early and late stage respectively against cold stress, we suspect that the relatively low expression of these two key genes along with their delayed response to the cold stress are among the main reasons for cold sensitive banana. Signals transduction As an important second messenger, Ca 2+ plays a vital role in the plant cold-stress response. The concentration of Ca 2+ inside the cell increases rapidly during cold stress, followed by a number of signals mediated by a series of protein phosphorylation cascades [31]. During rice domestication, an amino acid mutant of COLD1 from Met 187 /Thr 187 to Lys 187 in japonica cultivars was found to enhance cold tolerance partly because it facilitates the formation of an appropriate Ca 2+ signal by increased Ca 2+ concentration [15]. Interestingly, our study shows that most of the DEGs involving in signal transduction are indeed related to the calcium-dependent signal pathway, such as orthologs of CIPK (CBL-interacting protein kinase), KIC (Kinesin-like calmodulin binding protein) and CML (Calmodulin-like protein). All three genes in banana and plantain were up-regulated in response to cold stress. In addition, overexpression of OsMSR2, a novel rice calmodulin-like gene, improves resistance of drought and salt and increases ABA sensitivity in Arabidopsis [32]. In this work, we found the dramatically increased expression of CML7 (GSMUA_Achr6G35120_001), an ortholog of OsMSR2, in response to cold stress in plantain but not in banana, suggesting that there is a more efficient response of the Ca 2+ signal transduction pathway in plantain so that it can quickly and effectively regulate downstream signaling and gene expression in response to cold stress. As a signal molecule, auxin plays an important function under various abiotic stress conditions [33]. Intriguingly, compared to the control group (0 h), the expression of GSMUA_Achr4G16550_001 (Auxin-induced in root cultures protein 12, AIR12) was increased by 9 fold in 6 h cold treatment in plantain, while no differential expression of the gene was detected in banana. On the plasma membrane, AIR12 is able to receive auxin signal to promote lateral root morphogenesis and participates in the decomposition of glucose [34], while it has been proven that the content of soluble sugar and acid can affect the plant's cold tolerance [35,36]. Our results indicate that the increased expression of AIR12 in plantain could facilitate the growth of plantain root and the content of sugar and acid, which might be attributed to the better resistance to cold. Transcription regulation In this study, we have identified 10 differentially expressed transcription factors in response to cold stress in banana and plantain, including NAC, ERF (Ethylene response transcription factors), DREB (Dehydrationresponsive element-1binding protein), MYB,WRKY, C3H33, EIL1 (Ethylene insensitive 3-like 1 gene), ADO3 (Adagiolike gene 3), ZFP (Zinc finger protein) and RPOA (DNA-directed RNA polymerase subunit alpha). NAC transcription factors were up-regulated in banana and plantain after 6 h cold stress, and over-expression of SNAC2 was reported to increase cold and salt resistance in rice [37], suggesting that NACs are likely to participate in cold response in banana and plantain. Effects of ethylene on plants under cold stress have recently been recognized, the ERF transcription factors which related to ethylene, were up-regulated in banana and plantain after 6 h cold stress. Overexpression of transcription factor TERF2/ LeERF2 in tobacco and tomato was reported to result in cold tolerance by facilitating ethylene biosynthesis [38], which supports the important role of ERF in plant cold tolerance. DREB transcription factors, with a conservative AP2/EREBP domain, are involved in regulation of stressrelated gene in response to the external environment, through binding DRE CIS-acting elements [39]. Our data shows that overexpression of DREB1 occurs at 3 h of cold stress in plantain versus 6 h in banana, suggesting that the early response of DREB1 may be critical in cold-tolerant plantain. Due to a large number of MYB transcription factor found in plants such as Arabidopsis thaliana and Zea mays, an increased amount of research has been focused on its role in transcriptional regulation and its impact on a broad range of physiological functions, e.g., overexpression of rice MYB genes (OsMYB3R-2 and OsMYB4) enabled to significantly enhanced the cold tolerance of transgenic Arabidopsis thaliana [40]. In our work,we found GSMUA_Achr8G25220_001-a MYB transcription factor increased after 6 h cold stress while it was undetectable at 0 h in both banana and plantain, indicating that this gene is a cold-induced gene. The change of this MYB gene could affect downstream related genes. In Arabidopsis thaliana, the WRKY gene family contains 17 genes induced by cold stress, most of which are activated in its early stages [41,42]. After 6 h cold stress, the WRKY genes showed up-regulation, among them, GSMUA_Achr7G 05200_001 was overexpressed whereas it was undetectable at 0 h, indicating it is also a cold-induced gene. In plantain, only one cold-induced WRKY gene-GSMUA_ Achr6G15840_001 was detected after 6 h of cold stress. However, its expression was much higher than that in banana, suggesting that this WRKY gene may contribute to the cold-resistance of plantain. It has been reported that zinc-finger proteins are involved in resistance to adversity in plant [43]. For example, GmZF1 from soybean was found to enhance the tolerance of Arabidopsis to cold stress by expression of cold-regulation genes in the transgenic Arabidopsis [44]. Strikingly, banana ZFP1 is not up-regulated until 24 h of cold stress and starts to decrease at 48 h, while plantain ZFP1 is constantly upregulated beyond 48 h of cold stress, suggesting ZFP1 may play a role in late stages of cold stress ( Figure 3D). Expression of EIL1 in plantain reached~11-fold higher induction at 3 h cold treatment and then decreased back to initial levels at 48 h. In banana, the EIL1 was upregulated by~9-fold at 6 h and further increased tõ 13-fold at 48 h of cold treatment ( Figure 3B). As a primary transcription factor in ethylene signal transduction, EIL regulates transcription of downstream genes to complete the ethylene response [45]. Given the higher expression of EIL at very early stages and its rapid decrease in response to cold stress in plantain, we suspect that rapid and early activation of the ethylene signal transduction pathway appears to play a critical role in the rapid response to cold stress allowing early protection in plantain. Genes associated with stress response Plants often activate similar pathways in response to different types of abiotic stress. In this cold stress study, we found quite a few genes related to stress response in both banana and plantain, such as STHY (Probable salt tolerance-like protein), P2C32 (Probable protein phosphatase 2C 32), ubiquitin-protein ligase genes, THIL-2 (Thiamine thiazole synthase 2), GRP(Glycine-rich RNAbinding protein) and DRT100 (DNA-damage-repair/ toleration protein), etc. Those genes showed similar patterns of expression in response to cold treatment in banana and plantain, suggesting the stress response genes share some common response pathways in both species. However, it should be noted that some of the DEGs are located in the chloroplast of plantain only, such as ELIP, CTL1, SCA and MKS1. In Rhododendron catawbiens, expression of RcELIP (early light-induced protein) resulted in adaptive responses to cold and high light in winteradapted rhododendron leaves, suggesting a critical role of ELIP in protection of photosynthetic apparatus from these stresses [46]. In Arabidopsis thaliana, CTL1 (Chitinase-like protein) is involved in altering the architecture of the root system in response to multiple environmental conditions [47]. As an MAP kinase substrate, Arabidopsis MKS1 may be involved in MPK4-regulated activation of plant defense by coupling the kinase to specific WRKY transcription factors [48]. Due to the expression of ELIP, CTL1, SCA and MKS1 induced by cold treatment exclusively in plantain (not in banana), we believe that plantain possesses the highly superior aspects of photosynthesis, root architecture and plant defense regulated by MPK, which makes plantain broadly resist to abiotic stress resulting in a better cold tolerance. Other DEGs involved in functional regulations In addition to the above four categories, we found some DEGs in banana and plantain are also involved in protein/ RNA modification, cell wall composition and occurrence, transit, nucleosome assembly, cellular redox balance, ironsulfur cluster assembly, protein hydrolysis, oxidation and reduction, copper ion balance, photosynthesis, respiration and sugar stimulus response. But again some of the cold responsive DEGs are found exclusively in plantain, including MTP3 (a 3-fold increase at 6 hr cold stress) involved in copper ion balance, RBCS (a 10-fold decrease at 6 hr) functioning in photosynthesis and respiration in chloroplast, CP122 (an 80-fold decrease at 6 hr) involved in sugar stimulus response in chloroplast, and UBQ11 (a 5fold increase at 6 hr) functioning in protein modification. In yeast, PutMT2 (type 2 metallothionein-like protein in Puccinellia tenuiflora) has been verified to play a critical role in improving tolerance to metal and reactive oxygen species [49]. Thus the up-regulation of MTP3 would allow plantain for improved tolerance to the increased reactive oxygen species (ROS) due to the cold stress [10]. In plant, RBSC encodes the small subunit of Rubisco (Ribulose-1, 5-bisphosphate carboxylase/oxygenase) involved in the first major step of carbon fixation and the RBSC gene family functions to yield sufficient Rubisco content for leaf photosynthetic capacity [50]. As the expression of RBCS was highly repressed in plantain, we speculate that the protection mechanism is activated in response to cold treatment in chloroplast in order to decrease the production of ROS through the weakened photosynthesis. Arabidopsis CP12 forms a complex with GAPDH (Glyceraldehyde-3phosphate dehydrogenase) and PRK(Phosphoribulokinase) in regulating TCA cycle [51]. A dramatic repression of CP122 suggests that plantain must reduce the photosynthesis in response to cold stress. This is consistent with the decreased RBCS but as another pathway for the selfprotection mechanism. UBQ (poly-ubiquitin gene) is involved in protein hydrolysis in the ubiquitin-proteasome pathway. In order to compensate cells for ubiquitin molecules in signal transmission, expression of poly-ubiquitin gene is increased in response to stress [52]. Given the increased expression of UBQ in response to cold treatment, we suspect that UBQ might be involved in stress response in plantain. In summary,a global, comparative transcriptomic profile of banana and plantain in response to cold treatment has been intensively investigated by transcriptome sequencing (0 h, 3 h and 6 h) and quantitative RT-PCR For example, the cold-tolerant ICE1 and MYBS3 pathways were rapidly activated and switched in early (3 h) and late (24 h) stages respectively, of response to cold treatment in plantain. While in cold-sensitive banana, no such equivalent regulation for ICE1-CBF-COR pathway was found and slow response to MYBS3 pathway responsible for the cold stress was observed. Thus, the low expression of the two key genes along with their delayed response to the cold stress may be one of the main reasons for cold sensitivity of banana. The cold-tolerant plantain also appears closely related to expressions of several specific genes such as CML7, AIR12 (for signal transduction), ZFP1, EIL1 (for transcriptional regulation), ELIP, CTL1, SCA, MKS1 (for stress response), MTP3 (for copper ion balance), RBCS (for photosynthesis and photorespiration), CP122 (sugar stimuli response) and UBQ11 (protein modification). Combined with previous research, we rationalize that in early stage of cold stress response, changes in cell membrane phase trigger modification of actin cytoskeleton, which activates ICE1-CBF-COR metabolic pathways by Ca 2+ and phosphorylation signaling pathways. Also it triggers an early response via the ethylene signal transduction pathway. In late stage of cold stress, expression of MYBS3 begins to recover. MYBS3 is involved in coordination with the expression of multiple genes for regulation of oxidation/reduction, oxylipin biosynthetic process, photosynthesis, photorespiration, glycolysis, tricarboxylic acid cycle, carbohydrate metabolic process, fatty acid biosynthetic process and beta-oxidation, enhanced adoption to cold tress (Figure 4). The next questions need to be answered are what causes the observed different expression profiles between ICE1 and MYBS3 pathways in plantain? How do both coordinate together for effectively regulating cold-resistance? Addressing these questions will further enhance the understanding on signaling and metabolic pathways of cold tolerance in plantain, but also conducive to nurturing new varieties of cold tolerant banana cultivars. Plant materials Seedlings of the cold-tolerant plantain (Musa spp. Dajiao; ABB Group) and the cold-sensitive banana (Musa spp. Cavendish; AAA Group) with a uniform growth stage were obtained from Institute of Fruit Tree Research, Guangdong Academy of Agricultural Sciences, Guangzhou, P. R. of China. Experimental design and cold stress treatment The main objective in this study was to compare coldresponse genes between cold-sensitive banana and coldtolerant plantain in order to gain a better understanding of the underlying signal transduction and the molecular mechanisms of cold tolerance plantain at transcriptomics level. Mature plantain plants can tolerate temperatures of 0-4°C. In our previous quantitative proteomics analysis, we found 219 differentially expressed proteins in plantain seedlings with cold stress at 8°C for only 6 hours and the plant leaves drooped with wilting symptoms after 24 h of cold treatment [10]. To identify some sensitive and early cold-response genes in both banana and plantain, in this study we increased the cold-treatment temperature to 10°C and reduced exposure time at 0, 3 and 6 hours respectively. The comparative transcriptomic analysis was conducted for the cold stressed seedlings, followed by large scale identification and functional categorization of the differentially expressed, early responsive genes. Furthermore, quantitative real time-PCR was carried out to validate the early cold-responsive transcriptomic results and some late-responsive genes with the extended time of cold treatment for 24 and 48 hours. Seedlings were grown in a growth chamber at 30/28°C (day/night), a photon flux density of 240 μmol m −2 s −1 throughout a 12-h photoperiod, and a relative humidity of 60-80%. Six-leaf stage seedlings were used in the unstable ICE1 Oxidation reduction, biosynthetic process, Oxidation reduction, Oxylipin biosynthetic process, Photosynthesis, Photorespiration, Glycolysis, Tricarboxylic acid cycle, Carbohydrate metabolic process, Fatty acid biosynthetic process and betaoxidation, et al. [14] and revised based on this study. At the early stage of cold stress, plantain cells probably sense low temperatures through membrane rigidification and/or other cellular changes, which might induce a calcium signature and activate protein kinases necessary for cold tolerance. Constitutively expressed ICE1 is activated by cold stress through sumoylation and phosphorylation. Sumoylation of ICE1 is critical for ICE1-activation of transcription of CBFs and repression of MYB15. CBFs regulate the expression of COR genes that confer cold tolerance. The expression of CBFs is negatively regulated by MYB15. HOS1 mediates the ubiquitination and proteosomal degradation of ICE1 and, thus, negatively regulates CBF regulons. CBFs can constitutively regulate the expression of downstream cold-responsive transcription factor genes RAPs, which might control sub-regulons of the CBF regulon. CBFs also activate αAmy3 expression to hydrolyse reserved starch. At the late stage of cold stress,MYBS3 inhibits CBFs and αAmy3 expression. The effective coordination across the early and late stages of cold stress by at least two different regulatory pathways appears to efficiently regulate the following metabolic pathways including oxidation reduction, oxylipin biosynthetic process, photosynthesis, photorespiration, glycolysis, tricarboxylic acid cycle, carbohydrate metabolic process, fatty acid biosynthetic process and beta-oxidation. The rapid activation and selective induction of ICE1 and MYBS3 cold tolerance pathways in plantain, along with expression of other cold-specific genes, may be one of the main reasons that plantain has higher cold resistance than banana (Heatmaps show the expression of ICE1 and MYBS3 in banana and plantain under cold stress). Broken arrows indicate post-translational regulation; solid arrows indicate activation, whereas lines ending with a bar show negative regulation; the two stars (**) indicate unknown cis-elements. P, phosphorylation; S, SUMO; U, ubiquitin. experiment. Low temperature treatments were started at 12:00 AM on the first day by setting the temperature to 10°C, which was reached about 30 min later. The first young leaf was detached from the top of each of the 5 plants at each time point (10°C for 0, 3 and 6 h) for each biological replicate. The leaves from the 5 plants were cut into pieces (1.5 × 1.5 cm) and mixed well. Aliquots of the mixed tissues were frozen in liquid N 2 and stored at −80°C until use. Measurements of relative electrolyte leakage The leaves were cut into 1-cm segments and washed three times with ultrapure water. The segments were placed in tubes containing 5 mL of ultrapure water and incubated at 25°C. Two hours later, the electrical conductivity of the bathing solution (L1) was measured. Then the tubes were incubated at 100°C for 20 min and subsequently at 25°C for 1 h, and the electrical conductivity (L2) was measured again. The relative electrolyte leakage was calculated by the formula (L1-L0)/(L2-L0) × 100 (L0, conductivity of ultrapure water) [53]. Five replicates were performed for each sample. Sample preparation, cDNA library construction and illumina sequencing Total RNA was extracted from banana and plantain leaves (Four biological replicates of Cavendish and Dajiao seedlings at 10°C for 0, 3 and 6 h) using plant total RNA isolation kit (Tiandz Inc; Beijing, China). RNA degradation and contamination was monitored on 1% agarose gels; RNA purity was checked using the NanoPhotometer® spectrophotometer (IMPLEN, CA, USA) and RNA integrity was assessed using the Bioanalyzer 2100 system (Agilent Technologies, CA, USA). A total of 3 μg RNA per sample was used as input material in RNA sample preparations for subsequent cDNA library construction. All 24 samples had RIN values above 8.0. Sequencing libraries were generated using Illumina TruSeq™ RNA Sample Preparation Kit (Illumina, San Diego, USA) following manufacturer's recommendations and four index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in Illumina proprietary fragmentation buffer. First strand cDNA was synthesized using random oligonucleotides and SuperScript II. Second strand cDNA synthesis was subsequently performed using DNA Polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/ polymerase activities and enzymes were removed. After adenylation of 3′ ends of DNA fragments, Illumina PE adapter oligonucleotides were ligated to prepare for hybridization. In order to select cDNA fragments of preferentially 200 bp in length the library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). DNA fragments with ligated adaptor molecules on both ends were selectively enriched using Illumina PCR Primer Cocktail in a 10 cycle PCR reaction. Products were purified (AMPure XP system) and quantified using the Agilent high sensitivity DNA assay on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumina) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq 2000 platform and 100 bp fragment reads were generated. The data was submitted into the NCBI SRA database (Accession No. SRP047347). Sequence annotation Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing ploy-N, and low quality reads from raw data. At the same time, Q20, Q30, GC content and sequence duplication level of the clean data were calculated. All the downstream analyses were based on the clean data with high quality. Reference genome and gene model annotation files were downloaded from the banana genome website (http://banana-genome.cirad. fr/content/download-dh-pahang) directly. Index of the reference genome was built using Bowtie v0.12.8 and pairedend clean reads were aligned to the reference genome using TopHat v1.4.0. HTSeq v0.5.3 was used to count the reads numbers mapped to each gene. And then RPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. Identification of Differentially Expressed Genes (DEGs) Differential expression analysis was performed using the DEGSeq R package (1.12.0). P-values were adjusted using the Benjamini & Hochberg method. Corrected P-value of 0.05 and log2 (fold change) of 1 were set as the threshold for significantly differential expression. Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the GOseq R package, in which gene length bias was corrected. GO terms with corrected P-value less than 0.05 were considered significantly enriched by differential expressed genes. Quantitative RT-PCR Total RNA was isolated from banana and plantain leaves in four biological replicates at five different time points as described above. The resulting RNA (1 μg) was used as a template for first-strand cDNA synthesis using ReverTra Ace (Toyobo, Osaka, Japan) with random hexamers according to the manufacturer's instructions. Primer pairs for real-time quantitative PCR (see Additional file 5: Table S5 online) were designed using Primer Premier 5.0 (Premier Biosoft, Palo Alto, USA). The PCR reaction consisted of 10 μL of 2 × SYBR Green PCR Master Mix (Toyobo), 200 nM primers, and 2 μL of 1:40diluted template cDNA in a total volume of 20 μL. No template controls were also set for each primer pair. Realtime PCR was performed employing the DNA Engine Option 2 Real-Time PCR Detection system and Opticon Monitor software (Bio-Rad, USA).

v3-fos

2019-08-18T07:39:48.170Z

2015-01-01T00:00:00.000Z

212468097

s2

Effects of flavonol-rich green tea (Camellia sinensis L. cv. Sofu) on blood glucose and insulin levels in diabetic mice Findings from epidemiological studies and intervention trials seem to suggest that green tea consumption prevents type 2 diabetes. The anti-diabetic effects are most commonly attributed to the polyphenolic fraction of green tea. Green teas contain catechins; however, they also contain flavonols and their glycosides. Here, we compared between a common and a flavonol-rich tea cultivar, with regard to the anti-diabetic effects, in a type 2 diabetes mouse model using NSY (Nagoya-ShibataYasuda) mice. Water or a tea infusion, made from a common (control tea, TeaC) or a flavonol-rich (flavonol-rich tea, TeaF) cultivar, was given to the NSY mice as the solo drinking fluid from 4 until 13 weeks of age. At 12 weeks of age, fasting plasma insulin concentration was significantly lower in mice drinking TeaF than in mice drinking water. Relative to water, TeaC had no significant effect on plasma insulin levels. Thus, there were significant differences in efficacy with regard to maintenance of glucose homeostasis between a common and a flavonol-rich tea cultivars; therefore, tea flavonols are likely to have benefits with regard to preventing diabetes. Introduction Diabetes is serious public health issue, and its related conditions pose a growing and potentially enormous economic burden. Although effective surgical and pharmacological methods have been developed to treat symptoms related to diabetes, these treatments can be costly and are not without potential adverse effects [1][2][3][4]. The development of dietary agents for the prevention of diabetes could represent a cost-effective and safe approach to the public health problem. Epidemiological findings have indicated that green tea consumption may prevents type 2 diabetes, non-insulin dependent diabetes mellitus 5,6], and mounting evidence shows that green tea consumption improves glucose metabolism in human [7] and diabetic mice [8]. Green tea contains characteristic polyphenolic compounds, catechins which are thought to be primarily responsible for the physiological effects of green tea [9]. However, flavonols and their glycosides are also present in tea [10], and quercetin, one of the major tea flavonols, also has anti-diabetic effects in mouse models of diabetes [11][12][13]. We previously measured flavonol glycoside concentrations in tea infusions from various cultivars and identified cultivars with high flavonol contents [14]. Here, we compared the anti-diabetic effects between a common tea cultivar and a flavonol-rich cultivar to examine whether tea flavonols can ameliorate glucose intolerance in a mouse model of type 2 diabetes. Previously, NSY (Nagoya-Shibata-Yasuda) mice were generated by selective ICR mouse colony to establish a mouse model of type 2 diabetes [15]; these mice spontaneously develop renal lesions similar to diabetic nephropathy, but do not become severe obesity at any age of development [16]. These characteristics are similar to the pathophysiologic features of human type 2 diabetes patients; therefore, NSY mice were used as a model of type 2 diabetes in the present study. Materials and methods NSY mice (4-week-old, male) were purchased from Hoshino Lab Animals Co. (Ibaraki, Japan). The mice were given a standard laboratory diet (CRF-1, Charles River Laboratories Inc. Wilmington, MA) in an environmentally controlled room (24°C, 60% relative humidity, a 12-h light/dark cycle).This study was approved by the Ethical Committee on Animal Experiments at the NARO Institute of Vegetable and Tea Science (No.H26-01), and all animal experiments were performed by following Law no. 105 and Notification no. 6 of the government of Japan. 'Sofu' green tea leaves (Flavonol-rich Tea: TeaF) were obtained from the NARO plantation in Makurazaki, Kagoshima, Japan, and control 'Yabukita' tea leaves (Control Tea: TeaC) were obtained from the NARO plantation in Kanaya, Shizuoka, Japan. The dried green tea leaves of each cultivars were steeped separately in cold water for one hour; aliquots of the filtrates were frozen until used in experiments. The stock solutions were diluted with water just before being given to mice and fresh drinking fluid was provided to all mice every two days. LC/MS was used to measure flavonol glycoside levels in the diluted tea infusions as described previously [14]. HPLC was used to measure catechin and caffeine levels as described previously [17]. Results and discussion Using protocols from our previous study [14], we determined the concentrations of two myricetin, five quercetin and three kaempferol glycosides in each type of tea infusion (Table 1). Among the measured quercetin glycosides, quercetin-3-O-glucosyl-rhamnosyl-glucoside was the most abundant in both tea infusions, TeaC and TeaF, as was the case in the previous study [14]. The level of quercetin-3-O-glucosylrhamnosyl-glucoside was notably higher in TeaF than in TeaC. Total aglycone content was also higher in TeaF than in TeaC for all of the aglycones measured. As shown in Table 2, while there were minor variations in the composition of catechins between TeaC and TeaF, the total amounts of catechins and caffeine in TeaF were similar to those in TeaC. Daily intakes of total flavonolaglycones in TeaC and TeaF groups were approximately700 and 1500 μg, respectively. For both tea infusion groups, daily intake of total catechins and caffeine were approximately 7.0 mg and 1.3 mg, respectively. There were no significant differences among all groups with regard to body weight or food intake throughout the experiment (Table 3). Thus, relative to water, neither TeaC nor TeaF significantly affected body weight gain or food intake of NSY mice. The results of GTTs are shown in Figure 1. In the Water group, insulin response to glucose at 12 weeks of age ( Figure 1B and 1D) was impaired relative to that at 8 weeks of age ( Figure 1A and 1C). The result is consistent with previous findings that showed NSY mice spontaneously develop diabetes in an To investigate whether either tea infusion could affect glucose intolerance, TeaCand TeaF were given to NSY mice as the solo drinking fluid (TeaC and TeaF groups, respectively) for 8 weeks. Control NSY mice were given water (Water group) instead of tea infusions. Body weight and food consumption were measured once and twice a week, respectively. Glucose tolerance tests (GTTs) were performed by intraperitoneally injecting glucose (2 g/kg body weight) into mice that had fasted overnight and had been drinking the experimental fluids for 4 or 8 weeks; these animals were 8 or 12 weeks of age, respectively. Blood samples were obtained from the tail vein at 0, 30, 60, 120 and 240 min after the glucose injection. Blood glucose concentration was measured using a Glucose Pilot system (Iwai Chemical Co., Tokyo, Japan). For measurement of insulin, whole blood was collected from the tail vein at 0 and 30min during i.p. GTT. Each blood sample was immediately centrifuged (3,000 xg, 5min, 4°C) to separate the plasma. Libs Mouse Insulin ELISA Kits (Shibayagi Co., Ltd., Gunma, Japan) were used according to the manufacturer's protocol to measure plasma insulin levels. At the end of the experiment, the mice were 13 weeks of age; they fasted overnight and were then anesthetized with isoflurane. A blood sample was collected into a heparinized tube from the infraaxillary artery of each anesthetized mouse. The pancreas, liver, and epididymal fat pads were quickly removed from each animal and weighed. Triglyceride Test Wako kits (Wako Pure Chemical Industries, Ltd., Osaka, Japan) were used to measure plasma triglyceride levels enzymatically. All data obtained are expressed as the mean ± SEM. One-way factorial analysis of variance (ANOVA) and subsequent Scheffe's post-hoc test were used to compare means among groups. When data were not normally distributed, the Kruskal-Wallis test was applied. Differences with a p value less than 0.05 were considered significant. Notably, to determine the significance of the effects of tea infusions on the blood glucose and insulin levels (Figure 1), repeated measures ANOVA was performed, and then, if statistical significance was detected by this analysis, further statistical comparisons among the groups were conducted for each measurement time by one-way ANOVA and subsequent Scheffe's tests. Control Tea (TeaC) was made from a common tea cultivar, and Flavonol-rich Tea (TeaF) was made from a flavonol-rich tea cultivar. Total aglycone content was calculated from the concentrations of the corresponding glycosides. n.d.: not detected. age-dependent manner [16,18]. At 12 weeks of age, although glycemic excursions during the GTT were not significantly different among groups ( Figure 1B), fasting plasma insulin concentration of the TeaF group was significantly lower than that of the Water group ( Figure 1D). Fasting plasma insulin concentration of the TeaC group did not differ significantly from that of the Water group ( Figure 1D). These result indicated that consumption of TeaF, but not TeaC, could improve the impaired insulin response in the NSY mice. At the end of the experimental period, with the mice at 13 weeks of age and in a fasting state, there were no significant differences among the groups with regard to body weight, pancreatic weight, or liver weight (Table 4). However, epididymal fat pad weights were significantly less in the TeaF group than in the Water group. Mean fat pad weights in the TeaC group were also less than those in the Water group, however this difference was not significant (p<0.1).The previous studies found mild obesity in the NSY mice [16,18], and mean fat pad mass of the Water group was greater than that of age-matched outbred ICR mice (484.1 ± 60.6 mg, n=4, unpublished data), from which the NSY mice were selectively bred for glucose intolerance. Therefore, these tea infusions, especially TeaF, are thought to suppress the fat accumulation in NSY mice. Numerous studies demonstrate that green tea and its extracts have anti-obesity effects in mouse models of diabetes [8,19]. For each of the three treatment groups of the NSY mice, fasting plasma triglyceride levels were distinctly higher than those of the agematched ICR mice (85.5 ± 9.0 mg/dl, n=4, unpublished data) ( Table 4). However, for NSY mice, there were no significant differences in the triglyceride levels among the three treatment groups (Water, TeaC, and TeaF); suggesting that TeaC and TeaF did not affect plasma triglyceride levels in NSY mice. In the present study, we found that there were significant differences between a common and a flavonol-rich tea cultivars with regard to glucose homeostasis in NSY mice, and that tea flavonols are likely to have benefits for preventing diabetes. Further studies on tea flavonols and diabetes are warranted; such as those designed to obtain direct evidence of higher plasma levels of flavonols and their derivatives following consumption of flavonol-rich teas and examining the mechanisms in which flavonols improve insulin sensitivity in type 2 diabetic mouse models. All values are mean ± SEM (n=4 or 5). There were no significant between-group differences in the body weight or food intake throughout the experiment. At 13 weeks of age, animals were denied food overnight and then subject to these assays in a fasting state. All values are mean ± SEM (n=4 or 5). *p<0.05; significantly different from the Water group, determined by one-way ANOVA, followed by Scheffé's test. Copyright: ©2015 Nomura S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

v3-fos

2019-03-31T13:48:11.478Z

2015-09-01T00:00:00.000Z

88009977

s2

Evaluating Grafted Watermelon for Verticillium Wilt Severity, Yield, and Fruit Quality in Washington State Verticillium wilt caused by Verticillium dahliae is a serious disease for watermelon growers in Washington State. Grafting represents a possible alternative disease management strategy, but little is known about rootstock resistance to verticilliumwilt or the performance of grafted watermelon in the different production regions of the state. In this study, verticilliumwilt severity, yield, and fruit quality were evaluated at three contrasting field sites in Washington using verticillium wilt-susceptible ‘Sugar Baby’ (diploid) watermelon grafted onto four commercial rootstock cultivars (Marvel, Rampart, Tetsukabuto, and Titan); nongrafted ‘Sugar Baby’ was included as the control. Verticillium dahliae soil densities varied at each site (<1.0, 5.7, and 18.0 colony-forming units (cfu)/g soil at Othello, Eltopia, and Mount Vernon, respectively). Area under disease progress curve (AUDPC) values differed significantly among treatments at Eltopia and Mount Vernon. Nongrafted ‘Sugar Baby’ had the highest AUDPC value at all three sites, while ‘Sugar Baby’ grafted onto ‘Tetsukabuto’ had the lowest AUDPC value at Eltopia and Mount Vernon. Nongrafted ‘Sugar Baby’ also had the lowest fruit weight per plant at all sites, but ‘Sugar Baby’ grafted onto ‘Tetsukabuto’ had the highest fruit weight per plant at Eltopia and Mount Vernon. Marketable fruit weight per plant did not differ among treatments at Othello. Yield was negatively correlated with AUDPC values at both Eltopia and Mount Vernon. Fruit number per plant was only significantly impacted at Eltopia, where ‘Sugar Baby’ grafted onto ‘Tetsukabuto’ had more fruit per plant than all other treatments except ‘Sugar Baby’ grafted onto ‘Rampart’. Fruit quality (flesh firmness, total soluble solids, and lycopene content) was unaffected by grafting at either Othello or Eltopia, except for increased flesh firmness for ‘Sugar Baby’ grafted onto ‘Marvel’ and ‘Titan’ as compared with nongrafted ‘Sugar Baby’ at Eltopia. At season’s end, plants were sampled from all treatments at Eltopia and Mount Vernon and assayed for V. dahliae. Microsclerotia typical of this organism were observed in all samples. Results from this study indicate that verticillium wilt of watermelon can be successfully managed by grafting when the V. dahliae soil density exceeds 5.0 cfu/g in Washington. In addition, grafting does not reduce fruit quality and using certain rootstocks can improve the quality of flesh firmness at certain locations. Verticillium wilt caused by the soilborne fungus V. dahliae is a significant disease affecting watermelon (Citrullus lanatus) production in Washington State (Dung and Weiland, 2014; Sunseri and Johnson, 2001). Once established in the field, V. dahliae is extremely difficult to manage due to its wide host range and longlived resting structures called microsclerotia (Berlanger and Powelson, 2000; Tjamos, 1989). Microsclerotia in the soil germinate and invade the roots of host plants. The pathogen ultimately colonizes the xylem of its host, thereby disrupting the transpiration stream and leading to the characteristic symptoms of chlorosis, necrosis, and wilting (Fradin and Thomma, 2006; Klosterman et al., 2009). Traditionally, preplant soil fumigation has been used to manage V. dahliae; however, currently available fumigants (e.g., metam sodium) are not always reliable (Davis et al., 2008b; Klosterman et al., 2009; Woodward et al., 2011). Thus, alternative strategies are needed to achieve successful management of this pathogen. Many researchers have demonstrated that grafting can reduce soilborne disease severity of watermelon (King et al., 2008; Louws et al., 2010). While fusarium wilt (caused by Fusarium oxysporum) has been the primary focus of watermelon grafting research, some studies have explored the potential of grafting to control verticillium wilt. Paplomatas et al. (2000) screened 33 cucurbit rootstocks for verticillium wilt resistance and found many to be tolerant, although none were completely resistant. A comparable study conducted by Wimer et al. (2014) generated similar results. Paplomatas et al. (2002) showed that grafting watermelon onto disease-tolerant rootstocks could delay symptom onset by nearly 3 weeks, thus allowing sufficient time for crop maturation. Paroussi et al. (2007) observed decreased verticillium wilt incidence on grafted watermelon plants grown in artificially inoculated soil, and Buller et al. (2013) observed reduced verticillium wilt severity of grafted watermelon plants at a naturally infested field site with a relatively high V. dahliae soil density. While these results appear promising, growers in Washington are unlikely to adopt grafting as a verticillium wilt management strategy until its efficacy has been more thoroughly demonstrated. The conflicting reports in the literature regarding the effects of grafting on watermelon fruit flavor, yield, and quality also present a barrier to the adoption of this practice. Davis et al. (2008b) reported that sometimes an ‘‘insipid flavor’’ is associated with grafted watermelon; however, this may be due to harvesting fruit prematurely, as grafting can sometimes delay maturity. Buller et al. (2013), Bekhradi et al. (2011), and Miguel et al. (2004) reported no significant changes in total soluble solids (TSS), lycopene content, fruit firmness, fruit diameter, or fruit weight as a result of grafting, while Turhan et al. (2012) and Lopez-Galarza et al. (2004) observed a decrease in TSS as a result of grafting. In contrast, many researchers have observed positive effects on fruit yield and quality as a result of grafting, including increased lycopene content, flesh firmness, and fruit weight (Lee et al., 2010; Proietti et al., 2008; Salam et al., 2002; Taylor et al., 2006). Two primary factors that account for the variable effects of grafting on fruit yield and quality are rootstock species/cultivar and environmental conditions (Davis et al., 2008a). For instance, Yetis xir et al. (2003) observed decreased yield when certain Cucurbita rootstocks were used, while Bruton et al. (2009) found that flesh firmness was significantly increased by the use of interspecific hybrid squash rootstocks but not bottle gourd rootstocks. Petropoulos et al. (2012) found that TSS was significantly impacted by rootstock–scion combinations. Louws et al. (2010) reported that diseaseresistant rootstocks can sometimes decrease yield when certain pathogens are not present, highlighting the need for thorough identification and quantification of pathogen populations in the soil. Of the factors that influence the performance of grafted watermelon, rootstock Received for publication 14 May 2015. Accepted for publication 13 July 2015. Corresponding author. E-mail: [email protected]. 1332 HORTSCIENCE VOL. 50(9) SEPTEMBER 2015 cultivar/species is perhaps the easiest for the grower to manipulate. There are currently many available watermelon rootstock cultivars on the market; thus, special regard must be taken to select ones that are not only suitable for regional growing environments (including climate and pathogen density), but that also provide sufficient disease management without negatively impacting fruit yield or quality. As of yet, grafted watermelon plants have not been thoroughly evaluated across Washington’s diverse growing regions. Thus, the objective of this study was to determine the effects (if any) of various rootstock cultivars on verticillium wilt severity, yield, and fruit quality of grafted watermelon plants at three differing locations in Washington State. Materials and Methods Experimental conditions. This study was conducted at three contrasting locations in Washington State during the 2014 field season (Table 1). Two of the field sites were located on commercial watermelon farms in the Columbia Basin of eastern Washington near Eltopia and Othello, where the summer climate is hot and dry. The third site was located in the Skagit Valley at Washington State University (WSU) Mount Vernon, where the summers are cooler and more humid. At each site, at transplanting, 20 soil samples were taken randomly within the experimental plots to a depth of 15 cm, and the V. dahliae soil density was determined using a technique modified from Butterfield and DeVay (1977). Plant material, plot establishment, and field maintenance. There were five treatments included in this study: nongrafted verticillium wilt-susceptible ‘Sugar Baby’ watermelon (C. lanatus; diploid) and ‘Sugar Baby’ grafted onto the commercial rootstocks ‘Marvel’ (Cucurbita moschata), ‘Rampart’ (Lagenaria siceraria), ‘Tetsukabuto’ (Cucurbita maxima · C. moschata), and ‘Titan’ (Cucurbita hybrid). All plant material was propagated from seed at WSU Mount Vernon. The target transplanting date for Eltopia and Othello was 10 May; thus, ‘Sugar Baby’ was sown on 26 Mar., followed by ‘Rampart’ on 31 Mar., and ‘Marvel’, ‘Tetsukabuto’, and ‘Titan’ on 4 Apr. Grafting occurred on 12 Apr. using the one-cotyledon splice technique when both scion and rootstock plants were at the early true first leaf stage. The grafted seedlings were then placed in a healing chamber to facilitate graft union formation (Miles et al., 2013). All transplants were transported to their respective field sites on 6 May for acclimation, when plants reached the 2–3 true-leaf growth stage. Transplanting into plastic-covered raised beds (0.9 m in-row spacing) occurred on 8 and 13 May at Othello and Eltopia, respectively. At Othello, beds were 2.3 m center-tocenter, while at Eltopia bed spacing was 1.4 m center-to-center. At both sites, water was applied via drip irrigation at a rate of 50 mm per week throughout the growing season. The target transplanting date for Mount Vernon was 15 June; thus, ‘Sugar Baby’ was sown on 13 May, followed by ‘Rampart’ on 19 May, and ‘Marvel’, ‘Tetsukabuto’, and ‘Titan’ on 23 May. Grafting occurred on 2 June using the hole-insertion technique (because of a large size difference between the rootstocks and scion) when both scion and rootstock plants were at the early first true leaf stage (Miles et al., 2013). The grafted seedlings were then placed in a healing chamber to facilitate graft union formation following the procedures used above. Transplanting into plastic-covered raised beds (0.9 m in-row spacing, 3 m center-tocenter) occurred on 19 June, when plants were at the 2–3 true-leaf stage. Drip irrigation was applied at a rate of 25 mm of water through July and every 3 weeks thereafter for the remainder of the growing season. Field sites were not fumigated, and no other pesticides were applied to the plot areas. Verticillium wilt ratings.Verticillium wilt severity was rated visually at all sites and was recorded as the percent of the plot canopy displaying characteristic symptoms (chlorosis, necrosis, and wilting) (Dung and Johnson, 2012). These ratings were initiated at symptom onset and recorded at Othello on 49, 61, 69, and 76 d after transplanting (DAT), at Eltopia on 44, 56, 64, and 71 DAT, and at Mount Vernon on 42, 49, 56, 63, and 70 DAT. The disease severities (percentages) were plotted over time and the AUDPC value was calculated for each treatment at each site. At season’s end the most severely wilted plant from each plot at Eltopia (26 Aug.) andMount Vernon (18 Sept.) was assayed for Verticillium spp., while plants were not sampled at Othello due to early removal of the crop by the farmer. Plants were cut at the soil line and then cut again to attain a 20 cm stem sample that included the graft union. Samples were surface sterilized using a 10%bleach solution and rinsed with deionized (DI) water. Each sample was then cut in half longitudinally to expose the vascular tissue and incubated in a plastic container. After 4 weeks, the samples were examined for the presence of microsclerotia using a dissecting microscope (·40). Measuring fruit yield and quality. At Othello and Eltopia, fruit were harvested as they ripened, which was determined by the complete drying and browning of the tendril nearest the fruit. Fruit were harvested at Othello on 69, 76, 82, and 89 DAT and at Eltopia on 64, 71, 77, and 84 DAT. The number of marketable fruit and weight of marketable fruit per plant were recorded for each plot at both sites. Fruit were determined unmarketable if they had excessive insect damage, disease, scarring, or if the fruit was misshapen. Fruit did not reach maturity at Mount Vernon due to the cool, short growing season and late transplanting date; however, at season’s end (85 DAT) all nearly mature fruit (>2 kg) were harvested and the number and weight of these fruit per plant were recorded. For each harvest date at Othello and Eltopia, three marketable fruit were arbitrarily selected from each plot for fruit quality testing, and data for each treatment were pooled for all harvest dates. These fruit were cut in half along the longitudinal axis and a 5-cm samplewas taken just off center near the blossom end. Flesh firmness (newton, or N) was measured to a depth of 1 cm using a drillpress penetrometer (Ametek, Berwyn, PA) fixed with a 4 mm cylindrical blunt-end tip. The three firmness measurements for each plot were averaged, resulting in three data points for each treatment at each site for each harvest date. The TSS of the juice was measured using a Palm Abbe refractometer (MISCO, Cleveland, OH). After the instrument was calibrated with DI water, 1 ml of juice from each fruit sample was placed on the measuring surface. Following the reading, the instrument was cleaned with DI water before the next sample was loaded. As with firmness, the three TSS readings for each plot were averaged. Lycopene content was determined using a spectrophotometer protocol modified from Nagata & Yamashita (1992). For each plot, sections of flesh measuring 3 cm were removed from each of the three fruit, Table 1. Location, environmental conditions, and cropping history at the study sites near Othello, Eltopia, and Mount Vernon, WA, in 2014. Othello Eltopia Mount Vernon Latitude 46 52#32.21$ N 46 29#23.41## N 48 26#23.09## N Longitude 119 28#29.62$ W 119 11#10.54## W 122 23#44.04## W Elevation (m) 316 260 6 Avg temp ( C) 20 21 18 Avg min temp ( C) 13 12 12 Avg max temp ( C) 28 30 24 Avg RH (%) 53 56 82 Total precipitation (mm) 24 8 104 V. dahliae density <1.0 5.7 18.0 Soil type Ephrata fine sandy loam Tauncal very fine sandy loam Skagit silt loam Cropping history Alfalfa Melons Mixed cucurbits Weather data were obtained via Washington State University AgWeatherNet stations (Washington State University, 2014) located near the field sites. Verticillium dahliae soil density was measured in colony-forming units per gram of soil. Soil types were determined using the University of California’s SoilWeb: online soil survey browser (2010). 29 Apr. 2014. <http://calsoilresource.lawr.ucdavis.edu/>. Crop that was planted in the preceding year in the same field as the study. HORTSCIENCE VOL. 50(9) SEPTEMBER 2015 1333 combined to make one composite sample, and frozen at –20 C. Frozen samples were homogenized using a mortar and pestle. A 1-g subsample was taken from each homogenized sample and placed in 16mL of a chilled acetone:hexane (2:3) mixture. The supernatant from each sample was extracted and placed in a cuvette. The cuvettes were loaded into a Beckman DU-65 spectrophotometer (Beckman Coulter, Inc., Brea, CA) and absorbance readings were taken at 453, 505, 645, and 663 nm. Experimental design and statistical analysis. The experiment at each site was arranged as a randomized complete block design with three replications and six plants per plot. Data were analyzed using PROC GLM in SAS (version 9.2; SAS Institute, Cary, NC) with a = 0.05, and a correlation analysis for yield and AUDPC at each site was conducted using PROC CORR. The AUDPC data from all sites, and fruit weight and fruit number data from Mount Vernon required transformation for statistical analysis. Using the rangemethod outlined by Kirk (1982), the rank transformation was deemed most appropriate in all cases. Datawere ranked using PROCRANK in SAS. Due to differences in planting dates, soil types, climate, V. dahliae soil densities, and cultural practices, all sites were analyzed separately. Significant differences between treatment means were compared using Fisher’s least significant difference test with a = 0.05. Verticillium wilt caused by the soilborne fungus V. dahliae is a significant disease affecting watermelon (Citrullus lanatus) production in Washington State (Dung and Weiland, 2014;Sunseri and Johnson, 2001). Once established in the field, V. dahliae is extremely difficult to manage due to its wide host range and longlived resting structures called microsclerotia (Berlanger and Powelson, 2000;Tjamos, 1989). Microsclerotia in the soil germinate and invade the roots of host plants. The pathogen ultimately colonizes the xylem of its host, thereby disrupting the transpiration stream and leading to the characteristic symptoms of chlorosis, necrosis, and wilting (Fradin and Thomma, 2006;Klosterman et al., 2009). Traditionally, preplant soil fumigation has been used to manage V. dahliae; however, currently available fumigants (e.g., metam sodium) are not always reliable (Davis et al., 2008b;Klosterman et al., 2009;Woodward et al., 2011). Thus, alternative strategies are needed to achieve successful management of this pathogen. Many researchers have demonstrated that grafting can reduce soilborne disease severity of watermelon (King et al., 2008;Louws et al., 2010). While fusarium wilt (caused by Fusarium oxysporum) has been the primary focus of watermelon grafting research, some studies have explored the potential of grafting to control verticillium wilt. Paplomatas et al. (2000) screened 33 cucurbit rootstocks for verticillium wilt resistance and found many to be tolerant, although none were completely resistant. A comparable study conducted by Wimer et al. (2014) generated similar results. Paplomatas et al. (2002) showed that grafting watermelon onto disease-tolerant rootstocks could delay symptom onset by nearly 3 weeks, thus allowing sufficient time for crop maturation. Paroussi et al. (2007) observed decreased verticillium wilt incidence on grafted watermelon plants grown in artificially inoculated soil, and Buller et al. (2013) observed reduced verticillium wilt severity of grafted watermelon plants at a naturally infested field site with a relatively high V. dahliae soil density. While these results appear promising, growers in Washington are unlikely to adopt grafting as a verticillium wilt management strategy until its efficacy has been more thoroughly demonstrated. The conflicting reports in the literature regarding the effects of grafting on watermelon fruit flavor, yield, and quality also present a barrier to the adoption of this practice. Davis et al. (2008b) reported that sometimes an ''insipid flavor'' is associated with grafted watermelon; however, this may be due to harvesting fruit prematurely, as grafting can sometimes delay maturity. Buller et al. (2013), Bekhradi et al. (2011), andMiguel et al. (2004) reported no significant changes in total soluble solids (TSS), lycopene content, fruit firmness, fruit diameter, or fruit weight as a result of grafting, while Turhan et al. (2012) and Lopez-Galarza et al. (2004) observed a decrease in TSS as a result of grafting. In contrast, many researchers have observed positive effects on fruit yield and quality as a result of grafting, including increased lycopene content, flesh firmness, and fruit weight (Lee et al., 2010;Proietti et al., 2008;Salam et al., 2002;Taylor et al., 2006). Two primary factors that account for the variable effects of grafting on fruit yield and quality are rootstock species/cultivar and environmental conditions (Davis et al., 2008a). For instance, Yetis xir et al. (2003) observed decreased yield when certain Cucurbita rootstocks were used, while Bruton et al. (2009) found that flesh firmness was significantly increased by the use of interspecific hybrid squash rootstocks but not bottle gourd rootstocks. Petropoulos et al. (2012) found that TSS was significantly impacted by rootstock-scion combinations. Louws et al. (2010) reported that diseaseresistant rootstocks can sometimes decrease yield when certain pathogens are not present, highlighting the need for thorough identification and quantification of pathogen populations in the soil. Of the factors that influence the performance of grafted watermelon, rootstock cultivar/species is perhaps the easiest for the grower to manipulate. There are currently many available watermelon rootstock cultivars on the market; thus, special regard must be taken to select ones that are not only suitable for regional growing environments (including climate and pathogen density), but that also provide sufficient disease management without negatively impacting fruit yield or quality. As of yet, grafted watermelon plants have not been thoroughly evaluated across Washington's diverse growing regions. Thus, the objective of this study was to determine the effects (if any) of various rootstock cultivars on verticillium wilt severity, yield, and fruit quality of grafted watermelon plants at three differing locations in Washington State. Materials and Methods Experimental conditions. This study was conducted at three contrasting locations in Washington State during the 2014 field season ( Table 1). Two of the field sites were located on commercial watermelon farms in the Columbia Basin of eastern Washington near Eltopia and Othello, where the summer climate is hot and dry. The third site was located in the Skagit Valley at Washington State University (WSU) Mount Vernon, where the summers are cooler and more humid. At each site, at transplanting, 20 soil samples were taken randomly within the experimental plots to a depth of 15 cm, and the V. dahliae soil density was determined using a technique modified from Butterfield and DeVay (1977). Plant material, plot establishment, and field maintenance. There were five treatments included in this study: nongrafted verticillium wilt-susceptible 'Sugar Baby' watermelon (C. lanatus; diploid) and 'Sugar Baby' grafted onto the commercial rootstocks 'Marvel' (Cucurbita moschata), 'Rampart' (Lagenaria siceraria), 'Tetsukabuto' (Cucurbita maxima · C. moschata), and 'Titan' (Cucurbita hybrid). All plant material was propagated from seed at WSU Mount Vernon. The target transplanting date for Eltopia and Othello was 10 May; thus, 'Sugar Baby' was sown on 26 Mar., followed by 'Rampart' on 31 Mar., and 'Marvel', 'Tetsukabuto', and 'Titan' on 4 Apr. Grafting occurred on 12 Apr. using the one-cotyledon splice technique when both scion and rootstock plants were at the early true first leaf stage. The grafted seedlings were then placed in a healing chamber to facilitate graft union formation . All transplants were transported to their respective field sites on 6 May for acclimation, when plants reached the 2-3 true-leaf growth stage. Transplanting into plastic-covered raised beds (0.9 m in-row spacing) occurred on 8 and 13 May at Othello and Eltopia, respectively. At Othello, beds were 2.3 m center-tocenter, while at Eltopia bed spacing was 1.4 m center-to-center. At both sites, water was applied via drip irrigation at a rate of 50 mm per week throughout the growing season. The target transplanting date for Mount Vernon was 15 June; thus, 'Sugar Baby' was sown on 13 May, followed by 'Rampart' on 19 May, and 'Marvel', 'Tetsukabuto', and 'Titan' on 23 May. Grafting occurred on 2 June using the hole-insertion technique (because of a large size difference between the rootstocks and scion) when both scion and rootstock plants were at the early first true leaf stage . The grafted seedlings were then placed in a healing chamber to facilitate graft union formation following the procedures used above. Transplanting into plastic-covered raised beds (0.9 m in-row spacing, 3 m center-tocenter) occurred on 19 June, when plants were at the 2-3 true-leaf stage. Drip irrigation was applied at a rate of 25 mm of water through July and every 3 weeks thereafter for the remainder of the growing season. Field sites were not fumigated, and no other pesticides were applied to the plot areas. Verticillium wilt ratings. Verticillium wilt severity was rated visually at all sites and was recorded as the percent of the plot canopy displaying characteristic symptoms (chlorosis, necrosis, and wilting) (Dung and Johnson, 2012). These ratings were initiated at symptom onset and recorded at Othello on 49, 61, 69, and 76 d after transplanting (DAT), at Eltopia on 44, 56, 64, and 71 DAT, and at Mount Vernon on 42, 49, 56, 63, and 70 DAT. The disease severities (percentages) were plotted over time and the AUDPC value was calculated for each treatment at each site. At season's end the most severely wilted plant from each plot at Eltopia (26 Aug.) and Mount Vernon (18 Sept.) was assayed for Verticillium spp., while plants were not sampled at Othello due to early removal of the crop by the farmer. Plants were cut at the soil line and then cut again to attain a 20 cm stem sample that included the graft union. Samples were surface sterilized using a 10% bleach solution and rinsed with deionized (DI) water. Each sample was then cut in half longitudinally to expose the vascular tissue and incubated in a plastic container. After 4 weeks, the samples were examined for the presence of microsclerotia using a dissecting microscope (·40). Measuring fruit yield and quality. At Othello and Eltopia, fruit were harvested as they ripened, which was determined by the complete drying and browning of the tendril nearest the fruit. Fruit were harvested at Othello on 69, 76, 82, and 89 DAT and at Eltopia on 64, 71, 77, and 84 DAT. The number of marketable fruit and weight of marketable fruit per plant were recorded for each plot at both sites. Fruit were determined unmarketable if they had excessive insect damage, disease, scarring, or if the fruit was misshapen. Fruit did not reach maturity at Mount Vernon due to the cool, short growing season and late transplanting date; however, at season's end (85 DAT) all nearly mature fruit (>2 kg) were harvested and the number and weight of these fruit per plant were recorded. For each harvest date at Othello and Eltopia, three marketable fruit were arbitrarily selected from each plot for fruit quality testing, and data for each treatment were pooled for all harvest dates. These fruit were cut in half along the longitudinal axis and a 5-cm 3 sample was taken just off center near the blossom end. Flesh firmness (newton, or N) was measured to a depth of 1 cm using a drillpress penetrometer (Ametek, Berwyn, PA) fixed with a 4 mm cylindrical blunt-end tip. The three firmness measurements for each plot were averaged, resulting in three data points for each treatment at each site for each harvest date. The TSS of the juice was measured using a Palm Abbeä refractometer (MISCO, Cleveland, OH). After the instrument was calibrated with DI water, 1 ml of juice from each fruit sample was placed on the measuring surface. Following the reading, the instrument was cleaned with DI water before the next sample was loaded. As with firmness, the three TSS readings for each plot were averaged. Lycopene content was determined using a spectrophotometer protocol modified from Nagata & Yamashita (1992). For each plot, sections of flesh measuring 3 cm 3 were removed from each of the three fruit, combined to make one composite sample, and frozen at -20°C. Frozen samples were homogenized using a mortar and pestle. A 1-g subsample was taken from each homogenized sample and placed in 16 mL of a chilled acetone:hexane (2:3) mixture. The supernatant from each sample was extracted and placed in a cuvette. The cuvettes were loaded into a Beckman DU-65 spectrophotometer (Beckman Coulter, Inc., Brea, CA) and absorbance readings were taken at 453, 505, 645, and 663 nm. Experimental design and statistical analysis. The experiment at each site was arranged as a randomized complete block design with three replications and six plants per plot. Data were analyzed using PROC GLM in SAS (version 9.2; SAS Institute, Cary, NC) with a = 0.05, and a correlation analysis for yield and AUDPC at each site was conducted using PROC CORR. The AUDPC data from all sites, and fruit weight and fruit number data from Mount Vernon required transformation for statistical analysis. Using the range method outlined by Kirk (1982), the rank transformation was deemed most appropriate in all cases. Data were ranked using PROC RANK in SAS. Due to differences in planting dates, soil types, climate, V. dahliae soil densities, and cultural practices, all sites were analyzed separately. Significant differences between treatment means were compared using Fisher's least significant difference test with a = 0.05. Results Verticillium wilt severity. Verticillium wilt symptoms were observed in all treatments at all sites; and at each site, symptom onset occurred at the same time for all treatments, although disease severity differed among treatments. At Othello, the AUDPC values ranged from 22.7 ('Sugar Baby' grafted onto 'Marvel') to 154.0 (non-grafted 'Sugar Baby'), but ratings did not differ among treatments (P = 0.59) ( Table 2). At Eltopia, AUDPC values differed among treatments (P = 0.05). Non-grafted 'Sugar Baby' had the highest value (361.7) at this site but did not differ from 'Sugar Baby' grafted onto 'Marvel' and 'Titan' (137.7 and 243.7,respectively). 'Sugar Baby' grafted onto 'Tetsukabuto' and 'Rampart' had the lowest AUDPC values (17.3 and 76.7, respectively). At Mount Vernon, the AUDPC values also differed among treatments (P = 0.0006). Non-grafted 'Sugar Baby' had a higher value (502.4) than all other treatments at this site and 'Sugar Baby' grafted onto 'Tetsukabuto' had a lower value (24.1) than all other treatments. Microsclerotia typical of Verticillium spp. were observed on the incubated stem samples of all treatments at Eltopia and Mount Vernon. Fruit yield and quality. At Othello, there was no difference in marketable fruit weight per plant among entries (P = 0.07) (Fig. 1). The overall mean was 14.30 kg at this site and ranged from 11.86 kg (nongrafted 'Sugar Baby) to 17.80 kg ('Sugar Baby' grafted onto 'Titan'). At Eltopia, differences in marketable fruit weight per plant were observed among treatments (P = 0.006). The overall mean at this site was 12.99 kg, and nongrafted 'Sugar Baby' had a lower yield than all other treatments (8.11 kg). 'Sugar Baby' grafted onto 'Tetsukabuto' had the highest marketable fruit weight per plant (16.77 kg) but did not differ from 'Sugar Baby' grafted onto 'Rampart' (14.14 kg) and 'Marvel' (13.41 kg). At Mount Vernon, nearly mature fruit weight per plant differed among treatments (P = 0.0004). 'Sugar Baby' grafted onto 'Tetsukabuto' had a higher yield (15.02 kg) than all other treatments. Nongrafted 'Sugar Baby' had a lower yield (4.60 kg) than all other treatments except 'Sugar Baby' grafted onto 'Rampart' (5.49 kg). At Othello, there was no correlation between fruit weight per plant and AUDPC values (r 2 = -0.43; P = 0.11). However, a negative correlation between these two parameters was observed at both Eltopia (r 2 = -0.68; P = 0.005) and Mount Vernon (r 2 = -0.62; P = 0.01). At Othello, there were no differences in number of marketable fruit per plant among treatments (P = 0.48) ( Table 3). The overall mean at this site was 3.2 and ranged from 3.0 ('Sugar Baby' grafted onto 'Marvel') to 3.5 ('Sugar Baby' grafted onto 'Titan'). At Eltopia, differences in number of marketable fruit per plant were observed among treatments (P = 0.04). The overall mean at this site was 2.9. 'Sugar Baby' grafted onto 'Tetsukabuto' had the highest number of fruit per plant (3.7) and differed from all other treatments except 'Sugar Baby' grafted onto 'Rampart' (3.1). Nongrafted 'Sugar Baby' had the lowest number of fruit per plant (2.3). At Mount Vernon, there was no difference in number of fruit per plant among treatments (P = 0.09). The overall mean at this site was 1.9 and ranged from 1.4 (nongrafted 'Sugar Baby') to 3.5 ('Sugar Baby' grafted onto 'Tetsukabuto'). Marketable fruit weight differed due to treatment (P = 0.0002) but not location, and there was no significant interaction between treatment and location. The overall average marketable fruit weight was 4.2 kg, and was lowest for nongrafted 'Sugar Baby' (3.6 kg) and greatest for 'Sugar Baby' grafted onto 'Titan' (4.8 kg) which was statistically equivalent to 'Sugar Baby' grafted onto 'Marvel' (4.7 kg) and 'Sugar Baby' grafted onto 'Tetsukabuto' (4.6 kg). Discussion Previous researchers have found that grafting onto verticillium wilt-tolerant rootstocks can reduce verticillium wilt of watermelon; Table 2. Area under disease progress curve (AUDPC) values for severity of verticillium wilt symptoms on non-grafted verticillium wilt-susceptible 'Sugar Baby' watermelon, and 'Sugar Baby' grafted onto the commercial rootstocks 'Marvel', 'Rampart', 'Tetsukabuto', and 'Titan' at Othello, Eltopia, Disease severity was recorded as the percent of the plot canopy displaying verticillium wilt symptoms (chlorosis, necrosis, and wilting). Mean area under disease progress curve (AUDPC) values were calculated based on verticillium wilt severity visual assessments taken on four rating dates at Othello and Eltopia and five rating dates at Mount Vernon. y The scion 'Sugar Baby' of grafted plants is abbreviated as 'SB' and the rootstocks of grafted plants are given in parentheses. x The data for each site violated the assumptions of ANOVA and therefore required transformation. PROC RANK in SAS (Version 9.2, SAS Institute, Cary, NC) was used in all cases, and ranked data from each site were compared separately using PROC GLM with a = 0.05. However, the means presented in the table are non-transformed. Fisher's least significant difference test was used to locate differences in treatment means. Treatment means followed by the same letter within a column are not significantly different at a = 0.05. however, these observations are typically dependent on certain factors, including location and rootstock cultivar (Buller et al., 2013;Paplomatas et al., 2002;Paroussi et al., 2007). These observations can be partially explained by the climatic differences between these sites. The hot, dry summer conditions at Othello and Eltopia result in relatively high water demand which exacerbates verticillium wilt (Cappaert et al., 1994). Alternatively, the cool, humid summer conditions at Mount Vernon may have ''protected'' the grafted treatments due to lower water stress. This explanation, however, is not consistent with the verticillium wilt reactions observed for nongrafted 'Sugar Baby' at these sites. The AUDPC values observed for nongrafted 'Sugar Baby' were 154.0, 361.7, and 502.4 at Othello, Eltopia, and Mount Vernon, respectively. Thus, it may be that the susceptibility of 'Sugar. Baby' to V. dahliae did not change as a result of the milder Mount Vernon climate. Together, these results suggest that threshold V. dahliae soil densities as well as rootstock performance may be regionally specific. Results from this study demonstrate that yield is impacted by verticillium wilt in Washington. At Eltopia, marketable yield was greatest for 'Sugar Baby' grafted onto 'Tetsukabuto' and 'Rampart', which corresponds to these two treatments having the lowest AUDPC values. Nongrafted 'Sugar Baby' had the lowest marketable yield at Eltopia, reflecting the higher verticillium wilt severity sustained by this treatment. These observations are supported by the negative correlation between yield and AUDPC values at this site. Yield and AUDPC were also negatively correlated at Mount Vernon, where 'Sugar Baby' grafted onto 'Tetsukabuto' had the highest total yield and lowest AUDPC value, and nongrafted 'Sugar Baby' had the lowest total yield and the highest AUDPC value. At Othello, there were no differences in marketable yield or AUDPC values among treatments, and there was no correlation between these two parameters. Based on the findings of this study, grafting can lead to increased yield as compared with non-grafted plants when V. dahliae soil populations exceed certain levels, and the severity of verticillium wilt may differ by region because of climate and other factors. A future study focused on the interaction of V. dahliae soil densities with contrasting and controlled environmental conditions would be useful for assessing suitability of using grafted transplants across diverse production settings. Fruit quality parameters are important for assessing market acceptability of grafted watermelon. Increased flesh firmness is generally considered a desirable characteristic of watermelon (Davis et al., 2008a). In this study, flesh firmness was increased at Eltopia with the use of 'Marvel' and 'Titan', but not with 'Tetsukabuto' (all of which are Cucurbita hybrids). These findings are consistent with those of Bruton et al. (2009), who reported an increase in flesh firmness as a result of grafting watermelon onto certain hybrid squash rootstocks (RS 1330 and RS 1420) but not others (RS 1332 andRS 1421). 'Sugar Baby' grafted onto 'Rampart' (L. siceraria) did not result in different flesh firmness at Eltopia or Othello as compared with non-grafted 'Sugar Baby'. This finding also is consistent with reported literature, which generally states that Lagenaria rootstocks result in fruit quality similar to nongrafted plants (Bruton et al., 2009;King et al., 2010). The lack of differences in TSS and lycopene content among treatments at either site further suggest that grafting watermelon onto these rootstocks does not have a negative impact on fruit quality. Based on the findings from this study, any one of the four rootstocks may be appropriate for use in watermelon grafting systems under Washington's diverse growing conditions. 'Tetsukabuto' and 'Rampart' reduced disease severity at Eltopia and Mount Vernon, and also increased marketable yield at Eltopia. 'Titan' and 'Marvel' reduced disease severity at Mount Vernon but not at Eltopia, but did increase yield at both of these sites. In addition, 'Titan' and 'Marvel' increased flesh firmness at Eltopia. These results indicate that grafting watermelon onto such disease-tolerant rootstocks can reduce verticillium wilt severity and increase yield with no negative effects on fruit quality in Washington. 3.5 2.7 b 2.8 P value x 0.48 0.04 0.09 z Only marketable fruit were included at Othello and Eltopia, while at Mount Vernon all nearly mature fruit (>2 kg) were included. y The scion cultivar of grafted plants is 'Sugar Baby' and the rootstocks of grafted plants are given in parentheses. x The data for Mount Vernon violated the assumptions of ANOVA and therefore required transformation; thus, PROC RANK in SAS (Version 9.2, SAS Institute, Cary, NC) was used for this site, although the means presented in the table are non-transformed. Data from each site were analyzed separately using PROC GLM with a = 0.05. Fisher's least significant difference test was used to locate differences in treatment means. Treatment means followed by the same letter within a column are not significantly different at a = 0.05. The scion 'Sugar Baby' of grafted plants is abbreviated as 'SB' and the rootstocks of grafted plants are given in parentheses. y Data for each site was analyzed separately using PROC GLM in SAS (Version 9.2) with a = 0.05. Fisher's least significant difference test was used to locate differences in treatment means. Treatment means followed by the same letter within a column are not significantly different at a = 0.05.

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2016-05-12T22:15:10.714Z

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Long-term manure amendments reduced soil aggregate stability via redistribution of the glomalin-related soil protein in macroaggregates Glomalin-related soil protein (GRSP) contributes to the formation and maintenance of soil aggregates, it is however remains unclear whether long-term intensive manure amendments alter soil aggregates stability and whether GRSP regulates these changes. Based on a three-decade long fertilization experiment in northeast China, this study examined the impact of long-term manure input on soil organic carbon (SOC), total and easily extractable GRSP (GRSPt and GRSPe) and their respective allocations in four soil aggregates (>2000 μm; 2000–250 μm; 250–53 μm; and <53 μm). The treatments include no fertilization (CK), low and high manure amendment (M1, M2), chemical nitrogen, phosphorus and potassium fertilizers (NPK), and combined manure and chemical fertilizers (NPKM1, NPKM2). Though SOC, GRSPe and GRSPt in soil and SOC in each aggregate generally increased with increasing manure input, GRSPt and GRSPe in each aggregate showed varying changes with manure input. Both GRSP in macroaggregates (2000–250 μm) were significantly higher under low manure input, a pattern consistent with changes in soil aggregate stability. Constituting 38~49% of soil mass, macroaggregates likely contributed to the nonlinear changes of aggregate stability under manure amendments. The regulatory process of GRSP allocations in soil aggregates has important implications for manure management under intensive agriculture. Despite recalcitrant features, GRSP can be sensitive to various agricultural management practices, such as tillage [11][12][13][14] , cropping treatments 11,15 , and land use change [16][17][18] . Chemical and organic fertilizations are common practices and play a key role in maintaining long-term agricultural production; however, the effects of different types of fertilization on the changes in glomalin concentrations have received very limited attention. For example, long-term fertilization, especially amendments with manure and straw, increase soil GRSP accumulation 19,20 . However, the effects of different amounts of manure and mineral fertilizer and their interactions on GRSP dynamics have not been elucidated. Aggregates are composed of primary mineral particles and organic binding agents 21 . Therein, arbuscular mycorrhizal fungi produce large amounts of insoluble glycoprotein, glomalin and polysaccharides, which contribute to aggregate stability 2,4 . Furthermore, many studies have examined the glomalin concentration in soil aggregates, but most studies only focused on the 1000-to 2000-μ m aggregates 2,22 . It was found that approximately 20% of GRSP remained in the fine fraction (< 53 μ m) 12 . Other study indicated that tillage reduced the GRSP content in all of the aggregate classes (2000-1000 μ m, 1000-500 μ m and 250 μ m) 11 . These results collectively suggest a possible strong correlation of glomalin with aggregate stability 2 . However, the underlying mechanism of this tight association between GRSP and aggregate stabilization remains poorly investigated. Furthermore, understanding factors controlling GRSP production such as fungal community composition, fungal physiology, and cell biology aspects as well as soil biota, soil physicochemical characteristics, and fungus-host plant species combinations will elucidate soil aggregation in crop production systems 23 . Long-term experiments provide a realistic and effective means for obtaining valuable information that is required to maintain the soil quality and health by determining changes in the soil properties and processes 24,25 . Soil fertility degradation has long been a major concern in China due to the replacement of organic fertilizers by chemical fertilizers 26 . To monitor changes in soil fertility, a number of long-term experiments were initiated in typical agricultural regions in China in the 1980's with the application of chemical fertilizer, organic manure alone or both in combination 26 . One of these experiments was set up in a brown soil region located in Liaohe Plain to explore the effect of long-term fertilization on the soil properties and crop yield 27 . Soil aggregate formation and stability are key variables for investigation; however, the role of GRSP on soil aggregates during long-term fertilization experiments has received little attention in this carbon-rich and high-productivity agricultural region, which hindered our understandings of how management practices alter GRSP concentrations in soil aggregates and how to maintain soil aggregate stability, fertility and productivity under different fertilization practices. Based on a three-decade long fertilization experiment in a typical brown soil in Northeast China, we collected surface soil samples (0-20 cm), quantified soil aggregate and GRSP concentrations, and compared the long-term dynamics of GRSP in different soil aggregate sizes under a suite of long-term continuous chemical and organic fertilizer treatments. The objectives of this study were to examine the effects of the long-term application of mineral and organic fertilizers alone or in combination on the concentration and allocation of GRSP in different aggregate classes. This study is expected to clarify on the relationship between GRSP in different soil aggregate sizes and aggregate stability for the sake of optimal management practices in this region. Results Long-term manure inputs on aggregate distribution and stability. The proportional distribution of aggregates in soil generally followed a descending order in each fertilization regime: small macroaggregate > microaggregate > silt + clay > macroaggregate ( Table 1). The small macroaggregate comprised the largest proportion of the soil (35.9-49.1%), and the large macroaggregate accounted for 11.4% to 18.9%. Different fertilization regimes altered the aggregate percentages in the soil. Organic manure application alone or in combination with fertilizer (M1, M1NPK, M2 and M2NPK) increased the proportion of the small macroaggregate (P < 0.1) and decreased the percentages of microaggregate and silt + clay (P < 0.1) compared to CK and NPK. High amounts of organic manure input (M2, M2NPK) tended to diminish the proportion of large macroaggregate compared to the other treatments. Furthermore, NPK did not change the distribution of aggregates compared to CK. Compared to CK, NPK, M2 and M2NPK, low-manure application (M1 and M1NPK) increased significantly MWD by approximately 20% (P < 0.05). Compared to CK, NPK, M2 and M2NPK decreased MWD by 5%, 5% and 11%, respectively, but these effects are not statistically significant. Long-term manure inputs on the SOC in bulk soil and aggregates. Generally, organic manure application significantly increased the SOC concentration in bulk soil (P < 0.05). There were significant differences in the SOC between CK and all fertilization treatments. Compared to CK, SOC increased by 25.9% under NPK and by 30.8% to 47.7% under organic manure treatment alone or combined manure and chemical fertilizers (M2NPK > M1NPK > M2 > M1 > NPK > CK) ( Table 2). Across all fertilization treatments, SOC concentration in macroaggregates and microaggregates showed little difference, but SOC concentration in sum of macroaggregates and microaggregates (> 53 μ m) and silt + clay fractions (< 53 μ m) were significantly different (P < 0.05, Fig. 1). Fertilizer application significantly altered SOC concentration in each aggregate fraction with a descending order as M2, M2NPK > M1, M1NPK > NPK > CK. Compared to CK, SOC showed a significantly greater increase under organic manure application alone or in combination with chemical fertilizers than chemical fertilizers alone (P < 0.05, Fig. 1). Long-term manure inputs on the GRSP in soil aggregates. Similar to the patterns of SOC changes under fertilization, long-term fertilization significantly increased GRSP t and GRSP e concentrations in bulk soil (M2NPK, M2, M1NPK > M1 > NPK > CK) ( Table 1. lower GRSP e content and higher amount of GRSP t compared with NPK treatments. Chemical fertilizer treatment alone led to a greater ratio of GRSP e /GRSP t (NPK > M2, M1NPK, M2NPK). In general, high manure amendments induced significantly greater GRSP t /SOC ratios than other treatments (M2NPK, M2, M1NPK > M1, NPK, CK). Long-term fertilization significantly increased SOC allocation within each aggregate than no fertilization (M2NPK > NPK > CK, Fig. 1), whereas, fertilization effects on GRSP allocations were highly variable with different aggregate sizes. The above mentioned pattern of SOC allocation was true for GRSP e in macroaggregates only (Fig. 2) and true for GRSP t in silt + clay fraction only (Fig. 3). Discussion Manure amendments on soil aggregate content and stability. Generally, the combined application of organic manure and fertilizer increased the proportions of small macroaggregate and decreased the proportions of microaggregate in the soil 28,29 . In our study, changes in the proportions of soil aggregates varied with different fertilization treatments. For instance, NPK treatment decreased the proportion of small macroaggregates, but manure or manure plus chemical fertilizers increased the same size aggregate. In contrast, NPK increased the proportion of microaggregates, but manure or manure plus chemical fertilizers decreased the same size aggregate. As a measure of aggregate stability, mean weight diameter (MWD) has been used to assess manure amendments on soil aggregate stability. A recent study indicated that as compared to CK, 2-year long-term manure addition (60 Mg·hm −2 ) increased the MWD at the 0-5cm layer in soil type of Typic Haplargids 30 , whereas, this study showed that three-decade high manure application decreased the MWD and consequently resulted in lower aggregate stability as compared to CK. This contradiction may be due to the accumulation of large macroaggregates that were derived from different sources of manure materials. In this study, a very high amount of manure amendment provided POC 31 , which coated macroaggregates. Long-term manure applications with a large amount of organic input increased the macroaggregate dispersion and thus resulted in a decrease in aggregate stability 32 . However, other studies suggest the MWD increased after 1 year manure application and decreased after 5 years and increased again after 12 years, indicating that long-term manure application (1 Mg·hm −2 ) increase soil aggregate stability 33 . In addition, there is unclear relationships between aggregate stability and rates of organic input by analyzing the literatures due to different factors such as the quality, quantity and timing of organic matter addition 34 . In particular, few studies offered mechanistic understanding of manure amendments and soil aggregate stability. In the following discussions, this study addressed the fertilization effect on SOC, GRSP allocations in different soil aggregates and particularly examined the possible mechanisms of GRSP redistribution driving the change of soil aggregate stability. Manure amendments on SOC allocation in soil aggregates. Manure application has long been recognized as an effective way to increase SOC content 29,32,[35][36][37]40 . This study showed that manure application alone or mixed with chemical fertilizers significantly improved the total SOC content compared to that of CK and NPK. On the other hand, the application of NPK fertilizers also significantly increased the SOC content compared to that of CK, which is driven by greater yield and biomass return to the SOC pool 37 . The reason for this result is that the manure input directly increased the soil organic matter content and induced the additional input of organic material to soils due to higher crop productivity under fertilization [37][38][39] . This study further demonstrated that fertilizer application significantly increased the SOC content in every aggregate fraction compared with CK. Especially, manure and manure combined with fertilizer enhanced SOC concentration in macroaggregates and microaggregates (P < 0.05), indicating that the manure-derived C was more preferentially accumulated in these aggregate fractions 37 . For all of the fertilization treatments, the lowest SOC contents were found in the silt + clay fraction. A similar observation was reported through long-term fertilization on a Mollisol 36 . These observations are most likely associated with low or no binding capacity of SOC by free silt particles 36 , and also the limited protection of SOC by silt and clay 41 . Overall, this study revealed that manure application alone or in combination with chemical fertilizer increased SOC through their effects on the formation of macroaggregates. This result is consistent with a former study that showed that animal manure application increased SOC and consequently the formation of macroaggregates 38,41,42 . Given the relatively stable soil mineralization rate indicated in these studies, we speculate that the SOC change is directly related to C input from manure 38,43 . In addition, the low temperature in winter restricts the decomposition of manure 38 . Manure amendments on GRSP in bulk soil. As an important component in SOC, the concentrations of both GRSP e and GRSP t were enhanced significantly under treatments with manure input (P < 0.05; Table 2), which echoed with several recent studies 2,19,20,[44][45][46] . The main reason may lie in the release of the growth-stimulating substances due to increased soil biological activities and nutrients from organic manure 6,19,46 . On the other hand, the relatively low amount of GRSP t under NPK treatment compared with manure amendment treatments most likely due to the inhibition of AMF development by chemical fertilizers 20,46 . However, the greater GRSP e /GRSP t under NPK than manure amendment treatments could be caused by the immediate and pronounced effect of nutrient availability on GRSP e productions via part of AMF groups under NPK treatment. It thus remains to be further explored whether only some species of AMF development are more sensitive to chemical nutrient input than other species. The SOC content is often a good predictor of GRSP 9 . In our study, the GRSP t /SOC changed from 0.18 to 0.21 when manure was applied either with chemical fertilizers or at a higher input rate. This pattern of change under fertilization is much narrower in quantity in comparison to former studies in agroecosystem (0.14 to 0.27) 44 and in different land use types (0.21 to 0.29) 47 . This current result also showed a positive correlation between the GRSP and SOC content. This relationship was affected by land use type and soil type such as in pastures 48 , Mediterranean steppes 17 , North American soils 49 and a semiarid rangeland 50 . The exceptions to this trend are the Costa Rican study 51 and a strong acid soil result from the narrow range of SOC 52 . In our study, a high-manure amendment did not increase the contribution of GRSP t to SOC due to parallel increases in both GRSP t and SOC. This result clearly indicates that GRSP, as an important component of soil organic matter and binding agents 53 , can contribute to soil carbon sequestration under long-term manure amendments 54 . Manure amendments on GRSP allocation in soil aggregates. As we revealed above, three-decade-long manure amendments combined with mineral fertilizer application significantly increased soil aggregate stability, while the underlying mechanisms are not well identified. This study found that long-term manure amendment combined with chemical fertilizer application significantly increased the GRSP content in all soil aggregate fractions except for microaggregates (Fig. 1). In particular, intermediate amount of manure input in addition to chemical fertilizers (M1NPK) increased the content of macroaggregates and the overall soil aggregate stability (Table 1). These results suggest that glomalin accumulation influenced soil stability via its redistribution in macroaggregates under long-term fertilization. In all aggregate fractions, the relationship of GRSP and SOC showed significant trend ( Fig. 4. R 2 = 0.431 and R 2 = 0.317, P < 0.01). The accumulation of GRSP in total SOC is possibly attributed to the positive role of AMF in glomalin production at presence of long-term and relatively large amount of manure amendments in soils 6,19,55 . Although the application of organic manure positively affected the accumulation of GRSP in aggregates, the highest amount of organic manure did not result in the highest concentration of either GRSP e or GRSP t . In fact, the contents of GRSP e and GRSP t in the small macroaggregates were significantly lower under high manure input treatments than low manure input treatments. Thus, a high amount of organic manure amendment exceeding a certain threshold may otherwise reduce GRSP content and then decrease the soil aggregate stability by altering GRSP allocations to macroaggregates (Table 1). Methods Site description and soil sampling. This study was conducted on a long-term fertilization trial that was initiated in April 1979 at the Experimental Station of Shenyang Agricultural University (41°48´N, 123°33'E) in Liaoning Province, China. The annual mean temperature ranged from 7.0 to 8.1 °C, the annual mean precipitation ranged from 574 to 684 mm, and the average frost-free period was 147 to 164 days in the past 30 years. The soil is a Hapli-Udic Cambisol (FAO Classification). Prior to this experiment, the concentration of SOC was 9.2 g kg −1 , the total nitrogen concentration was 0.8 g kg −1 , and the soil pH was 6.5 (soil:water = 1:2.5) at the top 20-cm depth. The current long-term experiment consists of a randomized complete block design with three blocks and eighteen fertilization treatments. The area of one individual plot was 160 m 2 . The following six treatments were included in this study: (1) no fertilizer (CK); (2) chemical nitrogen, phosphorus and potassium fertilizers (NPK); (3) low manure amendment (M1); (4) combination of M1 and NPK (M1NPK); (5) high manure amendment (M2); and (6) combination of M2 and NPK (M2NPK). M1 and M2 refer to composted pig manure applied at the rate of 13.5 and 27 Mg hm −2 yr −1 (organic matter 119.6 g kg −1 ; total N 5.8 g kg −1 ; P 3.6 g kg −1 ; K 9.0 g kg −1 ), respectively; NPK denotes chemical N (urea), P (multiple superphosphate), and K (potassium sulfate) fertilizers added at the rate of 135, 29, and 56 kg hm −2 yr −1 , respectively. The plots have a cropping system of monoculture maize (Zea mays L.). Maize was planted in late April and harvested in late September every year. The mineral fertilizers were evenly distributed on the soil surface by hand and immediately incorporated into the soil by tillage before sowing in April. Dry-composted pig manure was spread over the soil surface after harvesting in October. Surface soil samples (0-20 cm) from each plot were collected in October 2008 prior to manure amendment. The field-moist soil samples were gently broken apart, sieved to pass through a 5-mm sieve, and air-dried for physiochemical analysis. Water-stable aggregate fractionation. Four aggregate-size fractions were separated by wet sieving according to Elliott's method 56 . and they were named as large macroaggregate (> 2000 μ m), small macroaggregate (2000-250 μ m), microaggregate (250-53 μ m), and silt + clay fraction (< 53 μ m). Briefly, 100 g of soil (oven-dry equivalent weight) was submerged in deionized water on top of a 2000-μ m sieve overnight at room temperature. The aggregates were then separated by moving the sieve up and down 50 times over a period of 2 min. Then, the intact aggregates were washed off the sieve and collected in an aluminum pan. The remaining soil slurry was passed through the 250-and 53-μ m sieves, while the sieving procedure described above was repeated. The silt + clay fraction was separated by centrifuging (2500 × g, 10 min) the soil suspension that passed through the 53-μ m sieve. After being oven dried at 50 °C, the four classes of aggregates were weighed and stored at room temperature for future use. The mean weight diameter (MWD) represents fraction of the sample on the sieve times mean intersieve aperture and was used to indicate the soil aggregate stability 57 . The total carbon in the soil aggregates was determined by dry combustion using an element analyzer Vario Elementar III (Elementar Analysensysteme GmbH, Hanau, Germany). Because these soil samples were free of carbonates, the total carbon content was equivalent to the soil organic carbon content. GRSP extraction and determination. GRSP was extracted according to the procedures described by Wright and Upadhyaya 2 . Briefly, extractable GRSP (GRSP e ) was extracted from 1 g of 2-mm-sieved soil with 8 ml of a 20 mM citrate solution at pH 7.0 by autoclaving at 121 °C for 30 min, and then the supernatant was removed by centrifugation at 10,000 × g for 5 min. The total GRSP (GRSP t ) was extracted with 8 ml of 50 mM citrate solution at pH 8.0 by autoclaving at 121 °C for 60 min, then centrifuged at 10,000 × g for 5 min to remove the supernatant. After each cycle, the sodium citrate was replenished for the extraction again until the GRSP content of supernatant was above the detection limits (ca. 2 mg ml −1 ). The supernatant was decanted and stored at 4 °C until being analyzed. The protein content was determined by the Bradford assay 58 using bovine serum albumin as a standard. Statistical analysis. The significant difference of the effects of aggregate size and the fertilization treatment on the SOC, GRSP t , GRSP e and GRSP t /SOC were assessed using one-way analyses of variance (ANOVA). Post hoc analyses were conducted using LSD tests. A statistical significance was set at P < 0.05 or P < 0.1. All of the statistical analyses were implemented in the R program 59 .

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2016-05-04T20:20:58.661Z

2015-02-04T00:00:00.000Z

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Effects of Flavonoid-rich Plant Extracts on In vitro Ruminal Methanogenesis, Microbial Populations and Fermentation Characteristics The objective of this study was to evaluate the in vitro effects of flavonoid-rich plant extracts (PE) on ruminal fermentation characteristics and methane emission by studying their effectiveness for methanogenesis in the rumen. A fistulated Holstein cow was used as a donor of rumen fluid. The PE (Punica granatum, Betula schmidtii, Ginkgo biloba, Camellia japonica, and Cudrania tricuspidata) known to have high concentrations of flavonoid were added to an in vitro fermentation incubated with rumen fluid. Total gas production and microbial growth with all PE was higher than that of the control at 24 h incubation, while the methane emission was significantly lower (p<0.05) than that of the control. The decrease in methane accumulation relative to the control was 47.6%, 39.6%, 46.7%, 47.9%, and 48.8% for Punica, Betula, Ginkgo, Camellia, and Cudrania treatments, respectively. Ciliate populations were reduced by more than 60% in flavonoid-rich PE treatments. The Fibrobacter succinogenes diversity in all added flavonoid-rich PE was shown to increase, while the Ruminoccocus albus and R. flavefaciens populations in all PE decreased as compared with the control. In particular, the F. succinogenes community with the addition of Birch extract increased to a greater extent than that of others. In conclusion, the results of this study showed that flavonoid-rich PE decreased ruminal methane emission without adversely affecting ruminal fermentation characteristics in vitro in 24 h incubation time, suggesting that the flavonoid-rich PE have potential possibility as bio-active regulator for ruminants. INTRODUCTION Agricultural greenhouse gas emission, mainly methane from ruminants, has currently been recognized as an important issue worldwide as it is a driver for global warming and climate change. Methane eructated from ruminants is considered to be one of the most important contributors to global warming, imposing an environmental burden that cannot be ignored. Meanwhile, it represents a loss of 2% to 15% of the gross energy intake (Johnson and Johnson, 1995;Ellis et al., 2007). Animal nutritionists have been studying manipulation of the rumen microbial ecosystem to reduce methane emission without the adverse effects on rumen function. There is a need to identify feed additives to modify ruminal fermentation characteristics and increase the efficiency of feed utilization, thereby inhibiting the ruminal methanogenesis. In recent years, essential oils (Benchaar, 2007), plant secondary metabolites such as condensed tannins and saponins (Pen et al., 2006;Bhatta et al., 2009) and dietary lipids (Dohme et al., 2001) have arisen as attractive rumen modifiers to improve rumen microbial metabolism as well as inhibit methane production in ruminants. The positive effects of flavonoid-rich plant extracts (PE) on methane emission and methanogens population in vitro as well as in vivo have been examined (Patra et al., 2006;Bodas et al., 2008;Patra and Saxena, addition, flavonoid supplementation could improve ruminal fermentation of dairy cows with increasing milk yield (Theodorou et al., 1994), protecting ruminal acidosis (Balcells et al., 2012), reducing methane emission and changing microbial populations such as protozoa and methanogen (Baker, 1999). The objective of this study was to evaluate the effect of flavonoid-rich PE on the growth of rumen microorganisms using quantitative real-time polymerase chain reaction (PCR) assay and in vitro rumen fermentation with respect to methane emissions. Preparation of plant extracts Plant extracts were obtained from Plant Extract Bank at the Korea Research Institute of Bioscience and Biotechnology (Daejeon, Korea). Plants were collected from fields in Korea (Table 1). Each plant was cut into small pieces and dried naturally under shade. The dried plant (100 g) were extracted with 99.9% methyl alcohol (1 L) using ultrasonic cleaner (Branson Ultrasonics corporation, Danbury, CT, USA) at room temperature for 3 days. After extraction, the solutions were filtered and the solvents were evaporated under vacuum. Stock solutions (20 mg/mL) of the extract were dissolved in dimethyl sulfoxide (Sigma-Aldrich Chemical Co., St. Louis, Mo, USA) and diluted using culture media immediately before experiments. Ruminal inoculum and in vitro incubation A fistulated Holstein cow was used as a donor of rumen fluid. Timothy and commercial concentrate in the ratio of 60:40 were fed at 2% of body weight twice a day (09:00 and 17:00). Water and mineral-vitamin block were allowed ad libitum. The rumen fluid was collected from the fistulated Holstein cow before morning feeding. Rumen liquor was filtered through four layers of cheesecloth before mixing with buffer and was maintained at 39°C. Fifteen mililiters of rumen fluid-buffer mixture, comprising McDougall buffer (McDougall, 1948) and rumen liquor in the ratio of 2 to 1, was dispensed anaerobically into 50 mL serum bottles containing 0.3 g of timothy substrate and PE (5% of substrate). The serum bottles were filled with O 2 -free N 2 gas capped with a rubber stopper and held in a shaking incubator (Jeio Tech, SI-900R, Daejeon, Korea; 120× rpm) at 39°C for 72 h. The in vitro experiment was evaluated in triplicate run for data analysis using 90 serum bottles (6 treatments×5 incubation times×3 replication) with a completely randomized design. Gas production measurement and analysis of gas profiles and ruminal fermentation At the end of incubation, total gas production was measured according to the assay outlined by Theodorou et al. (1994). A detachable pressure transducer and a digital readout voltmeter (Laurel Electronics, Inc., Costa Mesa, CA, USA) were used to measure the headspace gas pressure of fermenting cultures. For the total gas production measurement, the transducer was modified in a way that it could be linked to the inlet of a disposable Luer-lock threeway stopcock (Theodorou et al., 1994). Gas pressure in the headspace was read from the display unit after insertion of the hypodermic syringe needle through the butyl rubber stopper above the culture medium. The headspace gas in the serum bottle was collected for analyzing methane and hydrogen by gas chromatography (Agilent Technologies HP 5890, Santa Clara, CA, USA) conducted using a TCD detector with a Column Carboxen 1006PLOT capillary column 30 m×0.53 mm (Supelco). The culture was subsampled for the analysis of pH (Mettler-Toledo, MP230, Greifensee, Switzerland), volatile fatty acid (VFA) concentration and genomic DNA extraction. The VFA analysis was performed with a HPLC (High Performance Liquid Chromatography, Agilent-1200, Waldbronn, Germany) equipped with column (300 mm×7.8 mm I.d. MetaCarb 87H, Varian, Palo Alto, CA, USA). In vitro DM disappearance rate was estimated by the modified method of nylon bag digestion process. Briefly, after incubation, the nylon bag with substrate was washed twice in a water-bath equipped with Heidolphs Rotamax 120 (Heidolph Instrument, Nuremberg, Germany) at 100×rpm for 30 min. Washed nylon bags were then dried to a constant weight at 60°C. Dry matter disappearance was determined by weight difference before and after incubation in the serum bottle. Microbial growth rate Incubated samples taken from each fermentation period were centrifuged at 3,000×rpm for 3 min to remove feed particles, and the supernatants were re-centrifuged at 14,000×rpm for 3 min to settle the pellets down. After that, sodium phosphate buffer (pH 6.5) was added to these precipitates and vortexed. Growth rates of total microbes were estimated as optical density (OD) values using spectrophotometer (Model 680, Bio-Rad Laboratories, Hercules, CA, USA) at 550 nm. Quantitative polymerase chain reaction assays DNA extraction: A high-speed reciprocal shaker which retains samples in screw-capped tubes containing silica beads was used for DNA extraction. Total nucleic acid was extracted from the incubated rumen samples by using the modified bead-beating protocol with the Soil kit (Macherey-nagel, Düren, Germany). Briefly 1.0 mL aliquot was taken from the incubated culture solution and was centrifuged at 3,000×rpm. Nucleic acid concentrations were measured by using a NanoDrop Spectrophotometer (Thermo Scientific, Wilmington, DE, USA). PCR primers: The PCR primer sets (Table 2) used in this study for amplification of total bacteria, Fibrobacter succinogenes, Ruminococcus albus, Ruminococcus flavefaciens, methanogenic archaea, and ciliate protozoa were from the published reports (Koike and Kobayashi, 2001;Denman and McSweeney, 2005;and Denman et al., 2007). All microbial data were analyzed for calculating relative expressions to total bacteria (Denman and McSweeney, 2006). Quantitative Real-time PCR: Quantitative PCR assays for enumeration of microbes were performed according to the methods described by Denman and McSweeney (2006) and Denman et al. (2007) on a real-time PCR Machine (CFX96 Real-Time system, BIO RAD, Hercules, CA, USA) using the SYBR Green Supermix (QPK-201, Toyobo Co., LTD., Tokyo, Japan). The values of cycle threshold (Ct) after real-time PCR were used to determine fold change (number of fold difference) of different microbial population relative to control without additives. Abundance of these microbes was expressed by the equation: relative quantification = 2 -ΔCt(Target)-ΔCt(Control) , where Ct represents threshold cycle. All quantitative (q) PCR reaction mixtures (final volume of 20 μL) contained forward and reverse primers, the SYBR Green Supermix and DNA template. A negative control without the template DNA was used in every qPCR assay for each primer. The PCR amplification of the target DNA, included the annealing and the extension temperature, was conducted following the references in Table 2. Total polyphenol and total flavonoid concentration Total polyphenol concentration: Total polyphenol content in the PE was determined with Folin-Ciocalteu reagent using modified method by Velioglu et al. (1998) in a 96 well plate. Reaction mixture consisted of 10 μL of PE, 180 μL of Na 2 CO 3 (2%), 10 μL of Folin-Ciocalteu reagent (1:1 with water) and 10 μL distilled water. Total polyphenolic content in PE was estimated as OD values using enzyme-linked immunosorbent assay (ELISA) reader (Spectra Max reader M5, Molecular Devices, Sunnyvale, CA, USA) at 750 nm after 30 min incubation (37°C). The standard calibration plot was generated at 750 nm using known concentration of gallic acid. Total flavonoid concentration: The aluminum chloride method modified by Jia et al. (1999) was used for the determination of total flavonoid content of PE. Aliquots of PE solutions were taken and made up the volume 100 μL with methanol. Then, 7.5 μL of NaNO (5%), 15 μL of AlCl 3 (10%), 100 μL of NaOH (1 M) and 25 μL of distilled water were added sequentially. Total flavonoid content in PE was estimated as OD values using ELISA reader (Spectra Max reader M5, Molecular Devices, Sunnyvale, CA, USA) at 510 nm after 30 min incubation. The standard calibration plot was generated at 510 nm using known concentration of catechin. Statistical analysis Data were analyzed using the general linear model procedure of the Statistical Analysis System Institute, Inc. (SAS Institute, 2002). The effects of PE on total gas production, gas profiles, pH, VFA, and microbial growth were compared to the controls and significant differences between treatment means were examined using Duncan's multiple comparison tests. A p<0.05 was considered to indicate statistical significance. In vitro ruminal fermentation characteristics The concentration of total polyphenol and total flavonoid in PE used in this experiment is shown in Figure 1. In particular, the concentration of total flavonoid was higher in Pomegranate and Birch extracts compared with others. The in vitro ruminal fermentation profiles are shown in Table 3. pH did not significantly show a difference (p< 0.05) with the addition of all PE except at 72 h incubation time. Our study supports the previous studies that pH was not significant different in in vitro ruminal incubation with flavonoids such as flavone, myricetin, naringin, catechin, rutin, quercetin and kaempferol (Oskoueian et al., 2013) as well as flavonoid, tannin and essential oil (Bodas et al., 2008). The tVFA concentrations were decreased or increased by flavonoid-rich PE according to incubation times (6 h, 12 h, 24 h, 48 h, and 72 h) but were not affected significantly as compared to control. Although dry matter (DM) disappearance was not significantly different except with the addition of Cudrania tricuspidata at 24 h incubation and pomegranate at 72 h incubation (p<0.05), DM disappearance in added flavonoid-rich PE was lower than that of the control at 6 h, 12 h, and 24 h incubation. The effect of flavonoid-rich PE on gas production and gas profiles is shown in Table 4. In particular, total gas production in added all PE was higher than that of the control at 24 h incubation, while the methane emission was significantly lower (p<0.05) than that of the control. This finding supports the finding that flavonoid-rich PE reduced methane emission by 4.7% to 14% after 24 h incubation (Bodas et al., 2008). The decreased methane emission may be due to the changes in ciliate protozoan community ( Figure 3B). The in vitro change in microbial diversity in the rumen Rumen bacterial growth with the addition of flavonoidrich PE is shown in Figure 3. Although flavonoids are widely known to possess antifungal, antiviral and antibacterial activities (Cushnie and Lamb, 2005), the result of microbial growth under supplement of all PE was higher than that in control for 72 h incubation (Figure 2), which may be the cause of total gas production increase. The ciliate protozoa community with the addition flavonoid-rich PE was decreased more than that of the control ( Figure 3A). Patra et al. (2006) reported that extracts containing phenolics decreased the ruminal methane emission and protozoa count although they appeared not effective against ruminal methanogenesis. This study also showed that ciliate protozoan populations were reduced by more than 60% in flavonoid-rich PE treatments. Ciliate protozoa are an important key in methanogenesis in the rumen as methanogens attach to their surface. Flavonoid-rich PE reduced the ciliated-associated methanogens population and hence decreased the methane emission. Patra and Saxena (2010) reported that flavonoids gave direct effects against methanogens, and reduced protozoa related with ruminal methanogenesis. The Fibrobacter succinogenes diversity under all flavonoid-rich PE was shown to increase, while the Ruminococcus albus and Ruminococcus flavefaciens populations under all PE decreased as compared with control. In particular, the F. succinogenes community with the addition of Birch extract increased to a greater extent than that of others ( Figure 3C, 3D, and 3E). R. albus, one of ruminal fibrolytic bacteria, is a very promising bacteria to produce hydrogen (H 2 ) from energy forage, with the potential of utilizing the cellulosic and hemicellulosic biomass (Ntaikou et al., 2008). Latham and Wollin (1977) reported that succinic acid is produced by R. flavefaciens culture as a major fermentation product with acetic and formic acids, H 2 , and CO 2 . H 2 is the critical concern to the microbial ecosystem in ruminants. H 2 produced during enteric fermentation is the precursor of methane emission from ruminants and the regulation of H 2 rather than methane is the key to control ruminant methane emission. The formation of propionate from succinate would result in a lower availability of H 2 for the methanogenesis. The ruminal microbe population may show that PE with flavonoid influences ruminal methanogenesis in this study. In conclusion, the results of this study indicate that flavonoid-rich PE appears to have a potential possibility as bio-active regulator for ruminants with decreasing ruminal methane emission. Future studies need to be aimed at finding a suitable effective dose of PE for inhibiting ruminal methanogenesis.

v3-fos

2016-05-12T22:15:10.714Z

2015-10-30T00:00:00.000Z

12479459

s2

Iron Absorption from Two Milk Formulas Fortified with Iron Sulfate Stabilized with Maltodextrin and Citric Acid Background: Fortification of milk formulas with iron is a strategy widely used, but the absorption of non-heme iron is low. The purpose of this study was to measure the bioavailability of two iron fortified milk formulas designed to cover toddlers’ nutritional needs. These milks were fortified with iron sulfate stabilized with maltodextrin and citric acid. Methods: 15 women (33–47 years old) participated in study. They received on different days, after an overnight fast, 200 mL of Formula A; 200 mL of Formula B; 30 mL of a solution of iron and ascorbic acid as reference dose and 200 mL of full fat cow’s milk fortified with iron as ferrous sulfate. Milk formulas and reference dose were labeled with radioisotopes 59Fe or 55Fe, and the absorption of iron measured by erythrocyte incorporation of radioactive Fe. Results: The geometric mean iron absorption corrected to 40% of the reference dose was 20.6% for Formula A and 20.7% for Formula B, versus 7.5% of iron fortified cow’s milk (p < 0.001). The post hoc Sheffé indeed differences between the milk formulas and the cow’s milk (p < 0.001). Conclusion: Formulas A and B contain highly bioavailable iron, which contributes to covering toddlers’ requirements of this micronutrient. Introduction Iron deficiency is one of the most prevalent nutritional deficiencies worldwide. Infants, pre-school and school children, as well as women of child-bearing age and pregnant women are the most vulnerable groups [1]. Experts agree that food fortification is the best long-term strategy to prevent iron deficiency in the population in general [2]. However, there is a variety of relevant technical considerations regarding the use of iron as a fortifier. In the first place, the food vehicle must be consumed on a regular basis by the target population. In the second place, the absorption of fortifying iron must be regulated by the iron nutritional status of the subject; otherwise, there may be a potential risk of overload; this regulation has been described for both heme and non-heme iron [3]. In the third place, the fortificant must be bioavailable. From the nutrition standpoint, iron bioavailability has been shown to be more important than the iron content of a certain food. Over 95% of dietary iron is found as non-heme iron, the absorption of which is influenced by enhancers such as ascorbic acid [4] or inhibitors such as tannins [5], phytates [6], and calcium [7]. The main food source during early life is milk. However, this food has very low quantities of iron. Cow's milk has between 0.40 and 0.59 mg of iron/L and human milk has between 0.20 and 0.69 mg of iron/L [8]. Despite this similarity, 49% of the iron bioavailability of human milk is significantly higher than 19% of cow's milk [9]. This lower bioavailability of iron in cow's milk has mainly been attributed to calcium and to the proteins contained in this food [10]. When cow's milk is fortified with 15 mg of iron as ferrous sulfate, its bioavailability is reduced to 4%-6% and it is doubled when ascorbic acid is added in a molar ratio to iron of 2:1 [11]. Due to ethical constraints, and due to the use of radioisotopes, we use women as a surrogate for infants. Hurrell et al., have demonstrated that results obtained in adults on Fe absorption from infant formulas can be extrapolated to infants [12]. The purpose of this study was to measure the bioavailability of two iron fortified milk formulas designed to cover the nutritional needs of toddlers. These milks were fortified with iron sulfate stabilized with maltodextrin and citric acid. Experimental Section Subjects: Apparently healthy females between 35 and 46 years old using a birth control method (e.g., intrauterine device, oral contraceptive, or tube ligation) were recruited by local advertisements. The subjects were informed of study details and the first 15 women that agreed to participate in the study were selected. All of them signed a written informed consent previously approved by the Ethical Committee of the Institute of Nutrition and Food Technology (INTA) of the University of Chile (Approval Act No. 35, Wednesday, 13 November 2013). The Chilean Commission on Nuclear Energy approved the doses of radioisotopes used. None of the women were pregnant, as confirmed by a negative test for human chorionic gonadotropin in urine. None had consumed any vitamin or mineral supplement in the previous six months. Study design: Formula contents of total protein, casein, maltodextrin, calcium, iron, ascorbic acid, and prebiotic are given in Table 1. Milk based formulas and cow's milk in powdered form were prepared according to manufacturer instructions and tested. Formula A (Nutrilon 3 ) and Formula B (Vital 3 ) were manufactured by Kasdorf S.A, Buenos Aires, Argentina. Non-fortified Cow's milk was prepared by Milkaut S.A., Santa Fe, Argentina. The chemical composition of formulas was obtained from the label of the products. Iron isotopes ( 59 Fe and 55 Fe) of high specific activity were used as tracers (Du Pont de Nemours, Wilmington, DE, USA). Milk formulas and ferrous ascorbate aqueous solutions were mixed with isotopes immediately before administration to the subjects. New iron format, where the iron is encapsulated in a carrier material of maltodextrin, stabilized by citric acid was labeled intrinsically during the synthesis. This process was performed by the manufacturer. In brief, the iron was dissolved in food grade distilled water as anhydrous ferrous sulfate (Paul Lohmann, Germany) and 55 FeCl 3 or 59 FeCl 3 was added as tracer. Then, the iron solution was mixed with citric acid at 70˝C. After 10 min maltodextrin was added at 72% w/w at 45˝C. The specific activity of the labeled iron compound was 555 kBq of 55 Fe and 185 kBq of 59 Fe per mg elemental iron. Milk formulas and ferrous ascorbate were consumed after an overnight fast and no food or beverages other than water were allowed for the following 4 h after the ingestion of the test products. No additional dietary restrictions were provided. On day 1, the subjects ingested 200 mL of milk formula the Formula A, diluted to 14.8%, labeled with 111 kBq of 55 Fe; on day 2, they ingested 200 mL of the milk formula Formula B, diluted to 14% labeled with 37 kBq of 59 Fe. A venous blood sample was obtained two weeks later (day 14) to measure the circulating radioactivity and to determine the iron status of the subjects. This same sample also provided baseline values of 55 Fe and 59 Fe radioactivity in red blood cells for the next set of absorption studies. On day 14, subjects were given 30 mL of a solution with 3 mg iron and 18.9 mg ascorbic acid labeled with 37 kBq of 59 Fe, as a reference dose. On day 15, subjects ingested 200 mL of cow's milk, diluted to 12%, fortified with 8 mg iron per 100 g of powder (as ferrous sulfate) labeled with 111 kBq of 55 Fe. A final venous sample was obtained on day 28 to determine the increase in red blood cell radioactivity. Blood analysis: Venous blood samples were obtained on day 14 to determine iron status of the volunteers, and on day 14 and 28 to measure circulating radioactivity. Hemoglobin (Hb) and mean corpuscular volume (MCV) were measured by electronic cell counter (CELL-DYN 1700; ABBOTT Diagnostics, Abbott Park, IL, USA). Zinc protoporphyrin (Zpp) was determined in a ZP Hematofluorometer Model 206D; (AVIV Biomedical Inc., Lakewood, NJ, USA) and serum ferritin (SF) was measured by ELISA assay [13]. For the calculation of total radioactivity ingested, aliquots of the compounds were counted in sextuplicates as standards. Measurement of blood radioactivity was performed in duplicate venous samples according to the Eakins and Brown technique [14]. The samples were counted allowing sufficient time period to obtain a counting error of~3% in a liquid-scintillation counter (Beckman LS 5000 TD; Beckman Instruments, Fullerton, CA, USA). Radioactivity from labeled solution aliquots and venous samples were counted simultaneously at the end of the study to avoid an error in the calculation of iron absorption due to the decay of isotopes between administration and the absorption measurement 14 days later. In addition, absorptions of labeled iron administered on days 14 and 15 were corrected for the isotope given on days 1 and 2 by subtracting the radioactivity of the blood sample of day 14 from red blood cell radioactivity of day 28. The percentages of iron absorption were calculated on the basis of blood volume estimated for height and weight [15], and assuming 80% incorporation of the radioisotope into erythrocytes [16]. This method is reproducible in our laboratory with a coefficient variation of 5%. Statistical Analysis: A sample size of nine subjects was calculated using the software PRIMER, version 3.02, option "power and simple size of analysis of variance (ANOVA)". The sample size was calculated with an α error of 0.05, a power of 80%, an expected residual standard deviation of three, a number of treatment groups of four and a minimum detectable iron bioavailability difference of 5%. For the study, 15 volunteers were considered in order to account for possible participants lost due to the rejection of intake, and/or the presence of diarrhea or vomiting, producing significant losses of the administered compounds. Because the percentages of iron absorption and serum ferritin had a skewed distribution, these values were log-transformed before calculating means and SDs or performing statistical analyses. Results were re-transformed to recover original units and are expressed as geometric means˘1 standard deviation (SD). The iron bioavailability of each milk formula was corrected to 40% of the iron bioavailability of ferrous ascorbate [17]. Such assessment is made for the purpose of standardizing the comparison of results with other absorption studies. The relationship between the iron absorption and SF was evaluated by a Pearson correlation. Differences in iron absorption were evaluated by a one way ANOVA for repeated measures and post hoc Sheffé (Statistica for Windows, release 4.5; StatSoft Inc., Tulsa, OK, USA). All comparisons were done at the 5% level of significance. Table 2 shows that the iron nutrition status of the subjects was deficient. A women suffered iron deficiency anemia (Hb < 120 g/L and ě2 altered biochemical parameters: MCV < 80 fL and/or Zpp > 70 ug/dL RBC and/or %Sat > 15 and/or FS ď 12 µg/dL) and other 8 women had iron deficiency without anemia (Hb = normal and ě 2 altered biochemical parameters). Table 3 shows the study's individual iron bioavailability results. It is observed that the average bioavailability of the reference dose was 38.3% and that it corresponds to the iron absorption of a population deficient in iron, which is similar to the target age group of Formulas A and B. The relationship between the iron bioavailability of the reference dose and the serum ferritin levels of the subjects had a Pearson's correlation coefficient of 0.79 (p < 0.001). The milk formulas A and B had an iron bioavailability of 19.7 and 19.8%, respectively, versus a 7.2% of fortified cow's milk (one way ANOVA for repeated measures F = 157; p < 0.001). The post hoc Sheffé test did not show significant differences between Formulas A and B but there were indeed differences between the milk formulas and the cow's milk (p < 0.001). The iron bioavailability of modified milks and cow's milk had differences with respect to the reference dose of ferrous ascorbate (p < 0.001). Upon correcting the iron bioavailability figures of milk products to 40% of the reference dose [17] it is observed that the geometric mean bioavailability for Formulas A and B was 20.6 and 20.7% respectively, versus 7.5% of iron fortified cow's milk (Figure 1). Discussion Young children are particularly vulnerable to iron deficiency due to an increase of iron requirements determined by their fast growth [18], inadequate intake of the mineral and/or consumption of low-bioavailability iron. Many young children do not consume large quantities of food rich in bioavailable iron such as red meat. Even in a theoretical model of diet the conclusion Discussion Young children are particularly vulnerable to iron deficiency due to an increase of iron requirements determined by their fast growth [18], inadequate intake of the mineral and/or consumption of low-bioavailability iron. Many young children do not consume large quantities of food rich in bioavailable iron such as red meat. Even in a theoretical model of diet the conclusion was that it is very difficult to reach the recommended intakes of iron with a diet that perfectly adjusts to the food guides for infants and young children [19]. Iron deficiency anemia in children is linked to an increase of morbidity, a reduction in the cognitive development and, therefore, a drop in school activity. It has been evidenced that, when iron deficiency takes place during an early age, the damage to the psychomotor development may be irreversible, even after supplementation with iron [20,21]. Several actions have been proposed as strategies to lower iron deficiency in young children, including the diversification of diets by including food rich in highly-absorbable iron, treatment with anti-parasite medication, and the supplementation and fortification of food with iron [22]. This last strategy has been the most effective one to significantly reduce the prevalence of iron deficiency anemia in children [22][23][24]. The stabilized iron sulfate has been tested in different recipes for infant formulas, follow on formulas, and growing up milks and has proved to be stable for about 1.5-2 years shelf life, preserving the sensory characteristics and stability of fat, including long chain polyunsaturated fatty acids. This study showed that the iron contained in the milk formulas A and B is very well absorbed, with an average 20% bioavailability. A figure similar to the one previously shown by Hertrampf et al., in bioavailability studies of highly modified commercial infant milk formulas [25]. Regarding the absorption of iron fortified cow's milk, it must be highlighted that it was similar to what was informed in the literature [11,26]. The only major difference between the Formulas A and B was the first had prebiotics. As iron absorption from both formulas was similar it is concluded that prebiotics did not have an effect on iron absorption. This is consistent with other human studies that demonstrate no effect of these compounds [27,28]. Bioavailability data make it possible to estimate that a toddler consuming 500 mL of Formulas A and B on a daily basis would absorb approximately 1.2 mg of iron per day, which would cover over a 100% of their Recommended Daily Intakes, and which translates into an excellent contribution of this nutrient to the diet of young children [29]. Even if Formulas A and B provide sufficient quantities of iron to young children, there is a need to complement their diet by including meat, fish, fruits, and vegetables so as to provide them with other nutrients such as proteins, unsaturated fats, and vitamins that favor their complete growth and development. Conclusions In conclusion, both A and B milk formulas contain highly bioavailable iron, which contributes to covering the requirements of this micronutrient in toddlers. Acknowledgments: The study was supported by Danone Nutricia, Early Life Nutrition Argentina and New Countries. Author Contributions: All authors contributed to the manuscript preparation. F.P. and M.O. collected samples, obtained data, and/or analyzed data; F.P. and E.M. designed the study; E.M, G.K., and N.C. designed the milk formulas of study. All authors read and approved the final manuscript. Conflicts of Interest: The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

v3-fos

2018-04-03T02:55:03.612Z

2015-09-17T00:00:00.000Z

9095999

s2

Chilean Strawberry Consumption Protects against LPS-Induced Liver Injury by Anti-Inflammatory and Antioxidant Capability in Sprague-Dawley Rats The Chilean strawberry fruit has high content of antioxidants and polyphenols. Previous studies evidenced antioxidant properties by in vitro methods. However, the antioxidant effect and its impact as functional food on animal health have not been evaluated. In this study, rats were fed with a Chilean strawberry aqueous extract (4 g/kg of animal per day) and then subjected to LPS-induced liver injury (5 mg/kg). Transaminases and histological studies revealed a reduction in liver injury in rats fed with strawberry aqueous extract compared with the control group. Additionally, white strawberry supplementation significantly reduced the serum levels and gene expression of TNF-α, IL-6, and IL-1β cytokines compared with nonsupplemented rats. The level of F2-isoprostanes and GSH/GSSG indicated a reduction in liver oxidative stress by the consumption of strawberry aqueous extract. Altogether, the evidence suggests that dietary supplementation of rats with a Chilean white strawberry aqueous extract favours the normalization of oxidative and inflammatory responses after a liver injury induced by LPS. Introduction The native white Chilean strawberry (Fragaria chiloensis spp. chiloensis) is a native species from Chile and the maternal progenitor of the commercial strawberry (Fragaria x ananassa Duch) [1]. The Mapuche people cultivated this plant as a nutritive food, consumed as fresh or dried fruit or prepared for medicinal purposes [2]. During the last decade, in Chile there has been an increasing interest in expanding the culture and production of F. chiloensis to gain a niche in the local and global market, as well as take advantage of a resurgent interest in new crops [3]. Berry fruits are known to have an antioxidant effect that could prevent different pathological conditions [4]. Strawberry fruits possess a remarkable nutritional composition due to their high content of micronutrients such as folates, minerals, and vitamins and are also a rich source of phenolic constituents [5]. Particularly, white Chilean strawberries have been described as a good source of phenolic antioxidants [6]. Strawberry extracts have higher antioxidant activity compared with other common consumable fruits [7]. The antioxidant properties of strawberries are mainly due to phenolic compounds [8] and this capability has been proven to be effective against superoxide and hydrogen peroxide radicals [9]. In vitro studies have shown that white Chilean strawberry fruit has high free radical scavenging activity [1,8]. Despite the potential of this fruit as antioxidant, there is a lack of information about the in vivo effects on the oxidative status in animal models. Nevertheless, previous studies have reported that the consumption of commercial strawberry fruit provides beneficial health effects. The supplementation of diet with strawberry fruit, as a source of antioxidants, reduced the level of blood lipids and the oxidative damage of LDL in hyperlipidemic subjects [10]. Furthermore, a hypocholesterolemic effect and a decrease in lipid peroxidation were reported [11]. In another study, antiplatelet function 2 Evidence-Based Complementary and Alternative Medicine was evidenced by in vitro and in vivo approaches [12]. On the other hand, anti-inflammatory effect has been evidenced [13], in which strawberries are very effective inhibiting cyclooxygenase (i.e., COX2), a key enzyme in inflammation pathway and a target for different drugs. In addition, recent studies suggest that strawberry polyphenols might have a role in cancer prevention and treatment [5]. Considering that the available knowledge about beneficial health effect of commercial strawberry fruit and the converse scenario of white Chilean strawberry fruit has a different phenolic profile, it becomes relevant to gain insight into its potential properties as functional food. The lipopolysaccharide (LPS) is a major glycolipid component of the outer cell wall of Gram-negative bacteria, made up from a polysaccharide O-chain and a biologically active lipid-A moiety embedded within the bacterial membrane [14]. In rats, LPS triggers the rise of cytokines and reactive oxygen species (ROS) such as superoxide, hydroxyl radicals, and peroxynitrite [15]. The endotoxemia induced by LPS is characterized by the injury of various organs including liver, kidney, and brain [14]. Most of the toxicities observed in LPSinduced liver injury (and systemic) have been attributed to inflammatory mediators produced by activated macrophages, including tumour necrosis factor-(TNF-) and interleukins IL-1 , IL-6, IL-8, and IL-12 [16]. These toxic mediators can induce lipid peroxidation, oxidative damage, and depletion of intracellular stored antioxidants [17], creating a prooxidative and inflammatory status. Therefore, the present study was designed to evaluate the effects of an aqueous solution of strawberry fruit orally administrated on the inflammatory response and oxidative status in a LPS-injured liver. Biochemical changes and histological parameters were analysed. . After harvest, the fruit was immediately cold transported to the Institute of Biological Sciences at University of Talca, and after freezing it under liquid nitrogen it was stored at −80 ∘ C until use. Ripe F. chiloensis fruit was homogenized in distilled water (0.5 g/mL) with the help of an Ultraturrax (5 min at 4000 rpm) on an ice bath. The rats were fed twice a day with F. chiloensis extracts at the daily dosages of 2, 4, and 8 g/kg of animal per day (for the doses-response curve). All the administrations were performed with fresh aqueous extracts (Figure 1(a)). Animal Preparation and LPS-Induction of Liver Injury. Groups of rats were orally supplemented for 10 days with the aqueous F. chiloensis extract 2 g/kg of animal twice a day, that is, 4 g/kg/day of strawberry (Figure 1(b)), while control rat groups received isovolumetric amounts of saline solution (0.9% NaCl). At day 10 the animals were challenged to a LPS sepsis induced by a single intraperitoneal rat injection of 5 mg/kg LPS (lipopolysaccharide endotoxin, Escherichia coli, serotype 0111:B4, Sigma-Aldrich, San Luis, MO, USA) from E. coli 8 [18] dissolved in 0.9% NaCl. These generate four experimental groups: (a) sal-sal (saline pretreatment plus a saline LPS vehicle), (b) sal-LPS (saline pretreatment plus LPS inoculum), (c) Fch-sal (F. chiloensis extract during pretreatment plus LPS vehicle), and (d) Fch-LPS (Fch pretreatment plus LPS inoculum). Five to six animals composed each experimental group. After 3 hours of LPS challenge the animals were anesthetized with an intraperitoneal injection (1 mL/kg) of zolazepam chlorhydrate (25 mg/mL) and tiletamine chlorhydrate (25 mg/mL) (Zoletil 50; Virbac S/A, Carros, France). Blood samples were obtained by cardiac puncture for serum analysis. Liver samples were taken from the medial lobes, frozen in liquid nitrogen, and stored at −80 ∘ C for further analysis. Histological Analysis. Liver samples of each animal were fixed in phosphate-buffered formalin, dehydrated in increasing ethanol concentrations, and embedded in paraffin. Thereafter, sections of tissue were cut at 5 m on a rotatory microtome (Leica Ultracut, Solms, Germany), mounted on clean glass slides, and dried overnight at 37 ∘ C. Sections were cleared, hydrated, and stained with haematoxylin and eosin for histomorphological assessments. Blind histopathological evaluation was performed in at least ten randomly chosen microscopic fields of all histological slides (three to five slides per each animal assayed). All tissue sections were examined in a Nikon Eclipse 50i microscope (Tokyo, Japan) for characterization of histopathological changes. Photographs were digitalized using micrometrics SE premium 2.8 version camera and software for microscopy. Determination of Transaminases, Cytokines, F2-Isoprostanes, and Glutathione Assays. Transaminases levels, AST (aspartate transaminase) and ALT (alanine transaminase), were measured using a specific diagnostic kit (SpinReact, Girona, Spain) and expressed as international units/L. ELISA kits were used for assessment of serum levels (pg/mL) of TNF-, IL-6, IL-1 , and IL-10 cytokines (Biosource International, Camarillo, CA, USA) and F2-isoprostanes (Cayman Chemical, Ann Arbor, MI, USA). GSH and GSSG contents ( mol/g liver) were measured using a specific glutathione assay kit (Cayman Chemical). , and nuclease free water to reach the final reaction volume. The cycling conditions were 1 cycle of denaturation at 95 ∘ C for 5 min, followed by 40 two-segment cycles of amplification (95 ∘ C/15 sec, 60 ∘ C/45 sec) and a final melting cycle (95 ∘ C/1 min, 55 ∘ C/30 sec, and 95 ∘ C/30 sec). From each experimental group (5-6 animals) three liver samples were randomly chosen, from which RNA was independently isolated and cDNA prepared; qPCR runs were performed using three technical replicates and the mean was used for further analysis. Statistical Analysis. All values correspond to means ± standard error of the mean (SEM) or standard deviation (SD). The data were evaluated with GraphPad Prism 6 software (La Jolla, CA, USA). The statistical significance of differences for each parameter among the groups was evaluated by Tukey's test for unpaired data or one-way ANOVA. A value of less than 0.05 was considered significant. Protective Effect of F. chiloensis in Acute LPS-Induced Liver Injury. It has been reported that a LPS challenge induces a liver injury [19,20]. A significant increase in serum AST and ALT transaminases was observed as expected in our experimental conditions ( Figure 2). The effect of several Fch feeding dosages (0.5, 1, and 2 g per day of Fch extract) was tested for their capability to decrease AST and ALT exacerbation after 3 h of LPS challenge (Figure 2(a)). A strong reduction in transaminases was found at a dosage of 4 g/kg/day (2 doses of 2 g/kg of animal Fch) or higher dosages. A dosage of 4 g/kg/day of fruit extract was employed in further experiments. The supplementation of F. chiloensis extract on diet prior to LPS challenge avoids the exacerbation in serum AST (Figure 2(b)) and ALT (Figure 2(c)) activities, and values comparable to those in nonchallenged rats were determined. Control rats subjected to LPS single injection exhibited a 7.8and 4.3-fold increase ( < 0.05) in serum AST and ALT activities, respectively, in comparison to sal-sal treatment, and importantly this increment in activity was suppressed by Fch supplementation. In agreement with these data, liver histological assessments showed normal liver morphology in sal-sal and Fch-sal groups (Figures 3(a) and 3(c), resp.). Changes in liver architecture (disruption) in extensive areas, hepatocytes necrosis, and inflammatory infiltrates were observed in LPS challenged animals (Figure 3(b)). On the contrary, the livers of Fch-LPS group displayed normal architecture, with minimal or absence of necrosis (Figure 3(d)). This indicates that morphological changes induced by LPS are prevented by Fch supplementation. Fragaria chiloensis Reduces the Inflammatory Damage Induced by LPS. Cytokines pro-and anti-inflammatory were determined by ELISA in serum samples obtained from rats subjected to LPS challenge. In addition, gene expression analyses of the same cytokines were performed in liver samples by RT-qPCR. The levels of serum TNF- (Figure 4(a)), IL-6 ( Figure 4(b)), and IL-1 (Figure 4(c)) increased in response to LPS challenge by 2.3-, 1.8-, and 3.7-fold compared to salsal treatment ( < 0.05). In animals supplemented with F. chiloensis fruit extract the increment of cytokines pro-and anti-inflammatory in response to LPS challenge is prevented. There were nonsignificant changes in IL-10 in response to LPS treatment (Figure 4(d)). Liver Oxidative Stress Related Parameters Induced by LPS Are Diminished by F. chiloensis Supplementation. The levels of plasma 8-isoprostanes increased in response to LPS challenge (8.7-fold) compared to sal-sal treatment ( Figure 6). In animals supplemented with F. chiloensis aqueous extract the increment in 8-isoprostanes in response to LPS challenge is avoided. The content of hepatic reduced glutathione (GSH) diminished (23%) in response to LPS challenge compared to control (sal-sal) treatment (Figure 7(a)). The GSH content in animals supplemented with F. chiloensis aqueous extract was similar to controls without LPS inoculum; however a significant enhancement in GSH is observed after LPS challenge (Figure 7(a), inset). On the other hand, liver glutathione disulphide (GSSG) levels increased (23.6%) in response to LPS challenge compared to sal-sal treatment (Figure 7(b)). However, in response to LPS the animals pretreated with F. chiloensis achieved a net reduction in GSSG levels compared to nonsupplemented rats subjected to LPS challenge (Figure 7(b), inset). Discussion The focus of this study was to investigate the acute effects of LPS-induced hepatic damage on the inflammatory response and oxidative stress status and the possible protection offered by the oral administration of an aqueous extract of the native Chilean white strawberry. Typically, a portion of the released endotoxin (LPS) is absorbed into the portal circulation and delivered to the liver, where it is quickly cleared by intrahepatic Küpffer cells [21]; thus the liver plays a central role in the regulation of entry and metabolism of LPS inoculum. The model of LPS has been previously shown to result in a reproducible acute inflammatory response, with increments in cytokines and oxidative stress, mitochondrial dysfunction, and early biochemical changes associated with organ dysfunction, similar to the changes observed in human [22]. Mostly, the hepatic and systemic sepsis (toxicities) induced by LPS have been attributed to an overproduction of reactive oxygen species (ROS) and the release of chemical mediators such as peroxide, nitric oxide, and proinflammatory cytokines (massive release of TNF-, IL-1 , and IL-6), which are all formed as a result of the binding of LPS to Toll-like receptor 4 (TLR-4) on the surface of Küpffer cells [16,23]. As a response, hepatocytes strive to clear LPS, which is followed by inflammation, hepatocellular apoptosis, and even necrosis [24]. Oxidative stress is a well-known mechanism of LPSinduced hepatic injury and produces a redox imbalance which may result in depletion of endogenous antioxidant such as the antioxidant enzymes, alteration of GSH redox status [14], and generation of 8-isoprostanes, free radicalcatalysed products from lipid peroxidation (arachidonic acid derivatives) [25]. The antioxidant defence system and its equilibrium become necessary, especially during infection or against an oxidative insult. There are reports in which plant extracts, infusions, or isolated compounds have been used to reverse or prevent the hepatotoxicity and the oxidative stress generated by LPS, with beneficial effects associated with antioxidant and anti-inflammatory properties: Rooibos aqueous [14], Eucalyptus globulus leaf extract [26], polyphenol extract of Hibiscus sabdariffa [27,28], and fermented Barley extract [29]. In this study, we reported that a single injection of LPS resulted in hepatic injury as indicated by the elevation in the levels of serum ALT and AST, described as circulating markers of hepatocyte injury. The hepatic marker enzymes are cytoplasmic in physiological condition but are usually leaked into circulation when liver damage occurs due to an alteration in membrane integrity [14,30]. Results from the current study showed that supplementation of diet with the aqueous extract of native Chilean white strawberry for 10 days prior to the LPS challenge at a dose of 4 g/kg/day diminished the induced damage in the liver. Several studies have suggested that the phytochemical content and antioxidant/free radical scavenging effect of fruits and vegetables contribute to their protective effect against chronic and degenerative diseases [31]. The contribution of vitamin C to the total antioxidant activity of twelve different fruits analysed was estimated as being <15% [7]. Strawberry extracts were found to have higher antioxidant activity than extracts from other studied fruits. However, vitamin C is not the only one that contributes to the antioxidant activity of fruits and vegetables. The antioxidant properties of strawberries have been shown to be mainly due to high content of phenolic compounds more than to vitamin C [31][32][33]. Wang and Jiao [9] evidenced that strawberry aqueous extract exhibited a high level of antioxidant capacity against free radical species including superoxide radicals, hydrogen peroxide, hydroxyl radicals, and singlet oxygen; also it is important to mention that actually there does not exist any study that links the hepatoprotection with the antioxidant capability of strawberry. The polyphenolic composition, specifically flavonoid and phenolic compounds, of different strawberries cultivars differs amongst them [32,34,35]. In addition, the content of phenolic compounds differs significantly amongst strawberry species and subspecies and determines the free radical scavenging activity of these fruits [8]. The main phenolic compounds in the Chilean white strawberry are ellagic acid and hexahydroxydiphenolic acid-based hydrolysable tannins and procyanidins, as well as flavonol glycosides from quercetin and kaempferol [6] ( Table 1). The protective effect of F. chiloensis extract observed in our study may be due to the ability of its phenolic content to stabilize and maintain the integrity of the hepatocyte as well as repair damage tissue by stimulating hepatocyte regeneration and modulation of Küpffer cell activation. Küpffer cells have well-defined roles in the coordination of hepatic inflammation in a number of diseases [36,37]. During endotoxemia, LPS is detected by Toll-like receptor 4 (TLR4) on sentinel cell (endothelium, Küpffer cells, etc.) that initiates the subsequent inflammatory response, including neutrophil recruitment to the liver [37]. LPS binding to Küpffer cells initiates a cascade of events that upregulates expression of the inflammatory cytokines including TNFstimulating the production of ROS and reactive nitrogen intermediates by activated macrophages causing liver damage due to the oxidative stress. Additionally, LPS induces migration of activated polymorphonuclear leukocytes (PMNs) extending and keeping the liver injury [37]. In the present study, LPS challenge significantly increased levels of TNF-, IL-1 , and IL-6, and the oral administration of F. chiloensis prior to LPS challenge was able to reduce the increment in serum cytokines and the expression level in the liver of related genes at a comparable level compared to that in nonchallenged animals. Interestingly, these results are consistent with the data reported for green tea polyphenols [38], quercetin [39], and resveratrol [40]. These studies have shown an anti-inflammatory effect associated with the control of signal transduction, with the reduction in the expression of proinflammatory proteins (i.e., COX-2), inducible tumour necrosis factor-(TNF-), and nitric oxide synthase. On the other hand, we did not find any difference in the levels of IL-10 cytokines, although IL-10 is produced by macrophages as a negative-feedback mechanism to dampen uncontrolled production of inflammatory cytokines and excessive inflammation during infection. IL-10 is a potent anti-inflammatory cytokine with a broad effect on both innate and adaptive immune system [41]. IL-10 could downregulate TNF-as well as other cytokines by suppressing their gene expression in an autocrine-like feedback loop [42]. As our observations showed that the levels of IL-10 were similar between control and treated groups, these could indicate that the inhibition of the other cytokines observed by F. chiloensis supplementation may be independent of the activation of the feedback mediated by IL-10. Thus, we speculate that the protective effect detected is due to the antioxidant capability of F. chiloensis extract and another molecular mechanism associated with LPS signalling pathway. This idea is reinforced by the observed GSH/GSSG normalization and anti-inflammatory effect. The impairment of the antioxidants defence system is a critical step in LPS-induced injury. Evidence has shown that LPS insult is characterized by change in tissue and circulating antioxidant enzyme's level and antioxidant molecules, like GSH [14]. We found a modulation of the antioxidant system in the LPS-challenged rats consuming F. chiloensis, with the normalization of GSH/GSSG ratio and a depletion of 8isoprostane levels. Reduced glutathione (GSH) is the major nonprotein thiol in plant and animal cells. GSH is recognized as a highly effective antioxidant compound, as its scavenging and antioxidant properties allow the neutralization of ROS species. It is essential for the regulation of a variety of cellular functions [14], and a consistent and sufficient GSH level can prevent LPS-induced damage [43]. The ability to improve the GSH/GSSG ratio shown by F. chiloensis can be ascribed to the capability of the different fruit antioxidant components to quench free radicals, to upregulate the synthesis of GSH, and to restore the antioxidant status, results comparable with the total in vitro scavenging activity determined previously ( Table 1). The glutathione regulation observed is consistent with the low levels of 8-isoprostanes observed in LPS challenged rats supplemented with F. chiloensis extract. Isoprostanes comprise a group of free radical-catalysed peroxidation products of arachidonic acid in a COX (cyclooxygenase) independent mechanism. They are seen as oxidative stress markers and potentially mediate some of the adverse effects of oxidant injury [25,44]. ROS have been reported to drive inflammatory cytokines responses by a mechanism that comprises nuclear factor kappa B transcription factor (NF B) that regulates several cytokines including IL-1 and IL-6 [45]. Some antioxidants such as MitoQ, MitoE, and melatonin can reduce IL-1 and IL-6 levels and decrease NF B activation, effect observed in a rat model with acute LPS sepsis [22]. A recent study suggested that total flavonoids extracted from flowers of Abelmoschus manihot (L.) Medic (TFA) protected mice against carbon tetrachloride-(CCl 4 -) induced Evidence-Based Complementary and Alternative Medicine 9 liver injury through antioxidant stress and anti-inflammatory effects, which decreased the MDA level and elevated the content of GSH in the liver as compared to those in the CCl 4 group. Meanwhile, the inflammatory mediators (e.g., TNF-alpha, IL-1 , and NO) were inhibited by TFA treatment both at the serum and mRNA levels [46]. On the other side, quercetin alleviates inflammation after short-term treatment in high-fat-fed (HFD) mice. Increased nuclear import of NF B and elevated expressions of proinflammatory markers were further manifestations in the HFD group. All these changes were reversed in the quercetin-treated groups with significant improvement of antioxidant activity compared to the HFD group [47]. These data are consistent with the fact that NF B could be the transcription factor that regulates the pathways of hepatoprotection observed in F. chiloensis supplementation. The Pi3K/AKT/NF B signalling pathway is involved in LPS-induced injury; moreover, the NF B signalling pathway is known to play a critical role in sepsisassociated organ failure [18,48]. It has been reported that the flavonoid apigenin inhibits LPS-induced inflammation through inhibition of NF B activation by hypophosphorylation of ser536 in the p65 subunit in in vivo model [48]. Thus, further investigation may be warranted to design the relation between NF B and the liver protection observed in this study. Alternatively, the potential blocking of lipopolysaccharide binding protein (LBP) mechanism might be related to the anti-inflammatory observed results, where LBP is an acute phase protein which plays an important role in lipopolysaccharide (LPS) signalling and innate immunity and their level in acute liver injury and liver failure may significantly affect the physiological derangements that are observed in acute liver failure, liver transplantation, common bile duct ligation, alcoholic liver injury, and hemorrhagic shock [49,50]. However, there have been limited studies of the role of LBP in animal and human models of severe acute liver injury [49]. It is generally accepted that low levels of LBP augment the cell's response to LPS, whereas high levels of LBP have been shown to inhibit cell responses to LPS. Cells with LBP knockout became refractory to proinflammatory cytokines and other inflammatory stimuli (LPS and palmitate). This effect was mediated through decreased NF B signalling and reversed by exogenous LBP [51]. Also the administration of LBPK95A (LBP inhibitory peptide) attenuates liver injury after acetaminophen-induced hepatotoxicity administration as evidenced by reductions in serum transaminase levels and decreased centrilobular necrosis with poor Küpffer cell function; less liver injury was noted in the absence of LBP [50]. Conclusions Our study demonstrates, for the first time, the hepatoprotective activity of a native Chilean strawberry aqueous extract, which maintained hepatocellular membrane structural integrity, attenuated hepatic oxidative stress, and inhibited inflammatory response in LPS-induced liver injury. These effects were achieved by normalization of liver parameters, redox status (GSH/GSSG ratio and decrease of isoprostanes), and downregulation of cytokines (TNFa, IL-1 , and IL-6). The results of this study support the dietary supplementation with Chilean strawberry as a novel noninvasive strategy to protect the liver and other organs against LPS injury. Further experiments are being conducted by our research group.

v3-fos

2017-06-29T19:15:19.811Z

2015-11-19T00:00:00.000Z

14803129

s2

Protective effect of anti-SUAM antibodies on Streptococcus uberis mastitis In the present study, the effect of anti-recombinant Streptococcus uberis adhesion molecule (SUAM) antibodies against S. uberis intramammary infections (IMI) was evaluated using a passive protection model. Mammary quarters of healthy cows were infused with S. uberis UT888 opsonized with affinity purified anti-rSUAM antibodies or hyperimmune sera. Non-opsonized S. uberis UT888 were used as a control. Mammary quarters infused with opsonized S. uberis showed mild-to undetectable clinical symptoms of mastitis, lower milk bacterial counts, and less infected mammary quarters as compared to mammary quarters infused with non-opsonized S. uberis. These findings suggest that anti-rSUAM antibodies interfered with infection of mammary gland by S. uberis which might be through preventing adherence to and internalization into mammary gland cells, thus facilitating clearance of S. uberis, reducing colonization, and causing less IMI. Introduction Environmental streptococci, particularly Streptococcus uberis, account for a significant proportion of mastitis in lactating and nonlactating cows [1][2][3], and heifers [4]. Current prevention and control programs originally designed for the control of contagious mastitis pathogens such as Streptococcus agalactiae are only marginally effective against S. uberis. Susceptibility to S. uberis mastitis varies during the different stages of the lactation cycle, showing the highest prevalence during the early nonlactating and periparturient periods [5,6]. Research conducted in our lab lead to the discovery of a novel S. uberis virulence factor identified as S. uberis adhesion molecule (SUAM) [7]. SUAM is a fibrillar surface protein associated with the S. uberis cell wall by a hydrophobic region, and has affinity for lactoferrin (LF). Further in vitro studies showed that SUAM plays a central role during the early events of S. uberis IMI via adherence to and internalization into bovine mammary epithelial cells (BMEC). Mechanisms underlying the pathogenic involvement of SUAM rely partially on its affinity for LF, which together with a putative receptor on the surface of BMEC creates a molecular bridge which facilitates adherence to and internalization of S. uberis into BMEC [7][8][9]. We also discovered that SUAM has a LF-independent domain that also mediates adherence and internalization, and that anti-SUAM antibodies blocked both pathogenic mechanisms [9]. Further studies using a SUAM deletion mutant showed that adherence and internalization of the SUAM mutant strain into BMEC was markedly reduced as compared with the parent S. uberis strain [10]. In an attempt to enhance mammary immunity during the late nonlactating and periparturient periods, we conducted a vaccination study using recombinant SUAM (rSUAM) as antigen. Results showed that significant increases in anti-rSUAM antibodies in serum and mammary secretions can be achieved during these high mastitis prevalence periods [11]. Furthermore, vaccination-induced anti-rSUAM antibodies inhibited in vitro adherence to and internalization of S. uberis into BMEC [11]. The purpose of the present study was to extend our observations by using an in vivo approach to evaluate the effect of anti-rSUAM antibodies on the pathogenesis of S. uberis IMI. Antibody production Recombinant SUAM was purified as described [11]. Concentrated rSUAM was sent to Quality Bioresources, Inc. (Seguin, TX, USA) for production of antibodies. Anti-rSUAM antibodies were affinity purified from sera of rSUAM-immunized steers using rSUAM conjugated to Ultra Link Biosupport (Thermo Scientific, Rockford, IL, USA) and eluted with 0.1 M citrate buffer. Final antibody concentration as determined by ELISA was 21.0 mg/mL. Bacterial strain, culture conditions and preparation of challenge suspension Streptococcus uberis UT888, a strain originally isolated from a cow with chronic mastitis, was used in this study [1]. Frozen stocks of S. uberis UT888 were thawed in a 37 °C water bath, streaked onto blood agar plates (BAP), and incubated for 16 h at 37 °C in a CO 2 : air balanced incubator. A single colony from the BAP culture was used to inoculate 50 mL of Todd Hewitt broth (THB, Becton-Dickinson, Franklin Lakes, NJ, USA) and incubated for 16 h at 37 °C in an orbital rocking incubator at 150 rpm. The resulting suspension was then diluted in PBS (pH 7.4) to a concentration of 4.0 log 10 colony forming units/mL (CFU/mL), mixed with anti-rSUAM antibodies at a final concentration of 15.0 mg/mL and further incubated for 1 h at 37 °C. The challenge suspension used for positive control mammary quarters was prepared in parallel but omitting the addition of anti-rSUAM antibodies. Challenge protocol Twenty mastitis-free (negative bacteriological culture and milk SCC <250 000 cells/mL at quarter level) Holstein cows in their 2nd and 3rd lactations and in their first 60 days of the lactation were used. Cows were allocated randomly to the experimental (n = 10) or positive control (n = 10) groups. One mammary quarter of each cow in the experimental group was infused with S. uberis UT888 opsonized with affinity-purified anti-rSUAM antibodies (opsonized S. uberis). One uninfected mammary quarter of cows in the control group was infused with non-opsonized S. uberis UT888. Non-infused quarters were used as negative controls. The experimental IMI protocol was approved by The University of Tennessee Institutional Animal Care and Use Committee. Clinical assessment of animals following challenge Challenged cows were monitored twice daily during the 1st week (CH0 through CH + 7), and once daily at CH + 10 and CH + 14. During these inspections, rectal temperature, clinical assessment of milk and mammary glands, as well as local signs of inflammation were monitored and recorded. Milk and mammary scores were evaluated using a scoring system described in Table 1. Mammary quarters were considered infected and classified as IMI as described [12]. Subclinical mastitis was defined as quarters without clinical signs having positive isolation of S. uberis (≥500 colony forming units per mL (CFU/mL)) and/or corresponding increase of SCC (>2.5 × 10 5 ). Clinical mastitis was defined as quarters having scores of >2 for milk and mammary appearance. Milk sample evaluation Samples of foremilk were collected aseptically from each mammary quarter 7 days before challenge (CH − 7), immediately before challenge, twice daily at milking from CH0 through CH + 7 and once daily at CH + 10 and CH + 14. Microbiological evaluation of milk samples was done following procedures recommended by NMC. Identification of S. uberis strains used was as described [4,13]. Milk somatic cell counts (SCC) were analyzed at the Dairy Herd Improvement Association Laboratory, Knoxville, TN, USA. Statistical analysis Data on mammary scores, SCC and bacterial counts were analyzed using SAS software (Cary, NC, USA). A mixed model repeated measures (autoregressive variance structure) with cow as the subject was used to compare strains, time, and their interaction. Least squares means were separated using Fisher's protected LSD at the 5% significance level. Variables were Mammary scores Inflammatory changes in milk and mammary quarters infused with opsonized S. uberis were significantly lower than in cows infused with non-opsonized S. uberis (positive control group) (Figure 1). Mammary quarters infused with non-opsonized S. uberis began to show clinical signs of mastitis 36 h post-challenge, reaching the highest milk appearance and mammary score/demeanor at 3 (CH + 3) and 6 (CH + 6) days post-challenge, respectively. In contrast, mammary quarters infused with opsonized S. uberis had the highest milk appearance and mammary score 1 week post-challenge. During days 2-9 post-challenge, mammary scores of quarters infused with opsonized S. uberis were significantly lower than changes observed in mammary quarters infused with nonopsonized S. uberis (P ≤ 0.05). No scores were detected in milk or mammary gland parenchyma of non-infused quarters (negative controls). Microbiological findings Milk from mammary quarters infused with opsonized S. uberis had significantly lower bacterial counts than quarters infused with non-opsonized S. uberis (Figure 2). In mammary quarters challenged with non-opsonized S. uberis, the maximum numbers of bacteria in milk were detected on days 3 and 6 post-challenge and were about 2.5 log 10 higher than values used to challenge mammary quarters. In contrast, during the same period (CH + 2-CH + 6), numbers of bacteria in milk from mammary quarters infused with opsonized S. uberis were significantly lower than the corresponding number for the control group (P ≤ 0.05). No bacteria were isolated from milk of the negative controls quarters. Somatic cell counts Somatic cells counts in milk of challenged quarters of the opsonized and control group, increased markedly after challenge and continued increase throughout the observation period ( Figure 3). Somatic cell counts of the opsonized group were lower than these of the control groups reaching statistically significant level at CH + 6 and CH + 7 (P ≤ 0.05). Clinical signs Sixty percent of mammary quarters infused with nonopsonized S. uberis developed clinical mastitis and such percentage was significantly higher as compared to mammary quarters infused with opsonized S. uberis ( Figure 4). Intramammary infections (IMI) were detected in all quarters infused with the non-opsonized strain and in 10% of the quarters infused with S. uberis treated with anti-rSUAM antibodies. In addition, by the day 14 after challenge, IMI was detected in 50% of the quarters. In contrast, 20% of the quarters of the opsonized group had IMI. Only mild clinical signs of mastitis were observed in mammary quarters infused with opsonized S. uberis and while 50% of the control cows required antibiotic therapy, no treatment was needed for cows in the opsonized group (data not shown). Discussion In a previous communication, we reported a novel virulence factor from S. uberis identified as S. uberis adhesion molecule (SUAM) [7]. Further research showed that this molecule had a central role on adherence and internalization of S. uberis into BMEC and that anti SUAM antibodies from immunized cows were able to reduce adherence to and internalization of S. uberis into BMEC [11]. Even though these results were very promising, the lack of data generated from in vivo approaches was the piece missing in our research. To solve this void, we conducted an in vivo passive protection assay to specifically answer the question about the protective effect of anti-SUAM antibodies. Passive immunity is the transfer of antibodies from one individual to another and occurs naturally when maternal antibodies are transferred to the fetus through the placenta, or when antibodies specific for a pathogen or toxin are passively transferred to achieve immediate protection against a specific pathogen [14]. Passive protection is the status obtained by passive immunity and assays directed to test the efficacy of specific antibodies to neutralize pathogens or toxins are known as in vivo passive protection assay. Typically, in vivo passive protection assay consists of treatment of susceptible individuals with specific antibodies before experimental exposure to the target pathogen. Protective effect of the test antibodies is determined by measuring the reduction of symptoms or progression of the disease as compared to non-treated controls [15][16][17]. In this study, we used a variation of such a method. In our approach, S. uberis was opsonized with anti-rSUAM antibodies prior to infusion into healthy mammary glands of dairy cows and similarly as a control the same non-treated strain infused into healthy mammary glands. Results showed that mammary quarters infused with S. uberis opsonized with anti-rSUAM antibodies had less clinical mastitis, with mild symptoms, and lower bacterial counts in milk as compared to control quarters. Somatic cells counts and bacterial counts in CFU/mL were lower in mammary glands infused with S. uberis opsonized with anti-rSUAM antibodies from CH + 2 to CH + 5. In spite of these differences, by CH + 10 CFU/mL were higher in milk of quarters infused with opsonized S. uberis that in the control group. Such differences could be due to the fact that in absence of active production of anti-SUAM antibodies, a fraction of S. uberis not affected by the blocking effect of these antibodies or innate defenses of the mammary gland follow the pathogenic pathways of S. uberis IMI, resulting in augmented CFU/mL in the milk of these cows. It is important to note that the concentration of anti-rSUAM antibodies used (15.0 mg/ mL) was about 5 times more concentrated than normal IgG values (~3 mg/mL) during the peripartum period in dairy cows, as reported [18]. This suggests that optimization of local antibody responses through strategic vaccination schedules and routes of administration need to be achieved in order to confer effective protection during the peripartum period. Findings reported in this communication indicate that anti-rSUAM antibodies have a protective effect against S. uberis IMI, possibly either by blocking adherence and internalization of S. uberis into host cells [11], and/or likely by mediating the S. uberis phagocytosis by neutrophils and macrophages in the mammary glands. These findings confirm our previous in vitro observations about the protective role of anti-rSUAM antibodies [11] and establish the value of our in vitro experimental model based on cocultures of BMEC with S. uberis as an initial step in identification of S. uberis virulence factors. In conclusion, results from this investigation demonstrated that anti-rSUAM antibodies partially protected mammary glands from S. uberis infection following experimental challenge most likely by preventing adhesion and invasion of bacteria into host cells and/or through opsono-phagocytic removal of bacteria by phagocytic cells.

v3-fos

2018-04-03T01:56:01.069Z

2015-09-01T00:00:00.000Z

12934909

s2

Design, Development and Rationalization of Sarpagandha Ghanvati Sarpagandha ghanvati is a classical Ayurvedic formulation widely prescribed for anxiety and insomnia. It contains Sarpagandha (roots of Rauwolfia serpentina L. (Benth.) Ex Kurz; Family: Apocyanaceae), Khurasani ajowan (Hyocyamus niger L.; Family: Solanaceae) seeds, Jatamansi (Nardostachys jatamansi DC. Family: Valerianaceae) roots and Pipplamul (root of Piper longum L.; Family: Piperaceae). The objective of this study was to make a comparative evaluation of Ghanvatis and tablets of this formulation. Two tablet formulations were prepared; one incorporating only powders of all ingredients; the other with ethanol extracts of the first three ingredients and powder of Piper longum root. Similarly, two types of Sarpagandha ghanvati pills were prepared; one as per Ayurvedic Formulary of India; the other with ethanol extracts of the first three ingredients and powder of Piper longum root. Alcohol extracted 0.22% w/w of total alkaloids as against 0.061% w/w extracted by water. Tablets prepared with powders of all the ingredients had friability more than 3.0% where as those prepared with ethanol extract had very low friability. Ghanvatis, prepared as per the Ayurvedic formulary, did not show reserpine although other alkaloids were present. They showed less content uniformity and lower drug release. Ethanol extracted reserpine along with other alkaloids. Ghanvatis made with the alcoholic extracts exhibited better content uniformity and drug release than the traditional formulation. Tablets prepared with powders or extracts of the ingredients exhibited good content uniformity but the release of alkaloids from the tablets of powders was only 80%. Tablets of the extracts had good content uniformity with 90% release of the total alkaloids. Tablets prepared with alcoholic extracts using 1% polyvinylpyrrolidone as binder and 5% dried starch powder as disintegrating agent confirmed to all the requirements. Thus, the study shows tablets made with the extracts are superior to Ghanvatis and powder tablets. Ghanvatis prepared from ethanol extract of the ingredients. Powders of Rauwolfia root, Hyocyamus seed, Jatamansi root and Pipali root were purchased from an established local supplier, L. V. Gandhi and Sons, Ahmedabad, India and passed through a 60 mesh sieve. Other material used in this study such as lactose, microcrystalline cellulose (MCC), starch, gum acacia, polyvinylpyrrolidone (PVP), magnesium stearate and talc (Pharmacopoeial grade) were purchased from Saraiya Chemicals, Ahmedabad, India. Reserpine reference standard was gifted by Vinkem Labs. Private Limited, Kakkalur, Tiruvallur, India. TLC plates (0.2 mm thick) pre-coated with silica gel 60 F 254 (Cat. No. 1.05548, E. Merck, Darmstadt, Germany) were used. Absorbance of the color complex between the alkaloids and the acid dye was measured on a spectrophotometer (Elico, Hyderabad, India). Distilled water was used throughout the study and rectified spirit was used for the preparation of ethanol extracts. All chemicals used for the analysis were of analytical reagent grade. Various methods have been attempted to extract the alkaloids from R. serpentina powder. Simple cold maceration overnight employing water/chloroform/ ethanol/ethanol plus hydrochloric acid (1.0% v/v) was attempted and the total alkaloids extracted were assayed. Similarly, the drug powder was refluxed in alcohol plus hydrochloric acid (1.0% v/v) and the extracted alkaloids quantified. The extracts obtained in the above processes were spotted on a Silica gel GF 254 pre-coated aluminum plate and run in a solvent system consisting of toluene:ethyl acetate: diethyl amine (7:2:1) along with standard reserpine. The spots were visualized by spraying with modified Dragendorff's reagent to note the number of alkaloid spots and their R f values. Total alkaloids of R. serpentine in the formulations have been estimated using a method reported by Pundarikakshudu et al. [2] . This method is based on the formation of an ion pair complex between alkaloids and methyl orange at pH 4.5, which can be extracted in to chloroform, followed by release of the dye from the chloroform in to hydrochloric acid. Standard solution of reserpine (1 mg/ml) was prepared by dissolving 100 mg reserpine in 10 ml of chloroform and making the volume to 100 ml with methanol. Ten millilitres each of 5, 10, 15, 20, 25, 30 and 35 mg/ml concentration of reserpine was made by proper dilutions of standard solution with chloroform. It was taken in to a separating funnel, 5 ml of acetate buffer (pH 4.5) and 3 ml of 0.05% methyl orange solutions were added and the contents were shaken well. The complex formed was extracted thrice with chloroform (3×10 ml). The pooled chloroform extracts containing the complex were transferred to another separating funnel containing 25 ml of 1 M hydrochloric acid. The dye liberated in to hydrochloric acid from the complex was measured against a blank at 530 nm. Blank was prepared by the same method described above without addition of reserpine. The absorbance values were plotted against their respective concentrations of reserpine to obtain a linearity curve. For the extraction of alkaloids from the formulations, weighed quantities of the dosage forms were taken, moistened with 10% ammonia (2 ml), dried and refluxed with chloroform (50 ml) for 1 h. This mixture was filtered, filtrate concentrated and volume was adjusted to 25 ml with chloroform. Measured volume (0.5 ml) of this extract was taken and diluted to 10 ml with chloroform in a volumetric flask. This was treated with reagents as described above. The amount of total alkaloids from the dosage forms were calculated from the calibration curve and represented as reserpine. All experiments were carried out in triplicates. Sarpagandha ghanvatis were prepared by blending 11 part of Rauwolfia serpentina, 2 part of Hyocyamus niger, 1 part Nardostachys jatamansi, macerating and shaking occasionally for 24 h in water, warming, filtering and concentrating the extracts on water bath to 1 part to which 1 part of Piper longum root powder was added to make pills of 375 mg dry weight. For the preparation of Sarpagandha ghanvati of alcoholic extract (SGAE), 100 g powder of each drug was extracted separately in 95% ethanol with Soxhlet apparatus up to complete extraction of the drug. The extracts were filtered and concentrated on a water bath at 50±1° till a gummy mass was obtained. Sarpagandha ghanvatis of alcoholic extracts (SGAE) were prepared by mixing amount of extracts representing 11 part Rauwolfia root, 2 part Hyocyamus seed, and 1 part Jatamansi root. One part of this mixed extracts is added to 1 part of Pipali root powder. This was rolled into pills and dried at 50° to get pills of 375 mg. Tablets of SGAE were prepared by wet granulation technique. The extracts and pippali powder were mixed as described for the extract Ghanvatis. Since the extract is semisolid, less amount of binder would be necessary to prepare tablets. Diluent was selected on the basis of the results of previous study. PVP (1, 2 and 3%) or starch paste (3, 5 and 7%) and dried starch (5%) were added as binder and disintegrating agent, respectively. Granules were compressed using a Dhiman made single stroke multi punch tablet press with round punches. The tablets had an average weight of 300 mg. Ghanvatis made as per API were analyzed for the presence of reserpine by thin layer chromatography using mobile phase toluene:ethyl acetate: diethylamine (7:2:1). They were also evaluated for total alkaloids, crushing strength, disintegration time and release of the total alkaloids. Tablets made up of SGAE and powder ingredients of Sarpagandha ghanvati were evaluated for pre formulation and post formulation parameters. Angle of repose, Carr's index, Hausner's ratio, crushing strength, friability and disintegrating time were measured as per standard methods [3] . The best tablet formulation of SGAE/powders and Ghanvatis made from alcoholic/water extracts were subjected to in vitro dissolution study in USP 24 dissolution apparatus type II at 37±0.5° and at 100 rpm using simulated gastric fluid (pH 1.2) as dissolution medium. The dissolution medium was filtered through a Whatman filter paper and basified with ammonia to pH 9.0. The liberated alkaloids are extracted into chloroform (3×15 ml), chloroform extracts pooled, dried over anhydrous sodium sulphate and color developed as described above with acid dye reagent. In Sarpagandha ghanvati, Rauwolfia (Sarpagandha) is the main ingredient responsible for the therapeutic activity. About 30 alkaloids are reported to be present in Rauwolfia of which reserpine is the main alkaloid. Hence, we evaluated the formulations and raw material in terms of this alkaloid. Water did not extract reserpine but only some alkaloids other than reserpine were extracted. Ethanol and chloroform were found to be equally efficient, which extracted 0.22% w/w of total alkaloids including reserpine as the main alkaloid. The total alkaloids extracted in water were only 0.061% w/w. There was around 50% increase in efficiency of alkaloid extraction when acidic alcohol was used instead of only ethanol (Table 1). Starch gave better compressibility and flow properties as compared to other diluents ( Table 2). Starch paste and starch paste plus gum acacia did not give satisfactory results. As shown in Table 3, tablets prepared with starch paste and starch paste plus gum acacia had very high friability (1.7-5.2%) and low crushing strength (2.4-2.8 kgf). Polyvinyl pyrrolidone (PVP) at 3 and 5% showed better tablet hardness and low disintegration time, but the friability was more than 3%. Tablets of alcoholic extracts were prepared using wet granulation method. All the batches showed very good crushing strength at low concentration of binders. PVP gave better binding and hardness (6.0-8.5 kgf) in tablets made with ingredient extracts. Friabililty in these tablets was negligible. When starch paste was used in place of PVP, hardness decreased and friability increased ( Table 4). The Ghanvatis of the classical and modified methods had zero friability and 7.0-8.0 kgf crushing strength respectively. But Ghanvatis of the alcohol extracts had very high disintegration time of 45 min as against 18 min of the classical formulation ( Table 5). Tablets of the powders contained 0.65 mg of total alkaloids per tablet while those prepared with the ethanol extracts contained 1.20 mg of the total alkaloids. Ghanvatis prepared with the alcoholic extract had 1.2 mg of total alkaloids per pill while those prepared with the traditional process had only 0.33 mg. Batches WP-2 and WE1 with less disintegration time were selected for dissolution study. Tablets made with the ethanol extract released 90% of the alkaloids whereas powder tablets released 80% of the alkaloids. The release of alkaloids from the pills of the extracts was 71%. Traditional pills released only 56% of the alkaloids ( Table 6). The high disintegration time of the pills is due to non-inclusion of any disintegrating agent like starch powder which has been used in the tablet formulation. Since the total alkaloids have to get released within the 45 min of dissolution study from the powders, there was less release as compared to the release of the alkaloids from the extracts. The low content of the alkaloids in the traditional pills is expected as water was found to be unsuitable for the extraction of the alkaloids. From our experience, we found that it is very difficult to prepare pills of uniform content and it is not possible to predict the exact quantities of the alkaloids in the pills. Ethanol extracted all the alkaloids including reserpine and also gave consistent content uniformity and drug release. There has been a lot of renewed interest in the herbal and Ayurvedic products. Data on process optimization, evaluation of the product for content uniformity, dissolution and others, is not available for many of the classical formulations. Momin et al. and Momin and Pundarikakshudu [4,5] reported the superior nature of triphala tablets over the classical triphala powder and also applied the current understanding of targeted drug delivery systems to the development of colon targeted tablets of triphala. Their studies clearly showed the advantages of the modern dosage forms over the Classical method of preparation of Sarpagandha ghanvati involves concentration of water extract to 1/8 of the volume. Water did not extract the alkaloids effectively and it takes lot of time to concentrate water in large volumes. Hence, tablets prepared with extracts in our studies are superior to the classical pills as they can be manufactured in large scale with ease, evaluated for all the process parameters, and ensure elegant, uniform dosage form of this classical formulation. Financial support and sponsorship: Nil. Conflicts of interest: There are no conflicts of interest.

v3-fos

2016-03-22T00:56:01.885Z

2015-12-01T00:00:00.000Z

2851039

s2

Accurate Mass GC/LC-Quadrupole Time of Flight Mass Spectrometry Analysis of Fatty Acids and Triacylglycerols of Spicy Fruits from the Apiaceae Family The triacylglycerol (TAG) structure and the regio-stereospecific distribution of fatty acids (FA) of seed oils from most of the Apiaceae family are not well documented. The TAG structure ultimately determines the final physical properties of the oils and the position of FAs in the TAG molecule affects the digestion; absorption and metabolism; and physical and technological properties of TAGs. Fixed oils from the fruits of dill (Anethum graveolens), caraway (Carum carvi), cumin (Cuminum cyminum), coriander (Coriandrum sativum), anise (Pimpinella anisum), carrot (Daucus carota), celery (Apium graveolens), fennel (Foeniculum vulgare), and Khella (Ammi visnaga), all from the Apiaceae family, were extracted at room temperature in chloroform/methanol (2:1 v/v) using percolators. Crude lipids were fractionated by solid phase extraction to separate neutral triacylglycerols (TAGs) from other lipids components. Neutral TAGs were subjected to transesterification process to convert them to their corresponding fatty acids methyl esters (FAMES) using 1% boron trifluoride (BF3) in methanol. FAMES were analyzed by gas chromatography-quadrupole time of flight (GC-QTOF) mass spectrometry. Triglycerides were analyzed using high performance liquid chromatography-quadrupole time of flight (LC-QTOF) mass spectrometry. Petroselinic acid was the major fatty acid in all samples ranging from 57% of the total fatty acids in caraway up to 82% in fennel. All samples contained palmitic (16:0), palmitoleic (C16:1n-9), stearic (C18:0), petroselinic (C18:1n-12), linoleic (C18:2n-6), linolinic (18:3n-3), and arachidic (C20:0) acids. TAG were analyzed using LC-QTOF for accurate mass identification and mass spectrometry/mass spectrometry (MS/MS) techniques for regiospesific elucidation of the identified TAGs. Five major TAGs were detected in all samples but with different relative concentrations in all of the tested samples. Several other TAGs were detected as minor components and were present in some samples and absence in the others. Regiospecific analysis showed a non-random fatty acids distribution. Petroselinic acid was predominantly located at the sn-1 and sn-3 positions. Introduction The botanical Apiaceae family also known as Umbelliferae or the parsley family is one of the major families for culinary herbs and root crops comprising up to 400 genera of plants distributed throughout a wide variety of habitats in the temperate climate regions of the world [1]. Plants are widely used as vegetables, food spices, herbal folk remedies and as ornamentals [2]. Many seed oils of the family are rich in petroselinic acid (6Z-octadec-6-enoic acid) also known as 18:1n-12, which represent an Molecules 2015, 20, 21421-21432; doi:10.3390/molecules201219779 www.mdpi.com/journal/molecules interesting oleochemical for the food, cosmetics, and pharmaceutical industries [3,4]. Most medicinal and aromatic plants are often used as spices, vegetables or drugs owing to the presence of useful secondary metabolites. Some of them are known for their high level of polyunsaturated fatty acid in seed oil such as the fruits of the Apiaceae family [5,6]. The triacylglycerol (TAG) structure and the regio-and stereospecific distribution of fatty acids (FA) of seed oils from most of the Apiaceae family are not well documented. FA analysis can be used to evaluate the composition, stability and nutritional quality of fats and oils, but not their functional properties; however, the TAG structure ultimately determines the final physical properties of the oils. The position of FAs in the TAG molecule affects the digestion, absorption and metabolism, and physical and technological properties of TAGs, as it is known that gastric and pancreatic lipases are regioselective. Thus, the objectives of the present work were to use accurate mass spectrometry to identify the structure and regiostereochemistry of TAG species present in selected common seed oils of the Apiaceae family. Fatty Acids Composition Oil yield for extracted fruit ranged from 10 to 23 g/100 g of fruits with cumin giving the highest yield of oil and celery being the least, as shown in Table 1. Fatty acids compositions of the purified neutral triglycerides were analyzed in the form of methyl esters using accurate mass (GC-QTOF) mass spectrometry. Relative percentage composition of fatty acids methyl esters (FAMES) in each oil is shown in Table 1. FAMES were identified based on their retention times and their accurate mass data. Their electron ionization fragmentation and mass spectral data were also searched using Wiley10NIST mass spectral database. Petroselinic acid (6Z-octadecenoic acid) is a characteristic fatty acid of the Apiaceae family, and was found to be the major fatty acid in all of the tested samples as shown in Table 1. This acid is interesting because of its antimicrobial activity [7,8] and, because its oxidation gives lauric acid (C12:0), a very important fatty acid used in the soap, cosmetic, medical and perfume industries [9][10][11][12]. Palmitic acid (C16:0) was found in all samples with a concentration ranging from 4%-5%, except celery oil exceeding 8% of the total. Two isomers of palmitoleic acid (C16:1), the first, 9Z-hexadec-9-enoic acid, was found in all samples at concentration ranging from 0.3% to 0.9% of the total fatty acids composition, the second isomers was found to be 7Z-hexadec-9-enoic acid and was found in all samples as a minor component but was not present in dill oil. Stearic acid (C18:0) was found in all samples at a level of 1% to 2% but was not detected in the oil of cumin and coriander. Petroselinic acid (6Z-octadec-6-enoic acid) was the major fatty acids in all of the samples with a concentration of up to 80% of the total fatty acids in the oil of dill, coriander, carrot and fennel, with caraway oil having the least percentage in the group (58%). Oleic acid 18:1 was absent in all samples except the oils of caraway, cumin and anise where they contain less than 2%. Linolenic acid 18:2 was the second most abundance fatty acids in all samples with concentration ranging from 10% in Dill oil to as high as 31% in caraway oil. With regard to the overall yield of seed oil, cumin showed the highest yield (23.4%) and celery with the lowest yield (9.8%). GCMS analysis of the fatty acids methyl esters (FAMES) of seeds oil was achieved with base line resolution for all samples as shown in Figure 1 for the caraway sample as a representative example of the analysis. The identification of petroselinic acid methyl ester was confirmed based on retention time, exact molecular weight (296.27008) and excellent fit with mass spectral library search. Petroselinic acid was differentiated from oleic acid by the presence of the radical cation of m/z = 96 corresponding to the cleavage of the double bond at the 6 position and loss of a hydrogen molecule. On the other hand, oleic acid 9Z 18:1 would produce a radical cation with m/z = 138 as shown in Figure 2. Duy et al. (2009) [13] analyzed fatty acids compositions for caraway, carrot and celery seeds using gas chromatography retention time analysis without conformation of structure by mass spectra and reported similar results but lack structural conformation. Identification of Triacylglycerols TAG TAG composition in the oil samples was invigilated using the accurate mass LC-QTOF system. Five major TAGs were found in all samples, however, were at different relative concentrations for each sample. Ions were identified as positive ion sodium adducts with exact masses of 901.7256, 903.7412, 905.7562, 907.7720 and 909.7887. Additional minor TAGs were also identified, but were not found in all samples and were not analyzed further. Although The ion [M + Na] + with the accurate mass equivalent 901.7256 ± 0.0001 represents 186 possible TAG isomers, this number can be reduced to 16, by eliminating TAGs that have any fatty acid that was not detected in the oil (Table 1). Similarly, Identification of Triacylglycerols TAG TAG composition in the oil samples was invigilated using the accurate mass LC-QTOF system. Five major TAGs were found in all samples, however, were at different relative concentrations for each sample. Ions were identified as positive ion sodium adducts with exact masses of 901.7256, 903.7412, 905.7562, 907.7720 and 909.7887. Additional minor TAGs were also identified, but were not found in all samples and were not analyzed further. Although The ion [M + Na] + with the accurate mass equivalent 901.7256 ± 0.0001 represents 186 possible TAG isomers, this number can be reduced to 16, by eliminating TAGs that have any fatty acid that was not detected in the oil (Table 1). Similarly, Figure 2. Proposed fragmentation pattern in the EI mode for differentiation between Z6 and Z9 18:1 fatty acids. Identification of Triacylglycerols TAG TAG composition in the oil samples was invigilated using the accurate mass LC-QTOF system. Five major TAGs were found in all samples, however, were at different relative concentrations for each sample. Ions were identified as positive ion sodium adducts with exact masses of 901.7256, 903.7412, 905.7562, 907.7720 and 909.7887. Additional minor TAGs were also identified, but were not found in all samples and were not analyzed further. Although The ion [M + Na] + with the accurate mass equivalent 901.7256˘0.0001 represents 186 possible TAG isomers, this number can be reduced to 16, by eliminating TAGs that have any fatty acid that was not detected in the oil (Table 1). Similarly, the second TAG has an accurate mass of 903.7412 representing a possible 405 isomers than be reduced to 24 isomers. The third TAG has an accurate mass of 905.7569 representing a possible 405 isomers than be reduced to 33 isomers. The fourth TAG has an accurate mass of 907.7725 representing a possible 342 isomers than be reduced to 35 isomers by eliminating fatty acids that were not detected by FAMES analysis. The fifth TAG has an accurate mass of 909.7882 representing a possible 291 isomers than be reduced to 33 isomers by eliminating fatty acids that were not detected by FAMES analysis. A list of all of the possible fatty acids combinations for the observed [M + Na] + ions and their reduced numbers of isomers according to the identified fatty acids concluded by FAMES analysis is shown in Table 2. Total ion chromatogram of the nine examined samples are shown in Figure 3. Natural isotope abundance for the five major TAG molecular ions are shown in Figure 4. Percentage relative concentration of the detected major molecular ions in each sample is shown in Table 3. Minor identified TAGs and their distribution in the nine tested Apiaceae seeds are shown in Table 4. Determination of Regioisomers by MS/MS Experiments There are large number of different triacylglycerols species (TAGs), which differ in the total length of acyl chains and their degree of unsaturation. Isobaric TAGs are designated by having the same number of carbon atoms and double bonds possessing acyl chains with different length, position and configuration of double bonds. The acyl chain may be located in three different positions of TAG, known as the sn-1, sn-2, or sn-3 positions. The regiospecific analysis is restricted to determine the acyl chains orientation as sn-1(3) and sn-2 positions. Mass spectral fragmentation can provide information about the stereochemistry and regiospecific identification of the TAGs [14][15][16][17][18]. Based on our finding on the fragmentation of standard authentic TAGs and available published work [19,20], it can be concluded that fragmentation pattern for TAGs follow the following scheme: The most abundant ions observed in the mass spectra of TAG are positive ions containing two complete fatty acid chains and those containing only one complete chain corresponding to the loss of one or two fatty acids respectively. Two ions were found corresponding to the ion remaining after the loss of one acyloxy group from the molecular ion ions, corresponding to the loss of each different acyloxy group. However, due to steric and electronic property, the loss of the fatty acid located in the sn2 is energetically less favorable than one at the end positions (sn1 and sn3) [21,22]. Therefore, ions corresponding from the loss of fatty acids from the sn1 and sn3 positions are much more abundance the ion corresponding to the loss of fatty acid at the sn2 position [21,22]. The other class of intense ions characteristic of the individual fatty acid chains is that group of ions containing only one of the fatty acid moieties. The simplest of these are the acyl ions, RCO + . Since each fatty acid chain produces an RCO + ion, if two or three of the chains are different, two or three different RCO + are found but more for the sn1 and sn3 positions. Another ion of relatively high intensity is that corresponding to the acyl ion plus 74 amu equivalent to C 3 H 6 O 2 corresponds to the glyceryl moiety [RCO+74] + ion. Applying the experimental results observed with authentic TAGs and the above reported information about fragmentation of TAGs to the five major TAGs that were identified in the nine fruits of the Apiaceae family. Two of the identified TAG were found to have the same fatty acid in all of the three positions ( Materials All general use solvents and chemical reagents were purchased from VWR (Sugar Land, TX, USA). LCMS water and solvents were purchased from J.T.Baker (Sugar Land, TX, USA). Isooctane and 1% Boron trifluoride in methanol were obtained from Sigma-Aldrich (Milwaukee, WI, USA). Glyceryl trilinoleate (LLL), glyceryl trilinolenate (LnLnLn), glyceryl trioleate (OOO), glyceryl tripalmitate (PPP), glyceryl tripetroselinate (PsPsPs), and glyceryl tristearate (SSS) TAG were obtained from Sigma-Aldrich (USA) and used as standards for LC retention time. Complete set of fatty acids methyl esters both saturated and unsaturated from C4 to C26 were obtained from Sigma-Aldrich (USA) and were used for GC retention time comparison. Oil Extraction Mature dry seeds of the nine selected Apiaceae species were obtained from the seed company KATO Aromatic of Egypt. The seeds (100 g) were finely ground in an electric grinder. The oil from the resulting flour was extracted in glass percolators in 500 mL of chloroform/methanol (2:1 v/v) at room temperature. The extract was dried over anhydrous sodium sulfate, filtered and concentrated at less than 50˝C in a rotary evaporator, yielding yellow to greenish oils, which were kept sealed under argon at´20˝C until further use. The crude lipid extract was purified to obtain neutral glycerides using solid phase extraction on Strata NH2 cartridge (Strata C18E, 500 mg/3 mL (P/N 8B-S001-HBJ, Phenomenex, Torrance, CA, USA). Starta C18E cartridge was conditioned using 500 µL acetonitrile and equilibrated by 500 µL of water before applying the crude extract (1 mL in chloroform methanol) cartridge was then washed with 5% methanol in water, dried for 1 min and eluted with acetonitrile. Second eluent was passed into a NH 2 Sorbent cartridge, which was previously conditioned using hexane, and neutral lipids were eluted with 4 mL of Chloroform/2-propanol (2:1 v/v). Fatty Acids Methyl Esters (FAMES) Preparation Analysis Ten microliters of the neat neutral lipid extract was added to 2 mL of 1% BF 3 in methanol, mixed by vortex and placed on the heating block at 75˝C for 1 h. After cooling down to room temperature, 1 mL of saturated sodium chloride solution was added to step the reaction and FAMES were extracted in 2 mL of iso-octane, passed through anhydrous sodium sulfate and transferred to GC auto-sampler vials. Accurate Mass GC-QTOF Agilent 7200 accurate mass GC-QTOF System was used for analyzing FAMES samples. GC separation was done using a ZB-Wax plus column 30 mˆ0.25 mm, 0.25 µm film thickness column (Phenomenex, Torrance, CA, USA) run under average velocity of 1 cm/sec with a hold up time of 1 min. Temperature programming started at 175˝C, held for 3 min, and heated up to 225˝C at a rate of 2.5˝C/min, and held at 225˝C for 7 min. Total run time was 30 min; solvent delay 2 min; and equilibrium time 2 min. Nitrogen collision gas 1.5 mL/min; mass range from 100 to 400 m/z; quadrupole temperature at 150˝C injected volume 1 µL; split mode 50:1. The measurements and post-run analyses were controlled by Mass Hunter Qualitative Analysis B.06.01 (Agilent Technologies). FAMES were identified based on their retention times and their accurate mass data. Their electron ionization fragmentation and mass spectral data were also searched using Wiley10NIST mass spectral database. GCMS analysis of the fatty acids methyl esters (FAMES) of seeds oil was achieved with base line resolution for all samples, as shown in Figure 1 for the caraway sample as a representative example of the analysis. The identification of petroselinic acid methyl ester was confirmed based on retention time, exact molecular weight (296.27008) and excellent fit with mass spectral library search. Petroselinic acid was differentiated from oleic acid by the presence of the radical cation of m/z = 96 corresponding to the cleavage of the double bond at the 6 position and loss of a hydrogen molecule. On the other hand, oleic acid z9 18:1 would produce a radical cation with m/z = 138, as shown in Figure 2. Duy et al. (2009) [13] analyzed fatty acids compositions for caraway, carrot and celery seeds using gas chromatography retention time analysis without conformation of structure by mass spectra and reported similar results but lack structural conformation. LC-QTOF Agilent 6530 accurate mass LC-QTOF system equipped with 1290 binary pump, Phenomenex Kinetex C18 100 mmˆ3.0 mm 2.6 µm column. Solvents A was made of isopropanol; B1 acetonitrile run in a gradient protocol starting at 50% A, 50% B with a flow 0.2 mL/min reaching 100% solvent A at 10.0 min from the start, and held at 100% A for additional 5 min. Injection volume was 0.2 µL; mass range from 100 m/z to 1500 m/z, with a total run time of 15 min. The LC-QTOF instrument was operated under the following conditions: Ion source ESI + Agilent Jet Stream Technology in positive ionization mode. The Jet Stream ESI source was operated in negative mode, and instrument parameters were set as follows: sheath gas temperature, 350˝C; sheath gas flow, 8 L/min; nebulizer, 20 psi; dry gas temperature, 300˝C; dry gas flow, 5 L/min; and capillary entrance Voltage, 3500 V. Fragmentor and Skimmer1 were operated at 190 and 65 V, respectively. The MS scan data were collected at a rate of 1.02 spectra/s in the range of m/z 100-2000. All the MS data were collected with Mass Hunter Data Acquisition B.06.00 (Agilent Technologies), and Mass Hunter Qualitative Analysis B.06.00 (Agilent Technologies) was applied to identify lipid species. All EICs were obtained with˘10 ppm m/z expansion. Mass Profiler Professional 2.1 (Agilent Technologies) and Microsoft Office Excel 2013 (Microsoft, Redmond, WA, USA) were used for statistical data analysis and data visualization. Conclusions We report here for the first time the use of both accurate mass gas chromatography and liquid chromatography quadrupole time of flight mass spectrometry analysis for the identification of the composition and regiodistribution of triacylglycerols in nine of the most used Apiaceae seed oils. It also confirms the fatty acids composition of these seed oils, in addition to determining the presence of minor 16:1 and 18:1 positional isomers. The results show that the TAG composition and the positional distribution of petroselinic acid on the TAG of the examined Apiaceae seed oils were similar but different in their relative concentration. Among the species studied in this work, fennel seed oil contained the highest levels of petroselinic acid, making it potentially interesting source of petroselinic acid.

v3-fos

2019-03-16T13:02:18.846Z

2015-01-05T00:00:00.000Z

196470369

s2

Disgusting Foods, Pure Water and Beautiful Truth for Balanced Muscle Control Imagine stringy, smelly, fermented soy beans-Japanese natto. Third culture kids, like me have expanded our definition of disgusting foods by traveling widely, sampling mushy grey gruel in food cars on Chinese trains or sharp pungent onion salad, the only “greens” available on the Trans-Siberian railway or even spoiled key lime pie in Toronto, Canada sitting out in the summer heat, curdling my taste buds. the basal ganglia and the hypothalamus form a link between goal directed behavior and habit forming rewards. Damage to the basal ganglia disrupts our ability to achieve goals, earn specific rewards, or avoid disgusting experiences. With brain damage, the carrot and the stick are more difficult to achieve or said another way, natto and mangos seem more similar. Goal directed behavior also involves the basal ganglia, which is involved in cognitively controlled timing systems that requires attention. "Time is a fundamental dimension of life. It is crucial for decisions about quantity, speed of movement, and rate of return, as well as for motor control in walking, speech, appreciating music, and participating in sports." Buhusi [2] added, "It is now proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations." Perhaps an inability to tell funny jokes is a sign of basal ganglia dysfunction or practicing joke telling can improve this part of the brain. The basal ganglia has pathways that also carries the balance skills and ways to control the fine movements needs to be a ballet dancer or concert violinist. It controls our sensations, muscle movement [3], and internal states-how we feel inside and how flexible we are in our choices. Goal driven, we can seek out new foods, new experiences, or habitually order our same old favorite foods in restaurants. Maybe we are addicted to certain foods. Researchers call this a maladaptive type of habit learning or maybe we have an appetitive Pavlovian conditioning to certain foods we grew up with. Driven by the limbic system part of the brain we respond to a particular stimulus, like the smell of apple pie in the same way over and over [4]. This might not seem like such a big deal but "the adaptive significance of disgust has been related to a specific form of threat response associated with an internal defense system, as opposed to an external defense system related to fear," according to, Adolphs [5] in "Neural Systems for Recognizing Emotions From Facial Expressions." This means our emotions and ability to read the emotional states of other people keeps us safe-safe from internal things like food poisoning and from external things like bears. In other words our ability to feel and recognize disgust keeps us safe from the inside out. Think of your brain influenced food choices, as bright yellow buses on a highway. You can achieve your goals and get where you are going, on whichever one you want. You get to choose. By choosing wisely, you improve the journey, the road, and become more functional. Choose unwisely and you get food poisoning or ostracized from the community. In a similar way to our choices, walking, and taking fish oils improves brain function. Consciously noticing what disgusts or excites can lay down shiny new neural pathways and create memories that last a lifetime. Pattern recognition skills needed to experience and identify disgust in the faces of others is compromised in people with brain dysfunctions like depression, Huntington's disease (a genetic movement disorder), focal dystonia (unusually tight twisted muscles), Parkinson's disease (tremor and movement disorder), Wilson's disease (genetic copper processing disorder), Velo-cardio-facial syndrome [VCFS] (a genetic disorder associated with interstitial deletions of chromosome 22q11.2), and bipolar disorder (BD), associated with sensory dysfunctions and mood. And it is not just visual recognition. In one study, participants listened to emotional sentences expressing one of four emotions (anger, fear, disgust, happiness) or neutral sentences. People with problems of the basal ganglia "misclassified neutral sentences as disgust sentences more often than healthy controls," said Paulmann et al. [6], "Emotional Speech Perception Unfolding in Time: The Role of the Basal Ganglia." In a Parkinson's disease and dopaminergic pathways study, researchers noted, "results showed that the early Parkinson's disease patients performed more poorly in the ON [medications] condition than in the OFF one, for overall emotion recognition, as well as for the recognition of anger, disgust, and fear. Additionally, for anger, the early Parkinson's ON patients performed more poorly than controls. For overall emotion recognition, both advanced Parkinson's patients and early Parkinson's ON patients performed more poorly than controls. These results confirm the involvement of the dopaminergic pathways and basal ganglia in emotional prosody recognition, and suggest a possibly deleterious effect of dopatherapy on affective abilities in the early stages of Parkinson's," according to Peron et al. [7] in "Effect of Dopamine Therapy on Nonverbal Affect Burst Recognition in Parkinson's Disease." Dopamine is needed in the basal ganglia in order to help us read other people's emotional states as well as to suppress tremors. In people with Parkinson's disease a lack of dopamine results in tremors and other unwanted movements. Problems with dopamine and its relationship to disgust and fear is described in this 2015 article by Azuma et al. [8] "We selected fear and disgust out of the basic human emotional expressions because of their significance in the development of socialization skills," according to the Journal of Neurodevelopmental Disorders article, "An fMRI Study of Facial Emotion Processing in Children and Adolescents with 22q11.2 Deletion Syndrome." Researchers continued, "One possible explanation for differences in modulation of social brain regions by different types and intensity of facial expression may be variation in dopamine metabolism-for example, associated with variation in catechol-O-methyl transferase (COMT), a methylation enzyme that metabolizes catecholamines (including dopamine). " In other words, dopamine levels in social brain regions could be abnormal in people with 22q11DS. Other symptoms of the genetic condition include, heart defects, speech and language delay, developmental delay (including difficulties with social skills), palate problems, poor immunity to infections, emotional, behavioral and psychiatric issues, learning differences, feeding difficulties, and autistic tendencies. What if these symptoms could change depending on what we pay attention to and how we view the people and world around us? Dopamine is the neurochemical of the reward system. It is also the neurochemical associated with the placebo effect. If we think we are going to heal, get a reward, or be served something disgusting, dopamine levels change. In a 2015 article in Nature Reviews Neuroscience, Wager et al. [9] said, "Placebo effects are beneficial effects that are attributable to the brain-mind responses to the context in which a treatment is delivered rather than to the specific actions of the drug. They are mediated by diverse processes--including learning, expectations and social cognition--and can influence various clinical and physiological outcomes related to health. Emerging neuroscience evidence implicates multiple brain systems and neurochemical mediators, including opioids and dopamine." Our ability to recognize rewards, disgust, and other emotions is linked to how we feel. There are sensory exercises that can impact how we feel and experience the world. Vuillier et al. [10] recently said, "Emotional processing has been reported to effect sensory gating as measured by the event-related potential known as P50. Because both P50 and emotional processing are dysfunctional in bipolar disorder (BD), we sought to investigate the impact that concurrent emotional processing has on sensory gating in this psychiatric population." Researchers added, "The bipolar disorder group showed significant associations between sensory gating to disgust and measures of social functioning. Importantly, bipolar disorder showed impaired filtering of auditory information when paired with an emotionally salient image. Thus, it appears that patients with the greatest impairment in sensory gating also have the most difficulty engaging in social situations." Several diseases with psychological symptoms, facial emotion recognition, and movement disorder symptoms are correlated with dopamine. Parkinson's disease (too little) and schizophrenia (too much). can be considered to be on opposite ends of the same spectrum. Yang et al. [11] noted, "Although many studies have examined executive functions and facial emotion recognition in people with schizophrenia, few of them focused on the correlation between them. Furthermore, their relationship in the siblings of patients also remains unclear. Our study demonstrated that facial emotion recognition impairment correlated with executive function impairment in people with schizophrenia and their unaffected siblings but not in healthy controls." Awareness and consciously considering what is disgusting is one way to help heal the brain. Think of disgust exercises as weight training for several key functions of the brain. In addition to your brain's culinary ability, researchers Harris et al [12] Annals of Neurology noted another function of the basal ganglia. "The difference between believing and disbelieving a proposition is one of the most potent regulators of human behavior and emotion." Whether we accept something as true or reject it as a false string of words, depends on the health of our brain. Continuing he says, "Truth may be beauty, and beauty truth, in more than a metaphorical sense, and false propositions may actually disgust us." This idea also pertains to the placebo effect, where what a person believes about the treatment, pill, or health care professional matters. Or as is said in quantum physics, the observer matters. How we look at the people and the world around us changes everything. In a 2014 article in the International Journal of Psychology researchers noted, "Increased disgust sensitivity has also been reported to be associated with obsessive compulsive (OC) symptoms. No research, however, has investigated the mediating roles of thought-action fusion and disgust sensitivity between religiosity and obsessive compulsive symptoms. This study was composed of 244 undergraduate students who completed measures of obsessive compulsive symptoms, thought-action fusion, disgust sensitivity, religiosity and negative effect. Analyses revealed that the relationship between religiosity and obsessive compulsive symptoms was mediated by thought-action fusion and disgust sensitivity. More importantly, the mediating role of thought-action fusion was not different across obsessive compulsive symptom subtypes, whereas the mediating role of disgust sensitivity showed different patterns across obsessive compulsive symptom subtypes. These findings indicate that the tendency for highly religious Muslims to experience greater obsessive compulsive symptoms is related to their heightened beliefs about disgust sensitivity and the importance of thoughts," according to Inozu et al. [13] in "The Mediating Role of Disgust Sensitivity and Thought-Action Fusion Between Religiosity and Obsessive Compulsive Symptoms." Research seems to indicate that drinking clean water and staying hydrated can also help with brain function. Meier et al. [14] in "Rivalry of homeostatic and sensory-evoked emotions: Dehydration attenuates olfactory disgust and its neural correlates," said "Neural correlates have been described for emotions evoked by states of homeostatic imbalance (e.g. thirst, hunger, and breathlessness) and for emotions induced by external sensory stimulation (such as fear and disgust). " The study showed that the sensory function of the brain was impaired in cases of dehydration. Thirst lead to a lack of survival responses or the ability to keep one's self safe. "Twenty highly dehydrated male subjects rated a disgusting odor as significantly less repulsive when they were thirsty. On the neurobiological level, we found that this reduction in subjective disgust during thirst was accompanied by a significantly reduced neural activity in the insular cortex, a brain area known to be considerably involved in processing of disgust. Furthermore, during the experience of disgust in the satiated condition, we observed a significant functional connectivity between brain areas responding to the disgusting odor, which was absent during the stimulation in the thirsty condition. " It is interesting to note that in people with Huntington's disease, which affects the basal ganglia and hypothalamus there is an alteration in thirst and water consumption. Wood et al. [15] in "Increased Thirst and Drinking in Huntington's Disease," said, "While Huntington's disease (HD) is a condition that primarily involves the basal ganglia, there is evidence to suggest that the hypothalamus is also affected. Because the osmoreceptors regulating thirst are situated in the circumventricular region of the hypothalamus, we were interested in whether altered thirst is a part of the Huntington's disease phenotype. We gave a xerostomia (dry mouth) questionnaire to Huntington's disease patients and control subjects, and also measured their urine osmolality and serum vasopressin. The mean total xerostomia score was significantly higher in Huntington's disease patients than in controls, indicating greater thirst in Huntington's disease patients. Urine osmolality was unaffected in Huntington's disease patients up to clinical stage III, and none of the patients had diabetes. However, serum vasopressin was increased, suggesting a dysregulation in the control of hypothalamic vasopressin release. A dry mouth can affect taste, mastication and swallowing, all of which may contribute to the significant weight loss seen in both Huntington's disease patients." Sometimes we do disgusting things on purpose, like the time I drank some cactus juice that went down like thick gritty pulp but then ... I take in the color, the drums, the cactus, the smoky air, and touch the world around me. I have enhanced my gut sense, intuition, and brain clarity. I reach for the sunlight and the star light. I am perfectly placed, perfectly aligned to walk into the unknown with clarity and hope. My new sense of the world stay with me long after the disgust in my belly has gone. It is interesting to note the origin of the word disgust and its relationship with digestion and gustatory function. Even though as a child I loved mangos, for a few years in the 1980's I couldn't eat anything that tasted like mango because in Malaysia, I got sick drinking mango flavored water. Now, my rational mind knew it was probably some contamination in the water not the mango powder but my body carried a powerful memory of the last thing I drank before starting to throw up. I literally couldn't even smell a mango without that nauseas feeling coming back. It was compounded by the fact that I was on vacation on Tioman Island with a bad sunburn, throwing up sick, no appetite for spicy, the-only-food-available, sleeping in a little hut on the beach with sand and who knows what else in the sheets, and an Asian style squatty potty a ways down the beach. But, I still remember the beautiful sunsets and my partner looking at me and saying, with a laugh, "Just think, people at home are envying us." The way complementary medicine practitioners and health coaches can use this information is two-fold. One is to know that although Huntington's is a genetically based disorder, studies with identical twins (hence identical genetics) shows that there are environmental factors that influence quality of life and the progression of the disease. One identical twin may have a different symptom picture and progression from the other twin. Our environment is created by our choices in the areas of diet, lifestyle, exercise and more. Knowing that these choices make a difference in our quality of life, even in genetically based conditions, helps people consider their choices, stick to plans, and all of this can be supported and facilitated by a great health coach. The second way is to create a questionnaire or individual coaching program for the client with the coach that weird as it sounds encouraging them to think about disgusting things for a few minutes a day. This is a sample plan. Exercise: Disgust: Using the Mind to Heal the Brain Take about 10 to30 minutes to do this exercise. First, notice how you feel-your mood and connection to your sensory environment. Walk around a little, and notice how you are walking, or how your balance is, etc. Check in with yourself. Then answer these questions. Then recheck how you are feeling and notice what has changed. What is changed by this exercise and the attention your pay? 1. What is the most disgusting food you have ever eaten? 2. What foods do other people like that you find disgusting? 3. What was the last disgusting smell you experienced? 4. What has a disgusting feeling (touch or texture on your skin or in your mouth)? 5. Whose face did you see with a look of disgust most recently? 6. If you imagine someone offering you something that looks disgusting, how will you respond to them?

v3-fos

2019-04-02T13:13:55.335Z

2015-12-01T00:00:00.000Z

90389369

s2

Relationship between incidence of Leucinodes orbonalis (Guenee) and Chlorophyll content in leaves of Brinjal (Solanum melongena L.) The present study on biochemical basis of resistance against Leucinodes orbonalis infestation was conducted during the year 2011-2012. The results revealed that highest chlorophyll-‘a’- content of 0.497 mg/gfw was recorded in the susceptible genotype SHB-1.The lowest amount of 0.319 and 0.381 mg/gfw was observed in the resistant genotypes Brinjal-85 and Local long respectively, which were significantly different from other evaluated genotypes. The chlorophyll ‘a’content was positively correlated with the brinjal shoot and fruit borer infestation. Thehighest chlorophyll -‘b’- content of 0.442 mg/gfw was recorded at 70 DAT (days after transplanting). The amount of chlorophyll -‘b’- varied significantly among the genotypes at different ages and decreased with the age of crop. The average highest amount of chlorophyll -‘b’- was estimated in the genotype SBH-1 which was significantly at par with hybrid SBH-2. The lowest chlorophyll -‘b’- content was recorded at 40 DAT in the genotype Brinjal-85 followed by Local Long. The lowest amount of total chlorophyll was estimated in the resistant variety as compared to susceptible therefore exhibiting lowest level of infestation. INTRODUCTION Brinjal (Solanum melongena L.) also known as aubergine belonging to the family "Solanaceae", is one of the common and popular vegetables grown throughout the world. The crop is extensively damaged by different insect pests and important pests among them are shoot and fruits borer (Leucinodes orbonalis Guenee), jassids (Amrasca devastans Dist.), flea beetle (Peylliodes brettinghami Maulik), Epilachna beetle (Epilachna spp.) and aphids (Aphis gossypi Glover) (Shukla and Khatri, 2010). However in Kashmir valley, L.orbonalis Guenee is one of the major pests of the brinjal causing considerable damage every year (Dar et al., 2014). The damage caused by L. orbonalis starts soon after transplanting of seedling and continues till the harvest of the fruit. The newly hatched larvae bore into the petiole and midrib of the large leaves as well as young tender shoots, close the entry holes with their excreta and feed inside of the fruit (Butani and Jotwani, 1984;Dar et al., 2014). Attempts have been made to control this notorious pest with the use of different insecticides. With the growing realization of hazards and side ill effects connected with the indiscriminate use of pesticides, entomologists have developed integrated pest management programme to maintain the pest population at level below those ISSN : 0974-9411 (Print), 2231-5209 (Online) All Rights Reserved © Applied and Natural Science Foundation www.ansfoundation.org causing economic injury. According to Atwal and Singh (1989) a thorough knowledge about the economic significance of pest needs to be gained in terms of level of pest population, the extent of injury and consequent loss as prerequisite for development of management schedules for any pest. A chemical component like chlorophyll is considered as a yield determining component and a number of different types of chlorophylls occur in the plant kingdom, among them the chlorophyll -a-is of universal occurrence (Strain, 1994). Since, the information regarding the relationship between L.orbonalis incidence and chlorophyll content are limited. The experiment was undertaken to find the interrelationship between incidence of L.orbonalis and leaf chlorophyll content of brinjal (S. melongena) during 2011 -12. This research article provides a view of importance biochemical content common among plants. Therefore, close examinations of plant chemical characteristics are explained that contribute to pest resistance. In many cases it is obvious that the biochemical factors are more important than morphological and physiological factors in conferring non-preference and antibiosis. Some biochemical constituents may act as feeding stimuli for insects. Occurrence at lower concentration or total absence of such biochemical leads to non-preference, a form of insect resistance. The biochemical constituents are available in brinjal and these biochemical constituents possess insect resistant properties. MATERIALS AND METHODS Studies on the effect of different total chlorophyll content in the leaves of different genotypes of brinjal was conducted during Kharif season 2011-12 at experimental field of Division of Vegetable Sciences, Sher-e-Kashmir University of Agricultural Science and Technology of Kashmir, Shalimar (Jammu and Kashmir). Twelve brinjal genotypes were evaluated and the experiment was laid out in the Randomized Block Design (RBD) with three replications. Seedlings were spaced at 60×45cm in each individual plot of size 16×12 m 2 . Regular inter-cultivation practices and need based irrigation were performed. Leaf chlorophyll was estimated from the third leaf count from the top and from the shoots at 10 cm above the growing. The leaves were randomly selected from 5 different plants per plot of each genotype in the three replications. The leaf and shoot pigments were estimated and statistical analysis was done according the Gomez and Gomez (1984). ). At the same time the percentage of the infestation were recorded and were graded from the mean percentages, following the method of Mukhopadhay and Mendal (1984). Chlorophyll content was estimated by the method of Yoshida et al. (1978). RESULTS AND DISCUSSION Chlorophyll -a-content of third leaf of different brinjal genotypes varied significantly from 0.43 (resistant), 0.47 (moderately resistant), 0.53 (tolerant), 0.57 (moderately susceptible), 0.62 (susceptible) and 0.69 (highly susceptible) at 40, 70 and 100 DAT, respectively ( Table 1). Amount of chlorophyll -a-also varied significantly with the age of the brinjal plant having highest at 100 DAT (0.72) and lowest at 50 DAT (0.43), which was similar to that of 40 DAT ( Fig. 2 &Table 1). The correlation coefficient of chlorophyll -a-content of the third leaf between 40 and 70 DAT were 0.97 and significant at 1 % confidence level; but between 70 and 100 DAT (0.298) were insignificant. Besides, the infestation pattern of brinjal fruit and shoot borer with respect to chlorophyll -a-were significantly different at 40, 70 and 100 DAT. A strong positive correlation was observed between the pest infestation and chlorophyll -a-similarly the resistance was significantly positively correlated with the activity of peroxidase (POD) and the content of total chlorophyll (P<0.05) as observed by Zhou et al. (2012). On the basis of average value lowest chlorophyll -a-content was observed in the Brinjal-85 (0.25), which significantly different from the other varieties/hybrids, except Local Long. Similarly, the average highest amount of chlorophyll -a-content was recorded in Shalimar Brinjal Hybrid-1(0.69) which was statistically different from all varieties/genotypes except Shalimar Brinjal Hybrid-2(0.63). The chlorophyll -a-content was positively correlated (0.87) with brinjal shoot and fruit borer infestation i.e., the varieties Local Long, Brinjal-85, Dilruba-2 and Shalimar Brinjal Long-208 with purple coloured leaves and flowers at 70 DAT were less susceptible to brinjal shoot and fruit borer, than those with dark purple to light green leaves (Shalimar Brinjal Hybrid-1 and Shalimar Brinjal Hybrid-2). Asathi et al. (2002) found a strong positive correlation between the L.orbonalis infestation and chlorophyll content among five different genotypes in Chhattisgarh (India). However, Pathak (1961) and Kabir et al. (1989) reported that dark coloured leaves are more susceptible than purple coloured leaves, except varieties viz, BLO-100 and Islampuri in which infestation increased with increase in chlorophyll -a-content, but in present investigations the genotypes with dark coloured leaves were found comparatively less susceptible to borer damage. The chlorophyll -b-at 40 DAT was similar to the content at 100 DAT. The average highest content of chlorophyll -b-was observed in Shalimar Brinjal Hybrid-1 differs significantly, followed by Shalimar Brinjal Hybrid-2. The lowest average chlorophyll -b-was recorded in variety Brinjal-85 followed by Local Long, and were statistically at par with each other but different from rest of the genotypes taken under investigation. The chlorophyll -b-content was positively correlated with borer infestation i.e., infestation increases linearly with increase in chlorophyll -b-content (Shalimar Brinjal Hybrid-1 and Shalimar Brinjal Hybrid-2), and decreased at certain points in some varieties, this in contradiction with the findings of Teotia and Lal (1970), who found a negative correlation between the chlorophyll -b-and borer damage. Besides, the infestation pattern of brinjal fruit and shoot borer were different at 40, 70 and 100 DAT with respect to the chlorophyll -a-and -b - (Fig. 2). On the basis of average value lowest chlorophyll -b-content was observed in the Brinjal-85 (0.58), which was also significantly different from the other varieties/hybrids, except Local Long. Similarly, the average highest amount of chlorophyll -b-content was recorded in Shalimar Brinjal Hybrid-1, which was statistically different from all varieties except Shalimar Brinjal Hybrid-2. The chlorophyll -b-content was positively correlated (0.87) with brinjal shoot and fruit borer infestation i.e., the varieties with light purple to dark purple coloured leaves at 70 DAT were less susceptible to brinjal shoot and fruit borer, than those with light green leaves in which there is high content of chlorophyll -b-. However, in contrast to this Nilam and Patel (2012) observed that chlorophyll exhibited a non-significant but negatively correlated with infestation level of E. vittella to shoot and fruit. Average total chlorophyll content of different brinjal hybrids/varieties ranged from 0.823 (Shalimar Brinjal Hybrid-1) to 0.559 mg/gfw at 40 DAT; 0.0.598 to 0.627 mg/gfw at 70 DAT and from 0.547 to 0.501 mg/ Varieties/hybrids Mean chlorophyll content at 40,70 and 100 days after transplanting (mg/gfw; mg per gram fresh weight). Each value is the mean of three replicates;Figures in parentheses are arcsine-transformed values. In a column, means followed by the same letter (s) are not significantly different by DMRT (P=0.05) Fig. 1. Relationship between chlorophyll 'a' and 'b' content and brinjal shoot and fruit borer infestation at different days after transplantation. gfw at 100 DAT. Chlorophyll content varied significantly among hybrids and varieties at different ages of the crop (Fig. 2) which is also in conformity with the results of Sindhu (1992) in variety P-8 (0.026mg/g) and Ingale and Patil (1997) in variety PBR-91-1 (0.126mg/g). Elanchezhyan et al. (2008) observed the maximum of total chlorophyll 1.86 (mg/g) in the Bejo Sheetal (HS) exhibited the L.orbonalis infestation of the 35.7%.Total chlorophyll content is higher at fruiting stage than at the vegetative stage irrespective of the varieties. Asathi et al. (2002) reported that chlorophyll at vegetative stages ranged from 0.009 mg/g to 0.045mg/g while at fruiting stage it varied from 0.020 to 0.061 mg/g. Besides, the infestation pattern of L.orbonalis varied among different hybrids/varieties. The total average amount of chlorophyll content was positively correlated with borer infestation at 100 DAT, and lowest at 40 DAT. Similar results in brinjal were also reported by Murugesh (1997).The apparent fruits and leaf colour is dependent upon the total chlorophyll content, and that chemical constituents (Total sugars) were found to be maximum in Shalimar Brinjal Hybrid-1 and Shalimar Brinjal Hybrid-2, thus contributing towards susceptibility to the L.orbonalis, while as the varieties Brinjal-85 and Local long were resistant containing maximum of total phenol content and comparatively less total chlorophyll content. In the present work chlorophyll content had a positive correlation with the L. orbonalis infestation which is in conformity with the Saxena and Diwakar (2012) who found that due to infestation of Henosepilachna total chlorophyll get decreased which means that brinjal genotype having lowest chlorophyll cannot be preferred by L. orbonalis, similarly Prabhu et al. (2009) also observed a correlation between chlorophyll content and brinjal shoot and fruit borer. The correlation coefficient between total chlorophyll content and L.orbonalis infestation at 40 and 70 significant, 40 and 100 significant; 70 and 100 DAT were non-significant. The average highest content of total chlorophyll were recorded in Shalimar Brinjal Hybrid-1; while as, average lowest amount of chlorophyll content were recorded in Brinajl-85, which is in contradict with findings of Pathak (1961) and Kabir et al. (1989) who observed the average lowest amount of total chlorophyll content in susceptible variety Nayankajal which recorded the highest infestation. The total chlorophyll content in varied significantly among the different genotypes/varieties. The maximum chlorophyll -a-and -b-and brinjal shoot and fruit borer damage were found in Shalimar BrinjalHybrid-1.The correlation coefficient between chlorophyll -a-and -b -with borer attack were positive and high as compared to the resistant genotypes were lowest content of chlorophyll -a-and -b-were found, exhibited week correlation with the borer damage. At 40 DAT, the maximum of infestation of 4.25 and 4.11 per cent were recorded in Shalimar Brinjal Hybrid-1 and Shalimar Brinjal Hybrid-2 having the chlorophyll -a-content of 0.387 and 0.178 (mg/gfw), respectively. With the advance in the age of the crop the average of the total chlorophyll increases with the advance in vegetative stage of the crop, but decreases with maturity of the crop that corresponds with the decrease in the shoot infestation of the brinjal. However, the chlorophyll -b-also increases with the vegetative stage of the crop but is comparatively lower than the chlorophyll -a -damage by L.orbonalis. However, it was noted that percentage of total chlorophyll content was higher in locally developed hydrids therefore suffering more borer infestation in shoots as compared to the rest of the commercially cultivated brinjal varieties having comparatively less total chlorophyll content. Identification of suitable molecular markers which are linked with resistance. Conclusion From the results, it is clearly evident that genotypes viz, Shalimar Brinjal Hybrid-1 and Shalimar Brinjal Hybrid-2 having higher chlorophyll content received higher infestation, whereas genotypes like Local Long and Brinjal-85 with lower total chlorophyll content received lower infestation of L. orbonalis in both shoot and fruit. Therefore, the results of the present study suggested that genotypes having lower chlorophyll content in leaves could be utilized in the breeding programme for the development of BSFB resistant varieties in brinjal. ACKNOWLEDGEMENT Authors are highly thankful to the SKUAST-K, Shalimar for providing the necessary facilities to conduct the research.

v3-fos

2019-04-25T13:11:18.545Z

2015-01-10T00:00:00.000Z

130191209

s2

Greenhouse Gas Fluxes and Soil Carbon and Nitrogen Following Single Summer Tillage Event No-till farming results in gradual buildup of soil organic matter (SOM) and re-introduction of tillage can often reverse it. However, tillage in low precipitation regions may be needed to manage weeds and disperse accumulation of immobile soil nutrients. The main objective of this study was to assess the effects of a single summer tillage on carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), soil water filled pore space (WFPS), dissolved organic carbon (DOC) and nitrate (NO3) in winter wheat summer fallow systems that were either tilled for the first time after nine years of no-till (NTT), not-tilled (no-till, NT) or were frequently tilled (conventional, CT; and organic, CF). The study was established in the US Central High Plains region where annual precipitation averaged 332±39 mm. Soil and gas samples were collected before the tillage event (time zero) and at 1hr, 5 hrs, 25 hrs and 50 hrs after. Immediate increases in CO2 and N2O fluxes were observed in all tilled treatments within the first 1 to 5 hours but 50-hr cumulative N2O and CO2 in NTT did not differ from Original Research Article Bista et al.; IJPSS, 6(4): 183-193, 2015; Article no.IJPSS.2015.109 184 the values observed in NT. Tillage however, resulted in a 22% greater 50-hr cumulative CH4 assimilation in NTT compared with NT and was comparable with CH4 in CT suggesting enhanced soil aeration. Soil NO3 did not change in NTT unlike in CT and CF and soil DOC did not increase in NTT until 25 hrs after when, it returned to levels comparable with time zero. In contrast, DOC in CT and CF continued to stay elevated after 50 hrs. In conclusion, single tillage event of a long-term notill performed on dry soil during summer did not negate benefits associated with SOM accrual and may be a viable alternative for farmers to address some of the management-related problems. INTRODUCTION Tillage during the fallow phase is a common practice in dry land winter wheat (Triticum aestivum L.) production in the US Central High Plains. Repeated tillage of marginally productive soils in this low precipitation region (annual precipitation ranging between 300 to 400 mm yr -1 ) [1] has however, resulted in loss of soil organic matter (SOM) and decline in soil nutrient availability [2]. Conversely, long-term no-till management has helped accrue multiple agroecosystem benefits [2,3], which include increase in SOM, reduced soil erosion and improved soil profile water storage [4,5]. While producers who practice no-till in semi-arid regions are typically committed to this form of management, there are several reasons why occasional summer tillage may prove beneficial and offer solutions to some no-till related problems. For example, tillage can temporarily improve soil aeration [6], help incorporate crop residues, disperse near-soil-surface-accumulated low-mobility phosphorous (P) [7]; reduce soil compaction [8], control weeds [9] and reduce stratification of SOM [10]. Tilling of the dry soil however, can trigger microbial processes leading to SOM mineralization and greenhouse gas (GHG) emissions [11,12]. The mechanism of SOM decomposition starts with the release of newly formed or previously aggregate-protected labile organic substrates that are subsequently made available to soil microbes. This results in immediate production of carbon dioxide (CO 2 ) and nitrous oxide (N 2 O), and increased assimilation of methane (CH 4 ). These rapid changes are important indices demonstrating early soil response to disturbance. In addition, these three gases are of particular interest as they affect soil carbon (C) and nitrogen (N) exchanges with the atmosphere [13] and are important players in the global C cycle [14]. Factors affecting SOM decomposition following disturbance include temperature, water, aeration, pH, and mineral nutrients, plant residue quality and soil structure [15]. For example, frequently tilled soils in semi-arid regions generate twice as much CO 2 compared with long-term not tilled soils over a period of the growing season [16]. CO 2 , N 2 O and CH 4 are of particular importance as potent GHG species. N 2 O is produced primarily during the process of denitrification and carried out by anaerobic microorganisms ubiquitous in soils experiencing periodic water saturation [17]. The process of N 2 O production however, is not limited to water-saturated soils, but also takes place in any soil where anoxic microsites exist [18]. In addition, N 2 O is produced during aerobic nitrification in well-aerated soils [19]. A single rainfall event after prolonged periods of drought can trigger immediate N 2 O pulses that can equal 80-90% of total annual N 2 O emissions in semiarid native rangelands [20,21]. Similar water pulses can result in temporary increase in methanogenesis [14]. On the other hand, tillage can trigger CH 4 assimilation driven by methanotrophic microorganisms [14]. It is known that well drained soils effectively assimilate CH 4 and in general, dry soils are important sinks for atmospheric C [22]. The main objective of this study was to quantify GHG emissions and soil C and N after a single summer tillage event performed on a series of winter wheat fallows that have been tilled for the first time after nine years of no-till or are frequently tilled. Such information can help understand the SOM mineralization triggered by a tillage disturbance and demonstrate whether an occasional tillage jeopardizes long-accrued benefits of a no-till practice. Study Site The experiment was conducted in July 2011 at the University of Wyoming Sustainable Agriculture Research and Extension Center (SAREC) near Lingle, WY (42º 5' N, 104º 23'W and 1314 meters elevation). Soils at the location are classified as loamy, mixed, active, mesic Ustic Torriorthents, with less than one percent SOM and slightly alkaline soil pH. Climate is semi-arid with approximately 125 frost-free days, average maximum and minimum temperatures of 17.9ºC and 0.2ºC, respectively, and average annual precipitation of 332±39 mm [1]. Two-week antecedent precipitation before the start of experiment amounted to 28 mm and no precipitation occurred during the five-day period prior to the experiment. Experimental Design and Treatments The experiment was established in a series of 5ha fields under different long-term tillage treatments that were first applied in 2002. Fields were located adjacent to each other and positioned on a similar landscape. Treatments consisted of: first-time tillage after nine years of a no-till (NTT); no-till managed exclusively with chemicals for weed control (NT), a combination of tillage and chemical weed control also referred to as "conventional" (CT), and chemical-free frequently tilled organic system (CF) ( Table 1). The CF treatment involved a maximum of six tillage operations per year and tillage was the only form of soil management and weed control. The CF treatment was designed to reflect organically certified wheat production in eastern Wyoming. This system relies on no external (fertilizer and herbicides) inputs and tillage frequency is determined based on need for weed control. The CT treatment involved a maximum of four tillage operations per year. Due to reoccurring plant-available water shortages, low fertility soils and low overall crop yields, no fertilizer was used in any of the systems. Spring and early summer tillage is replaced with herbicide applications. Early summer tillage operations to a depth of 15 cm in CF were performed using Krause tandem disk (Khun Krause Inc., Hutchinson, KS). Subsequent summer tillage operations to a depth of 10 cm were performed using a Sunflower Fallow-King® (Sunflower Manufacturing, Beloit, KS). Fertilizers have not been applied in any of the treatments since 2002. Five 10 m × 10 m plots were established at randomly selected locations in NT, CT and CF treatments in fallow strips that were 60 meters long. The NTT plots were also established within the same fallow strips as NT plots. Constraining NTT plots to the same filed as NT treatment plots was intended to assure that concurrent GHG and soil measurements were performed within a comparable window of time. Individual plots representing NT and NTT were located at least 10 meters away from each other. Fallow strips in CT and CF were plowed two times in spring before the experiment (May and June 2011). One week prior to the experiment, all plots were staked out, locations marked using GPS and the polyvinyl chloride (PVC) rings (25 cm diameter x 10 cm high) were deployed in each plot by inserting them 7 cm deep in the soil. These rings served as bases for periodic GHG measurements. Soil and Air Sampling In the morning of July 19th, the first set of soil and air samples were taken (time zero,T0). Shortly after, PVC rings were removed from NTT, CT and CF plots, and plots were tilled with Sunflower Fallow-King® to a depth of 10 cm. Immediately following the tillage event, PVC rings were reinserted to the ground in the original locations and soil and GHG samples collected from all tilled and NT treatments. Measurements were taken at 1hr (T1), 5 hrs (T5), 25 hrs (T25), and 50 hrs (T50) after tillage. Soil and air temperatures were recorded at each time interval using a digital thermometer placed adjacently to the chambers. Each time, GHG samples were obtained at 0, 15, and 30 min after deployment of chamber tops on the bases using an enclosure technique by Hutchinson and Mosier [23,24]. GHG samples were drawn using a 60-ml polypropylene syringe (Fisher Scientific Inc.), from which 30 ml of sample was flushed out and remaining 30-ml was injected into 12 ml pre-evacuated LabcoExetainer® glass vials sealed with rubber septa. In the lab, gas samples were analyzed using a Shimadzu GC-2014 Gas Chromatograph (Shimadzu, Kyoto, Japan) equipped with autosampler and thermal conductivity, flame ionization, and electron capture detectors to capture CO 2 , CH 4 and N 2 O, respectively. Fluxes were calculated from the change in GHG concentrations in the chamber headspace over time. Cumulative fluxes of individual gas species over 50-h period were determined by linearly interpolating hourly emissions and integrating the underlying area as described in Hutchinson and Mosier [25]. Concurrently with gas sampling, soil samples (0-10 cm) were collected from three random plot locations within a minimum distance of 0.5 meter away from GHG chamber bases. Three soil cores were homogenized, coarse fragments removed, and a single 5 g subsample was immediately field extracted with 50 ml of 2 molar potassium chloride (2M KCl). The remaining soil was bagged, stored in a cooler and transported to the lab for further analyses. Laboratory Analyses Soil water content was determined by the gravimetric technique [26], dissolved organic carbon (DOC) was quantified using a Shimadzu TOC Analyzer (TOC-VCPH, Shimadzu, Kyoto, Japan) and soil nitrate (NO 3 ) concentration was determined using a micro plate spectrophotometer (Biotek Inc.) [27]. A sub-set of soil samples collected at the beginning of the study was analyzed for particlesize distribution using the hydrometer method [28], bulk density by the core method [29], and pH and electrical conductivity by electrode [30]. Total C and total N (Total N) contents were determined by dry combustion using a NC-2100 elemental analyzer (Carlo Erba Instruments, Milan, Italy). Inorganic C was determined using the modified pressure-calcimeter method [31]. Soil organic C (SOC) was determined by subtracting inorganic C from total C. Water filled pore space (WFPS) was calculated from soil bulk density and gravimetric water content [32]. Particle density of 2.65 g m -3 was used in WFPS calculation. Statistical Analyses Data were analyzed using PROC MIXED in the Statistical Analysis System (SAS ver. 9.3, SAS Institute, Cary, NC) [33]. Plots within each treatment though spatially explicit and well replicated, were considered as pseudoreplicates. The statistical analysis considered treatment as a fixed term, time of sampling as a repeated measure, and replications as random terms in the statistical model. The cumulative CO 2, CH 4 , and N 2 O fluxes were analyzed using one-way ANOVA. Means were separated using PDIFF test in the LSMEANS procedures. Treatment effects were considered significant at P≤ 0.05. Change in WFPS over time was analyzed using (PROC REG) in SAS. Regression analyses were performed to compare slopes representing change in WFPS over time. Baseline Soil Properties Soils at the location were comparable among the treatments and classified as sandy loams. Soils had BD 1.37 g cm -3 , EC 0.97 ds cm -1 , pH 8.64, and IC 2.70 g kg -1. Soil in NT and NTT had comparable Total N, which was 36% and 34% higher than in CT and CF, respectively (Table 2). In addition, NT and NTT had 17% and 12% higher SOC content than CT and CF. Soil and air temperatures during the experiment were high and ranged between 27ºC and 40ºC. Water Filled Pore Space Soil WFPS showed significant effects of tillage (P≤ 0.02) and time (P<0.001) but no tillage x time interaction. The highest WFPS was reported in NT and the lowest in CF soils. There were however, differences between regression slopes representing WFPS response to tillage treatments in time (Fig. 1). While NT soil was losing soil water at a rate of 0.09% per hr, water loss in NTT soils was only 0.03% higher, while loss in most frequently tilled CF soils were the highest and amounted to 0.20% per hr, respectively. Carbon Dioxide Carbon dioxide showed significant treatment x time interaction (P≤0.001). Before tillage, CO 2 fluxes in NTT did not differ from fluxes in NT and CT but were significantly (33%) smaller than in CF (Fig. 2a). Within the first hour, CO 2 in NTT increased from 10.7 mg C m -2 hr -1 to 25.6 mg C m -2 hr -1 which was 68% more than CO 2 flux in NT at T1". CO 2 flux in NTT was comparable with CF and 22% lower than in CT. The CO 2 flux in NTT was, however, short-lived and became comparable with flux observed at T0 within five hrs. In contrast, CO 2 in CT and CF at T1 and T5 were 25% and 67% greater compared with T0. These two fluxes declined to levels comparable with T0 after 25 hrs. The 50-hr cumulative CO 2 in NTT averaged 591 mg C m -2 and was not significantly different than cumulative CO 2 in NT (555 mg C m -2 ). It was however; significantly lower than CO 2 in CF (983 mg C m -2 ) and CT (921 mg C m -2 ). Methane Methane also showed significant treatment x time interaction (P≤0.001). All treatments had comparable CH 4 assimilation at T0 that averaged 7.0 μg C m -2 hr -1 (Fig. 2b). At T1, the CH 4 assimilation in NTT doubled compared with T0, and it was significantly greater than NT and CF but similar to CH 4 assimilation in CT. This increase in NTT was, however, short-lived and the CH 4 assimilation became comparable with T0 in NT after five hrs. The 50-hr cumulative CH 4 assimilation in NTT (540 μg C m -2 ) was 28% greater than in NT, 22% greater than in CF but 16% lower than CH 4 in CT. Nitrous Oxide Nitrous oxide also showed significant treatment x time interaction (P≤0.001). All treatments had comparable N 2 O fluxes at T0 (Fig. 2c). Tillage did not generate an initial N 2 O pulse in NTT at T1 unlike in CF and CT when N 2 O increased by 122% and 65%, respectively. On contrary, the N 2 O flux in NTT was significantly reduced (20%) in T1 compared with T0 (37.2 µg N m -2 hr -1 ). Soil Dissolved Organic Carbon Soil DOC also demonstrated significant treatment x time interactions (P≤0.05). Before tillage, all treatments had comparable DOC (Table 3). At T1, DOC in CT and CF was significantly greater compared with values in NTT and NT. At T25 however, DOC in NTT became significantly greater than in NT and CT but comparable with CF. Twenty five hrs later at T50, DOC became significantly lower in CT and CF compared with NT and NTT. Soil DOC in NTT and NT did not change following tillage except for T25 when DOC in NT was significantly lower than at T0. Soil Nitrate Soil NO 3 at T0 was comparable among NTT, CF, and NT, and they were significantly lower than in CT (Table 3). Tillage did not increase NO 3 in NTT at T1 or thereafter, unlike in CT and CF where it increased by 4.04 and 4.92 mg kg -1 to values that were significantly greater than in NT and NTT. Nitrate remained elevated in CT and CF until T50. Nitrate in NT at T50 was significantly greater compared with T0, but the values were lower than NO 3 in CT and CF and comparable with NTT. DISCUSSION Results from this experiment suggest that a single tillage performed during warm summer on previously not tilled dry soils had an insignificant impact on soil C and N as demonstrated by the lack of difference in cumulative CO 2 and N 2 O fluxes between NTT and NT. These fluxes were also significantly lower than CT and CF despite higher overall soil Total N and SOC contents. Tillage however, did result in an immediate but short-lived CO 2 pulse in all tilled treatments including NTT, but the magnitude of initial CO 2 flux in NTT was only one-third of that from CT and CF. Elevated GHG fluxes from frequently tilled CT and CF soils further confirmed that repetitive tillage contributes to SOM mineralization [16,34]. It is likely that the initial CO 2 pulse in NTT was attributed more to the release of CO 2 trapped in soil pores under nontilled soil surface as proposed by Kessavalou et al. [35]. Greater WFPS loss in CT and CF than in NT and NTT over time indicated greater soil water retention under the long-term no-till system, which was conserved even after a single tillage. One-time tillage in NTT also had no significant impact on soil DOC. Unlike CT and CF, where concentrations were initially greater but then significantly declined between 25 and 50 hrs to below NT and NTT levels. Al-Kaisi et al. [36] and Reicosky et al. [37] attributed these changes to soil aggregate disruption and exposure of aggregate-protected C to microbial activity. This newly released C was likely utilized as a microbial substrate during respiration or in support of microbial biomass as proposed by Norton et al. [21] and Ghimire et al. [38] and not measured in this study. Interestingly, tillage resulted in an initial decline in N 2 O fluxes within 1 hr after the event in NTT only. This observation agreed in part with the findings by Kessavalou et al. [35] who reported flux declines in frequently tilled soils as well. Moreover, the magnitude of the decline in NTT was much lower compared to the other study in which 83% reduction in N 2 O for the period of two hours after tillage was observed in spring and 64% reduction for the period of 0.5 hr was observed in summer. Less NO 3 in NTT compared with CT and CF suggested that a single tillage did not trigger anticipated N mineralization as often observed in less water limited agroecosystems [34]. In addition, nitrification was likely the process of N 2 O production in the studied soils as previously proposed by Grandy and Robertson [39]. This was demonstrated by the synchrony between N 2 O fluxes and soil NO 3 concentrations in CT and CF soils. However, one-time tillage of a no-till increased soil aeration and allowed for a very short-lived (observed at T1 only) increase in CH 4 assimilation. Similar increases in assimilation were also observed as early as 30 min after tillage in wheat-fallow systems in the same region [35]. Such response suggested greater gas exchange between soil and atmospheric air and enhanced activity of methanotrophic microorganisms living in a soil layer below top 0-10 cm [40]. CONCLUSION Our study suggested that single summer tillage performed for the first time in nine years in the dry and cold agroecosytem of the central High Plains did not negate the benefits of long-term no-till. Therefore, a summer tillage performed as needed, every several years can be a useful management tool for no-till dry land farmers. However, as soil moisture retention is very critical for dry land production, caution should be applied on how to schedule the timing of such operation. Even small water loss can have longlasting consequences affecting crop yield in low precipitation regions. Additional research is needed to determine best tillage strategies (depth, intensity, spatial extend and the level of disturbance) to help advance our understanding of the effects of periodic tillage on soil properties and agroecosystem sustainability.

v3-fos

2016-05-12T22:15:10.714Z

2015-10-23T00:00:00.000Z

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Effects of Forest Gaps on Soil Properties in Castanopsis kawakamii Nature Forest The aim of this study is to analyze the effects of forest gaps on the variations of soil properties in Castanopsis kawakamii natural forest. Soil physical and chemical properties in various sizes and development stages were studied in C. kawakamii natural forest gaps. The results showed that forest gaps in various sizes and development stages could improve soil pore space structure and water characteristics, which may effectively promote the water absorbing capacity for plant root growth and play an important role in forest regeneration. Soil pore space structure and water characteristics in small gaps showed more obvious improvements, followed by the medium and large gaps. Soil pore space structure and water characteristics in the later development stage of forest gaps demonstrated more obvious improvements, followed by the early and medium development stages. The contents of hydrolysable N and available K in various sizes and development stages of forest gaps were higher than those of non-gaps, whereas the contents of total N, total P, available P, organic matter, and organic carbon were lower. The contents of total N, hydrolysable N, available K, organic matter, and organic carbon in medium gaps were higher than those of large and small gaps. The disturbance of forest gaps could improve the soils’ physical and chemical properties and increase the population species’ richness, which would provide an ecological basis for the species coexistence in C. kawakamii natural forest. Introduction Forest gap occurrence is due to internal factors, external factors, or the combined effects of these factors, which lead to the death of dominant trees in the mature stage and subsequently create a gap in the canopy layer of the forest. As an important interference that occurs frequently in the forest, gap disturbance has a close relationship with biodiversity, which is the basis for species' coexistence in forest communities [1,2]. It is also an important process for forest regeneration and succession. Gap disturbance promotes the improvement of micro-environmental conditions including solar radiation, air temperature, relative humidity, soil temperature, and soil water content. These conditions affect soil physical and chemical properties which correlate with gap sizes and development stages [3]. The variations of soil properties in forest gaps have a vital role in seed germination, seedlings' establishment, and recruitment, which affect the regeneration of different plant species and the community structure dynamic [4,5]. Therefore, a study of soils' physical and chemical properties in forest gaps can provide a better understanding of the potential capacity of soil supplying nutrients to plant roots. This reference value provides a detailed understanding of the relationship between plants and soil in forest gaps and demonstrates the gap regeneration mechanism. Castanopsis kawakamii Hayata is a valuable and rare plant in the southern forest region of China that distributes sporadically in mountain and hilly evergreen broad-leaved forests of Fujian, Guangdong, Guangxi, and Taiwan [6]. However, above 700 hectares there is an abundance of pure forest. The age of the population is around 100 years in Sanming C. kawakamii Nature Reserve, Fujian Province. This is a transitional forest type ranging from central to southern subtropical evergreen broad-leaved forests [7,8]. Therefore, many researchers have launched research on gap regeneration and soil research in this district. The spatial and temporal characteristics of microclimates were heterogeneous in C. kawakamii natural forest gaps, which led to abundant ecological differentiation, rich variety of forest cover, and species coexistence. This may directly affect the soils' physical and chemical properties in forest gaps [9]. Meanwhile, many researchers studied soil carbon balance [10] and soil respiration [11] in this natural forest, which helps us to understand the local soil fertility and ecosystem function. However, the effects of gap formation on soil physical and chemical features remains unknown, especially with severe fragmentation in canopy layers of the forest, which limits our understanding of the regeneration pattern of this natural forest. Therefore, the main objective of this study was to observe the effects of forest gaps in different sizes (between 150~500 m 2 ) and development stages (early, medium and later) on the soil properties in forest gaps, which could provide a theoretical basis for forest regeneration and population restoration in this C. kawakamii natural forest. Study site and stand history Sanming Castanopsis kawakamii Nature Reserve gave the permission to conduct the study on this site. The authority responsible for a national park, the relevant regulatory body concerned with protection of wildlife, etc. We confirm that the field studies did not involve endangered or protected species. This study site was located in C. kawakamii Nature Reserve (N26°07'~26°12', E117°2 4'~117°29') in the middle subtropical area of China. The altitude varied between 180~604 m as shown in Fig 1. With a middle subtropical monsoonal climate, the mean annual temperature is 19.5°C (average of 40 years data by Sanming city Meteorological Bureau), annual precipitation is 1 500 mm, the annual average relative humidity is 79%, and mean velocity of wind is 1.6 m/s, respectively. The soil type in this forest mainly consists of dark-red earth with abundant humus, which is rich in soil nutrition. It is the largest and purest C.kawakamii natural forest in the world, with the canopy closure of about 80% [6]. The main species consisted of C. kawakamii, C. carlesii, C. fargesii, C. eyrei, Pinus massoniana, and Schima superba, etc, which formed a unique landscape in subtropical evergreen broad-leaved forest. Selection of forest gaps Based on the previous survey in the permanent sample plots of forest gaps in 2003, we investigated 12 forest gaps according to gap sizes and development stages. Forest gap size was divided by gap area, which was calculated by an oval area or divided into multiple triangles in order to accurately measure them. The oval-shaped areas were calculated by the length axis and short axis. The average gap area of C. kawakamii natural forest was 327.83 m 2 . We categorized gap area ranging from 100 to 250 m 2 into small gap, from 250 to 400 m 2 into medium gap, and the area above 400 m 2 into large gap. In the present study, 3 small gaps, 6 medium gaps, and 3 large gaps were designed to analyze the effect of gap size on soil properties. Meanwhile, the developmental stages of forest gaps were classified into early, medium, and later stages by the gap formation time, the decomposition degree of gap makers, and species regeneration dynamic in herb and shrub layers [5]. The early stage gap formation occurred within the last 10 years and is mainly composed of strong pioneer species. The medium stage of forest gap consisted of both pioneer species and shadow-tolerant species and its formation age ranged from 10 to 20 years. The gap formation age of the later stage was more than 20 years and species composition mainly consisted of shadow-tolerant species. 3 early stages, 4 medium stages, and 5 later stages of forest gaps were surveyed to study the response of soil properties to the development stages in this natural forest. Meanwhile, we randomly set three non-gap soil samples which were 10 meters away from the gap edge as control groups. Soil sample collected and measurement Three soil profiles from 0 to 30 cm below the soil surface were excavated in each gap. The soil samples were collected by the quarter method. We used the soil core samplers with a capacity of 200 cm 3 for physical properties collection. Meanwhile, the soils were blended before sealing the plastic bag and transporting them back to lab for chemical properties' measurement. Accordingly, we randomly set three non-gap soil samples as control groups to compare the differences of soil properties between forest gaps and non-gaps. The measurements of soil properties were based on the reference of Forest Soil Analysis Method [12]. Soil moisture and pore composition were measured by the soil core method including soil bulk density, soil water mass content, soil volumetric moisture content, maximum moisture capacity, capillary water capacity, minimum water-holding capacity, non-capillary porosity, capillary porosity, soil total porosity, and soil aeration degree. Meanwhile, chemical properties of soil pH, total nitrogen (TN), hydrolysable nitrogen (HN), total phosphorus (TP), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM) were measured in each soil plot. Each soil sample was repeated 3 times on average. Data processing Four groups were divided to analyze the significant differences of soil physical and chemical properties for large, medium, small gaps and non-gaps. Also another four groups of early stage, medium stage, later stage and non-gaps were analyzed the significant differences of soil physical and chemical properties. Differences in soil moisture and pore composition, and soil chemical properties of different gap sizes and development stages of forest gaps were analyzed with single-factor analysis of variance (ANONA) and Bonferroni multiple comparisons test. All statistical analyses were performed using the program SPSS 19.0 for Windows. Results Soil physical and chemical properties in different gap sizes of C. kawakamii natural forest The soil water mass content quality and capillary porosity of large and medium gaps were significantly higher than those of small gaps and non-gaps. The soil volumetric moisture content of large gaps was significantly higher than those of medium gaps and non-gaps. The ratio of non-capillary porosity to capillary porosity along with non-capillary porosity of small gaps was significantly higher than those of large, medium, and non-gaps ( Table 1). The moisture factors and porosity of the soil composition were increased compared with non-gaps. The values of soil bulk density, soil water mass content, soil volumetric water content, and capillary porosity in large gaps were superior to the medium, small, and non-gaps. The soil chemical properties in different gap sizes of C. kawakamii natural forest are shown in Table 2. The pH value and C/N ratio in large gaps is higher than those of non-gaps. The concentration of total N in non-gaps is higher than that of forest gaps, while the concentration of hydrolysable N in non-gaps is lower than those of forest gaps, which indicated that forest gaps could improve the convention rate from inorganic nitrogen to organic nitrogen. Meanwhile, the contents of total P and available P in non-gaps are superior to those of forest gaps, which demonstrate that the soil in forest gaps lacks enough phosphorus to promote plant growth. With the increasing size of forest gaps, the contents of total K and available K also increased, while those in non-gaps were relatively low. The contents of organic matter and organic carbon in non-gaps were the highest, while the hydrolysable N and available K were the lowest among various gap sizes. Soil physical and chemical properties in different development stages of C. kawakamii natural forest gaps The different developmental stages of forest gaps could effectively improve soil moisture characteristics and porosity composition, in particular, with the early stage and later stage ( Table 3). The values of maximum moisture capacity, capillary water capacity, capillary porosity, soil total porosity, and soil aeration porosity in the early stage of forest gaps were higher than those of the medium and later stages of forest gaps and non-gaps. However, the values of soil water mass content, minimum water-holding capacity, non-capillary porosity, and non-capillary porosity/ capillary porosity ratio were superior to those of the early and medium stages of forest gaps and non-gaps. According to the significant difference tests, the contents of soil aeration porosity in the early stage of forest gaps were significantly higher than those of medium gaps, while soil bulk density was lower than those of medium stage gaps. The content of capillary water capacity was higher in early stage of forest gaps than those of non-gaps. Moreover, the values of soil volumetric moisture content in the medium stage of forest gaps were higher than those of non-gaps. However, no significant differences of certain soil physical factors were found in different stages of forest gaps and non-gaps such as soil water mass content, maximum moisture capacity, minimum water-holding capacity, and the ratio of non-capillary porosity/capillary porosity. The concentrations of soil hydrolysable N in different stages of forest gaps were higher than those of non-gaps, which indicated that gap soil was rich in organic nitrogen that could promote the growth of plants (Table 4). However, the contents of total N, total P, available P, organic matter, and organic carbon in non-gaps were superior to those of forest gaps in different stages, which presented a similar trend in different gap sizes. The values of pH, total K, available K, and C/N ratio in medium stage gaps were higher than those of early and later stages of forest gaps, which demonstrated that medium stage gaps could maintain soil fertilization. According to the significant difference tests, there were no significant differences among the concentration of total K and C/N ratio in different stages of forest gaps and non-gaps. The values of pH and concentrations of available K in the medium development stage of forest gaps were significantly higher than those of non-gaps, while the concentrations of total N, total P, and available P were lower than those of non-gaps. The concentrations of hydrolysable N and available K in later stages of forest gaps were significantly higher than those of non-gaps, while the concentrations of available P, organic matter, and organic carbon were less than those of non-gaps. Discussions Gap formation enhances the heterogeneity of micro-environmental factors [4]. Meanwhile, gap area and developmental stages are also important factors in determining soil properties, which can consequently change the variations of soil physical and chemical properties, respiration, microbial activity, and enzyme activity. Moreover, it also could lead the variations of the soil pore composition, soil water balance, and nutrition cycle, which could directly or indirectly affect plant growth and regeneration [13]. The different gap sizes and development stages of forest gaps can effectively improve soil moisture and pore composition, which consequently develop soil water retention capacity and water absorption for plants [14]. The small gaps demonstrated an obvious improvement in soil moisture and porosity composition, followed by medium and large gaps. The turnover time of large gaps was longer than that of medium and small gaps. This is due to high density and relative low depth of litter in soil surface, which led to the decline of soil aeration in large gaps. However, it was in a comparatively stable stage in small gaps with relative low disturbance. The later development stage of forest gaps can apparently improve soil porosity composition and moisture, followed by the early and medium stages. During the early stage of forest gaps, forest disturbance affected the moisture of soil pore composition, but less quickly than solar light and temperature, which is an indirect and long-term process. The species and ratio of crow inclination of gap border trees [15], fine root distribution, litter thickness, microtopography, and climate factors may also affect spatial characteristics of soil moisture in forest gaps. The medium stage of forest gaps illustrated an increasing trend in the contents of soil compaction and soil volumetric moisture content due to the adaptation to the gap disturbance and species composition. Meanwhile, it was a better condition for soil aeration due to the higher vegetation density and richness in biodiversity in the later stage of forest gaps. However, the soil water absorption in non-gaps was less than in forest gaps as a result of interception from trees in the canopy layer. This declined the water permeability, strengthened the soil mechanical resistance, inhibited the root growth, and finally limited the improvement of plant growth and regeneration in non-gaps. Our result testified the hypothesis that forest gaps create opportunities for the optimum growth of plant species [16]. The contents of hydrolysable N and available K in different gap sizes and development stages of forest gaps were higher than those of forest non-gaps, whereas the contents of total N, total P, available P, organic matter, and organic carbon were lower than those of forest non- gaps. Large gaps could effectively increase the contents of soil pH, total K, and the ratio of carbon to nitrogen (C/N), while the contents of total N, hydrolysable N, available K, organic matter, and organic carbon in medium gaps were higher than those of large and small gaps. The contents of total N, hydrolysable N, total P, available P, organic matter, and organic carbon in early stage were higher than those of medium and later stage of forest gaps, while the contents of total N, hydrolysable N, total P, available P, organic matter, and organic carbon in medium stage were higher than those of early and later stages of forest gaps. Gap makers decreased the nutrition absorption after the formation of forest gaps [17]. Meanwhile, microbial activity in forest gaps increased the amount of organic matter and promoted the release of total N in soil nutrition due to the decomposition of gap makers and microenvironment heterogeneity. This led to a decreased concentration in soil total N, total P, organic matter, and organic carbon. Consequently it could develop the soil acidic environment and available nutrition supplements in different gap sizes and development stages of forest gaps. Therefore, species richness was relatively high in tree and shrub layer of forest gaps [18]. Moreover, the phosphorus compound in soil was less liable to be absorbed by plants due to metal ions such as Fe 3+ and Al 3+ in the southern forest soil. This would dictate that the available phosphorus be fixed [19]. Moreover, the reduction of litter in forest gaps would lead to the declination of the contents in soil total P and available P in forest gaps, in accordance with the results in a subtropical humid forest [20]. The effect of forest gaps on soil physical and chemical properties is a complex process [21]. The variations of soil properties are not only related to the gap sizes and development stages, but also related to the litter thickness and its decomposition rate, the return of root biomass, and other factors [22]. The litter decomposition in various sizes of C. kawakamii natural forest gaps showed that litter loss rates were relatively high in non-gaps and small gaps, while large gaps could significantly decrease the microbial activity and litter decomposition rate. However, the medium gaps with a diameter of about 15 m played a decisive role in the soil nutrition release during the process of litter decomposition [23]. Therefore, C. kawakamii natural forest gaps could improve soil physical and chemical properties and increase the population species richness, which could provide an ecological basis for the species coexistence and regeneration. Conclusions Forest gaps in various sizes and development stages could improve soil pore space structure and water characteristics (Tables 1 and 3). Soil pore space structure and water characteristics in small gaps showed more obvious improvements, followed by the medium and large gaps. Soil pore space structure and water characteristics in the later development stage of forest gaps demonstrated more obvious improvements, followed by the early and medium development stages. The contents of hydrolysable N and available K in various sizes and development stages of forest gaps were higher than those of non-gaps, whereas the contents of total N, total P, available P, organic matter, and organic carbon were lower (Tables 2 and 4). The disturbance of forest gaps could improve the soil physical and chemical properties and increase the population species' richness, which would provide an ecological basis for the species coexistence in C. kawakamii natural forest. valuable suggestions during the revision of this manuscript. The authors also record sincere appreciation for helpful and constructive comments made by reviewers of the draft manuscript.

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2019-01-03T03:14:09.460Z

2015-11-14T00:00:00.000Z

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Use of immunohistochemistry (IHC) in the detection of Newcastle disease virus (NDV) in experimentally and naturally infected birds 1 Departamento de Medicina Veterinária, Universidade Estadual do Centro-Oeste (UNICENTRO), Guarapuava, PR, Brazil. 2 Laboratório de Imunoparasitologia, Instituto de Biociências, Universidade Federal de Uberlândia (UFU), Uberlândia, MG, Brazil. 3 Departamento de Patologia Veterinária, Faculdade de Ciências Agrárias e Veterinárias da Universidade Estadual Paulista (FCAV/UNESP), Jaboticabal, SP, Brazil. INTRODUCTION Newcastle disease (ND) is an acute, highly contagious and widespread viral disease of birds that can cause high mortality (up to 100%) and severe economic losses in poultry, the most important natural host of the disease. The virus can also affect a wide variety of avian species causing severe disease (Alexander, 2003). ND is regarded as endemic in many countries, and is caused by an avian Paramyxovirus type 1 (APMV 1), a member of the genus Avulavirus, from the Paramyxoviridae family (Mayo, 2002). There are five pathotypes of ND in chickens: viscerotropic velogenic, neurotropic velogenic, mesogenic, lentogenic and the asymptomatic enteric form (Alexander, 1995). As demonstrated in intensive surveys, nearly 236 free-living species from 27 of the 50 orders of birds have been reported to be susceptible to either natural or experimental infection with ND (Wan et al., 2004). On several occasions, Newcastle disease virus (NDV) was isolated from wildlife birds (Hoque et al., 2012), and most outbreaks of NDV has involved unvaccinated susceptible birds. Contact with infected exotic birds or free-living birds, such as ducks, geese, pigeons, pheasants, partridges, crows, sparrows, mynas and martins, may transmit ND virus to poultry (Alexander, 2003), and ND outbreaks may occur under field conditions, if a pathogenic strain is introduced in a previously unchallenged area (Alexander, 1995).In some cases, the source of the virus in poultry has been presumed to be wild birds, because avirulent NDVs have commonly been found in them (Hoque et al., 2012). The presence of virulent strains in poultry or free-living birds requires screening and control measures even in countries where the virus is endemic, because the existence of the agent severely affects commercial productivity and international trade of poultry and poultry products (Miller et al., 2010). This fact shows the importance of wild birds in the maintenance and transmission of NDV (Jindal et al., 2010). The objective of ND diagnosis is to guide decisionmaking in the control of the disease in a way to prevent the spread of the disease (Alexander, 2003). Therefore, a reliable, safe and easy-to-perform method for the diagnosis should be considered, as the quicker the diagnosis, the more efficient the disease control measures to be put in place, preventing greater losses and the spread of the disease (Kho et al., 2000). Studies involving the use of tissue samples are extremely important for better understanding of the distribution of the viral agent in infected organs, the protection ability of a vaccine, or the pathogenicity of a strain (Barbezange and Jestin, 2005;Nakamura et al., 2008Nakamura et al., , 2014Ezema et al., 2009;Cattoli et al., 2011). Conventionally, ND was characterized by isolation of the virus in embryonated chicken eggs or cell culture, followed by in vivo tests to determine the virulence of the strain, such as intracerebral pathogenicity index (ICPI), intravenous pathogenicity index (IVPI) and mean death time (MDT) in SPF chicken embryos/birds. These tests are cumbersome, labor-intensive, inhumane and, sometimes, inconclusive (Tiwari et al., 2004). Virological, pathologic and immunohistochemical analysis of chickens with ND in field conditions have been useful in the investigation of the mechanisms of ND outbreaks in vaccinated chickens (Nakamura et al., 2008;Bwala et al., 2012). IHC is performed on formalin-fixed, paraffinembedded tissues and, in many cases, the viral antigen can be detected in autholyzed tissues. This technique has been valuable in determining virus distribution in samples in NDV pathogenesis studies. The advantage of this method is that diagnosis is still possible when fresh sera or tissues are unavailable (Lockaby et al., 1993;Wakamatsu et al., 2007;Bwala et al., 2012). IHQ is not in routine use as a diagnostic assay, but the information from experimental studies can supply a roadmap in understanding the clinicopathological picture presented with the various pathotypes (Cattoli et al., 2011). As ND does not cause pathognomonic histopathological lesions, immunological techniques, such as IHC have become important tools in diagnosis and may, therefore, detect the agent in tissue samples (Ojok and Brown, 1996;Oldoni et al., 2005;Piacenti et al., 2006;Wakamatsu et al., 2006;Nakamura et al., 2008). Besides, this technique may replace virus isolation, or even molecular tests, in places where there are no laboratories of adequate biosafety level for this procedure (Brown et al., 1999a, b;Wakamatsu et al., 2006). Based on these observations, the objective of the present study was to standardize an immunohistochemical reaction for the diagnosis of NDV in samples of experimentally infected birds, followed by the use of the technique in the diagnosis of NDV in free-living birds. Birds In order to standardize the IHC technique, a total of 15 pigeons (Columba livia) and 15 chickens (Gallus gallus), adults, were used for the experimental infection with a pathogenic strain of NDV. Ten birds of both species (pigeons and chickens) were experimentally infected,and the five remaining birds of both species were inoculated with PBS pH 7.2 to be used as negative controls. Experimental infection was performed by oral route. These ten birds were kept in separate facilities. On the day of experimental infection, pigeons and chickens, divided into two experimental groups, were moved to Negative Pressure Isolators (Alesco ® , Brazil), under biosafety conditions. All procedures were performed according to the Ethical Principles in Animal Research adopted by the Brazilian College of Animal Experimentation, and to the 2000 Report of the AVMA Panel on Euthanasia (AVMA, 2001) and were approved by Ethics and Animal Welfare Commission of the Biomedical Sciences Institute, University of Sao Paulo (N 093; P.16; B.2). Viruses Experimental infection was performed using the Sao Joao do Meriti strain (Gene Bank Number: EF534701), a highly pathogenic NDV (VVNDV-Velogenic Viscerotropic Newcastle Disease Virus) strain for chickens (mean death time in chicken embryos = 48 h; ICPI in day-old chicken = 1.78). This virus stock solution titer was 10 9.0 median embryo lethal dose/mL (ELD50 /0.1 mL). All virus dilutions were carried out with sterile PBS, pH 7.2. Tissue collection Post-mortem examination was carried out in birds that died (natural infection) or were euthanized (experimental infection) during the experimental period (20 days), and their tissues were submitted to microscopic analysis. All chickens died until the 5 th day postinoculation (D.P.I.). As the pigeons did not show any clinical sign, they were euthanized on day 20 D.P.I.Tissue samples were collected and fixed by immersion in 10% neutral buffered formalin for approximately 60 h. Then, samples were embedded in paraffin by routine methods. Samples from free-living birds were collected throughout a period of one year. They were processed soon after the birds died and stored in paraffin blocks until the moment of IHC analysis. Samples of liver, spleen, lungs and trachea were collected from the birds submitted to experimental infection (chickens and pigeons), including the negative controls. From the free-living birds, only the trachea and spleen were collected, once these tissues presented better results in the evaluation of experimental infection. Positive and negative controls were made up by samples of trachea and spleen that came from animals that were experimentally infected with NDV and in which positivity and negativity were confirmed by RT-PCR. Immunohistochemistry Immunohistochemical (IHC) assays were performed in paraffinembedded tissues according to a previously published protocol (Mineo et al., 2009), with some modifications. Briefly, slides were assayed with polyclonal antibodies against Newcastle disease virus (1:800) obtained from experimentally infected rabbits, as primary antibodies. For the production of primary antibodies, specificpathogen free (SPF) rabbits were inoculated with 1mL of a purified NDV suspension by intramuscular route. This suspension was produced in embryonated eggs and later on, 1 mL of Freund's complete adjuvant was added. The mixture (NDV + adjuvant) was administered three times at 21-day intervals. Later on, blood was collected from the rabbits, followed by titration of polyclonal antibodies. When the reaction was carried out, primary antibodies were incubated for 60 min at 25°C, after removal of paraffin and blockage of endogenous peroxidase (hydrogen peroxide 3% solution in methanol). For signal amplification, the EasyLink One ® (Immunobioscience Corp. -USA, imported by Erviegas ® , Brazil) kit was used according to the manufacturer's instructions. Counter staining was performed with Harris hematoxylin (10%), and slides were covered with coverslips after dehydration. The reaction was read under a light microscope (Nikon, Japan). RESULTS Results of the experimental infection showed that from the 20 infected birds, 17 were positive for Newcastle disease antigen immunomarking in the trachea, 11 were positive in the spleen, with immunomarking mainly observed in the cytoplasm (Figure 1). None of the other tissues (lungs and liver) were positive. A large number of unspecific reactions were observed. Negative controls did not show immunomarking in any of the samples. Results for free-living birds are shown in Table 1. From the 46 samples analyzed, 24 presented positive immunomarking in at least one of the tissues (trachea or spleen). From these positive samples, 23 showed positive reaction in trachea, and only one sample was positive only in the spleen. From the 24 positive birds, only 5 presented positive results in both tissue samples. DISCUSSION This is the first study in Brazil using the standardization of immunohistochemistry for NDV diagnosis in samples of free-living birds. The use of polyclonal antibodies showed was effective in the standardization of the technique, enabling NDV diagnosis in experimentally and naturally infected birds. Unsatisfactory results of IHC for NDV have already been described in some cases, as when monoclonal antibodies are used (Bhaiyat et al., 2004). The results of this study were partially similar to those presented elsewhere (Nakamura et al., 2008),with the use of immunohistochemistry after an outbreak in the detection of NDV antigens of the disease in different samples of tissues from 25 broilers that had been previously vaccinated. This study also showed immunomarking in the epithelium of the trachea, as well as other organs, such as the lungs. Experimental infection carried out in the present study showed that lung and liver were not efficient for IHC: none of the experimentally infected birds presented positive reactions in these tissues, and they also showed a large number of unspecific reactions, making it difficult to interpret IHC results. Because of this, the evaluation of free-living birds was only carried out in trachea and spleen samples. In contrast, Cattoli et al. (2011),showed that birds infected with VVNDV presented intense distribution of the virus, in various tissues (bursa, spleen and thymus), detected by IHC. Columbiformes 46 Columba livia + + +: Positive immunomarking; -: negative immunomarking. virulent one (CA END strain), observed immunomarking in four samples (infected with the virulent strain), collected 3 to 5 days after inoculation, both in the spleen and lungs. Oldoni et al. (2005), also observed in embryos, 72 h after NDV infection, immunomarking in the lungs, as well as in muscles, skin, kidneys and corioalantoid membrane, when eggs were inoculated with mesogenic and velogenic strains. This finding demonstrated greater infectivity to other organs when infection was caused by virulent strains, as well as the presence of clinical signs. Finding of the viral antigen is directly related to the lesions and clinical signs presented by the birds (Nakamura et al., 2008). Because of this, as the trachea is the primary site of replication of NDV no matter the strain involved, it is the main tissue used in IHC (Alexander, 2003). In another investigation, Bwala et al.(2012) used immunohistochemistry to determine the distribution of NDV in the oviduct of chickens vaccinated with LaSota strain and experimentally infected with the virulent strain. Immunomarking was observed in epithelial cells and lymphocytes in the interstitium of the oviduct, corroborating greater infectivity to different organs, when virulent samples are considered. In free-living birds, from the 11 avian orders analyzed, only one (Caprimulgiforms) did not show any positive individual (Table 1). It should be emphasized that, as these were dead birds that were sent to our facilities, the number of individuals analyzed was not standardized. But it could be observed that the Passeriform order was the one with the greatest number of individuals analyzed and, consequently, the greatest number of positive birds (N =11). From the 24 positive free-living birds, 19 presented immunomarking exclusively in the trachea, 5 showed immunostaining in trachea and spleen, and only one presented immunostaining exclusively in the spleen. It is possible that the amount of circulating virus that goes through the spleen is too small to be detected by IHC, as already described (Kumar et al., 2010). This finding may be even more pronounced in the case of the present study, as birds did not show clinical signs compatible with NDV, and died of other causes. Birds analyzed in the present study were sent to the wildlife center by environmental authorities (Environmental Police and Environmental Institute of Paraná). These birds were undernourished, had traumas and fractures because they were apprehended from wild animal traffic, and died suddenly. Post-mortem descriptive analysis was carried out, and none of the birds showed macro-or microscopic lesions compatible with ND. There are nine serotypes of Avian Paramyxo virus (APMV), and virulence varies according to the virus strain and host species. The possible occurrence of crossreactions between APMV-1, which causes Newcastle disease, and APMV-3, whose pathogenicity is little known, has already been reported, and these crossreactions may affect diagnosis (Kumar et al., 2010). As the present study was based on polyclonal antibodies, cross-reactivity with other APMV may have occurred, once a high number of positive birds was found. This finding does not invalidate the present study, but demonstrates both APMV circulation and the need for typing studies to assess which virus strains may be found in free-living bird populations. Another possibility that supports the large number of positive results is the wide use of live vaccines against ND in Brazil (La Sota and Ulster strains). These live vaccines behave as pathogenic strains in the host, including primary replication in the trachea. Besides, the contact between vaccinated and unvaccinated birds may transmit the vaccine virus, leading to antibody levels similar to those of vaccinated birds ). Therefore, it is possible that positive birds had contact with vaccinated birds, although Wakamatsu et al. (2007) demonstrated that vaccinated birds did not show positive IHC reaction in lung and spleen samples. It should be emphasized that, although IHC provides important information on the distribution of NDV in tissues, molecular techniques should be also used, adding to the diagnostic sensitivity. Several differences have been observed in virus strains isolated from different species of birds, mainly free-living birds in different locations throughout the planet. It is very important to devise more accurate methods to evaluate the virulence of NDV isolates, especially in hosts other than chickens. Further studies are also needed to investigate the determinant factors in interspecies transmission (Guo et al., 2014). These NDV strains circulate in bird populations, generally without causing the disease, in a parasite vs. host balance. Outbreaks may occur when these free-living birds get in contact with commercial birds, with considerable losses to countries that raise and export poultry and poultry products. In conclusion, IHC, using polyclonal antibodies, is a diagnostic tool that may be used in locations that do not have biosafety levels for virus isolation, or that are even not able to perform molecular assays. IHC is applicable to free living birds, and brings important contributions to the knowledge on the circulation of both NDV and the other APMV, adapting, for example, the use of monoclonal antibodies.

v3-fos

2018-04-03T02:00:27.977Z

2015-11-14T00:00:00.000Z

18559709

s2

15‐F2t‐Isoprostane Concentrations and Oxidant Status in Lactating Dairy Cattle with Acute Coliform Mastitis Background Severe mammary tissue damage during acute coliform mastitis in cattle is partially caused by oxidative stress. Although considered a gold standard biomarker in some human conditions, the utility of 15‐F2t‐Isoprostanes (15‐F2t‐Isop) in detecting oxidative stress in dairy cattle has not been validated. Hypothesis Concentrations of 15‐F2t‐Isop in plasma, urine, and milk correlate with changes in oxidant status during severe coliform mastitis in cattle. Animals Eleven lactating Holstein‐Friesian dairy cows in their 3rd–6th lactation. Methods A case–control study using cows with acute coliform mastitis and matched healthy controls were enrolled into this study. Measures of inflammation, oxidant status, and redox status in plasma and milk samples were quantified using commercial assays. Plasma, urine, and milk 15‐F2t‐Isop were quantified by liquid chromatography/tandem mass spectrometry (LC‐MS/MS) and ELISA assays. Data were analyzed by Wilcoxon rank sum tests (α = 0.05). Results Plasma 15‐F2t‐Isop quantified by LC‐MS/MS was positively correlated with systemic oxidant status (r = 0.83; P = .01). Urine 15‐F2t‐Isop quantified by LC‐MS/MS did not correlate with systemic oxidant status, but was negatively correlated with redox status variables (r = −0.83; P = .01). Milk 15‐F2t‐Isop quantified by LC‐MS/MS was negatively correlated (r = −0.86; P = .007) with local oxidant status. Total 15‐F2t‐Isop in milk quantified by a commercial ELISA (cbELISA) was positively correlated with oxidant status in milk (r = 0.98; P < .001). Conclusions and Clinical Importance Free plasma 15‐F2t‐Isop quantified by LC‐MS/MS and total milk 15‐F2t‐Isop quantified by cbELISA are accurate biomarkers of systemic and mammary gland oxidant status, respectively. Establishing reference intervals for free and total 15‐F2t‐Isops for evaluating oxidative stress in dairy cows should currently be based on the LC‐MS/MS method. E scherichia coli bacteria are a major cause of clinical coliform mastitis in dairy cattle. 1 Uncontrolled bacterial replication caused by dysfunctional immune responses results in severe mammary tissue damage and death. 2,3 Excessive production of reactive metabolites (RM) by phagocytic cells results in oxidative mammary tissue damage observed during coliform mastitis. 4 Increased metabolism of polyunsaturated fatty acids (PUFA) such as arachidonic acid (AA) generates lipid hydroperoxides that contribute to the RM pool. 5 Enhanced mitochondrial metabolism also contributes large amounts of superoxide ions to the toxic pool of RM during inflammation. 5 Oxidative stress occurs when elevated RM overwhelm the antioxidant defenses and induce tissue damage. 6 Antioxidants include enzymatic and nonenzymatic systems that quench the damaging effects of RM. 5 The role of oxidative stress in clinical coliform mastitis was demonstrated by the increased severity of disease associated with decreased vitamin C and increased lipid hydroperoxides. In addition, supplementation of vitamin E and selenium in the transition period decreased the severity of clinical disease. [7][8][9] Reliable biomarkers of oxidative stress in cattle are currently lacking despite experimental evidence supporting the critical role of RM in the pathophysiology of coliform mastitis in cattle. 10 Lipids are particularly sensitive to RM attack resulting in generation of lipid hydroperoxides and isoprostanes. 6 Isoprostanes are prostaglandin-like metabolites of nonenzymatic peroxidation of AA. 11 Formation of these chemically stable peroxidation end-products starts with the free radical-mediated generation of an AA peroxyl radical followed by the cyclization into an F-pentane peroxyl ring that is then immediately reduced to F 2 -isoprostanes. 11 A total of generated and can be detected in biological samples by chromatography and mass spectrometry methods. 12 However, 15-F 2t -Isoprostanes (15-F 2t -Isop, also known as 8-isoprostanes) were the major isoform validated as gold standard markers of oxidative stress in humans. 12,13 Immune-based assays such as ELISAs that are specific to the common pentane ring in isoprostanes are used for 15-F 2t -Isop detection in some human biological samples, but are less accurate than the gold standard mass spectrometry techniques. 14,15 The detection of oxidative stress in cattle utilizes lipid hydroperoxides that are quantified by measuring their low molecular weight degradation aldehyde products such as malondialdehyde (MDA) using the thiobarbituric acid reactive substances (TBARS) method. 16 The TBARS method, however, lacks specificity to the lipidderived MDA because they can react with metabolites derived from other macromolecules including DNA and polysaccharides. 10 Therefore, determining the utility of 15-F 2t -Isop might provide an accurate marker for diagnosis of oxidative stress and monitoring treatment responses in veterinary medicine. 11 To date, 15-F 2t -Isop was not evaluated as biomarkers of oxidative stress during acute coliform mastitis. The purpose of this study, therefore, was to determine whether 15-F 2t -Isop could predict systemic and local mammary gland oxidant status during coliform mastitis using liquid chromatography/tandem mass spectrometry (LC-MS/MS). The potential utility of using commercial ELISA assays, validated for use in samples from humans, also were evaluated as alternative 15-F 2t -Isop quantification techniques on bovine samples. The hypothesis for this study was that 15-F 2t -Isop in plasma, urine, and milk correlate with the oxidant status associated with severe bovine coliform mastitis. This study determined both the utility of 15-F 2t -Isop as a biomarker of oxidative stress and provided a basis for defining reference intervals for evaluating oxidative stress associated with clinical and subclinical coliform mastitis. Animals Control and coliform mastitis cows in this study (n = 4/group) were randomly selected from larger groups with housing and diet information published elsewhere. 17 Another group of healthy cows (n = 3) was selected for assessment of ELISA assays before utilizing them in analyses of samples from the control and coliform mastitis study groups. This study was approved by the Michigan State University Institutional Animal Care and Use Committee (IACUC) and all cows were enrolled from the same herd with client consent. Study Design All cows enrolled in this study were multiparous Holstein dairy cows that ranged from 3rd to 6th lactation and averaged 69 (3-105) days in milk. Cows affected with acute coliform mastitis (n = 4) and matched healthy control (n = 4) made up the 2 experi-mental groups. The average body condition score was 3.06 (range: 2.75-3.50) for control cows and 3.00 (range: 2.50-3.50) for coliform mastitis cows. Cows in the coliform mastitis group had positive E. coli milk cultures (>100 colony forming units) and exhibited at least 2 signs of systemic clinical disease. Signs of acute systemic coliform mastitis included increased rectal temperature (>39.2°C), tachycardia (heart rate > 80 beats/minute), tachypnea (respiratory rate > 30 breaths/minute), episcleral injection, local signs of mammary gland inflammation including discoloration, swelling, heat and pain on palpation, and typical serum-like watery milk. By the time of sampling, coliform mastitis affected cattle had received at least a single dose of flunixine meglumine (2.2 mg/kg IV), ceftiofur sodium (2.2 mg/kg SC), and oral electrolyte fluids after standard farm treatment protocols. Healthy control cows had negative bacterial milk cultures, absence of overt clinical signs and a somatic cell count of <250,000 cells/mL on the last test day before the start of the study. Bacterial milk cultures were performed according to the National Mastitis Council guidelines. 18 Milk and blood samples were collected at the same time from mastitis and healthy control cows within 12 hours following a clinical diagnosis of systemic coliform mastitis. Sample Collection and Analyses Blood samples were collected in serum-separator and EDTA tubes, whereas urine and milk samples were collected in plain 15 mL tubes and processed on the day of collection and stored at À80°C until analyzed. Whole blood aliquot from EDTA tubes was processed, and analyzed for reduced (GSH) and oxidized (GSSG) glutathione a as previously described. 19 Plasma and serum were harvested after centrifuging at 711 9 g for 15 minutes. Plasma, milk, and urine for 15-F 2t -Isop quantification were mixed with an antioxidant reducing agent (AOR, 4 lL/mL) as described previously. 17 Using commercial assays, RM b were analyzed in plasma and milk with no AOR, whereas, serum amyloid A (SAA) c and haptoglobin (Hp) d were analyzed in serum. Serum albumin and nonesterified fatty acids (NEFA) were analyzed at the Diagnostic Center for Population and Animal Health (Lansing, MI). Plasma and milk antioxidant potential (AOP) were measured in samples collected without AOR agent as described previously. 20 Briefly, the AOP of a sample was standardized to the reduction capacity of trolox e (synthetic vitamin E analog) in 2,2 0 -azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) f solution. 15-F 2t -Isoprostane Quantification: LC-MS/MS Details for chemicals, sample processing, sample extraction and the LC-MS/MS protocol for the detection of 15-F 2t -Isop in plasma, urine, and milk were as previously described with some modifications. 17 Briefly, modifications included urine sample preparation where the first step was mixing 4 mL of sample with 24 lL of formic acid. Thereafter, urine samples were processed in the same way as plasma samples. Prostaglandin E 2 -d 9 (PGE 2 _d 9 ) was the single deuterated standard used as a reference for the quantification of 15- 15-F 2t -Isoprostane Quantification: ELISA assays The ELISA assays validated for human plasma and urine samples from Cell Biolabs (cbELISA) g and Cayman Chemicals (ccE-LISA), h were used for quantifying 15-F 2t -Isop in milk, plasma and urine samples. Preliminary performance of the ELISA assays was first determined on samples (milk, plasma, and urine) from healthy third lactation cows (n = 3) in the first 30 days in milk. Samples were pooled by type, split into 3 aliquots and assayed independently. Samples were assayed for free (unbound) and for total (free + esterified) 15-F 2t -Isop. Total 15-F 2t -Isop were measured after alkaline hydrolysis for milk and plasma, and acidic hydrolysis for urine. Hydrolysis of samples was based on the Cell Biolabs protocol with some modifications. Briefly, 200 lL of milk or plasma were combined with 50 lL of 10N sodium hydroxide and incubated at 45°C for 2 hours. For cbELISA analyses, after incubation, 55 lL of 6N hydrochloric acid (HCl) were added and samples were centrifuged for 5 minutes at 4,816 9 g and room temperature. Finally, a 1 : 2 sample dilution with neutralization solution to achieve a pH between 6 and 8 was performed. For ccELISA analyses, after incubation, plasma and milk samples were diluted to 1 : 6 using acetonitrile with 1% formic acid and centrifuged (4,816 9 g, room temperature for 5 minutes). The supernatant was eluted through 1 mL phenomenex solid phase extraction columns and dried in a SpeedVac (55°C, 2 hour). Residues were suspended in ccELISA buffer. For acidic hydrolysis, 200 lL of urine were combined with 50 lL of 6N HCL until a pH < 3.0 was reached and then diluted 1 : 6 with phosphate buffered saline. A final 1 : 3 urine sample dilution was performed with neutralization solution. In addition, a 10 ng quantity of a 15-F 2t -Isop standard was added to samples to assess the effect of the various sample preparation methods on 15-F 2t -Isop recovery. All ELISA assays were performed in duplicate following manufacturers' recommendations. Statistical Analyses No assumptions for normality of data were made because of the small sample size. All variables were expressed as median (range) concentrations and analyzed using the Wilcoxon rank sum procedure (a = 0.05) using the SAS i software. Spearman correlations between plasma and urine 15-F 2t -Isop concentrations to systemic inflammatory, oxidant status and redox status parameters were calculated. Similarly, Spearman correlations between milk 15-F 2t -Isop and the oxidant status and redox status parameters for the local environment in the mammary gland were calculated. For correlations, all data were combined to obtain a range of values for a given variable from normal to severely diseased cows. The ELISA assays were also compared for the detection and quantification of 15-F 2t -Isop concentrations in similarly processed samples. Results All 4 coliform mastitis cows exhibited local mammary gland signs of inflammation as well as signs of systemic involvement including tachycardia, tachypnea, pyrexia, and scleral injection. Within the coliform mastitis group, 3 cows died on days 1, 3, and 8 post sampling and 1 cow was still present in the herd at 105 days post sampling. Cows with naturally occurring coliform mastitis, in this study, had significant differences in the acute phase proteins with greater SAA and Hp (P = .014) and lower albumin (P = .043) concentrations than control cows. Serum NEFAs also were increased significantly (P = .029) in coliform mastitis cows compared to control cows (Table 1). Although AOP did not differ between experimental groups in milk or plasma, RM concentrations were greater in plasma (P = .029) and milk (P = .014) from coliform mastitis than control cows ( Table 2). Concentrations of reduced glutathione (GSH) were lower (P = .014), whereas concentrations of the oxidized form (GSSG) were greater (P = .057) in coliform mastitis than control cows. The ratio of reduced to oxidized glutathione (GSH : GSSG) was lower in mastitis than control cows (P = .051) ( Table 2). Plasma RM correlated positively with SAA (r = 0.69, P = .058) and Hp (r = 0.67, P = .071) and NEFAs (r = 0.31, P = .456) but negatively with serum albumin (r = À0.85, P = .008). ELISA Based 15-F 2t -Isop Quantification in Plasma, Urine and Milk Using the cbELISA, total 15-F 2t -Isop were greater (P = .05) in milk and plasma than the free 15-F 2t -Isop in samples (Fig 1A and B). For free 15-F 2t -Isop, spiking resulted in greater 15-F 2t -Isop (P = .05) compared to non-spiked and was associated with recovery rates of 73, 69 and 118% in milk, plasma, and urine, respectively. In spiked milk and plasma samples, hydrolysis resulted in greater total 15-F 2t -Isop (P = .05) with recovery rates of 106 and 291%, respectively. Using the ccELISA, there was no difference between free and total 15-F 2t -Isop (P = .20) in both milk and plasma (Fig 2A and B). For free 15-F 2t -Isop, spiking resulted in greater 15-F 2t -Isop (P = .05) compared to non-spiked and was associated with recovery rates of 102, 362 and 154% in milk, plasma, and urine, respectively. In spiked samples, hydrolysis resulted in greater total 15-F 2t -Isop (P = .05) in plasma with a recovery rate of 552%. Interestingly, hydrolysis of spiked milk samples resulted in significant (P = .05) lower 15-F 2t -Isop concentrations representing a 60% loss of the spiked amount. Based on significant differences between free and total 15-F 2t -Isop, milk and plasma samples were analyzed for both free and total 15-F 2t -Isop for the cbELISA. Only free 15-F 2t -Isop were analyzed by ccELISA in plasma and milk based on the lack of differences from total 15-F 2t -Isop. Following manufacturers' recommendations, urine samples for cbELISA were analyzed for both free and total 15-F 2t -Isop, whereas only free 15-F 2t -Isop were quantified by ccELISA. Total 15-F 2t -Isop in plasma and urine samples quantified by cbELISA did not differ significantly between control and mastitis cows, whereas greater 15-F 2t -Isop concentrations were detected in milk from coliform mastitis than control cows (Table 4). Free 15-F 2t -Isop quantified by cbELISA in urine and milk did not differ significantly between the mastitis and control group ( Table 4). The cbELISA estimated significantly greater (P = .014) free 15-F 2t -Isop concentrations in urine relative to the ccELISA within each of the mastitis and control cow groups (Table 4). Free 15-F 2t -Isop concentrations quantified by both cbELISA and ccELISA in nonhydrolyzed urine samples did not correlate with plasma oxidant or redox status parameters (Table 5). Similarly, free 15-F 2t -Isop concentrations quantified by cbELISA in milk did not correlate with milk oxidant status parameters (Table 5). Total plasma and urine 15-F 2t -Isop concentrations quantified by cbELISA in hydrolyzed samples did not correlate with oxidant status or redox status in plasma ( Table 6). Total milk 15-F 2t -Isop concentrations quantified by cbELISA were positively correlated with milk oxidant status variables (Table 6). Discussion Plasma and urine 15-F 2t -Isop concentrations are well established oxidative stress markers in several human diseases. 13 Cows suffering from naturally occurring with multi-organ damage in humans. 13,21 Plasma 15-F 2t -Isop are validated as indicating endogenous production in different tissues and the renal excretion closely reflects plasma levels. 22 In humans with acute respiratory distress syndrome (ARDS), exhaled breadth condensate and plasma 15-F 2t -Isop concentrations correlated significantly with urinary levels. 23 Plasma and urine samples are thus acceptable for evaluating 15-F 2t -Isop during oxidative stress in humans. In this study, both plasma and urine 15-F 2t -Isop correlated negatively with GSH, however, only plasma 15-F 2t -Isop significantly correlated with the systemic oxidant status. Reduced glutathione (GSH) is an important donor of thiol groups involved in scavenging of oxidants and maintaining redox balance. 5,24 A decrease in the GSH : GSSG ratio indicating depletion of the thiol donor is considered a useful measure of oxidative stress in sepsis-induced ARDS in humans. 25 On the basis of increased 15-F 2t -Isop that correlated positively with oxidant status and negatively with GSH, plasma is ideal for quantifying 15-F 2t -Isop reflective of systemic oxidant status in bovine coliform mastitis. The lack of significant correlation of urine 15-F 2t -Isop with oxidant status was unexpected as the renal excretion of 15-F 2t -Isop is related directly to its plasma concentrations. For example, a murine model of ischemia-reperfusion injury showed that renal excretion of 15-F 2t -Isop was increased by up to 300%. 26 In the same study, intrarenal infusion of 15-F 2t -Isop was associated with diminished glomerular filtration rate in a dose dependent manner suggesting a possible contribution of 15-F 2t -Isop in the pathogenesis of renal failure. 26 Renal failure is common in humans with sepsis and the association with plasma 15-F 2t -Isop is direct evidence for oxidative stress mediated damage. 21 Renal failure frequently occurs in cows with severe coliform NEFA, nonesterified fatty acids; RM, reactive metabolites represent reactive oxygen and nitrogen species; AOP, antioxidant potential; GSH, reduced glutathione; GSSG, oxidized glutathione; cbELISA, Cell Biolabs ELISA; 15-F 2t -Isop, 15-F 2t -isoprostane. ***P < .001 (Spearman correlation, a = 0.05) . The lower concentrations of 15-F 2t -Isop and its inverse correlation with the abundance of RM in milk was unexpected because oxidative stress mediates mammary gland damage, especially during coliform mastitis. 29 The presence of increased PUFA substrates in the same local environment of the mammary with excess RM could be expected to also generate increased 15-F 2t -Isop. A recent study found that several PUFA substrates were increased in milk during coliform mastitis in tandem with some nonenzymatic derived oxylipids including hydroperoxy acids from AA. 17 The formation of 15-F 2t -Isop, which occurs predominantly, while AA is esterified to phospholipids, 11 could explain the lack of prediction of oxidant status by free 15-F 2t -Isop quantified by LC-MS/MS in milk. The concentrations of free 15-F 2t -Isop in milk also were inversely correlated with free 15-F 2t -Isop concentrations in plasma suggesting that differential release from esterification sites might exist across compartments. The 15-F 2t -Isop initially formed in situ esterified to phospholipids are subsequently hydrolyzed to yield free 15-F 2t -Isop by phospholipase (PL) enzymes. 28 Differential PL activity was detected in humans where the activity in plasma was greater with more 15-F 2t -Isop hydrolysis compared to intracellular PL. 30 The concept of differential hydrolysis was supported by the use of a hydrolysis method and analyzing for total 15-F 2t -Isop by 1 of the 2 ELISA assays (cbELISA) in this study which yielded greater concentrations that positively correlated with milk oxidant status. Therefore, it appears that predictive ability of 15-F 2t -Isop concentrations on local mammary gland oxidant status during coliform mastitis can be improved by performing sample hydrolysis. Further research is required to understand the counterintuitive decrease in 15-F 2t -Isop concentrations in the presence of increased RM especially when other nonenzymatic oxylipid metabolites were detected in nonhydrolyzed samples. An alternate approach to LC-MS/MS for the quantification of 15-F 2t -Isop is by use of immunoassays such as ELISA. 12 Despite the reported accuracies of plasma and urine 15-F 2t -Isop quantified by ELISAs of 95-101%, ELISAs are often affected by cross-reactivity from prostaglandin and other isoprostane metabolites because they target a single metabolite. 12,14 Free 15-F 2t -Isop in milk and urine as well as total 15-F 2t -Isop in plasma and urine, analyzed by cbELISA, failed to predict oxidant status. Only the total 15-F 2t -Isop quantified in milk by cbELISA demonstrated potential reliability that was supported by the accurate recovery (106%) of the spiked 15-F 2t -Isop standard (Fig 1A). Variable performances of ELISAs in quantifying 15-F 2t -Isop were previously reported in studies in veterinary species and humans that reported poor correlations with GC/MS or LC-MS/MS as well as between different ELISA assays. [31][32][33] Results of this study showed that, despite acceptable recovery rates by the ccELISA (102%) on free milk 15-F 2t -Isop and cbELISA (118%) on free urine 15-F 2t -Isop, there was no correlation with oxidant status. Further, the variable performances of the ELISAs as shown by both overestimation (plasma, cbELISA, Fig 1; plasma and urine, ccELISA, Fig 2) and underestimation (milk, ccELISA Fig 2) make it impossible for general recommendations for using ELISA in quantifying 15-F 2t -Isop in bovine samples. A recent study reported a positive linear correlation between milk and plasma 15-F 2t -Isop by utilizing an ELISA based (ccELISA) assay. The investigators of that study suggested that milk was a possible alternate route of 15-F 2t -Isop excretion. 34 The inverse correlation between free 15-F 2t -Isop in plasma and milk using LC-MS/MS in this study does not support the possibility of milk as a route of excretion for 15-F 2t -Isop. An expanded lipidomic profile during coliform mastitis showed lack of correlation among several oxylipids suggesting that oxylipid biosynthesis, including isoprostanes, between plasma and milk could be independent of each other. 17 The difference in the correlation with the present findings might be the use of a disease model associated with high degree of oxidative stress, as well as different sample extraction methods. It is unclear whether the study 34 analyzed free or total 15-F 2t -Isop in both milk and plasma. The performance of ELISA assays in quantifying 15-F 2t -Isop in bovine samples should be validated with the gold standard mass spectrometry-based methods such as the LC-MS/MS. In conclusion, results of this study show that free plasma 15-F 2t -Isop concentrations are predictive of systemic oxidant status during acute coliform mastitis. Free 15-F 2t -Isop in urine and milk were not predictive of systemic or local mammary gland environment oxidant status, respectively. Quantification of total 15-F 2t -Isop in milk by cbELISA is an accurate alternative to LC-MS/MS and suggests that milk samples should be hydrolyzed when determining 15-F 2t -Isop associated with oxidant status in the mammary gland. The lack of significance for some variables in this study might have been because of the small number of experimental animals in this study. Findings of this study can thus be used as a basis for further studies designed to provide broader scope inferences. Establishing threshold concentrations for 15-F 2t -Isop during clinical coliform mastitis will provide a basis for formulation and application of practical interventions to control oxidative stress in dairy cows and currently should be based on gold standard methods such as LC-MS/MS.

v3-fos

2015-09-18T23:22:04.000Z

2015-06-01T00:00:00.000Z

18060749

s2

Transcriptomic Analysis of Flower Blooming in Jasminum sambac through De Novo RNA Sequencing Flower blooming is a critical and complicated plant developmental process in flowering plants. However, insufficient information is available about the complex network that regulates flower blooming in Jasminum sambac. In this study, we used the RNA-Seq platform to analyze the molecular regulation of flower blooming in J. sambac by comparing the transcript profiles at two flower developmental stages: budding and blooming. A total of 4577 differentially-expressed genes (DEGs) were identified between the two floral stages. The Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed that the DEGs in the “oxidation-reduction process”, “extracellular region”, “steroid biosynthesis”, “glycosphingolipid biosynthesis”, “plant hormone signal transduction” and “pentose and glucuronate interconversions” might be associated with flower development. A total of 103 and 92 unigenes exhibited sequence similarities to the known flower development and floral scent genes from other plants. Among these unigenes, five flower development and 19 floral scent unigenes exhibited at least four-fold differences in expression between the two stages. Our results provide abundant genetic resources for studying the flower blooming mechanisms and molecular breeding of J. sambac. Introduction Jasminum sambac (L.) Ait. (Oleaceae) is a small erect or climbing shrub that is native to Bhutan and India. This shrub is cultivated as an ornamental plant worldwide for its attractive and sweetly fragrant flowers. The species grows up to 0.5 to 3 m in height. The leaves are ovate, and the phyllotaxy is opposite or in whorls of three. The flowers bloom from May to August and are produced in clusters of three to 12 together at the ends of branches. To date, no pollination studies have been reported on J. sambac. This species has a few morphological and biological characteristics adapted to cross-pollination; these characteristics include large and white petals and strong and sweet fragrances. Previous studies on J. sambac have mainly focused on its aromatic compounds [1][2][3], medicinal value [4][5][6] and cultivation physiology [7][8][9]. Molecular biology studies on this species are rare. Two studies cloned three genes involved in the biosynthesis of aromatic volatiles. These genes are deoxyoxylulose-5-phosphate synthase [10], fatty acid hydroperoxide lyase and germacrene D synthase [11]. The transition to blooming is a critical phase switch from vegetative growth to reproductive growth in flowering plants, which ensures sexual reproduction and subsequent generation development. Endogenous and environmental signals initiate a complex network of genetic pathways to activate blooming. The molecular regulatory mechanism underlying flower development has been extensively studied in model plants, such as Arabidopsis and Antirrhinum [12]. A few transcriptomic studies in recent years have investigated the molecular regulation of flower development in non-model plants, such as Litchi chinensis [13] and Nelumbo nucifera [14]. However, these studies have focused more on the molecular regulation of floral initiation than blooming. Flower blooming is also a key developmental stage, especially in out-crossing flowering plants. Transcriptome sequencing is an efficient method to provide extensive data in a short period with enormous depth and coverage. Such data are important to understand the development processes in plants [13][14][15]. In the present study, the RNA-Seq platform based on the Illumina sequencing system was used to characterize the transcriptomic response during flower blooming by comparing the different transcriptomes at two developmental stages of J. sambac. This study aims to characterize the transcriptomes of J. sambac and increase the genetic resources available for the genetic or breeding analysis of J. sambac. RNA-Seq and Assembly To understand the molecular basis of flower blooming in J. sambac, the flower budding stage (T1) and flower blooming stage (T2) were used to build two libraries for high-throughput sequencing ( Figure 1). After cleaning and quality checks, the two libraries produced 3975 and 4570 MB of raw data ( Table 1). The phred quality score of >30 (Q30) and guanine-cytosine (GC) percentages of the two libraries were 91.36% and 45.27% and 90.51% and 44.64%, respectively. Approximately 42 million reads (about 19.68 and 22.67 million for T1 and T2, respectively) were obtained from the total RNA-Seq data. Assembly of reads resulted in 113,394 transcripts and 49,772 unigenes with mean sizes of 1425 and 846 bp, respectively (Table 2 and Supplementary Material 1). Transcriptome Functional Annotation No closely-related species genome has been reported to date. The genes of this species were annotated as transcriptome without genome. A total of 25,131 unigenes were annotated by searching in the non-redundant (Nr) protein, Swiss-Prot, Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Groups (COG) and Gene Ontology (GO) protein databases. The Nr, Swiss-Prot, KEGG, COG and GO protein databases identified 25,110, 327, 5750, 8236 and 5074 unigenes, respectively. GO functional classification was performed using BLAST to understand the distribution of the function of unigenes at the macro level. The results showed that these unigenes were assigned to a total of 54 subgroups: 15 subgroups in the "cellular component" group, 15 in "molecular function" and 24 in "biological process" (Figure 2). The top five largest subgroups containing the most unigenes were "metabolic process", "cell", "cell part", "organelle" and "binding" (Figure 2). Pathway analysis with KEGG annotation indicated that these unigenes were involved in 131 pathways (Supplementary Material 2). The highest levels of gene representation were found in "ribosome", followed by "protein processing in endoplasmic reticulum" and "spliceosome". Differentially-Expressed Genes The false discovery rate (FDR) ≤ 0.01 and the absolute value of log2 ratio ≥2 served as the criteria to screen differentially-expressed genes (DEGs). A total of 4577 DEGs (9.20%) were identified between the two floral stages. Among these DEGs, 2292 were upregulated and 2282 were downregulated at T2 compared with T1; 3638 of the 4577 DEGs could be identified in the five protein databases (Supplementary Material 3). The GO annotation of DEGs showed that these genes were assigned to 44 subgroups: 12 in the "cellular component" group, 11 in "molecular function" and 21 in "biological process". The top five largest subgroups containing the most DEGs were "metabolic process", "cellular process", "catalytic activity", "cell part" and "cell" (Supplementary Material 4). GO enrichment analysis indicated that significant differences in the DEGs between the two stages in "biological process: oxidation-reduction process" (p = 0.0008) and "cellular component: extracellular region" (p = 0.0287). KEGG annotation of DEGs indicated that these genes were involved in 111 pathways (Supplementary Material 5). The highest levels of gene representation were found in "ribosome", followed by "plant hormone signal transduction" and "starch and sucrose metabolism". KEGG enrichment analysis indicated that the DEGs significantly differed in "steroid biosynthesis" (p = 0.0045), "glycosphingolipid biosynthesis-globo series" (p = 0.0248), "plant hormone signal transduction" (p = 0.0380) and "pentose and glucuronate interconversions" (p = 0.0407). Manual Identification of Flower Development and Floral Scent Genes To identify flower development genes in J. sambac, we used the unigene sequences in the BLAST searches of the five protein libraries. A total of 103 unigenes had sequence similarities to the known flower development genes from other plants (Supplementary Material 6). However, most of the flowering development genes (98 of 103) identified in the present study showed no significant differences. The five DEGs were CLAVATA2 (CLV2; c33279.graph_c0), minichromosome maintenance protein 3 (MCM3; c32310.graph_c0), minichromosome maintenance protein 5 (MCM5; c34031.graph_c0), Tesmin/TSO1-like CXC2 (TCX2; c28717.graph_c0) and AGAMOUS-like 15 (AGL15; c31056.graph_c0), which were all downregulated when compared T2 with T1 (Supplementary Material 6). Previous studies reported that the aromatic constituents of J. sambac were more than 90 compounds [2]. In this study, we searched the genes that were related to the synthesis of 15 aromatic compounds with the highest relative content in J. sambac [2]. A total of 92 floral scent unigenes were found, 19 of which were identified as DEGs (nine upregulated and 10 downregulated; Table 3). Discussion Transcriptome analysis is a powerful tool that enables gene discovery and improves our understanding of the molecular regulatory mechanisms of plants under different developmental stages or different growth conditions [16][17][18]. This method has been recently employed in studies on flower development [14,15]. Flower development is an important process throughout the life cycle of seed plants; this process targets successful fertilization and propagation of the subsequent generation. Previous studies on flower development have focused on floral initiation, which determines floral organ or controls blossom time [19]. However, flower blooming is also a highly coordinated event that ensures sexual reproduction, and this stage is accompanied by the enlargement of floral organ, maturity of pistil and stamen, a change in flower color and the emission of floral scent. To date, only one study has conducted the transcriptome analysis of flower blooming in Rosa chinensis [20]. The present study used RNA-Seq technology to profile the transcriptome of J. sambac and obtained approximately 42 million reads. A total of 25,131 unigenes were successfully annotated against five public protein databases, suggesting their relatively conserved functions. These unigenes were then assigned to 54 GO subgroups and 131 pathways, which indicated the complex regulatory machinery involved in flower blooming. Although only petals of J. sambac were selected as the material, our results suggested that a large number of genes were involved in this process. Analyses of GO categories revealed that the five largest subgroups containing the most unigenes were "metabolic process", "cell", "cell part", "organelle" and "binding". Three of these subgroups were in the "cellular component", which suggested that the main changes between the two stages resulted from the enlargement of cell size or the increase in cell number. Pathway analysis with KEGG annotation indicated that the highest levels of gene representation were found in "ribosome", "protein processing in endoplasmic reticulum" and "spliceosome". Two of them were related to the synthesis and processing of proteins. To isolate DEGs between T1 and T2, 4577 DEGs were identified. The GO annotation of DEGs showed that the top five largest subgroups were "metabolic process", "cellular process", "catalytic activity", "cell part" and "cell". Three of these subgroups were related to the cellularity, which further confirmed that the main changes between the two stages resulted from the enlargement in cell size or the increase in cell number. This result is consistent with the GO analyses of all unigenes. KEGG enrichment analysis indicated significant differences in the DEGs between the two stages in "steroid biosynthesis", "glycosphingolipid biosynthesis-globo series", "plant hormone signal transduction" and "pentose and glucuronate interconversions". The pathways associated with flower development, such as "steroid biosynthesis", "plant hormone signal transduction" and "pentose and glucuronate interconversions", had also been found in other plants [21][22][23][24]. However, previous studies have not reported the involvement of "glycosphingolipid biosynthesis-globo series" in flower development. The current study is the first to report that pathways show significant differences during flower development. Unigenes related to flower development were manually identified in this study. However, most of the flowering development-related genes were non-DEGs. The five DEGs related to flower development (CLV2, MCM3, MCM5, TCX2 and AGL15) might be involved in flower blooming. The CLV2 gene regulates both meristem and organ development in Arabidopsis [25]. MCM3 and MCM5 are abundantly expressed in flower buds in Arabidopsis, which are related to the DNA replication [26,27]. In Arabidopsis, TCX2 regulates cell proliferation and differentiation during flower development [28]. AGL15 as a member of the MADS regulatory factors can delay senescence and increase floral organ longevity [29]. These findings provide new research directions that might deepen our understanding of blooming regulation in J. sambac. Few aromatic compounds are released at the bud stage in J. sambac. However, the release quantity of compounds increases rapidly at the blooming stage [1]. The release mechanism of this floral scent is probably to attract pollinators. In this study, we identified 92 candidate floral scent genes related to 15 aromatic compounds with the highest content. Most of them (73 of 92) did not express significant differences between two stages. The remaining 19 unigenes were DEGs: three related to linalool, one to alpha.-farnesene, one to alpha.-caryophyllene, two to 3-hexen-1-ol, benzoate, three to acetic acid, phenylmenthyl ester, five to methyl salicylate, one to benzyl benzoate, one to indole and two to benzyl alcohol. The 3-hexen-1-ol, benzoate, acetic acid, phenylmenthyl ester, linalool, alpha-farnesene and methyl salicylate had the top five highest content of the aromatic compounds in J. sambac. Our results explained the significant aromatic compound differences between the two stages. Plant Material J. sambac plants were bred in the trial plot of the Ornamental Horticulture Laboratory at Henan Agricultural University under the same cultivation conditions. Two stages were sampled for transcriptomic sequencing: flower bud stage (T1) and flower blooming stage (T2) (Figure 1). Samples at the T1 stage were collected at 18:00 h, and samples at the T2 stage were collected at 18:00 h the next day. The petals of each stage were sampled from three comparable plants using three biological replications. All samples were immediately frozen in liquid nitrogen and stored at −80 °C for RNA extraction. RNA Isolation, Library Construction and Sequencing Total RNA of each sample was isolated using a Quick RNA isolation kit (Bioteke Corporation, Beijing, China) according to the manufacturer's protocol and treated with RNase-free DNase I (Takara, Dalian, China) to remove genomic DNA contamination. Thereafter, RNA was characterized on a 1% agarose gel and examined with a NanoDrop ND1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). The RNA integrity number values of these samples were assessed using a 2100 Bioanalyzer RNA Nano chip device (Agilent, Santa Clara, CA, USA). The RNA integrity number was greater than 8.0 for all samples. Thirty micrograms of total RNA were pooled in equal amounts from the three biological replicates for subsequent RNA-Seq. The construction of the libraries and the RNA-Seq were performed by the Biomarker Biotechnology Corporation (Beijing, China). Poly (A) mRNA was purified from total RNA using oligo (dT)-attached magnetic beads and then broken into short fragments by fragmentation buffer. Taking these cleaved mRNA fragments as templates, the first strand of cDNA was synthesized by priming with random hexamer. The second strand was generated with buffer, dNTPs, RNase H and DNA polymerase I. The double-stranded cDNA fragments were purified with an Agencourt AMPure XP kit (Beckman Coulter, Brea, CA, USA) and resolved with elution buffer (EB) for end repair and the addition of single nucleotide A, and then sequencing adaptors were ligated to the fragments. The suitable size range fragments were selected and purified by AMPure XP beads, and the purified cDNA templates were further enriched using PCR amplification. The cDNA library was sequenced using an Illumina HiSeq 2500 sequencing system (Illumina Inc., San Diego, CA, USA). Sequence Cleaning, Assembly and Contig Annotation The raw reads were cleaned by removing adapter sequences, reads with unknown bases greater than 10% and reads with quality scores lower than 20. The left files from all libraries were pooled into one big left.fq file and right files into one big right.fq file. Transcriptome assembly was accomplished based on the left.fq and right.fq using Trinity [30] with min_kmer_cov set to 2 by default and all other parameters set as the default. The contigs with a length less than 200 bp were discarded due to a low annotation rate [31]. The filtered data were deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under the Accession Numbers SRX868770 and SRX868796. In this study, about 4 G of sequencing data per sample were finally collected. The present sequencing data were completely saturated [32] and sufficient for subsequent analysis (Figure 3). Expression Annotation Gene expression was carried out with RNA-Seq by Expectation-Maximization (RSEM) software [39] bundled with the Trinity package. The gene expression level was calculated using the fragments per kilobase of transcript per million mapped (FPKM) method [40]. The FPKM method eliminates the influence of different gene lengths and sequencing discrepancies on the quantification of gene expression to enable the direct comparison of gene expression between samples. For gene expression difference analysis, Benjamini-Hochberg's method [41] was used to correct the p-values. FDR ≤ 0.01 and the absolute log2 ratio ≥ 2 were used as the thresholds to determine the significance of gene expression differences between samples at the T1 and T2 stages. For GO enrichment analysis, topGO [42] was used to identify the statistically overrepresented GO terms for the DEGs. For pathway enrichment analysis, all DEGs were searched for significantly enriched KEGG terms compared with the entire transcriptome background with Fisher's exact test [43]. Conclusions This study represents the first broad-scale gene expression study on J. sambac. The transcriptome analysis based on the Illumina sequencing system to monitor global transcriptional changes at two flower developmental stages has enabled the comprehensive description of differential transcriptional events during blooming in J. sambac. A total of 49,772 unigenes were assembled, and 25,131 unigenes were successfully annotated. These unigenes were assigned to 54 GO subgroups and 131 pathways, which indicated the complex regulatory machinery involved in flower blooming. We also identified 103 flower development candidate genes and 92 floral scent candidate genes. Among these genes, five flower development genes and 19 floral scent genes were DEGs. Notably, transcriptome analysis with more samples at different flower developmental stages and gene function validation using real-time qRT-PCR were necessary for future studies on J. sambac.

v3-fos

2018-04-03T05:12:34.801Z

2015-05-30T00:00:00.000Z

16330519

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Transcriptomic analyses of maize ys1 and ys3 mutants reveal maize iron homeostasis To acquire iron (Fe), graminaceous plants secrete mugineic acid family phytosiderophores (MAs) (Takagi, 1976 [1]) through the MAs efflux transporter TOM1 (Nozoye et al., 2011 [2]) and take up Fe in the form of Fe(III)–MAs complexes through the Fe(III)-MAs transporter YS1 (Curie et al., 2001 [3]). Yellow stripe 1 (ys1) and ys3 are recessive mutants of maize (Zea mays L.) that result in symptoms typical of Fe deficiency, i.e., interveinal chlorosis of the leaves. The ys1 mutant is defective in the YS1 transporter and is therefore unable to take up Fe(III)–MAs complexes. While the ys3 mutant has been shown to be defective in MA release, the causative gene has not been identified. The objective of the present work was to identify the genes responsible for the ys1 and ys3 phenotypes, so as to extend our understanding of Fe homeostasis in maize by qRT-PCR. In agreement with previous reports, the expression level of YS1 was decreased in the ys1 mutant. Moreover, we identified that the expression level of a homolog of TOM1 in maize (ZmTOM1) was significantly decreased in the ys3 mutant. Here described the quality control and analysis that were performed on the dataset. The data is publicly available through the GEO database with accession number GSE44557. The interpretation and description of these data are included in a manuscript (Nozoye et al., 2013 [4]). Plant materials The homozygous seeds of Yellow stripe 1 (ys1) and ys3 mutant plants were used to identify the genes responsible for the ys1 and ys3 phenotypes, and to extend our understanding of Fe homeostasis in maize. A WT cultivar (Alice) was used as a control, as even though it has a different genetic background from ys1 [3] and ys3 [4], this line was previously used in a study of the ys1 mutant [5]. Seedlings germinated for 4 days in the dark at 25°C were grown hydroponically in a nutrient solution that contained 0.7 mM K 2 SO 4 , 0. RNA preparation The maize plants grown hydroponically were immediately frozen in liquid nitrogen. Total RNA was extracted from the shoots and roots of Contents lists available at ScienceDirect Genomics Data j o u r n a l h o m e p a g e : h t t p : / / w w w . j o u r n a l s . e l s e v i e r . c o m / g e n o m i c s -d a t a / three plants per treatment using an RNeasy Plant Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer's instructions. The yield and purity of the RNA were determined spectrophotometrically. To confirm the biological replicates, RNA was separately extracted from the shoots and roots of three to five plants per treatment. Quantitative real-time PCR Total RNA (3 μg) was treated with RNase-free DNase I (Takara, Kyoto, Japan) to remove contaminating genomic DNA. First-strand cDNA was synthesized using ReverTra Ace reverse transcriptase (Toyobo, Tokyo, Japan) by priming with oligo-d(T) 30 . For quantitative RT-PCR, a fragment was amplified by PCR in a StepOnePlus Real-Time PCR system (Applied Biosystems, Foster City, CA) with SYBR Green I and ExTaq™ Real-Time PCR Version (Takara) according to the manufacturers' instructions. The template concentration was adjusted to 30 ng per reaction. The primers used for real-time PCR are described in Table 1. The primers used as the internal control (ZmUbiquitin, GRMZM2G118637) in RT-PCR were as follows: ZmUbiquitin forward, 5′-GTTGAAGCTGCTGCTGTA TCTGG-3′ and ZmUbiquitin reverse, 5′-GCGGTCGCACGATAGTTTTG-3′. Data normalization Because the maize genes analyzed in this study were not cloned, normalization of quantitative real-time PCR was performed by the comparative Ct method calculation according to the manufacturer's instructions (Applied Biosystems StepOnePlus™ Real-Time PCR system). Briefly, relative quantitation was calculated as follows. The threshold cycle (Ct) indicates the fractional cycle number at which the quantity of amplified target reaches a specified threshold. First, the amount of target was normalized to endogenous reference. There is a relation between the amount of the endogenous reference and the amount of PCR products by Ct value as follows: the amounts of PCR products by Ct value = the amount of the endogenous reference X 2Ct. Therefore, △Ct value is calculated as follows: △Ct = Ct value of the target -Ct value of the endogenous reference. Secondly, the difference between the calibrator which is used as base and the △Ct is calculated as follows: △△Ct = △Ct value of the target -△Ct value of the endogenous reference. Finally, the relative quantitative value is calculated as follows: the relative quantitative value = 2 -△△Ct. Since the relative quantitative value of the calibrator is 20 = 1, the other samples are calculated as the relative quantitative value when the value of calibrator is 1.The principle of the comparative Ct method calculation is described in ABI PRISMⓇ 7700 Sequence Detection Systems User Bulletin #2 (www.appliedbiosystems.co.jp). Table 1 Primers used for quantitative real-time PCR. Gene name Gene ID in Gramene Data validation The data show the relative increase or decrease of the gene expression level in each sample compared to the gene expression levels in Fe-sufficient shoots of the non-transformant (NT) in three experimental replicates and three to five biological replicates. Because the cultivar among ys1, ys3 and WT were different from each other, it was possible that there are polymorphisms in the analyzed genes and the efficiency of PCR are different from each other. Therefore, the sizes and sequences of the amplified fragments were confirmed by agarose gel electrophoresis (Fig. 1) and with an automated sequencer (3130 Genetic Analyzer; Applied Biosystems), respectively. Analysis of variance with the Tukey-Kramer HSD test was used to compare data. Discussion Herein we described transcriptional profiling of Fe recessive mutants ys1 and ys3 in the different cultivars. In this dataset, we confirmed the decrease of YS1 expression level in ys1 compared to WT as described previously. The expression level of YS1 was not altered in ys3. In addition, we found that the expression level of ZmTOM1 was decreased in ys3 compared to WT, but not in ys1. Both YS1 [3] and TOM1 [2] are important transporter of MAs [1] which is involved in not only Fe acquisition from soil but also Fe homeostasis in the plant body. We believe that this dataset could provide insights into the characteristics of the YS1 and TOM1 transporters which involved in MAs transport to maintain Fe homeostasis in maize. We believed that the method in this dataset may assist in elucidation of the various mutants which are from different cultivars. Disclosures All authors possess no conflicts of interests.

v3-fos

2019-04-29T13:07:25.698Z

2015-08-30T00:00:00.000Z

138093269

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Experimental investigation on heat transfer characteristics of soft clay at high temperatures Fire occurred in underground engineering such as tunnel will cause the change of the temperature field in the surrounding soil. The study on thermal conductivity of soils in fire environment is very important. This paper focuses on the experimental study on heat transfer characteristics of soft clay in Shanghai in high temperature environment over 100°C. The test results show that the change of internal temperature of initial saturated soils can be roughly divided into four stages, namely rapid heating stage I, constant temperature stage II, the second rapid heating stage III and the final constant temperature stage IV, when the drainage and exhaust are allowed in the high temperature environment. There is a peak value in the high temperature curve, the higher the temperature the bigger the peak value. According to comprehensive analysis of the heating curves under different temperature, high temperature has significant influence on thermal conductivity of soils and causes the increasing of thermal conductivity for wet soil and dry soil. The thermal conductivity of dry soil is relatively smaller than that of wet soil. INTRODUCTION With the development underground engineering such as tunnels, more accidents were caused by fire in underground engineering (Yan, 2007;Qiang et al., 2006;Ulm et al., 1999;Carvel, 2004) and the fire will cause the changing of the temperature field in the soil around the structure. When the temperature field changes in the soil, the stress field, displacement field, and seepage field will change correspondingly. These changes influence each other and will do harm to tunnels and other underground structures in turn. Therefore, the temperature field in the surrounding soils of the structure has attracted scientific and technological workers' attention. The thermal conductivity is an important indicator of soils to properly evaluate its thermal characteristics, which reflects the capacity of soils to conduct heat. Therefore, it is very important to study the thermal conductivity of soils in fire environment. A lot of researches have been carried out on thermal characteristics of soils. DE Varies and Peck (1958), proposed the cylindrical probe method used to measure the thermal conductivity of soils in 1957; Johansen (1975) published Thermal Conductivity of Soils detailing the way of heat transfer in soils and methods of measuring thermal conductivity in 1975; Farouki (1986) published Thermal Properties of Soils describing in detail the transfer mechanism of heat in soils, and measuring methods, factors and computing method of thermal characteristics in 1981; Becker, Misra and Fricke (1992), studied the impact of the saturation and dry density on five types of soils and established a set of correlation empirical formula in 1992; Côté and Konrad (2005), studied thermal conductivity of several types of soils and established a generalized model for thermal conductivity of soils in 2005; Ludynia and Orman (2013), conducted macro and micro experiments of thermal conductivity of soils in 2013. Zhang (2004) studied the thermal conductivity of mixtures of sandy soils and soils in Eastern China and gave an experimental correlation; Lu (2009) studied thermal conductivity of rock-soils at various temperatures, and the results showed that the temperature significantly impacted the thermal conductivity of soils; Chen (2011) studied the thermal conductivity of the No. 4 soft silty clay in Shanghai, and analyzed the correlation between the thermal conductivity and void ratio. These studies focused on thermal characteristics at temperatures below 100°C, and there were scarce researches on the influence of temperature on thermal characteristics of soil under fire conditions in which the temperature often were higher than 100°C (Xu, 2012). Therefore, it is meaningful to study the thermal conductivity of soils under high temperature above 100°C. Based on self-developed high-temperature heating equipment, experimental study was carried out on thermal characteristics of soils for temperatures above 100°C, and the law of thermal conductivity changing with temperature was obtained. Soil material The soil samples used in this experiment was taken from an industrial plant located in east of Qishen Road, west of Wupo Road, south of Huxing Road, Minhang District, Shanghai. The site is in the leading edge of the estuary of the Yangtze River Delta, and its landform belongs to coastal plain which is one of the four major landforms in Shanghai. Soils was digged from 10m underground and was marine sediments of Holocene Q 4 2 .The soils belonged to warp clay with gray surface and was a main soil layer often crossed by subway tunnel projects in Shanghai. The basic physical properties of the natural soil samples are showed in Table 1. The self-made pressure controllable multifunctional soils heating experimental system was used in this experiment (patented by State Intellectual Property Office of the R.P.C), which could achieve rapid heating with temperature controlled, as shown in figure 1. The experiment system consists a soil sample sealer placed in a temperature controlled heating furnace connected to a pneumatic valve at the upper. The interior dimension of sealer is 39.1 mm in diameter D and 80 mm in height H. In order to measure the temperature in the soil samples, three high precision probe type K-thermocouples were positioned at regular interval in the radius direction. The probe was 20 mm in length and 3 mm in diameter. High temperature wires are utilized for thermocouples. Three thermocouples were combined with data acquisition device called datataker at the same time, then data were outputted to a terminal computer. The test principle is shown in figure 2, in which TC represents thermocouples. 39 Test procedure The natural soil samples were loaded in the soil sample sealer after drying and crushing. Saturated soil samples were prepared according to GBT 50123-1999 and were placed in a sealed container for later use. The water content of soil samples was 48.3%, and the weight density was 17.5 KN/m 3 . The prepared saturated soil samples were loaded in the soil sample sealer as shown in Figure 2. The samples was prepared by the way of loading, vibrating and shaving in layers, instead of the method for triaxial test in GBT 50123-1999, in order to ensure the uniformity of soil samples (preparing steps of soil samples could be found in the literature by Chen (2015)). If using the method in GBT 50123-1999, the liquidity of samples was very poor, and the samples was uneven due to serious stratification. And if loaded in layers using compacting instrument and sleeve according to GBT 50123-1999, the viscosity of soils would make some or all of the soils adhere to compacting instrument. And the samples were still seriously stratified. Permeable stones were covered and fixed at both ends of the sealer with soil samples, so that water and air could be exhausted from both ends of samples freely. Then the sealer was installed into the temperature controlled heating furnace, and began to be rapidly heated (10°C/min), the data acquisition system opened at the same time. The temperatures of soils were measured respectively for four hours at constant temperature of 105°C, 150°C and 200°C. The temperature change and heat transfer characteristic of soil The experimental results are shown in Fig. 3 and Fig. 4, in which T, t and TC respectively represented temperature, time and thermocouple. As can be seen from Fig. 3, the changing of temperature can be roughly divided into two stages, rapid heating stage I and constant temperature stage II. After four hours at a constant temperature, the temperature of soil samples still did not reach 105°C. The soil was completely saturated at initial conditions and the heat was conducted mainly through the mixture of soils and water, namely both water and soils acted as the bridge for conducting heat. At this time, the mixture of soils and water could be regarded as a uniform heat conductor as the soil particles were completely surrounded by water. Therefore, the interior temperature of samples rose quickly, namely rapid heating stage. As the temperature rose, the water vapor gradually increased, and with the escape of water vapor, the pore increased inside soils. Then the heat was conducted mainly through soil particles, water and steam, and the temperature of soils continued increasing. When the moisture in soil was completely evaporated, the heat in soils was conducted mainly through the steam and soil particles. At this time, the temperature of soils remained at about 100°C and would not rise due to the presence of water vapor, namely constant temperature stage in the Fig. 3. However, if the heating time was long enough, the water vapor in the soil would got out completely, then the heat would be conducted completely by the soil particles and the temperature would continue rising until the temperature of soils reach the heating temperature. As can be seen from Fig.4, the change of temperature could be divided into four stages, namely rapid heating stage I, constant temperature stage II, the second rapid heating stage III and the final constant temperature stage IV. The mechanism of the first two stages in Fig.4 was similar to that in Fig.3, but there were two differences. First, there was a peak exceeding 100°C in rapid heating stage, and the higher the temperature the greater the peak. At ambient temperature of 105°C, the evaporation of water was relatively slow, the vapor bubble was less and impacted a little on conduction of heat. When the ambient temperature became higher, moisture was evaporated faster and the soil pores were filled with more bubbles of water vapor. The presence of water vapor bubbles obstructed the passage of heat conduction, resulting in the moisture evaporation delayed. Only the vapor bubbles were burst by higher temperature, could channel for heat conduction open, and could water become steam completely. The higher the temperature the greater the peak, due to that the temperature increased, the rate of producing of vapor bubbles became greater, the pore channels became more crowded, and more energy were required to burst steam bubble. This phenomenon was also found in the literature by Liu (2012). Second, the constant temperature stage is short. This was because the higher the temperature the faster the water evaporate. When water vapor was completely escaped, heat was totally conducted by solids granule, namely dry soil. Because TC3 was at out where soil firstly became dry and its temperature rose in advance. Then interior soil became dry. Because there was no moisture, the temperature of soil rose quickly again (second rapid heating stage) until the soil temperature was equal to heating temperature (final constant temperature stage). Hence, for the initial saturated soil which was allowed to drain and exhaust, under the conditions of high temperatures for a long enough time, the changing of temperature inside soils could be divided into four stages, namely rapid heating stage I, constant temperature stage II, the second rapid heating stage III and the final constant temperature stage IV. In rapid heating stage I, heat was conducted by wet soil mixed by soils, water and steam. In constant temperature stage II, heat was conducted by mixture of soils and vapor as water was completely evaporated. This stage temperature was maintained at about 100°C. The second rapid heating stage III was dry soil conducting phase. The final constant temperature stage IV was the phase when soil temperature was as same as environmental temperature. The thermal conductivity of soils It can also be seen from the Fig.4, the slope of second rapid heating stage III of heating curves at 150°C and 200°C were less than that of rapid heating stage I, namely k III <k I . It was more evident in the heating curve at 150°C, which shows that the thermal conductivity of dry soil was less than that of wet soil. It can also be seen from the Fig.4 that the slope of the rapid heating stage I of heating curve at 150°Cwas less than that at 200°C, namely k I 150°C < k I 200°C . In fact, the slope of the rapid heating stage I of heating curve at 105°C was apparently less than that at 150°C, namely k I 105°C < k I 200°C . This shows that the thermal conductivity of wet soil increased with temperature rising, and this result was consistent with experimental results of Nikolaev et al (2013).When studying Ottawa sands and Richmond Hill fine sandy soils at temperature of 2°C -92°C, Nikolaev et al found that, the effect of temperature on the thermal conductivity of soils became obvious at temperature higher than 40°C, and the thermal conductivity increased as temperature rose. However, it can be seen from Fig.4, heating rate performed different when the soils begin to be heated. It shows that thermal conductivity were different at different temperatures and just were not pronounced below about 40°C. Because the amount of vaporization of water was small at low temperatures, and the movement of water vapor conducted little heat. At this time the heat conduction of soils depended mainly on soil particles. But when the temperature was higher than 40°C, the amount of vaporization of water got larger, and water vapor conducted heat significantly, resulting in an increment of the effective thermal conductivity of the soil. Therefore, the heating rates were significant difference. It can also be seen from the Fig.4, the second rapid heating stage of heating curve at 150°C lagged more significantly behind that at 200°C, and the difference of the slope was obvious, namely, k III 150°C <k III 200°C . This shows that the thermal conductivity of dry soil increased significantly as the temperature rose. And this conclusion was consistent with the thermal conductivity of dry soil at temperature of below 100°C. CONCLUSIONS (1) It can be inferred from the analysis of temperature changes and heat transfer characteristics of the soil that, for the initial saturated soil which was allowed to drain and exhaust, under the condition of high temperature for a long enough time, the change of temperature inside the soil could be divided into four stages, namely rapid heating stage I (heat conducted by wet soil mixed by soils, water and steam), constant temperature stage II (heat was conducted by mixture of soil and vapor as water was completely evaporated, and the temperature was remained at about 100°C), the second rapid heating stage III (dry soil conducting phase) and the final constant temperature stage IV(soil temperature was equal to environmental temperature). (2) At high temperature of 150°C and 200°C, there was a peak value in the heating curve, and the higher the temperature the greater the peak. (3) The high temperature environment had a significant influence on thermal conductivity of soils from the differences of heating curve at temperature of 105°C, 150°C and 200°C. With the temperature rising, thermal conductivity of both wet soil and dry soil increased, and thermal conductivity of wet soil was greater than that of dry soil.

v3-fos

2019-05-30T13:17:41.028Z

2015-09-05T00:00:00.000Z

169016099

s2

Traditional Husbandry Practices and Major Challenge of Young Stock (Camel Calf) in Fafen Zone, Ethiopian Somali Regional State, Ethiopia Copyright: © 2015 Awoke K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Traditional Husbandry Practices and Major Challenge of Young Stock (Camel Calf) in Fafen Zone, Ethiopian Somali Regional State, Ethiopia Introduction The one-humped camel (Camelus dromedarius) plays an important role as a primary source of subsistence production system in the lowlands of Ethiopia. It lives in arid and semi-arid areas which are not suitable for crop production and where other livestock species hardly thrive. Pastoralists in the eastern lowlands of Ethiopia rely mainly on camels for their livelihood. Ethiopia possesses over 1 million dromedary camels [1] and the majority of these camels are found in eastern part of the country. In spite of the large number of camels in Ethiopia, the productivity of camels is generally low and the camel has been given little research and development attention. Until recently, there is no development project in the country that neither features the camel nor is any attention given to this domestic species in connection with other livestock development programs. The primary reasons for keeping dromedary camels and management of camels vary from country to country and from one place to the other. For instance, camels are kept mainly for riding in countries in the Arabian Peninsula [2], for transportation in Eritrea [3] and for milk production in Somalia [4]. Camel rearing in Somali region, Jigjiga zones of eastern Ethiopia represents a highly rational adaptation of human life to a severe and adverse environment. It is the only efficient way of exploiting the arid areas where cultivation and small stock rearing are impossible. The pastoralists clearly understand that the camel is, and for the coming decades will remain, their basic means of survival. The position of the camel in providing food for the pastoralists in eastern Ethiopia will become even more important in the face of global warming and climate change [5]. The starting setting up of a camel herd is the calf. Calves form the replacement stock without which the herd cannot grow and neither would milk be available for the camel keepers. However, rearing of camel calves under traditional pastoral production systems is faced with several challenges that result in high death rates of the calves. Mortality rates of up to 60% have been reported in calves between birth and weaning [6][7][8][9][10]. This has to a large extent slowed down the growth of pastoral camel herds. In comparison with pastoral production systems, low camel calf mortality rates of 0 to 24.4% were reported in Kenyan commercial ranches [11]. Understanding the major role of camels and the traditional management practices used by camel owning societies would help to design appropriate intervention techniques that are applicable to local situations. To date, little information if any has been reported about the major contributions of pastorally managed Abstract The study was conducted between July 2013 and January 2014. The objective of this study was to examine the existing challenges and opportunities of traditional camel calf management practices. The importance of camels as a source of livelihood for pastoralists in eastern Ethiopia cannot be overemphasized. A study was carried out in the districts of Jigjiga, Babile, and Gursum in Fafen zone of Ethiopian Somali regional state, eastern Ethiopia to collect baseline data on camel calf colostrums feeding and management by the Jigjiga, Gurusum and Babile districts that inhabit the area and rearing of camel production. The primary and secondary data were collected to assess the impact of improved camel calf management and information whose dissemination was underway on the productivity of camel calves. During this study, between 30 and 60 households were purposively selected from three locations drawn from the three districts. A total of 130 respondents purposively selected from 60 households in Jigjiga district, 40 from Babile district and 40 household in Gursum per location were interviewed using a semi-structured questionnaire. The questions targeted different aspects of camel calf management and colostrums feeding. Analysis of the data revealed malpractices in the areas of breeding management, colostrums feeding, milk allowance, feeding, and watering and health management, among others, across the studied districts. The feeding of with full suckling of colostrums across studied district Jigjiga (31.7%), Babile (27%) and Gurusm (46.4%). In the other hand, the percentage of case of death camel calves was disease (32.7%) and drought (27.8%) was the second across the studied area. The calves were herd with all-in one 71.7%, 69.1% and 56.1% for Jigjiga, Babilie and Gurusum, respectively. The average culling of bull from herd of camels during the survey year was 16 ± 4 years across the studied districts. In the study areas, the results further indicated that the pastoralists were aware of the challenges facing their camel calves but did not have the knowledge to adequately deal with the constraints and colostrums feeding. This study concluded that the existing indigenous camel calf and information on camel calf management have great potential to improve camel calf performance if widely disseminated among the studied districts. Awareness creation among pastoralists and agro pastoral on the dangers of Methods of data collection The primary Data were collected through interviewing of pastoral districts and to address the objectives of the study formal (diagnostic) survey by using semi-structured questionnaire used to collect data on Camel calf production and management system, challenges and opportunities for camel farming in the area, status of individuals and cooperatives involved in camel dairy farming, interest of the community and cooperatives toward keeping camel dairy, and camel calf replacement to herd in the area. In addition, secondary information from office of agriculture and other organizations relevant for this study were collected. Before the start of the real survey the questionnaire was pre-tested on two-three non-sampled households from each study district. In the formal survey stage of the study, all require data were collected for a specific period from individual house hold. Methods of data analysis All the responses were coded to facilitate data entry and management in such a way that the qualitative as well as quantitative variables were select and also coded for analysis. The data collect by using semistructured questionnaire were entree in to Epi data and import to MS-excel and imported to SPSS (version 16) software. Descriptive statistics were used to describe quantitative factors. Standard errors of mean ± (SE) were used to describe means while percentage is used for describing qualitative characteristics. The data were analyzed one way analysis of variance (one-ANOVA). The results were expressed in percentage and mean ± SD of the results from the questionnaire. The analysis (means, standard errors, frequency summaries and tabulation of results) was done. Major constraints to livestock production In most part of the study area 80.0% of the respondents were stated that the importance of shortage of feed as a limiting factor for camel production followed by water shortage (61.7%) as shown below Table 1. However, the factors to be considered as a production constraint in the study area were include shortage of feed, shortage of water, shortage of grazing land, animal health problem and predator. Breeding management About 84% of respondents (n=130) selected breeding bulls from within the herd or immediate neighbors. Over 56.7% of the respondents in all the districts kept one breeding bull with the rest (43.3%) keeping more than one bull not for the purpose of controlling breeding but to ensure that there was a bull in the herd throughout in case one fell sick. Breeding bulls were culled from breeding at an average age of 16 ± 4 dromedary camel's calf in Eastern Ethiopia and there is limited information on the traditional management practices used by camel owning pastoralists in this region. This study was, therefore, designed to assess the opportunity and challenges of dromedary camel calf production and indigenous colostrums feeding practices in targeted districts in fafen zones of Ethiopian Somali regional state, Eastern Ethiopia. Objectives of the project To identify available information on challenges and opportunities of traditional camel calf management practices in Jigjiga Zone, Somali Regional State, Ethiopia Specific objectives of the study • To assess constraints of pastoral indigenous calf production and management practices of camel calf managements in the area. • To assess indigenous colostrums feeding practice in the study area. • To generate base line data on traditional camel calf opportunity and to give information for extension programmers and workers. Study design The study design was cross-sectional descriptive concerning assessment of challenges and opportunities of traditional camel calf management practices in Jigjiga Zone, Somali Regional State, Ethiopia. Description of the Study Area The study will be conducted in Jigjiga town, eastern Ethiopia and the capital of the Somali region ( Figure 1). It is located 650 Km from Addis Ababa and approximately 80 km (50 mi) east of Harar and 60 km (37 mi) west of the border with Somalia, this town has a latitude and longitude of 9°21′N 42°48′E with an elevation of 1,609 meters above sea level. Based on figures from the Central Statistical Agency in 2005, Jijiga has an estimated total population of 98,076 of whom 50,355 are men and 47,721 are women. The dominant ethnic group living in the town was Somali (99.0%), the next 3 largest groups were the Amhara (0.25%), the Oromo (0.44%), and the Gurage (0.30%); all other ethnic groups made up 0.08% of the population. Various forms of Christianity (Orthodox, Protestant and Catholic), Islam and other beliefs are commonly practiced in the town. Zone is administratively divided in to 6 districts and has its administrative capital in Jigjiga town. Jigjiga zone has a population of 1,034,823 people (80% rural). Techniques of sampling procedure The study was part of a larger benchmarking survey for Assessment on Challenges and Opportunities of Traditional Camel Calf Management Practices in Jigjiga Zone, Somali Regional State, Ethiopia it took the form of household surveys where between 40 and 60 randomly selected respondents each representing a household was interviewed per study location using a semi-structured questionnaire. The sampling was done in two stages where the first stage was random and meant to identify the households. The sampling frame was the total number of households in each of the study sites. The second stage of sampling to identify the household member to be interviewed was purposive, targeting members who were knowledgeable about camels. A total of 130 respondents were interviewed including 40 from the Babile, 30 from Gursum, and 60 from Jigjiga districts. The data collected related to the current camel calf management practices years in all the districts. The culling was done by way of selling the male, assigning it baggage duties and complete separation from the female herd or castration. The culling method used varied from districts to the other with the Jigjiga and babile doing the castration while Grusum sold out the males or converted them into baggage animals. Breeding females on the other hand were either not retired from breeding (30%, n=130 or were retired late (18 ± 3 years). 64 percent (Jigjiga district, n=60) and 80% (Babile, n=40) denied bull from mating its mother while 80% of the overall respondents (n=130) did not restrain the bull from serving its sisters and daughters. This practice pre-disposed the herd to the risks of inbreeding and weak or malformed calves at birth due to use of aged parents and the fact that the bull was mating with related females. This is in agreement with previous observations by Kuria. Simpkin (1996) and Kaufmann (1998) [8,10] had earlier recognized birth weight as an important factor in determining survival and growth rate of newborn camel calves. Calf management Young animals are managed in a traditional way. Nursing calves are kept separate from their dams, except when calves are used to stimulate milk letdown. Traditionally, calves are allowed to suckle twoquarters on the left side, while the other two-quarters are hand milked by women. This practice is believed to stimulate milk letdown. If the calf dies, the hide is stuffed with cereal straw or grass with four legs made of sticks. Salt is added to the hide of the stuffed calf and the dam is allowed to lick it in order to simulate the presence of the calf and stimulate milk letdown. Young children and females in general do most of the tending of small ruminants and calves near encampments. Management by female members of the family includes gathering cut-and-carry forages and hauling water for relatively immobile calves, which are kept in or near the family hut. Herders are well aware of colostrums feeding for the new born animals and understand the beneficial effect on health of the young. The overall average weaning age of cattle and camel calves is 10.08 ± 0.23 and 12.0 ± 4.6 months, respectively (Table 2). However, weaning age is often determined by the season of birth of calves, the health status of the dam and the need for milk by the family. Complete weaning is practiced when the dam ceases to lactate or becomes pregnant. This result agrees with the report of Coppock who reported weaning age of 7-12 months for Boran calves. If the dam is weak or gets ill, the farmers practice forced weaning at an earlier age. Traditionally, the herders use different types of weaning methods. Weaning is performed by piercing the nose of the calf with thorns, twisting up the nose skin of the calves to prevent suckling (as this causes pain when the wounded nose touches the teat) and smearing of teats with animal dung. According to this the survey result indicates that the camel Calves are provided with soil salt licks before they start feeding on forages. This is practiced because it is generally believed that direct exposure of calves to forage immediately after cessation of milk feeding causes diarrhea. On average around the first months (34 ± 5.02 for camel calves) of life, the calf diet consists of milk and a combination of cut-and-carry forage and calves are allowed to graze around the encampment. The amount of milk that a calf receives varies with season and the human demand for the milk. Colostrum's feeding Data on colostrum's feeding of camel calves by the various districts are presented in Table 3. As shown in Table 3, a large percentage of agro pastoralists allowed full suckling of colostrums in 31.7% of Jigjiga, 46.4% in Gursum but 38.3% restricted colostrums suckling by the calve in Babile. This practice by gursum and Jigjiga use for calves the benefit of passive immunity usually associated with colostrums than Babile. Colostrums' enhances survival and also cleans the stomach by facilitating passing of the first faces (meconium). These findings are in agreement with an earlier report by Njanja (2007) [9] who indicated that 77% of Rendille pastoralists (n=13) ensured that newborn camel calves suckled immediately after birth while a small proportion of the herders (10%) milked down some little milk before allowing the camel calves to suckle. In the current study and that of Njanja (2007) [9], pastoralists who allowed unlimited amount of colostrums to the calf coincided that colostrums strengthened the calves and promoted growth of camel calf. Milk allowance to the calf Milk allowance to the calf is very critical, especially in the first three months of growth before the calf starts grazing. Wilson et al. (1981) [6] and Schwartz et al. (1982) [12] considered malnutrition resulting from competition of human beings and camel calves for milk a major cause of mortality. In the current study, between 10% and 21% of the respondents across the study sites recognized competition for milk between calves and humans as one of the causes of retarded growth before weaning. One way of controlling this competition is by allowing the calf to follow the mother during the day over this critical period of growth for it to get enough milk. The number of teats allowed to the calf in the first two months and after six months by different districts involved in the study is shown in Tables 4 and 5, respectively. Tables 4 and 5 show that most of the agro pastoralists in the three districts allowed the calves to suckle two teats for the better part of the period before weaning. The Jigjiga and Gursum districts allowed calves the highest amount of milk during the two periods of growth. However, 25.5% (n=40) of the Babile agro pastoralists allowed the calf to suckle only one teat during the period below two months, suggesting competition for milk between humans and the calves. As earlier explained, this has a negative implication on calf growth and overall performance. Calf grazing Ages of introduction to grazing, watering and mineral supplementation are important factors in influencing calf growth. Early introduction of the calf to grazing facilitates development of the rumen which is important for feed digestion. This has a positive effect on the calf growth. The age at which different districts introduced calves to grazing, mineral supplementation and watering is presented in Table 6 and Figure 2. The Jigjiga and Babile camel calves started grazing earlier (less than 1.4 months) than those of the Gurusum districts. In an earlier study by Njanja (2007) [9], pre-weaned Somali camel calves began grazing at the age of 3-4 months which this study supports. Jigjiga and Babile agro pastoralists also delayed commencement of watering of their camel calves which is in agreement with Njanja (2007) [9] who reported first watering at the age of 6-8 months. The Gursum districts started giving mineral supplements to their calves after 9 months of age. Delayed watering and mineral supplementation has a negative implication on the growth of the calf particularly during the dry season. Dehydration reduces feed intake while feed availability in terms of quantity and quality tend to decline during dry periods necessitating supplementation with minerals and other feed material. One way of ensuring that the calves start grazing early is by herding them together with the rest of the camels. Table 7 clearly shows that the Jigjiga, Babile and Grusum districts were not separating the calves from rest of the herd and this explains the early commencement of grazing among their calves. Separation of the calves from the main herd among the Jigjiga, Babile and Grusum (Table 7) explains why their calves started grazing late. Distance to grazing and water resources It is important that camel calves are not walked far for water or grazing to minimize stress which impact negatively on calf growth. Table 8 gives the distance traveled by calves to water and graze during different seasons of the year. Data from this study show that while the Gursum and Babile camel calves walked far for water and grazing in the wet season, those of the Jigjiga district agro pastoral covered shorter distances to both resources (Table 8 ). This can be explained by the fact that the Jigjiga district agro pastorals separated calves from the rest of the herd retaining them near 'home' unlike the Gursum and Babile whose calves followed the main herd to water and grazing sources far from 'home'. However, across all the districts, camel calves had to walk far for water and grazing in dry season, thus suffering considerable degree of stress. Health management Health management is critical in controlling mortality and enhancing growth in camel calves. In the current study, between 60% and 76% of the respondents across districts ranked diseases and parasites high as far as retarded growth in camel calves was concerned. Ecto-parasites especially ticks and, diarrhea were ranked high on the list of constraints to calf health in all the districts in agreement with earlier reports by Field and Rutagwenda. These authors, however, reported some other diseases such as gastrointestinal haemorrhagic conditions, camel pox; worms, mange, bloat, pneumonia and wounds as common clinical diseases and conditions in camel calves alongside ticks and diarrhea. Studies by Kaufmann (1998) and Njanja (2007) [8,9] also singled out diseases as a major cause of mortality among pre-weaned camel calves. Important diseases mentioned by these authors were largely similar to those mentioned earlier by Field and Rutagwenda including orf, mange, ringworms, wounds and pneumonia. Table 9, the overall percentage of preweaning mortality for and camels was 61.5 ± 11.40. The differences in mortality rates between the post weaning and pre weaning was largely an indication of management techniques used by the herders and the ability to resist/tolerate diseases and stressful conditions increase after pre weaning. However, the percentage post-weaning mortality was lower than the pre-weaning mortality. The respective percentages of post-weaning mortality were 33.5 ± 0.96 camel's calves. Mortality: As indicated in The lower post-weaning mortality could be due to improved management provided to young animals kept in and around the homestead for up to one year of age. During this period, calves rely exclusively on wet leaves or grasses that are provided mostly by the female members of the household. The current result is also in agreement with the reports of Gebre-egziabiher who indicated that with an increase in age, mortality decreased probably because of improved adaptation of animals to both climatic and nutritional factors. The overall mortality for the cattle herd was 43.7 ± 5.20. Wagenaar reported that in Fulani cattle herds, pre-weaning calf mortality up to one year age was 43%, and decreased to 7.5% during the post weaning period. These high losses have invariably been attributed to poor young management practices and/or poor veterinary services. As indicated in Table 9, mortality due to diseases was the major (32.6%) cause of loss in all the districts of animals followed by drought (28.7%), abortion (17.2%) and poisoning (16.4%). The least cause of Similarly, as a report from the Maasai pastoralist indicated, the major cause of death for young (76%) and adult (54%) camel was diseases followed by predator (11%) and physical injury (4%). Control methods: In all the districts, common camel calf diseases were mainly controlled using indigenous technical knowledge including herbal concoctions and branding, necessitated by poor animal health delivery system. Other control methods included traditional mobility, quarantines, cleaning of night enclosures and avoidance of parasite infested areas. However, pastoralists near town centers did use conventional veterinary drugs. The Data from this study suggest that Jigjiga and Babile took treatment of diseases more seriously than the Gurusum district (Table 10). Control of ecto-parasites: Six five percent Jigjiga (n=60) and 72.6% Babile (n=40) and 74.9 Gurusum (n=30), respectively, did routine control of ecto-parasites mostly did spot control. The statistics on camel calf disease treatment and parasite control presented in Table 11 suggests that Jigjiga, Babile were keener than the Gurusum districts in the management of camel calf health. All the agro pastoral and pastoralists paid particular attention to diarrhea, describing it as a serious killer of the very young camel calves. Worth noting also is the fact that agro pastoral and pastoralists from all the districts attempted to control diarrhea using different traditional and conventional methods, confirming the seriousness of the problem in camel calves. The traditional methods used to treat diarrhea included; giving the calf black tea and depriving it of milk, depriving the calf of colostrums for the very young ones, oral administration of sheep and goat fat, salted water. While the use of sheep and goat fat was practiced by all the districts (Jigjiga-13.7%, Babile-9.7%, Gurusum-5.9%), black tea and salted water respectively were commonly used by Jigjiga (7.3%) and Babile (6.6%, respectively. Conclusion and Recommendations Conclusion The resulted of the survey, conclude that, this factor affect camels' management and husbandry practice such as shortage of feed, scarce of water seasonal variation, disease and low Management and husbandry practices such as colostrums feeding and allowances in fafen zone. Most of camel harder applied traditional Management and husbandry practice and there is no special breeding techniques applied by herders in fafen zone. Therefore, • This study revealed malpractices in camel calf management among the studied districts including poor breeding management, restricted colostrums feeding, poor care for the calves in terms of milk allowance, grazing, watering and health management. • While many agro pastoralists appeared to be aware of the challenges their camel calves were facing, they seemed not to have adequate knowledge to deal with the challenges. • The existing technologies and information on camel calf management has great potential to improve camel calf performance if widely disseminated among the studied districts. Recommendations • From this survey result, the following recommendation is given. Therefore, there is call for to create awareness among agro pastoralists and pastoral on the dangers associated with the current calf management practices. • Thorough training of agro pastoralists and pastoral on the existing camel calf management technologies is required as these technologies have potential to improve the current situation of colostrums feeding and salt supplementation. • A follow up to ensure application of the technologies and knowledge by the agro pastoralists and pastoral is also required. • Another survey should be conducted at the end of dissemination period and the data compared with the one from the current study to determine the impact camel calves production in the study area.

v3-fos

2019-03-30T13:06:52.301Z

2015-01-08T00:00:00.000Z

46081539

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Effect of feeding on olive oil and thyme on pregnancy and lactation periods This study aimed to evaluate the effect of feeding on virgin olive oil (VOO) and extra virgin olive oil (EVOO) at 50% and 100% with or without thyme leaves at 1% and 2.5% on pregnancy and lactation periods. Methods: One hundred and twenty adult female rats (120 ±5g) were randomly divided into 15 groups (n=8) for month before mating. On 19 th day of pregnancy, half of pregnant rats were weighted, killed and their fetuses take off with uterus. Another half of pregnant rats were left to evaluate the lactation period. Biochemical assays, bone measurements and fertility hormones were evaluated. Results: Generally, the VOO groups were improved the health status of pregnant and lactating rats more than EVOO groups. The pregnant rats in VOO and thyme leaves powder groups were lower of body weight gain (BWG) without their fetuses than EVOO and thyme leaves powder groups. The mean weight of fetuses in VOO and thyme leaves powder groups were higher than EVOO combined with thyme leaves groups. Also, the feeding on olive oils with thyme leaves had an increase of number of fetuses and bone Ca and P contents. The results showed that, in an increasing of number of fetuses caused decrease in bone mineral density (BMD). Pregnant and lactating rats fed on 100% olive oils had TC, TG, LDL-C, and VLDL-C lower than the rats fed on 50% olive oils. Also, the rats fed on olive oils and thyme leaves powder had increase in both E2 and progesterone levels before mating and at the end of lactation period compared to control group. Meanwhile, the prolactin hormone levels for rats at the end of lactation period were lower than on 19 th day of pregnancy period. Conclusion: Diet which containing with olive oil improved the health status, especially during pregnancy and lactation periods. Consumption of olive oil and olive oil and thyme leaves could be reduce the risk of infertility in females. Introduction Nutrition and reproduction have always been linked in that the reproductive success of an animal depends on its nutritional status. One of the most significant dietary changes that can be made to influence the reproductive system is the addition of fat to the diet. Several studies on reproductive activity of fat-supplemented rats demonstrated an increase in diameter and number of follicles present on the ovary, as well as a shorter period to the first postpartum ovulation [1]. Olive oil is the principal source of lipid within the traditional Mediterranean diet [2]. Olive oil is considered a healthy product because of its constituents, which include oleic acid, palmitic acid and other fatty acids; in addition to traces of squalence and sterols. There is a considerable data demonstrating that the consumption of olive oil is beneficial to cardiovascular health; specifically it has a favorable effect on cholesterol regulation and LDL cholesterol oxidation. It has also been shown to have anti-inflammatory, antithrombotic, antihypertensive and vasodilator effects in both animals and humans [3].Olive oil is an important preventive factor in the pathogenesis of numerous degenerative disease and conditions. Extra virgin olive oil is the best nutritional supplement for pregnant women, due to its ideally balanced nutritionally valuable fats important for intrauterine fetal development as well as optional fatty tissue development during early infancy [4]. Fertility hormones regulate the reproductive cycle and are used to test for various associated conditions including infertility and impotence in men and women, early or delayed puberty as well as non-reproductive disorder. The most common causes of female infertility are hormones. These are commonly associated with ovulation, ovarian syndrome and premature ovarian failure, damage to the Fallopian tube or uterus, or problem with cervix [5]. The female reproductive cycles function primarily by the interplay between the luteinizing hormone (LH), follicle stimulating hormone (FSH), progesterone, estradiol, prolactin and testosterone. Hormonal replacement therapy (HRT) is not only possibility to manage certain aspects of adult women's health. Huge women's health initiative study assessing the impact of HRT mainly on cardiovascular health and malignant disease have constructed not only users, but prescribers too. Increase cancer, stroke and coronary heart disease risks associated with long term use of postmenopausal hormone therapy (HT) have rapidly declined the number of women treated with HT either estrogen alone or estrogen plus progesterone [6]. An experimental model showed that bone remodeling was more pronounced in laboratory animals which had been treated with a polyphenols-rich diet [7]. According, [8] reported that the high quality of olive oil reduces low density lipoprotein cholesterol (LDL), peroxidation to significant higher extent than sunflower oil in hypercholesterolemia postmenopausal women. Also, [9] reported that olive oil consumption during adult life was not associated with the risk of breast cancer. While, [10] found that diet supplemented with olive oil modifies iron concentration in serum and liver tissues. Concerning thyme effect on health status, a little/no information about its effect but [11] reported that thyme causes flood blowing and invokes sexual activities and promotes consciousness and intelligences as well. The present study designed to study the effect of olive oil and thyme leaves pregnant and lactating rats which evaluated the lipid profile, liver and kidney functions, steroid hormones such as estradiol (E2) and progesterone, and prolactin. Materials Virgin olive oil (Olea europaea L.) VOO was purchased from the privet sector (peroxide value = 0.05 and acidity < 0.01) at Sadat City, Egypt. The extra virgin olive oil (EVOO) was obtained from Food Technology Research Institute, Agriculture Research Center, Egypt (peroxide value and acidity were 0.36 and < 0.01). Thyme leaves (Thymus vulgaris) was obtained from Horticulture Research Institute, A.R.C. Egypt; which ground to powder. Casein, vitamins, minerals, cellulose, and choline were purchased from El-Gomhoria Company, Cairo, Egypt. Starch and corn oil were purchased from local market, Giza, Egypt. Kits used to determine serum total cholesterol TC, total triglycerides TG, high density lipoprotein cholesterol (HDL), urea, creatinine, ALT, AST, ALP and minerals were punched from Gamma-Tread Company, Cairo Egypt. Biological Experiment One hundred and twenty adult Sprague-Dawely female rats (113-123g) were purchased from the lab of Animal Department of House in Ophthalmology Research Institute Giza, Egypt. The animals were housed in well aerated cages under hygienic condition (22 ± 2°C and 40-60 Relative humidity) and fed basal diet [12], for one week as adaptation period. After that the rats were randomly divided into 15 group (n=8) according to the following experimental diets ( Table 1), feeding a month before mating and carried out using one male to 2 females. On 19 th day of pregnancy, half of pregnant rats were fasted overnight before weighting and sacrificing. The fetuses were removing with uterus and put it in formalin (10% v/v) to analysis. Another half of pregnant rats were left to birth and lactating their fetuses. At the end of each stage, rats were fasted overnight before sacrificing. Blood sample were collected from eye plexuses of each rat. It cold in refrigerator for 15 min and centrifuged at 3000 rpm for 15 min to separate the serum. Serum was carefully separated and transferred into dry clean Eppendorf tubes and kept frozen at -18°C till analysis. Liver, kidney, heat and also femur were removed by careful dissection and blotted free of adhering blood immediately after sacrificing the rats. The organs and fetuses were washed in saline and dried using filter paper, then weighted and kept in formalin (10% v/v) according to [13]. Methods Biochemical assays: Serum total triglycerides (TG), total cholesterol (TC) and high density lipoprotein cholesterol (HDL) were determined according to [14], [15] and [16], respectively. Meanwhile, low and very low density lipoprotein cholesterol (LDL and VLDL) were calculated using the equation reported by [17]. The risk factor (TC/HDL-C ratio) was calculated using the equation reported by [18]. Serum urea and creatinine as kidney function were determined by the methods of [19] and [20], respectively. Serum AST and ALT were assayed according to [21]. Serum alkaline phosphatase (ALP) was determined according to [22]. Bone analysis: Bone Ca and P were determined according to the methods outlined in [23]. Bon length of each femur was measured using a varnein caliper according to the method of [24]. Bone mineral density (BMD) was determined using Dual energy x-ray absorptiometry (Norland XR -46) as described by [25]. Estradiol (E2), progesterone and prolactin hormones were determined according to [26], [27] and [28], respectively. Minerals determination of fetuses: Fetuses body minerals were determined using the following procedure: immediately after removal and placed in beakers then, desiccated to the body weight at 100 ͦ C in a convection oven. Fetus Ca, Fe, Zn and P of dry weight (DW) determined according to [29]. Statistical analysis: Statistical analyses were carried out by SPSS19 program. Data were expressed as means ± SEM and the Statistical analysis was performed using one-way analysis of variance followed by Duncan's tests as according to [30]. Effect of Feeding Olive Oil and Thyme Leaves Powder on BWG, Number and Weight of Fetuses Weight gain of pregnant and lactating rats, number and weight of fetuses were recorded in Table (2). A month later of feeding the female rats weight ranged from 163.3 -183.3g and mating to induce pregnancy. The results reported, the pregnant rats fed on 50% VOO had higher BWG1 than that fed on 100% VOO. While, the results showed high significant increases in 100% VOO group compared to 50% VOO group in weight of fetuses. Concerning, EVOO groups (both 50 and 100%) resulted in non-significant differences for mother's BWG1 and weight of fetuses. The pregnant rats fed on 2.5% thyme leaves powder only with basal diet had higher weight of fetuses and lower mother's BWG1 than that group fed on 1% of thyme leaves powder. The VOO groups and thyme leaves were higher than EVOO groups for number and weight of fetuses. The pregnant rats were left to delivery and lactating their babies for 4 weeks, and weighted before sacrificing. The data collected in this stage showed the BWG of female rats from initial weight to end of lactation period. Generally, all groups had lower than control groups of BWG except the group fed on 100% of VOO only. Also, the groups fed on olive oil (50 and 100%) and thyme leaves powder (2.5%) had lower than groups fed on olive oil (50 and 100%) and thyme leaves powder (1%). It is worth mentioning that the presence of olive oil with/without thyme resulted in an increase in the number of fetuses by about 1.33 to 2.00 fold as that of control. Effect of Feeding Olive Oil and Thyme Leaves Powder on Organs Weight Table (3) showed the effect of feeding olive oil combined with thyme on the organs of the pregnant and lactating female rats. Generally, the organs weight (liver, heart and kidney) of lactating rats were higher than pregnant rats, but the spleen weight was a low weight of lactating rats compared to pregnant rats. The rats in control group were the lowest value of heart weight (0.39g), and the highest values of liver and spleen weight (9.17 and 1.50g, respectively) for pregnant rats. The additional of 2.5% of thyme leaves increased in heart, kidney and spleen weight for pregnant and lactating rats compared to additional 1% of thyme leaves. The same table (3) resulted in VOO groups had lower than EVOO groups for liver, heart and spleen weight on 19 th day of pregnancy. While, VOO groups had higher than EVOO groups at the end of lactation period. The feeding on VOO combined with thyme leaves showed decrease when compared to feeding on EVOO combined with thyme leaves for liver weight. There were a high significantly differences between groups for liver, kidney and spleen weight. Effect of Feeding Olive Oil and Thyme Leaves Powder on Some Minerals Contents of Fetuses The results in table (4) showed the Ca, P, Fe and Zn of fetuses as resulted in feeding pregnant rats on olive oils with/without thyme leaves powder. Generally, fetuses in control group were lowest levels of Ca and P, but the highest levels of Fe and Zn. The rats in 100% groups (both VOO and EVOO) were higher than 50% for Ca and P contents. Also, the additional (2.5%) of thyme leaves powder caused a slight increase in both Ca and P compared to (1%) level. The rats fed on VOO and thyme leaves groups were higher Fe and Zn contents than rats in EVOO combined with thyme leaves groups. Effect of Feeding Olive Oil and Thyme Leaves Powder on Bone Ash, Ca and P Contents The results in table (5) showed that, the effect of feeding on olive oils combined with/without thyme leaves on bone analysis. The rats in control group had the lowest levels of bone ash, Ca and P contents (47.94 vs 39.84%), (18.65 vs 15.54 mg/100g) and (9.14 vs 8.20 mg/100g) for pregnant vs lactating rats, respectively. Generally, the lactating rats were lower than pregnant rats for bone ash, Ca and P contents. The VOO groups were higher bone Ca and P contents than EVOO groups. Also, 100% olive oils groups were higher than 50% for Ca and P contents. The decrease in ash, Ca and P in lactating rats' bone may be due to the transportation of these mineral to the fetus during pregnancy and to milk during lactation period, too. Effect of Feeding Olive Oil and Thyme Leaves Powder on Bone Measurements Bone mineral density (BMD), bone minerals concentration (BMC), bone length (L) and bone weight (W) were measured for the pregnant and lactating rats fed olive oils and thyme leaves powder as shown as in (Table 6). Generally, BMD values for lactating rats were lower than pregnant rats. The results showed that, a slight differences between VOO groups and EVOO groups for bone mineral density of femurs (BMD). Data in Table (2) and Table (6) showed a negative relationship between no. of fetuses and BMD. The pregnant and lactating rats showed low values of BMD with a high no. of fetuses. The VOO groups had higher levels of BMD than EVOO groups. Almost there were not differences between groups in bone length. The VOO groups had higher bone weight than EVOO groups. Also, 100% of olive oils groups had higher bone weight than 50% groups. From the above data, it could be concluded the olive oil with/without thyme leaves powder affected on bone BMD, BMC, length and weight of both pregnant and lactating rats. Effect of Feeding Olive Oil and Thyme Leaves Powder on Lipid Profile The results in table (7) showed that, the effect of VOO and EVOO combined with thyme leaves on lipid profile in serum pregnant and lactating rats. The results indicated that, lipid profile was lower in pregnant rats fed on VOO than the other rats fed on EVOO. The 2.5% thyme leaves powder caused decrease in lipid profile compared to 1%. Moreover, feeding rats EVOO and thyme leaves powder had lower levels of lipid profile than feeding on VOO with thyme leaves for pregnant rats. Concerning the lactating rats, which feeding 11 weeks (before mating, pregnancy period and lactating period) on VOO groups had decrease of TC more than lactating rats fed on EVOO groups, and increase in TG. The addition of (100%) olive oil diets caused decrease in lipid profile more than 50% groups. The same table (7) indicated that, the pregnant rats which feeding on olive oil diets for 7 weeks (before mating, pregnancy period) had high levels of TC/HDL-C ratio compared to control group. While, lactating rats which feeding (11 weeks) were low levels of TC/HDL-C ratio compared to control group, expect group fed on EVOO (50%) had the highest level (4.77) of TC/HDL-C ratio. Effect of Feeding Olive Oil and Thyme Leaves Powder on Liver and Kidney Function Table (8) showed the effect of feeding olive oil and thyme leaves powder in different levels on the kidney and liver function of both pregnant and lactating female rats. Generally, the liver and kidney functions of lactating rats were higher than pregnant rats. The results indicated that, 100% of olive oil diets caused decrease in liver and kidney function compared to 50% of olive oil diets. Moreover, in additional 2.5% of thyme leaves powder caused decrease in kidney functions and ALP, and increase in AST and ALT for pregnant and lactating rats. Also, feeding on olive oil and thyme leaves diets (2.5%) had lower liver and kidney functions than rats fed on olive oil and thyme leaves diets (1%). Effect of Feeding Olive Oil and Thyme Leaves Powder on Fertility Hormones The Fertility hormones for female rats during experimental stages are shown in Table ( 9). Generally, the rats fed on 100% of olive oil diets groups were higher in E2 and progesterone levels than rats fed on 50% of olive oil diets before mating and at the end of lactation period. Also, the rats fed on olive oils combined with thyme leaves had increase in E2 and progesterone levels before mating and at the end of lactation period compared to control group. Meanwhile, the prolactin hormone levels for rats at the end of lactation period were lower than on 19 th day of pregnancy period. The rats feeding VOO and thyme leaves powder diets were lower that feeding EVOO and thyme leaves powder diets for prolactin level. Discussion In this study, the author attempted to clarify the potential of the olive oil and thyme on pregnant and lactating health. The results indicated that, the BWG was decrease compared to control at the end of experimental period. These results of body weight gain are in the line with [31] who found the BWG after second month was lower than BWG in the first month. These results are in the line with [10] who found that, the olive oil diet reduced the serum Fe compared to control group (corn oil diet). An experimental model showed that bone remodeling was more pronounced in laboratory animals which had been treated with a paly phenol diet [7]. A possible influence of olive oil on bone mass inteance and osteoporosis prevention, its results showed that women on a Mediterranean diet rich in olive oil had better bone density levels than those on a standard diet [32]. Concerning monounsaturated fatty acids, a positive association between BMD and monounsaturated fat, derived mostly from olive oil, has been reported in a sample of Greek men and women [33]. The investigators discussed the influence that vitamin E, abundant in olive oil, exerts on prostaglandin levels and therefore on bone formation and resorption. Furthermore, a dose-response protective effect of oleuropain, an olive oil polyphenol, has been found on bone mass in an experimental in vivo model of bone loss in rats [34]. Accordingly, [35] concluded that olive polyphenols, particularly hydroxytyrosol, prevented bone loss in ovariectomized mice, and suggested olive polyphenols may provide insights into the development of tools useful in preventing and treating osteoporosis. The results of lipid profile are in the line with [36] who found that organic olive oil was most efficacious in addressing levels of TC, HDL, LDL, and AI. For all the parameters (except TG and VLDL), organic olive oil not only ameliorated but also prevented changes. In this respect, [37] reported that the intake of phenol rich virgin olive oil decrease total cholesterol TC, LDL and TG levels and substantially increased HDL concentrations. Controlled studies carried out with phenol-rich olive oils also have shown reductions of blood lipids and also of aortic lesions in hypercholesterolemic rabbits when fed with diets devoid of cholesterol [38]. The results of liver functions are in the line with [36] who reported maximum reduction of these measures as compared to the control (+) group was found in the thyme oil and organic olive oil and in fact, the AST, ALT and ALP. Also, the olive oil and thyme leaves had a high significantly differences compared to negative control. Our results are not in the line with [39] who found the estradiol (E2) for group which administered olive oil showed a non-significant difference when compared to the control group. The groups administered soybean oil and olive oil showed a non-significant decrease in progesterone levels relative to the control group. Progesterone and estradiol are among the most important sex hormones for implantation of the blastocyst and pregnancy maintenance [40]. In pregnant females, with a normal menstrual cycle, the progesterone level remains relatively constant throughout the follicular phase of the menstrual cycle and then increases rapidly following ovulation, while the estradiol secretion follows a cyclic biphasic pattern, with highest concentration found immediately prior to ovulation [41]. Based on the results obtained in this study, it shows that the two kind of olive oil (virgin olive oil and extra virgin olive oil) which contained omega-3 and omega-6 PUFAs and MUFAs have strong capability of enhancing hormonal functions by stimulating hypothalamus-pituitary ovarian axis and subsequently the fertility in females. Estradiol is mainly synthesized by the granulose and theca cells of the ovaries. Serum estradiol level is principally used to monitor the induction of ovulation and differential diagnosis of amenorrhea. From the results of this study serum progesterone level was non-significantly decrease in soy oil and olive oil treated groups when comparison with the control group. Furthermore, serum estradiol level showed that, olive oil group showed an insignificant difference relative to the control group, indicating that the hypothalamus-pituitary gonadal axis was not affected [40]. Prolactin is a hormone that plays a role in fertility by inhibiting follicle stimulating hormone and gonadotropin releasing hormone (GnRH), the hormones that trigger ovulation and allow eggs to develop and mature. In the present study, prolactin level in the olive oil treated group was significantly increased relative to the control group. High prolactin levels tend to suppress the ovulatory cycle by inhibiting the secretion of both follicle stimulating hormone and gonadotropin-releasing hormones (Gn RH) [42] which are necessary for ovulation. Based on the results obtained in this study, it shows that the two kind of olive oil (virgin olive oil and extra virgin olive oil) which contained omega-3 and omega-6 PUFAs and MUFAs have strong capability of enhancing hormonal functions by stimulating hypothalamuspituitary ovarian axis and subsequently the fertility in females. Conclusion From the obtained data it could be concluded that, diets containing olive oil with/without thyme leaves powder improved lipid profile, liver and kidney functions especially for the pregnant and lactating, provided that doses do not greatly exceed the amounts used in food. Olive oils and thyme leaves have strong capability of enhancing hormonal functions by subsequently the fertility of females. Hence, consumption of these oils could be reduce risk of infertility in females. Traditionally, thyme is reported to the effect the menstrual cycle and, therefore, large amounts could not be ingested. * BWG1= (body weight gain on 19 th days of pregnancy -weight rats before mating). BWG; without weight of fetuses= (BWG1 -mean weight of fetuses). BWG2= (body weight gain in the end experimental -initial). ** Each value in a column followed by the same letter are not significantly different at p≤0.05. * Each value in a column followed by the same letter are not significantly different at (p≤0.05). * Each value in a column followed by the same letter is not significantly different at p≤0.05.

v3-fos

2016-05-04T20:20:58.661Z

2015-12-01T00:00:00.000Z

11921539

s2

Detection of Anaplasma sp. in Korean Native Goats (Capra aegagrus hircus) on Jeju Island, Korea Anaplasma species are obligate intracellular pathogens that can cause tick-borne diseases in mammalian hosts. To date, very few studies of their occurrence in Korean native goats (Capra aegagrus hircus) have been reported. In the present study, we investigated Anaplasma infection of Korean native goats on Jeju Island, Republic of Korea, and performed phylogenetic analysis based on the 16S rRNA gene sequences. Our results showed that Anaplasma infection was found mostly in adult female goats. The phylogenetic tree revealed that the 7 sequences identified in Korean native goats could belong to Anaplasma sp. and were distinct from A. marginale, A. centrale, and A. ovis. The results indicated that the sequences identified to belong to Anaplasma were closely related to sequences isolated from goats in China and were clustered within the same group. To our knowledge, this is the first study to detect Anaplasma sp. infection in Korean native goats. Anaplasmosis is a tick-borne disease caused by Anaplasma species, which are obligate intracellular pathogens that infect humans and animals [1,2]. Clinical manifestations of the disease include anemia, fever, weight loss, decreased milk production, abortion, and frequently, death. The genus Anaplasma is composed of 6 species that vary in host preference and cell tropism. A. marginale, A. centrale, and A. ovis infect the red blood cells of ruminants [3][4][5]. A. bovis infects the monocytes of ruminants and small mammals [6]. A. phagocytophilum is the causative agent of human granulocytic anaplasmosis and infects the neutrophils of humans, ruminants, dogs, and horses [7,8]. Finally, A. platys is a platelet pathogen that infects dogs, and can cause canine cyclic thrombocytopenia [9]. Of these Anaplasma species, A. marginale, A. centrale, and A. ovis are prominent pathogens in ruminants worldwide [3,10,11]. In particular, A. marginale and A. ovis have considerable eco-nomic importance in tropical and subtropical areas [4]. A. marginale is known to be highly pathogenic in cattle, while A. centrale is less pathogenic. A. ovis is moderately pathogenic in sheep, goats, and wild ruminants [1,12] and causes acute disease in animals exposed to stress or other predisposing factors such as hot weather, deworming, tick infestation, and animal movement [13]. The importance of anaplasmosis in small ruminants in the Republic of Korea (ROK) is not yet known. The infection in sheep and goats is usually asymptomatic; however, it can sporadically cause hemolytic anemia and hemoglobinuria. Anaplasma infection may likely be neglected because of its low economic importance in the goat production industry of the ROK. Although there have been previous reports of Anaplasma infection in Korean native goats (Capra aegagrus hircus) [14,15], epidemiological studies on Anaplasma infection in these animals have not been well reported. Therefore, the objective of this study was to investigate Anaplasma infection in Korean native goats pastured on Jeju Island where ticks are most widely distributed and to perform molecular characterization of Anaplasma species detected on Jeju Island. Whole blood samples from 39 Korean native goats on Jeju Island, ROK, were collected in April 2014. This herd typically grazed in the pasture for at least 1 season every year; that is, the animals were housed in stables in the cooler months (November-April), whereas in the warmer months (May-October), they grazed in the pasture. All goats were clinically healthy and no blood-sucking ticks were found on them. Blood samples were collected and immediately frozen at -80˚C until DNA extraction was performed. Genomic DNA was extracted from whole blood samples using the DNeasy Blood & Tissue Kit (Qiagen, Valencia, California, USA) according to the manufacturer's instructions. For the detection of Anaplasma infection, PCR was performed using the AccuPower ® Rickettsiales 3-Plex PCR Kit (Bioneer, Daejeon, Korea). Specific primer sets targeting the 16S rRNA were used to detect species belonging to Anaplasma (F, 5´-TACCTCTGT-GTTGTAGCTAACGC-3´; R, 5´-CTTGCGACATTGCAACCTATT-GT-3´), Ehrlichia (F, 5´-CGGAATTCCTAGTGTAGAGG-3´; R, 5´-AGGAGGGATACGACCTTC AT-3´), and Rickettsia (F, 5´-TAGGGGATGATGGAATTCCTA-3´; R, 5´-CCCCCGTCA ATTCCTTTGAG-3´). The predicted sizes of the amplified PCR products for Anaplasma, Ehrlichia, and Rickettsia were 429 bp, 340 bp, and 252 bp, respectively. The following cycling conditions were used: 95˚C for 15 min; 40 cycles of 95˚C for 10 sec, 58˚C for 30 sec, and 72˚C for 30 sec; and final extension at 72˚C for 5 min. PCR products were separated by gel electrophoresis on 1.5% agarose gels and visualized by staining with ethidium bromide. The PCR products were purified with the QIAquick PCR Purification Kit (Qiagen). The nucleotide sequences were determined by direct sequencing of the PCR products using the BigDye Terminator Cycle Sequencing Kit (Applied Biosystems, Foster City, California, USA) and analyzed on ABI PRISM ® DNA Analyzer (Applied Biosystems). The sequence data were aligned initially using the Clustal X program (version 1.8) [16]. Additional sequences from representative anaplasmosis isolates were obtained from the GenBank database and then integrated with each set of alignments. A phylogenetic tree based on the nucleotide alignment was constructed using the neigh-bor-joining method [17]. Bootstrap analysis was carried out with 1,000 replications and the tree was visualized using Treeview. Statistical analyses were performed by one-way ANOVA with IBM SPSS Statistics (version 19.0) and GraphPad Prism (version 6.0). In all statistical tests, P-value of < 0.05 were considered significant. Anaplasma infection was analyzed in a population of 39 Korean native goats; blood samples from 7 animals (17.9%) tested positive for Anaplasma by 16S rRNA gene-based PCR. Infections with Ehrlichia and Rickettsia were not detected. None of the goats exhibited any clinical signs of illness, and no ticks were found on these animals. Additionally, no hematological abnormalities were observed. The incidence of Anaplasma infection in Korean native goats in all age groups and in male and female goats was investigated. Anaplasma infection was detected in female goats only (29.2%; Table 1), and the incidence was 38.9% in goats of 12 months of age (Table 2). Anaplasma infection was not detected in male goats or in other age groups. Seven 16S rRNA gene sequences of Anaplasma sp. (GenBank Accession No. KR024571-KR024577) were obtained from the 7 Anaplasma-positive blood samples after direct sequencing. The sequence analysis of these 7 samples led to the identification of Anaplasma sp. The phylogenetic tree analysis revealed that there were 3 main clusters for the established Anaplasma spp.: A. marginale, A. ovis, and A. centrale clusters. The 7 sequences obtained from Korean native goats on Jeju Island formed a fourth, separate cluster, that is, Anaplasma sp., which diverged from A. marginale, A. centrale, and A. ovis, but was closely related to A. centrale (Fig. 1). These isolates had a 98% similarity with A. centrale, 96.4-97.5% similarity with A. ovis, and 96.9-97.8% similarity with A. marginale. The phylogenetic analyses showed that the 7 Anaplasma sp. identified in Korean native goats could potentially be new species, mainly because The unrooted phylogenetic tree was constructed using the neighbor-joining methods. Bootstrapping was carried out with 1,000 replications. they clustered separately from the 3 established species, A. marginale, A. centrale, and A. ovis. Our 7 sequences are quite similar to the species isolated from goats in China (EU709493 and FJ389576), which also belong to Anaplasma sp., and are clustered in the same group. To our knowledge, this is the first study to identify Anaplasma sp. infection in Korean native goats by PCR. Although anaplasmosis is one of the most widespread tickborne diseases, very little is known about Anaplasma infection and its distribution in the ROK. Most studies concerning Anaplasma in the ROK have addressed ticks and humans [18,19], while the role of Anaplasma in goat pathology has not yet been described. In our study, a high prevalence of Anaplasma infection was observed in female and adult goats although it was not statistically significant. This result indicates that adult goats may have more opportunities for exposure to ticks carrying the pathogen than younger animals. Additionally, our findings suggest the presence of Anaplasma infection in Korean native goats on Jeju Island, which has a subtropical climate and a much higher distribution of ticks than other regions in the ROK. These conditions increase the possibility of tick-borne diseases spreading to livestock, wild animals, and humans. In the present study, PCR and sequence analyses based on the 16S rRNA provided evidence of a new Anaplasma sp. infecting Korean native goats; these isolates were closely related to the previously reported Chinese isolates. The pathogenicity and role of Anaplasma sp. was not determined in Korean native goats; however, infection with this protozoan may have an impact on the health of these animals and consequently on their milk and meat production. Evidence of infection with a new Anaplasma sp. infection in Korean native goats would be very important, as the pathogens could considerably affect animal production, and outbreaks may occur under specific conditions. Accordingly, these findings indicate infection with a new species from the genus Anaplasma among Korean native goats on Jeju Island, ROK. The current study demonstrates the presence of infection with Anaplasma sp. in Korean native goats, although none of the animals in our study exhibited clinical symptoms. Since the sample size was not sufficiently large to determine the incidence of Anaplasma infection, more studies are necessary to investigate epidemiological data and to elucidate the pathogenicity of Anaplasma sp. in these animals.

v3-fos

2019-01-23T22:22:52.048Z

2015-05-22T00:00:00.000Z

196414519

s2

Epidemic situation of rift valley fever in Egypt and Saudi Arabia RVF is an Office International des Epizooties (OIE)-listed. RVFV is caused by an arbovirus, a single stranded RNA virus that belonged to Phlebovirus of in the Bunyaviridae family that contained a wide variety of arthropod borne viruses that infect mammals and insects. The disease was discovered by Daubney et al.1 during his work at the Veterinary Research Laboratory at Kabete in Kenya. The virus was reported in Kenya in 1931 by Stordy2 during an outbreak occurred in wool exotic sheep in the Rift Valley area. Since then, the diseases have been reported in North Africa until a major outbreak occurred in Egypt in 1977. In September 2000, RVF cases were firstly reported in Saudi Arabia and Yemen, making the first report of the disease outside Africa.3 This considers the first report of the disease occurrence outside the African continent–where it had been confined so far–becoming a threat to the Middle East. In 2007, there were outbreaks in Kenya, Somalia, and Tanzania,4,5 while in 2008 and 2010, recent outbreaks of RFV occurred in Sudan.6,7 In the year 2000, Saudi Arabia and Yemen were exposed to a huge RVF outbreak.8,9 It was considered the first outbreak occurred in the Middle East. The improper quarantine measures leads to the spreads of the RVFV in Saudi Arabia and Yemen during importation of infected animals from Eastern Africa10 as well as the extension of RVFV from Sudan to Egypt in 1977.11 The virus strain which causing the Saudi Arabia outbreak belonged to the same strain that caused East Africa outbreaks in 1997-1998.12 Limited information and data is available on the Epidemiology and transmission of RVF in Egypt and Saudi Arabia. Introduction RVF is an Office International des Epizooties (OIE)-listed. RVFV is caused by an arbovirus, a single stranded RNA virus that belonged to Phlebovirus of in the Bunyaviridae family that contained a wide variety of arthropod borne viruses that infect mammals and insects. The disease was discovered by Daubney et al. 1 during his work at the Veterinary Research Laboratory at Kabete in Kenya. The virus was reported in Kenya in 1931 by Stordy 2 during an outbreak occurred in wool exotic sheep in the Rift Valley area. Since then, the diseases have been reported in North Africa until a major outbreak occurred in Egypt in 1977. In September 2000, RVF cases were firstly reported in Saudi Arabia and Yemen, making the first report of the disease outside Africa. 3 This considers the first report of the disease occurrence outside the African continent-where it had been confined so far-becoming a threat to the Middle East. In 2007, there were outbreaks in Kenya, Somalia, and Tanzania, 4,5 while in 2008 and 2010, recent outbreaks of RFV occurred in Sudan. 6,7 In the year 2000, Saudi Arabia and Yemen were exposed to a huge RVF outbreak. 8,9 It was considered the first outbreak occurred in the Middle East. The improper quarantine measures leads to the spreads of the RVFV in Saudi Arabia and Yemen during importation of infected animals from Eastern Africa 10 as well as the extension of RVFV from Sudan to Egypt in 1977. 11 The virus strain which causing the Saudi Arabia outbreak belonged to the same strain that caused East Africa outbreaks in 1997-1998. 12 Limited information and data is available on the Epidemiology and transmission of RVF in Egypt and Saudi Arabia. Endemicity of RVFV in Egypt RVFV are maintained in the environment by replication and transmission between insects and susceptible hosts. 13 There are many factors helps RVFV to persist in environment in Egypt depends upon certain factors. 14 Firstly, the appropriate climatic conditions for multiplication of insects with absence of effective insects control programs. Secondly, camels and wild animals play an important role in establishment the endemic RVFV cycle. 15,16 Thirdly, vaccination of livestock with RVF vaccines plays an important role in the endemicity of the disease in Egypt. 17 Fourthly, partial herd vaccination of susceptible hosts by inactivated vaccines. Fifthly, the massive losses of human during the first RVFV outbreak, as result of the absence of public health instruction, social and medical situations. Lastly, the field trials in Egypt are not under control which leads to environmental contaminations with RVFV live vaccine strains. Epidemicity of RVFV in Egypt RVFV infected a wide range of hosts including cattle, sheep, goats, buffaloes, camels, and others. Sheep is the most susceptible host with high rates of abortions during gestation period and high mortality rates among newborns. 18,19 The first record for RVF outbreak in Egypt was recorded at Belbies city in Sharqiya Province in 1977. It appeared as acute febrile dengue-like disease in human. 20 In 1977, some investigations revealed that RVFV was isolated from different animal hosts, rats and man during RVF outbreak in Egypt and some areas of North Africa. In 1993, the second outbreak was mainly due to infection or using of vaccine strains. Some investigation was suggesting the virus continued endemic this two outbreaks until reinstated in 1993 from Sudan. 21 In 1994, RVFV was isolated from 139(31.65%) cattle and 84(57.1%) sheep in Kafr El Sheikh and Behira Provinces. However, the locally produced RVF vaccine showed failure of its application. 22 In 1997, the high incidence of abortion and mortalities among sheep and cattle was observed in Upper Egypt. 23 In spite of RVFV outbreak occurred 3 years only after the last epidemic in 1994, the failure of vaccination programme was occurred. In 2003, other outbreak was encountered in various localities of Egypt. 24 The Egyptian Ministry of Agriculture did not announce this epidemic until now. However, WHO received reports of 45 Epidemicity of RVFV in Saudi Arabia Epidemics of RVF were limited to the African continent until 2000. In 2000, the first confirmed occurrence of RVF outside Africa was firstly reported in Saudi Arabia. The Ministry of Health (MOH) of Saudi Arabia received reports of unexplained severe hepatitis in 7 patients from the Jizan region at the south western border of the kingdom. During this outbreak it was estimated that around 40,000 animals including sheep, goats, cattle and camels died whereas about 10,000 of them aborted. 26 During the outbreak of 2007 in Sudan, The livestock trade between Saudi Arabia and Sudan were prohibited. 27 The main route for transmission of the disease among livestock through mosquitoes bites. In addition, disease can also be occurred vertically between animals. 28 The massive infections of human result from direct or indirect contact with the blood, secretions and consumption of unpasteurized milk from infected animals. [29][30][31] The virus was mostly transmitted to human through bites of infected Aedes mosquito. 32,33 RVFV was transmitted vertically in the flood water of Aedes mosquitoes. 34,35 Other mosquitoes in the Culex and Anopheles genus are thought to be important in amplification of virus activity during outbreaks. Up till now, the virus transmission from human to human not documented. A strategy called "One Health" was applied by cooperation between all collaborating authorities in Saudi Arabia on both animal and human hosts to prevent and control the disease. 33,36 During the outbreak, active surveillance surveys to detect the RVF cases among animals and humans to locate infected areas for animal vaccination. 8,9,26 Urgent control measures were implemented included disposal of infected dead animals under complete hygienic measures. Around 1million doses of the vaccine were used and more than 10million ruminants being vaccinated. 37 Importation of animals from RVF-epidemic countries and restricting the movement of animals will reduce the extension of the virus to outside the affected areas. 16 Ministry of Health in Saudi Arabia well-prepared the laboratories for detection of RVFV antibodies in suspected cases. 8,26 Some epidemiological and entomological studies were performed to recognize the main predisposing factors of the disease. 9 In addition, an intensive control program for mosquitoes was applied. 9,38 This strategy succeeded to limit the disease from spreading to other areas. Since 2000, the local authorities of Saudi Arabia was recorded a few sporadic cases of the disease. 8 Discussion and conclusion RVFV is an endemic disease in Africa and Arabian Peninsula. 39 This virus is classified as OIE, List A with a highly potential pathogen for international spread. 40 The disease considered a highly fatal zoonotic disease for human. The use of effective vaccine was helping in break the life cycle of the pathogen. 41 The viremic animals as well as infected mosquitoes serve as a main source of direct infection of humans. 42 Since 1977 outbreak, the live attenuated and killed vaccine was used in Egypt. 43,44 In 2008, the Egyptian General Organization of Veterinary Services (GOVS) revealed that RVF live vaccine don't used in Egypt in the present time. Consequently, the vaccination of RVF performed by the killed vaccines only. 45 It is one of the most promising vaccines to date, and if effective, could be tested in the field in Egypt. 46 Whereas RVF was previously restricted to specific areas in Africa, the disease seems to be spreading into new territories beyond the traditional foci as evidenced by outbreaks in Saudi Arabia and the Arabian Peninsula. The epidemiology of RVF is complex and transmission involves multiple mosquito vector species. While the scientific community has started to address the possibility of large-scale epidemics and preventive measures that can be used to stop them, there are still no low-cost, broadly effective vaccines approved for use by the general public. In the nearest future, we hope to some of the vaccine in a wide scale. It is also clear that with enhanced coordination among stakeholders, Ministries of Health and epidemiologist to handle future outbreaks in Saudi Arabia. Clear strategies and action plans for handling of future outbreaks include strong surveillance systems, adequate and well trained personnel, should be done. To facilitate the control and eradication of RFV in Saudi Arabia and Arabian Peninsula, we have many things to do. First, regional or national wide eradication should be initiated and implemented. Second, the cooperation between the government and stakeholders to fight against RFV jointly. Third, proper animal vaccination program. Fourth, disruption the breeding sites by using the larvicidal agents are the most effective manner of vector control. Lastly, we need to know more about the virus: how does it replicate/infect and establish infection? How does it interact with the host? This may lead to more efficient intervention strategies for RFV.

v3-fos

2019-03-30T13:13:32.355Z

2015-04-30T00:00:00.000Z

59378709

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Evaluation of Enset Clones Resistance against Enset Bacterial Wilt Disease (Xanthomonas campestris pv. musacearum) Enset (Ensete ventricosum Welw. Cheesman) is one of the most important staple and co-stable food crops for around 20 million people in Ethiopia. However its production has been threatened by a devastating bacterial disease caused by Xanthomonas campestris pv. musacearum. This disease was officially reported in Ethiopia for the first time in the 1960‟s. Therefore, this study was conducted with the objective to screen field-grown Enset clones collected for reaction against bacterial wilt and to assess the farmers practices used for the management of the target pathogen. A large number of Enset clones (20) assessed and collected from the Dire Inchini, Jibat and Wonchi distrcts and were screened against resistance/tolerance to Enset bacterial wilt, X. campestris through artificial inoculation. All artificially inoculated Enset clones with X. campesrtris suspensions of different concentration were developed disease symptom of variable intensity levels during the first 30 days after inoculation. The Enset clones, Suite, Warke, Bidu, Astera and Kekari showed 100% disease symptoms at 30 days after inoculation and could, hence, be used as susceptible checks in future screening trials. This vascular disease was resulted in yellowing of the leaves, wilting and finally collapsing of the entire plant. Disease symptoms were not observed on Enset clones of Mezya, Bedadet, Hiniba and Nech Enset after 90 days of inoculation periods and were taken relatively as resistant to the target wilt causing pathogen. Those Enset clones showed tolerance to Enset bacterial wilt causing pathogen should be multiplied, demonstrated and addressed for the final user or Enset producing farmers and help as one disease management option; in addition to cultural practices and others effective phyto-sanitary measures Enset producing farmers are using. Evaluation of Enset Clones Resistance against Enset Bacterial Wilt Disease (Xanthomonas campestris pv. musacearum) Introduction Enset, Ensete ventricosum is a perennial, herbaceous and a monocarpic, crop, belonging to the family musaceae and the genus Ensete [1]. It is commonly known as "false banana" for its close resemblance to the domesticated banana plant. About 25 species of Ensete are equally distributed in Asia and Africa [2]. Among these species, E. ventricosum is widely grown in Ethiopia and is a traditional staple food crop for over 20 million people in the South and South West parts of the country. It is estimated that about 146 thousand hectares in Southern Nations, Nationalities and Peoples Regional State (SNNPRS) and 79 thousand hectares in Oromia are covered with Enset [3]. Enset can grow in a wide range of altitude, however the best elevation for its cultivation is between 2000 and 2750 m. a. s. l with an average annual rainfall of 1100 to 1500 mm [4]. The crop can withstand relatively long period of drought (about 5 months). The average temperature of Enset growing areas is between 10 and 21°C and a relative humidity of 63 to 80 percent [4]. The ideal soils for Enset cultivation are moderately acidic to alkaline (pH of 5.6 to 7.3) [5]. Enset grows well in most of the soil types, if they are sufficiently fertile and well drained. Cattle manure is used as the main organic fertilizer. It prefers nitosols than vertisols [4,6]. Enset is a drought tolerance and multi-purpose crop; it makes major contribution to the food security scheme of the country. All plant parts of Enset are utilized for different purposes. The parts of Enset used as food vary from region to region. Enset is used as food in three forms: amicho, kocho and bulla. Enset is attractive to farmers because its ability to produce more food than other cultural crops on a small piece of land with minimum inputs [7]. Enset provides fiber as a byproduct of decorticating the leaf-sheaths. Enset fiber accounts for more than 30% of the Ethiopian fiber production and its strength is equivalent to the fiber of Abaca [4]. Enset products are available throughout the year and can be stored in pits for long periods of time without spoiling. Fresh Enset leaves are used as bread and food wrappers, cattle feed, serving plates and pit liners for store kocho for fermentation [4]. Enset is rich in carbohydrate and mineral substances like calcium and iron [8]. Enset plantations prevent soil erosion and conserve soils, hence, contributing to the sustainability of the farming system [9]. Regions where Enset is used as staple or co-staple food are usually less affected by the recurrent drought periods that occur in Ethiopia [10]. However, there are lots of biotic and abiotic problems threatening Enset production [10]. Among the biotic constraints, diseases caused by bacteria, fungi, nematodes and viruses; mammalian pests such as porcupine, mole rat, wild pig and insect pests such as mealy bugs have been identified as serious problems. Of all the biotic constraints, bacterial wilt disease, which is caused by Xanthomonas campestris pv. musacearum (Xcm) is the most important disease affecting yield [11]. Enset bacterial wilt is known to cause severe damage, as it attacks and kills the plants at any growth stages, including full maturity (ready for harvest). Once the plants are attacked by the disease, especially at late maturity stage, it affects whole systems, and usually causing a maximum yield loss. A serious outbreak Journal of V Journal of Veterinary Science & eterinary Science & T Technology echnology of the disease was reported by Westphal [1] with losses up to 70%. The results obtained from recent bacterial wilt disease assessment made in some Enset fields of the SNNPR, showed losses of up to 100% under severe damage [12]. Many researchers [13][14][15] reported that both the area and productivity of Enset is declining continuously due to this disease. Brandt et al. [4] reported that the only recommended control measures for the bacterial wilt of Enset are cultural practices which include the use of healthy, disease-free suckers for planting material, destruction and controlled movement of diseased plants, cleaning of equipment that has come in contact with diseased plant material and rotation of crops. Although the phytosanitary approaches currently being recommended are labors intensive and not easily adopted by farmers they are presently the only known means of preventing further spread of the epidemic until more sustainable management options are available. Enset bacterial wilt can effectively be controlled by growing of resistant varieties. Thus, this study was initiated to screen and provide Enset clones relatively resistant to Enset bacterial wilt disease in Ethiopia. Therefore, the objectives this research works:  To screen and evaluate Enset clones resistance to Enset bacterial wilt disease and  To assess the farmers" practices used for the management of Enset bacterial wilt. Collection of diseased Enset samples and clones Diseased Enset Samples and Clones were collected from the major Enset growing districts west and south west zones of Oromiya region, Ethiopia viz., Tikur Inchini, Wanchi, Waliso and Jibat districts. Both diseased Enset samples and young health clones were collected from five kebeles in each district in random sample form. The clone collected was about one year old. Additionally, Enset field, supplementary information's (like clone type, date of collection, elevation, latitude and longitude, field history, plant growth stages, etc.) was recorded. The samples were labeled properly and brought into Ambo Plant Protection Research Center for further studies. Isolation of Xcm The pathogen, Xanthomonas campestris pv. musacearum, was isolated from Enset plant parts (petioles and midrib leaves) by growing on the selective media i.e. Yeast Dextrose Calcium Carbonate (YDC) agar media (yeast 10 g, dextrose 20 g, calcium carbonate 20 g and agar 15-20 g per 1000 ml of sterile distilled water, when targeted to prepared one litre). Calcium carbonate was added after cooling of the other ingredients. Diseased Enset saples were surface sterilized by 1% sodium hypochlorite"s, crashed and streaked on solid surface of YDC plates and incubated at 28°C for about one to three days as done by Blanchard and Talter [16]. After 48 to 72 hours of incubation, colonies showed light yellow mucoid growth, typical of Xcm was transferred to YDC broth and preserved with 20% glycerol and maintained at 4°C in refrigerator for further studies [17]. Biochemical characterization of the pathogen, Xcm The biochemical test includes; KOH solubility test, Oxidase, Catalase, Starch hydrolysis and Tween 80 hydrolysis were made and the characters were recorded for each test. KOH solubility test: The KOH solubility test was performed by the method of Fahy and Hayward [18] using 24 h culture. Two drops of 3% KOH were put onto glass slide and the Xcm colony was stirred into the solution with clean loop for 10 s. When the solution was viscous enough to stick to the loop causing a thin strand of slime, then the test was recorded as KOH soluble positive or not. Oxidase test: Oxidase activity was detected by the method of Kovacs [19]. Freshly grown 24 h cultures from YDC agar media with 1% glucose were patched onto a filter paper moistened with a fresh oxidase reagent (1% w/v aqueous solution of tetramethyl-paraphenylene diamine dihydrochloride) using a wooden stick. A purple reaction in 30 s was recorded as oxidase positive [20]. Catalase test: Catalase test were performed according to methods described by He et al. [21]. One ml of a 3% solution of hydrogen peroxide was added to a Petri dish and a loop of fresh culture grown on YDC agar medium were rubbed into the solution. Release of bubbles from the culture was recorded as catalase positive [20]. Tween 80 hydrolysis: Fatty acid esterase activity was tested by streaking the bacteria onto a nutrient agar medium containing calcium chloride and Tween 80, a polymer consisting of polyoxyethylene-sorbitanmonooleate as stated by Sands [20]. The medium contains: peptone, 10 g; CaC12 dihydrochloride, 0.1 g; NaCl, 5 g; agar, 15 g; distilled water, 1 l; with the pH adjusted to 7.4. Tween 80 were autoclaved separately and added with 10 ml/1 and mixed before plating. Incubation was made at 30°C for up to 7 days [18]. An opaque zone of crystals around a colony was recorded as positive reaction for hydrolysis of Tween 80. Starch hydrolysis: Nutrient agar plates containing 0.2% soluble starch (w/v) was streaked by the test Enset bacterial strains and incubated at 30°C until heavy growth occurred. Then plates were flooded with IKI solution (iodine, 1 g; potassium iodide, 2 g; distilled water, 100 ml). A clear zone around a colony was recorded as positive reaction. Based on the Bergey's Manual of Systematic Bacteriology, the bacterial isolate, Xcm was confirmed and identified [22]. Screening of Enset clones for resistance against Xcm Screening of Enset clones for resistance to Xcm, the one year old young clones of each of the twenty genotypes (Table 1) were used and planted on PVC pots (30 cm in diameter and 30 cm height) filled with 6 kg of sterilized mixture of top soil, manure and sand of 3:2:1 ratio ( Figure 1). Single clone was planted per pot (three clones per genotype represent for a replication) and each treatment was replicated three times in a Randomized Complete Block Design (RCBD). The total numbers of clones planted were 180. Enset clones of Meziya and Suite of nearly having one year old was used as a resistant and susceptible check, respectively. Bacterial suspension was prepared from pure culture of Xcm for artificial inoculation. The cells of the suspensions of 1 × 10 7 and 1 × 10 8 cfu/mL were used. Bacterial suspension of 3 ml (1 day old) was used for inoculation of the clones. Five ml capacity of sterile hypodermic syringe with metal needle was used to inject the bacterial suspension into the petiole of the youngest open leaf. The same quantity of sterile water was injected into control plants. Plants incubated under field conditions and were monitored for 12 weeks. The observation for symptom development was made at five days interval after inoculation. The presence of bacterial ooze and discolored vessels was checked by cutting the inoculated leaf petiole close to pseudo-stem. Re-isolation of the pathogen was made from infected leaf petiole and sheaths of inoculated plants. Disease assessment was done at 8, 13, 18, 23, 28, 33, 38 to 90 days (five days intervals) after inoculation. The data was recorded on disease incubation on each plant of each clone. The number of infected plants per clone at each disease assessment period was recorded. Disease severity was assessed on whole plant basis of number of wilted leaves using the following scale is developed viz., 0: no symptoms; 1:1 inoculated leaf wilted; 2:2-3 leaves wilted; 3:4 leaves wilted; 4: all leaves wilted and 5: plant dead. The data was analyzed by using SAS programme [23]. Assessment of farmer's practices towards the management of Enset bacterial wilt From each district, major Enset growing localities survey was conducted to get supplementary information and practices used for the management of Enset bacterial wilt based on questionnaire and interviews. Based on farmers interviewed at different localities, Enset farmers were practices used for the management of Enset bacterial wilt i.e., avoiding source of inoculum, field rotation, protecting animals" interferences and phytosanitary practices in implements utilization. Data analysis The incidence and prevalence data were analyzed by using the descriptive statistical analysis (mean) and were presented in tables and graphs. The statistical differences for resistance among Enset clones; the disease severity means for the various genotypes were analysed on one way ANOVA using SAS version 9.1 [23] by using Duncan"s Multiple Range Test (DMRT). Results and Discussion Isolation and identification of Xcm EBW disease samples were taken from infected plant parts of Enset leaf petioles, corm and pseudo-stem showing discoloration of plant tissue with large air pocket filled with creamy or yellowish exudates (ooze) (Figure 2). The bacterial ooze sign sample was collected from Waldo Hindhe locality, Tikur Inchini district. SAS [24] also reported that the similar yellow bacterial ooze exudates come out from the cut pseudo stem and leaf petioles of Enset plants. Under laboratory condition, the samples were cultured on YDC solid plates and the culture was observed after 72 hours of incubation; bacterial colonies were developed a light yellow, circular, high convex, dome shaped and shiny appearance of mucoid colonies (Figure 3). The similar results were also reported by Tsehay [25], that bacterial isolates of Enset grown on YDC agar culture plates produced creamy, yellow, and light yellow mucoid circular colonies with dome shaped and shiny appearance. Tween 80 hydrolysis: Fatty acid esterase activity was tested was result to negative response/reaction as per the Sands [20] method. An opaque zone of crystals around a colony was not formed and recorded as negative reaction for hydrolysis of Tween 80 which is similar result with the test method of Fahy and Hayward [18]. Finally based on the Bergey's Manual of Systematic Bacteriology, the Enset bacterial wilt isolates were identified as Xanthomonas campestris pv musacearum (Xcm). Evaluation of Enset clones for resistance to Xcm pathogen Enset clones collected were screened against Enset bacterial wilt pathogen, Xanthomonas campestris pv. musacearum (Xcm) using artificial inoculation under pot culture condition at Ambo Plant Protection Research Center, Ambo, Ethiopia ( Figure 5). The clone Meziya was used as positive control or resistance and Suite negative check or susceptible. The relative resistance and susceptibility of Enset clones to Enset bacterial wilt was evaluated three months after inoculation based on wilt incidence and pathogen incubation period till it develop symptoms. Disease evaluation data was recorded at 7 days interval for 3 months. The first symptoms of disease on infected clones were yellowish of central leaf at the apex and wilting. Average disease incidence as measured by percent infected and/or dead Enset plants, which showed varied differences among test clones at different disease assessment period after inoculation. All Xcm inoculated Enset clones developed disease symptoms to various intensity levels after 15 to 30 days inoculation ( Figure 6). However, several Enset clones showed relative tolerance to the disease. A difference in progression of the disease also was apparent. In all disease assessment periods, the ranges of disease incidence were variable ranging from 20 to 100% or total death of some Enset clones were observed. Re-isolation of the pathogen was done and there was no bacterial colonies in Enset clones remain tolerant to Xcm. Out of the 20 Enset clones, only 6 Enset clones showed a mean disease incidence of less than 50 percent. Some of the clones were more severely affected within shorter period of time than others. But there is no significant difference between Enset clones artificial inoculated from bacterial suspension concentration of @1 × 10 7 and 1 × 10 8 cfu/ ml the development of symptoms and incidence into the clones showed the disease incidence was not variable. The Enset clones, Warke bidu, Awenyi, and Kekar showed 100% disease symptoms at 30 days after inoculation and could, hence be used as susceptible checks in future screening trials. Disease symptoms were observed on Meziya, Hineba, Bedadet and Warke Dima between 21 and 30 days after inoculation. These clones were the immune clones throughout the evaluation period. The remaining Enset clones were relatively resistant /tolerant after inoculation of Xcm (Table 2). Among all "Meziya" was found to have the lowest percentage of disease incidence (19.31%) followed by "Hiniba" (30.18%) and "Bedadet" (34.26%). Based on the evaluation of their reaction, none of the Enset clones had complete resistance to Xcm. These results are in accordance with the earlier reports of "Meziya" that was considered as better tolerant clone [26][27][28]. In the present study, the Enset clones, "Meziya", "Hineba", "Bedadet" and "Warke Dima" clones were exhibited better tolerance to the bacterial wilt, under artificial inoculation conditions @ both 10 7 and 10 8 dilutions/concentration. Hence, "Meziya", "Hineba", "Bedadet" and "Warke Dima" Enset clones should be considered as most tolerant/resistant clones to the pathogen and these four clones could be used as a bacterial wilt management component. Developing and use of resistant/tolerant Enset clones is one of the best approaches in the management of EBW, cheaper to the farmers and safer to environment similarly, variable levels of clonal response against the Xcm disease have been observed under farmer's field conditions and using artificial inoculation in on station trials by Welde-Michael [11] and Anita et al. [13]. Farmer's practices towards management of Enset bacterial wilt The assessed farmers practices on the management of EBW disease were totally related to sanitary measurements. The survey result was indicated that, only about 40% of respondent farmers in all sampled kebeles used sanitary practices as management measurements but they not implemented it properly, instead, they were expecting chemical control from concerned body and others farmers were not know as the cause of the problem is disease case or BW (46%). Most farmers or 54% of interviewed believed that it is due to disease cause and its dissemination is by farming tools and browsing animals that are the most important factor, play major role in dissemination of the pathogen in their fields. Generally, the phytosanitary measures will minimize the EBW disease severity. The results of this survey was agreed with the earlier studies of Million, about 71% of the farmers reported that careful application of sanitary control measures helps to control EBW. An EBW disease sanitary management measure that helps to prevent reduce or eliminate the spread of Xcm disease in the field was summarized as follows. • Avoiding source of inoculum by uprooting the diseased Enset plants and burring in the pit or burning it. • Flaming the Enset cutting/working tools after use. • Preventing animals (wild and livestock) from browsing. • The use of disease free suckers as planting material. • Cleaning and flaming of equipment that has come in contact with diseased plants and • Rotations of crops, if the damage is severe were also identified during Enset bacterial wilt disease management assessment from the users point of view that was similarly reported by Brandt et al. [4]. Such measures should be taken in a manner of campaign and as regular practices in all Enset-growing areas. During survey, these practices were conducted in above mentioned districts, some farmers' also practice of tying down the leaves, allowing the diseased plants to dry and then burning as a sanitary control practice (Figure 7). It could be prevent contamination of adjacent plants that could occur during the recommended practices of removal of diseased plants. All respondents agreed that flaming of the Enset cutting/working tools after using them on diseased plant, uprooting and discarding of infected plant is a major control measures, while by contrast, some farmers are tie the animals in the infested field carelessly which contribute to the dissemination of Enset bacterial wilt from infested area to un-infested area. Additionally, they are not practice flaming contaminated farming tools before cutting healthy leaves for different purposes. Farmers traditionally fencing and digging deep ditch around the Enset farm to prevent the movement of animals (domestic and wild) into the Enset field, and traps for catching them. An animals that feed on the corms such as the mole rat and porcupine, not only disseminates the disease but, also one porcupine especially at one night can potentially feed healthy 3-5 Enset plants per field per day, which decline the production and productivity (Figure 8). Additionally, porcupines can choice of Enset plants as human beings that prefer for corm/amicho due to its sweetness. Contrarily, Feresiye and Shertiye corm is due to its bitter cannot eaten by porcupine which is advantages was identified during assessment of Enset producers practice for the management of EBW that further used in integrated management of the target disease [29,30]. Conclusions In the study of evaluation of 20 Enset clones resistance/tolerance to Xcm using artificial inoculation under pot culture condition, among all "Meziya" was found to have the lowest percentage of disease incidence (19.31%) followed by "Hiniba" (30.18%) and "Bedadet" (34.26%) Enset clones. The Enset clones, "Meziya", "Hineba", "Bedadet" and "Warke Dima" have exhibited better resistant/ tolerant against Enset bacterial wilt. Hence, "Meziya", "Hineba", "Bedadet" and "Warke Dima" Enset clones could be considered as most tolerant clones to the pathogen and those clones can be used as a bacterial wilt management component. Developing and use of resistant/tolerant Enset clones is one of the best approaches in the management of EBW, cheaper to the farmers and safer to environments. The Enset clones, "Warke bidu", "Awenyi", and "Kekar" showed 100 % disease symptoms at 30 days after inoculation and could, hence be used as susceptible checks in future screening trials. This study shows that Enset clones vary in their reaction to EBW. The farmers have also learned a lot from the collaborative experiments, they are very sure that the contaminated farming tools are the most important factor, play major role in disseminations of the pathogen in their Enset fields. In these regards use of resistant / tolerant clones along with cultural practices and sanitary control measure is viewed to be the most feasible of the bacterial wilt management. In the future Enset producing farmers should prefer to multiply and plant the above mentioned clones due to its resistance to EBW and its multipurpose day-to-day function. Additionally, the Enset clones that showed a resistant or tolerant reaction to the wilt pathogen should be further evaluated against Xcm isolate under field conditions. The current work alone cannot be conclusive; it is believed that the results obtained were facilitating further works for the satisfactory control of the bacterial disease of Enset in the country. However, more research is needed considering the various Enset clones from the different Enset-growing regions and the future use of molecular techniques to produce markers linked to tolerance in Enset clones.

v3-fos

2018-04-03T02:16:17.655Z

2015-12-02T00:00:00.000Z

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Dairy proteins and soy proteins in infant foods nitrogen-to-protein conversion factors Protein content of any source is classically determined through the analysis of its nitrogen content done for more 100 years by the Kjeldahl method, and the obtained result is multiplied by a number named nitrogen conversion factor (NCF). The value of NCF is related to the amino acid composition of the protein source and to the eventual presence of side groups covalently bound to some amino acids of the protein chain. Consequently, the value of NCF cannot be identical for all sources of food proteins. The aim of this paper is to review the available knowledge on the two allowed protein sources for infant food formulas, milk and soybean, in order to bring the right scientific basis which should be used for the revision of both European legislation and Codex Standard for Infant Formulas. Introduction Like most of the foods consumed by human beings, milk and soybeans contain proteins which are sources of essential nutrients for growth and for the maintenance of physiological functions. Human milk is undoubtedly the optimal food for infants, and all the recent acquired knowledge on it strengthens the conclusion that breast feeding should be the golden rule all over the world because it is still impossible to duplicate the composition and component structure of mother's milk (Jensen et al. 1995). Nevertheless, there are needs to palliate several medical or social difficulties of mothers, and as a result, infant food formulas have been proposed as substitutes for human milk since one century (Fomon 1974). In the framework of revision of both European legislation and Codex Standard for Infant Formulas, the amount and quality of proteins contained in these infant formulas are under discussion. The only allowed protein sources for these infant formulas are milk and soybean (and their respective derivatives), so given the specific characteristics of each source, it appears necessary to review their analytical estimation. Indeed, adequate knowledge of protein nature and protein content is essential for evaluating the nutritional value of foods correctly, informing the consumer adequately, estimating the yielding capacity in manufactured products precisely (for example, cheese from milk and tofu from soy juice), and insuring fair trade exchanges. General scientific knowledge The protein content referred to as 'total protein' is determined through analysis of nitrogen contained in the foods, and then the obtained result is multiplied by a number named nitrogen conversion factor (NCF). In foods, two nitrogen forms are distinguished: protein nitrogen and non protein nitrogen. & Protein nitrogen corresponds to 'True Proteins' i.e. for milk, mainly, caseins, β-lactoglobulin, α-lactalbumin, serum albumin, immuno-globulins and proteose-peptones and for soy, mainly, β-conglycinin and glycinin. Proteins are defined as a sequence (determined by the organism's genome) of amino acids bound by covalent bounds (primary structure) and to which carbohydrate groups can be also attached by covalent bounds (for example, on Threonin for milk κ-casein and for egg yolk phosvitin). These side groups are constituting parts of the protein, not only because they are covalently bound to the amino acid chain but also for their nutritional, physiological and technological functions. For example, it is the release of κ-glycomacopeptide through hydrolysis of casein micelle by rennet and pepsin in the stomach that regulates the differential bio-availability kinetics of caseins and whey proteins (Boirie et al. 1997). This release also induces the secretion of the cholecystokinin hormone implied in the regulation of gallbladder and pancreatic functions (Beucher et al. 1994); it is equally involved in the phenomenon of milk coagulation by rennet, an essential step of cheesemaking. & Non protein nitrogen (NPN) amounts 5% of the total nitrogen in cow's milk (Alais 1984) and between 7.8 and 2.9% (average 5%) of total nitrogen in defatted soybean flour prior to heat treatment (Becker et al. 1940;Smith and Circle 1972). The NPN is mainly constituted by small peptides, free amino acids and other nitrogenous components, such as creatinin, urea and ammonia, in both protein sources Robertson and van der Westhuizen (1990). The analytical method, used for determining total nitrogen content for more than a hundred years, is the Kjeldahl method (Kjeldahl 1883) (ISO 2014) which consists of the following: & Mineralising the sample with concentrated sulphuric acid, in the presence of a catalyst (copper and potassium sulphates) that quantitatively converts all the organic nitrogen into ammonium sulphate and & Displacing the ammonia from the ammonium sulphate by concentrated sodium hydroxide, then distilling the ammonia and collecting it in a boric acid solution and finally, titrating it with hydrochloric acid. The protein content of the sample is then calculated by multiplying the sodetermined nitrogen content by a NCF. The different calculation methods of this conversion factor are detailed below. As proteins are particularly complex heteropolymers, consisting of chains of variable number of α-amino acids (20 different types), some of which may be amidated, glycosylated or phosphorylated, it is obvious that the value of the conversion factor depends on the primary structure of the analysed protein (composition in amino acids and sequence). Methods for determining protein content In theory, the definition of the NCF seems simple and unambiguous: it is the ratio between the protein molecular weight and the nitrogen content of this protein. But, in practice, precise analytical determination faces numerous difficulties inherent to the methods used (Mossé 1990). Determination of the conversion factor with the Kjeldahl method Initially, the NCF was obtained through the simple determination of nitrogen content of a highly purified protein. That was the case of the 6.38 factor calculated by Hammarsten and Sebelien (1892) for isoelectric casein (Jones 1931) and further adopted for any milk proteins. However, most of the protein sources are not so easy to purify as casein and scientists have turned to determining the NCF from the amino acid composition. Determination of the conversion factor from amino acid profiles Further determinations of NCF were based on the amino acid composition determined, after acid hydrolysis, in protein samples, but this analytical method, even if it is performed in optimum conditions (three hydrolysis times, use of internal markers, etc.), suffers, at least, a 10% lack of precision, because of (1) some of amino acid residues (particularly Try, Thr, Ser, Met, Tyr, Val, Ileu) are partially destroyed by acid hydrolysis and others are not 100% released and (2) it requires complementary steps for recovery of amides, sulphur and aromatic amino acids. Moreover, this method does not give information on side groups (glycosylated, phosphorylated), which are constitutive parts of the native protein chain after post-translational biosynthesis. The same uncertainty is also existing if amino acid composition is determined by using RP-HPLC method with precolumn derivatization (Grappin and Ribadeau-Dumas 1992). Determination of the conversion factor from the amino acid sequence of proteins This is the only method that gives a scientifically founded NCF value because it is calculated from the complete primary structure of the protein: all the amino acid residues composing the protein chain and all the side groups. The NCF value is obtained by relating the nitrogen content of all amino acids to the molecular weight of the protein (determined either by calculation or by mass spectrometry). This obviously requires a thorough knowledge of the primary structures of proteins which was acquired for most (99.5%) of milk proteins and for the main soy proteins, but is not yet available in its entirety for numerous other protein sources. This determination of NCF should be the reference method because it cannot be contested. If this knowledge of the primary structure is not available, an approximate value for NCF can be calculated from the protein sequence determination based on the specific gene coding. 4 Conversion factors for milk, specific milk proteins, some dairy products and milk infant formulas 4.1 Milk, milk proteins and dairy products Thanks to the pioneering work realised by the INRA (French National Institute For Research in Agronomy) team under the leadership of Ribadeau-Dumas, in the 1970s for the milk caseins, as well as the specific work done on κ-casein by Jolles et al. (1970) and Alais (1984) and the studies of Eigel et al. (1984) and of Brew et al. (1970) on whey proteins, the complete primary structure of the main milk proteins is known and internationally recognised (Farrell et al. 2004). This knowledge enabled Karman and van Boekel (1986) and later Van Boekel and Ribadeau-Dumas (1987) to determine, with a high degree of precision, the values of NCF for the main protein sources of milk (Table 1) It can be seen that for total milk proteins, the conversion factor value obtained by taking into account the known sequences of all the main individual proteins with their lateral groups and their proportions in milk is 6.36, the value which is very close to the historically used value of 6.38. From these results, it can be said that the values of NCF which must be used for the proteins contained in milk infant formulas are 6.36 for the casein part (isoelectric casein being effectively used for this type of formula) and 6.41 for the whey proteins part (most of the infant formulas being made with rennet whey proteins derivatives). Values of NCF which are given in some papers for other dairy products such as cheese (Mariotti et al. 2008) are totally erroneous because they do not take in account the extreme diversity of technological treatments applied to cheese milk (heat, specific protein enrichment) which lead to variable retention of whey proteins and the continuous proteolysis involved in the mechanisms of cheese ripening. Consequently, the best value of NCF for cheese and other dairy products cannot be other than that of milk proteins, i.e. 6.38. Milk infant formulas In Table 2, the values of NCF in milk infant formulas have been calculated for different whey protein/casein proportions usually proposed for term infants at birth (Jensen et al. 1995). These calculations clearly show that whatever are the relative proportions of whey proteins and casein in milk infant formulas, the nitrogen conversion factor still remains around the value of 6.38. Whether one is dealing with milk proteins as whole or fractions isolated from these milk proteins for an use in infant formulas, it is scientifically established from the knowledge of primary structure that the nitrogen conversion factor is undoubtedly 6.38. The first value of NCF proposed for soy proteins was 5.71 (Jones 1931) which was calculated from the nitrogen determinations performed by Osborne and Campbell (1898) on soy protein extracts. Then, with no known scientific reason other than a theoretical 16% nitrogen content in all protein sources, the value of 6.25 was agreed for all vegetable proteins and applied for soy proteins by soy producers as well as the Association of Official Analytical Chemists (AOAC). That was done despite since 1946 this value was considered too high, in view of the studies performed on soy isolates (Smiley and Smith 1946, Smith and Circle 1972, Mossé 1990, Sosulski and Imafidon 1990. In 1969, Tkachuck suggested the value of 5.69 for the total proteins contained in defatted unskinned soybean flour. Later, Mossé (1990), from the amino acid profiles of six samples of soy protein powders, determined a value of 5.52±0.02. From the described sequences of the main soy proteins (Utsumi 1992), we calculated the NCF values shown in Table 3. Given the variability of the relative proportions between glycinin (11S) and β-conglycinin (7S), 0.5 to 1.7 (Utsumi 1992) in the cultivars, it is not easy to calculate a mean value of NCF but the values calculated in Table 3 lie in a very narrow range. One can therefore consider that the ratios protein/nitrogen in all soy cultivars are varying between 5.56 and 5.66 that leads to a mean value of 5.61. However, this value does not take into account the covalently bound side groups. According to Utsumi et al. 1997, the three subunits of the β-conglycinin (7S) are glycosylated (Kosiyama 1969) as well as the hemagglutinin component (Lis et al. 1966) which amounts to 3% of soy flour (Liener and Rose 1953). Soy hemagglutinin is always denatured by the heat treatments applied to soy proteins for inhibiting its antinutritional action, but its glycosylation as well as that of β-conglycinin (7S) has to be taken into account for the calculation of NCF. Consequently, the respective specific values for hemagglutinin and β-conglycinin (7S) become 7.58 (Wolf 1972) and 5.91. Thus, it can be calculated by taking into consideration these new values and the relative It can be concluded from these calculations which agreed with numerous published data that whatever is the soy cultivar, the use of a conversion factor of 6.25 for soy proteins leads to an overestimation of protein content comprised between 7.4 and 9.0%. This conclusion was recently confirmed by Fujihara et al. (2010) who consider as realistic for these proteins a NCF value between 5.43 and 5.51. Variation factors Apart the aforementioned analytical variation factors, technological treatments especially the intense heat treatments can affect the value of NCF by inducing glycation reactions between amino acids (Lys or Arg) and sugar residues present in the heated product (Maillard reaction) as well as deamidations able to ultimately lead to a release of CO 2 and amines (Strecker reaction) (Finot 1997). In order to avoid protein allergenicity, some infant formulas contain enzymatic hydrolysates issued from proteins. It is obvious that for these hydrolysates, essentially composed of peptides and free amino acids, the conversion factor is meaningless (there is no protein anymore!). Other analytical parameters have to be proposed for characterizing these products, such as average peptide size, Gaussian distribution or amino acid sequence determination of all the individual peptides. The same conclusion comes to mind when there is a supplementation with free amino acids, generally added at very low levels in order to avoid osmotic shocks. Milk infant formulas are increasingly formulated with milk and/or whey protein concentrates or isolates obtained through various separation technologies based on either steric size exclusion of milk and whey proteins (membrane ultrafiltration and 0.1-μm microfiltration or gel filtration chromatography) or according to the electro-chemical charge of proteins (membrane nanofiltration, electro-dialysis and ion exchange resins) (Maubois and Ollivier 1997). Without entering into the details of these formulations which are in the field of industrial property, it must be pointed out that the concentrates (WPC) or isolates (WPI) obtained through these separation processes are not enriched in NPN (a very complex group of likely more than 100 molecular species) as stated erroneously in the ESPGHAN report (Koletzko et al. 2005). Indeed, the NPN-constituting molecules because either their low molecular weight (less than 500 Da according to Wolfschoon-Pombo andKlostermeyer 1981, Alais 1984) cannot be retained by the ultrafiltration (UF) membranes of which the molecular cut-off is around 5000 to 20,000 Da. They are also excluded by the gel permeation resins and separated by the ion exchange resins used in the chromatography processes. In all the demineralisation processes (electrodialysis, ion exchange, membrane nanofiltration), according to Hoppe and Higgins (1992), the NPN losses represent between 25 and 30% of the initial whey NPN. Moreover, some little losses in low molecular weight whey proteins (about 0.02%), such as α-lactalbumin, have been observed industrially (Hargrove et al. 1976, Delaney 1976Boer and Robbertsen 1983). So, the WPC and WPI have a lower NPN content than the dairy products of which they originated. This lower content in NPN of which the value of NCF would be, according Karman and van Boekel (1986), in the ranges from 7.36 (κ-caseinomacropeptide) to 3.60 (milk NPN fraction), evidently leads in all the products used in infant formulas (demineralised whey, whey protein concentrates, whey protein isolates, etc.) to a balanced variation of the value of NCF, but which always remains between 6.30 and 6.45 (values determined by Karman and van Boekel (1986) for, respectively, rennet whey proteins), and acid whey proteins), and consequently does not highly affect the used 6.38 value. Processing and anti-nutritional factors In infant food formula being used for nutrition of particularly sensitive human beings, it must be mentioned that technological treatments such as heating, applied for killing contaminant micro-organisms, have a deleterious effect on the nutritional value and the potential physiological role of proteins. Minimization of the successive heatings which have a cumulative damageable effect must be the rule of the infant food manufacturers. Moreover, intense heating has always to be applied on all sources of soy proteins, because, unlike milk proteins, they contain anti-nutritional components, notably (1) hemagglutinin and (2) trypsin and chymotrypsin inhibitors able to block these enzymes which are essential for the protein digestion by mammals (Jaffe 1969). These inhibitors (polypeptides which represent 6% of total soy proteins) distinguished in Bowman-Birk (Birk 1968;Frattali 1969) and Kunitz (Kunitz 1946) could equally increase endogenous nitrogen losses by enhancing pancreatic proteases secretion (Finot 1997). Consequently, all the soy-protein-based foods are highly heated (at least, 100°C for 15 min according to Rackis (1966) for inactivating these anti-nutritional components. But, such a heat treatment, of which the intensity is far from the one applied to milk-based infant formula (145°C during 2 to 3 s, at the maximum) has also multiple negative effects on protein bio-availability: induction of Maillard and Strecker reactions which leads to a decrease of absorption of basic essential amino-acids (lysine and arginine) as well as tryptophan and sulphur amino acids (cystein and methionin) (Finot 1997). These serious anti-nutritional defects of soybean-based infant formulae have recently led paediatric community to limit them as much possible for infant nutrition (Turck 2007). On the other hand, there are many other differences between milk-based infant formula and those based on soy protein, particularly composition and structure of the fat component for which we can wonder if the added vegetable fat, totally cholesterol free (human and cow milks contain around 150 mg.L −1 , Jensen et al. 1995) and not structured in globules, fulfills or not the requirements for an optimal growth and development of children (Jensen et al. 1995). Conclusions The 6.38 factor converting the nitrogen content determined by the Kjeldahl method in milk proteins, used for more than one century in all the international standards and recognised by Codex for all the dairy products, is based on deepen scientific knowledge which cannot be contested, notably the amino acid sequential chain of the milk proteins as well as the precise identification of the post-translational glycosylated and phosphorylated side groups. Although studies have recently determined the sequences of numerous other proteins, this knowledge of milk proteins has no equivalent in the field of vegetable proteins, probably because of the high genetic polymorphism of cultivars. Nevertheless, the available knowledge existing for soy proteins shows, whatever is the cultivar, the conversion factor is never over 5.79 with an average value of 5.61, both values agreeing with that (5.71) encountered in many published scientific papers. Considering the values of the conversion factors for milk proteins (6.38) and for soy proteins (5.71), it is scientifically justified that this difference is kept. The recent proposal of the use of a unique 6.25 conversion factor for all the protein sources (Koletzko et al. 2005) is unacceptable because it forgot the enormous research work realised, for more than 50 years, by the world scientific community in order to improve knowledge on that essential nutriment for human beings which are the proteins with their differences in terms of amino acid composition and their specific nutritional quality. Such a 6.25 value has absolutely no recognised scientific basis (Morr 1982;Sriperm et al. 2011), and especially for infant formulas, it is not appropriate for any used protein source: it overestimates by around 10% soy proteins and underestimates by 2% milk proteins. Only use of both specific conversion factors will give a true indication of the protein content. Moreover, it can be added that if the protein content of a food is a basic indication of its nutritional quality, that quality is also constituted by the following: -The presence or absence of anti-nutritional components (such as anti-trypsic factors and hemagglutinin of soy proteins) which obligatory requires an intense heat pretreatment [damageable for the bio-availability of several essential amino acids (Lys, Arg particularly)]. -The amino acid composition which governs the protein metabolism of the human physiology. -The specific amino acid sequence which leads after the hydrolysis by the digestive enzymes to the release of particular and unique bioactive peptides of which the physiological action has been demonstrated during these last 15 years.

v3-fos

2018-04-03T02:47:38.073Z

2015-09-15T00:00:00.000Z

25567929

s2

Aluminum uptake and migration from the soil compartment into Betula pendula for two different environments: a polluted and environmentally protected area of Poland This paper presents the impact of soil contamination on aluminum (Al) concentrations in plant parts of Betula pendula and a possible way of migration and transformation of Al in the soil-root-stem-twig-leaf system. A new procedure of Al fractionation based on extraction in water phase was applied to obtain and measure the most available forms of Al in soils and B. pendula samples. In addition, total Al content was determined in biological samples and pseudo total Al content in soil samples collected under plant saplings, using atomic absorption spectrometry with flame atomization. A number of relations concerning the occurrence of Al and Ca in soils and plant parts of B. pendula (tap roots, lateral roots, stem, twigs, and leaves) were observed. Based on the research findings, the mechanism of Al migration from soil to the leaves of B. pendula can be presented. It was found that aluminum uptake may be limited in roots by high calcium concentration. The application of a new procedure based on the simple sequential extraction of water-soluble fractions (the most available and exchangeable fractions of Al) can be used as an effective tool for the estimation of aluminum toxicity in soils and plants. Introduction Al is one of the four most common elements occurring in soils. It is one of the most important components of soils, and to the same extent as silicon, it determines the crystalline frame of soil minerals. Al toxicity is the subject of many papers and reviews (e.g., Berthon 1996;Nayak 2002;Willhite et al. 2014), and research on Al impact on the environment is commonplace. The main symptom of Al toxic effects is the dramatic inhibition of root growth, which occurs within minutes after exposure to Al, even at micromolar concentrations (Tanaka et al. 1987;Illėš et al. 2006;Tolrà et al. 2011;Morita et al. 2011). Al toxicity is considered as one of the main factors limiting plant growth in acid soils (comprising about 40 % of the world's arable lands) (Rout et al. 2001;Rezaee et al. 2013;Kovácik et al. 2012;Iqbal 2014). The speciation of Al in soils is a key factor in its potential not only to plant toxicity but also to living organisms as well. Al toxicity in soils and plants is not well understood, and the mechanism of Al migration is most commonly associated with the organic acid ions of citrate and malate (e.g., Flaten 2002; Fransson et al. 2004;Nunes-Nesi et al. 2014). Several papers describe the impact of Al on plants based on the use of Al salts, and most of them mainly focus on the root and its growth (Yang et al. 2013;Kidd and Proctor 2001;Klug et al. 2011;Yan et al. 2012, Doshi et al. 2008. It has been found that the occurrence of Al in soils is strongly connected with Al in leaves and its speciation (e.g., Frankowski et al. 2013, Karak et al. 2015. Moreover, research on the fractionation of Al shows that water extract fraction is the most important one due to the availability of Al species and their possible toxic impact. However, it should be noted that the total content or pseudo total content is important as well (e.g., Milačič et al. 2012;Frankowski et al. 2013). The most frequently used single-step extraction methods for Al and other elements, including heavy metals or metalloids, include the deionized water method (for the water-soluble fraction). Taking toxicity into account and Al bioavailability and migration from soils to living organisms, the determination of possible pathways of the migration and accumulation of particular Al species seems necessary. Especially, the mobile Al species (cold-and warm water-soluble fractions) and the total concentration of Al should be under focus. Mobile Al fractions are fundamental to learn more about possible pathways of Al transport in plants. In previous studies, the single-step extraction procedure was used to fractionate Al in agricultural soils (Takeda et al. 2006), forest soils (Zhu et al. 2004), flood plain soils (Drabek et al. 2005), sedimentary rocks, soils from mining areas (e.g., Matúš et al. 2006;Kubová et al. 2005), and soils from areas polluted with Al (Frankowski et al. 2010;Zioła-Frankowska 2010, Frankowski 2012). The objectives of this research are to (1) develop the procedure for fractionation of Al in biological samples, based on water extract fractions, (2) determine the impact of soil contamination on Al concentration in the plant parts of Betula pendula, (3) determine the correlation of Al vs. Ca in soils and particular plant parts of B. pendula, and (4) determine the possible pathway of migration and transformation of Al in the soil-root-stem-twig-leaf system. To determine the spatial variability in Al content/concentration, the study area was divided into two Bcritical^areas with different Al concentrations in the soils-Luboń Chemical Plant (LU) and Wielkopolski National Park (WNP) (Fig. 1, Table 1). LU is located in the southeastern part of the town of Luboń, 2.5 km south of the artificial recharge well field BDębina^for the city of Poznań (Poland). The plant takes up the area of about 59 ha. To the north of the chemical plant, there are industrial grounds and afforested areas spreading across the meanders of the Warta River. To the south, there is an aggregate mine, and in a distance of about 0.7 km runs the border of WNP. In a distance of about 200 m to the southwest of the chemical plant, there is a post-crystallization leachate disposal site. The post-production disposal facility is a dammed-up underground tank with a built-up superstructure, which does not contain any additional safety devices to reduce the migration of pollutants to the water-bearing layer. It takes up the area of about 2 ha, and its removal began in the year 2005. The chemical plant produced aluminum fluoride for about 20 years. Post-crystallization leachate generated in the production process was stored at the post-crystallization leachate disposal site in the form of semi-fluid pulp. In the 1980s, such chemicals as superphosphate, hydrofluoric acid, aluminum fluoride, potassium fluoroborate, and vanadium catalyst were also produced there. Soil samples for the analysis were collected in a depth profile of 0-20 cm. Samples were dried at room temperature. Hygroscopic substances dissolved in water were treated as an integral component of the samples. After drying, each soil sample was sieved through 2.0-, 1.0-, 0.5-, 0.25-, 0.1-, and 0.063mm mesh size sieves, in accordance with the Polish Standards: PN-ISO 565:2000 and PN-ISO 3310-1:2000, using a LAB-11-200/UP sieve shaker (EKO-LAB, Brzesko, Poland). The grain size fraction between 0.1 and 0.25 mm was predominant and was used to prepare soil extracts. Leaf samples were ground, and the other parts of the trees were divided into 0.5-cm pieces. Subsequently, these samples were stored in polypropylene bags until extraction and mineralization. All the 0.5-cm pieces of particular plant parts were used for extraction. Fractionation of Al and Ca in the water fraction of soils and biological samples: The F1 extracts were prepared in a 1:10 (v/v) proportion with deionized water. They were homogenized during 1 h in a magnetic mixer (the predominant 0.1-0.25-mm grain size fraction was used for the soil samples). Subsequently, the F1 extracts were placed in falcon tubes and a new portion (10 ml) of deionized water was added. During that step, the extraction temperature was increased to 80°C (hence named fraction F2). The pH was determined for all the water extracts, using an Orion 5-star Plus (Thermo, USA) meter with a Single Pore pH electrode (Hamilton, USA). In the next step, the soil samples were mineralized using a modified EPA 3051 method (Frankowski et al. 2013) to separate the pseudo total concentration (PTC) of Al and the total concentration (TC) of Ca. The same method was used for the mineralization of biological samples. Measurements of Al and Ca were performed in three replications, and the relative standard deviation did not exceed 7 %. The elements were determined using a Shimadzu AA7000 spectrometer (Shimadzu, Japan), with an air-acetylene flame atomization for Ca and with a nitrous oxideacetylene flame atomization for Al. To check the accuracy of the flame atomic absorption spectrometry analytical technique, a standard procedure making use of certified reference materials was adopted: -The SRM 2709-for soils (soil samples prepared in accordance with EPA method for FAAS) -The SRM 1515-for leaves (National Institute of Standards and Technology, USA) The SRM 2709 and SRM 1515 reference materials were analyzed in six replications. Average recoveries for all the Results and discussion Research on Al fractionation using single-step extraction and simple sequential extraction of soils and particular plant parts of B. pendula indicated the requirement to investigate the issue of Al availability and bioavailability. This subject has to date been included in the studies by Drabek et al. (2005), Álvarez et al. (2002), Walna et al. (2005), and Zołotajkin et al. (2011). Soil samples most frequently originate from highly acidified areas. Moreover, it should be emphasized that knowledge about Al availability and bioavailability, from soils through roots and finally to leaves, is important to determine possible toxic effects for plants and possible pathways of Al transport in the plant system. Total Al in B. pendula-detailed characterization for different plant organs The highest content of Al was identified in lateral roots, especially in samples taken from the contaminated area (LU). Samples 4 and 7 had Al contents of 3.1 and 4.7 mg kg −1 , respectively. The other samples ranged from 463.1 to 1429 mg kg − 1 in the LU case and from 289.3 to 419.3 mg kg −1 in the WNP case. Relatively high Al concentrations were found as well in tap root samples taken from the LU area, ranging from 212.2 to 450.3 mg kg −1 , and from the WNP area, ranging from 113.8 to 145.1 mg kg −1 . Based on results of Al measurements in tap roots, we could observe a clear difference between samples, depending on the sampling site (LU or WNP). A similar phenomenon was found for leaves as well, where Al seems to accumulate. In the samples from the contaminated area (LU), Al content in leaves ranged from 147.3 to 605.7 mg kg −1 . The highest Al content in leaves was determined for sample 7 (also the highest Al content in lateral root). As for the samples taken from the WNP area, the content of Al ranged from 12.41 to 55.75 mg kg −1 . Similar relations regarding Al content were found for the samples of other plant organs: twigs and stems. However, for these samples, Al content was much lower, respectively, in the range 23.5-153.8 mg kg −1 for twig samples taken in the LU area and 9.6-17.1 mg kg −1 for the samples taken from the WPN area. In the case of stem samples, Al content ranged from 24.6 to 165.3 mg kg −1 (LU site) and from 9.6 to 22.5 mg kg −1 (WNP site). It was observed that Al content in stems was lower than in lateral roots (LU site), while for samples collected in the WNP site, the dependence of Al content in stems and lateral roots was not clear; 2 out of 4 samples had higher Al contents in stems than in lateral roots. PTC of Al in soils vs. Al in B. pendula Pseudo total content (PTC) of Al represents the fraction occluded on the grains of soils and not bound to the soil crystalline structures. Table 2 presents the concentrations of Al for the 0.1-0.25-mm grain size fraction and the percentage of F1 and F2 fractions in PTC. PTC for the samples collected in the LU area was variable and averaged to a value of 3601 mg kg −1 . The highest concentration was found for sample 5. For the WNP area, Al concentrations were similar, with an average value of 1588 mg kg −1 . Still, the contribution of fractions F1 and F2 (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2) 11 Fig. 2 Total content of aluminum in particular parts of Betula pendula (1-11, samples 1 and 2 mean that they have been collected at the LU and WNP sites, respectively) Fig. 3. Based on the percentage share of Al PTC in soil and TC in B. pendula, it was observed that, except for samples 4 and 7, the proportions were similar in the LU and WNP areas. It means that the content of Al in particular plant parts did not depend on soil contamination. The uptake of Al, which was strongly connected with the concentration of Al in leaves, was evenly distributed in B. pendula plant parts, and it was limited by the root system. The Al concentration in the F1 fraction demonstrated a similar variability as total content of Al. Fraction F1 is the most mobile fraction of Al, and considering the samples taken at the LU site versus those taken at the WNP site, it can be noted that the availability of Al for the two areas was different. This refers particularly to the results obtained for leaf samples, in which the Al concentration was much lower for the WNP site. It can be emphasized as well that Al concentrations were highest in the lateral and tap roots when compared with the other plant parts of B. pendula. This was confirmed by the results for the TC fraction. For lateral root samples, Al concentrations (in the F1 fraction) of 86.2-640.6 and 12.0-30.3 mg kg −1 were determined, whereas for tap roots, the ranges were as follows: 14.0-175.1 and 7.9-55.5 mg kg −1 for the LU and WNP sites, respectively. Al concentrations in leaves ranged from 15.0 to 205.8 mg kg −1 for samples collected at the LU site and from 2.8 to 7.1 mg kg −1 for samples collected in the WNP area. Regarding twigs and stems, the concentration of Al was lower for stem samples. The concentration ranges were as follows: twigs 3.0-76.0 (LU site) and 3.4-10.1 mg kg −1 (WNP site) and stems 4.9-86.1 mg kg −1 (LU site) and 2.1-4.5 mg kg −1 (WNP site). Low Al concentration in F2 samples of twigs and stems indicated the transport of ions in these plant parts and the accumulation of Al in leaves. For the F2 fraction, the Al concentration in leaves was as follows: 1.3-2.4 mg kg −1 for WNP samples and 9.9-63.1 mg kg −1 for samples taken at the LU (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 F2 in B. pendula-detailed plant characterization (2) 10 (2) 11 Fig. 4 Concentration of aluminum in the F1 fraction of the particular plant parts of Betula pendula (1-11, samples 1 and 2 mean that they have been collected at the LU and WNP sites, respectively) site. Such a variation of Al concentrations in the two environment types (LU vs. WNP) suggests the accumulation of Al with time and binding of Al to soluble complexes which are not extracted by water during F1 extraction. A similar relation was found for lateral root samples, for which the F2 fraction Al concentrations were as follows: 7.9-21.7 mg kg −1 for the samples taken at the WNP site and 23.8-283.1 mg kg −1 for the LU site samples. It was observed that the binding of Al by the specific plant parts was much higher for the samples collected from the LU site than for the samples taken at the WNP site. This suggests the continuous accumulation of Al during the vegetation season. To determine the degree of Al binding, the % value of fraction F1 versus F2 is presented in Fig. 6. The % of fraction 1 versus fraction 2 varied, especially for samples 1 and 2 taken at the LU site, in which a higher extraction degree was observed for the F2 fraction than for the other samples taken from that site. Besides, the extraction degree for samples 1 and 2 indicated complex mechanisms of Al binding to structures of particular plant parts. For samples 3 to 7, the F1 versus F2 variability was similar and the highest % of the F1/F2 ratio was found in the samples of lateral roots and leaves. In the case of samples taken at the WNP site, the variability in F1/F2 percentage was similar and the tendency for particular plant parts was comparable. Bioavailability of Al (TC vs. F1) The percentage F1 fraction versus TC reflects the availability of Al which has been transported from the root system to the leaves of B. pendula. The variable F1/TC also indicates the concentration of mobile Al which is subject to transformations (especially concerning its chemical forms) and contributes to the toxicity of this element. Figure 7 presents the % share of F1 in total content of Al for particular plant parts of B. pendula. Based on the F1/TC values of Al, it is difficult to pinpoint a relationship between the results obtained for the LU and WNP sites. This particularly pertains to the values obtained for the samples of twigs and stems. The degree of extraction for these plant parts was variable: 12.7-49.4 and 17.8-58.8 %, respectively, for the LU and WNP site twig samples and 17.1-52.1 and 16.7-31.1 % for the LU and WNP site stem samples. In the other plant parts, i.e., the lateral roots and tap roots, a lower degree of the extraction of F1 in relation to TC was observed, especially for samples 9-11 (WNP site). In the case of leaf samples, it was observed that variability was low in the extraction efficiency, indicating the presence of weakly bound Al, e.g., organic Al complexes. (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 The impact of pH (2) 8 (2) 9 (2) 10 (2) 11 Fig. 5 Concentration of aluminum in the F2 fraction of particular plant parts of Betula pendula (1-11, samples 1 and 2 mean that they have been collected at the LU and WNP sites, respectively) sites (Fig. 8). However, pH variability in samples of leaf water extracts, taking values from 3.9 to 6.7 for the LU site and from 4.1 to 4.8 for the WNP site, should be further discussed. Low pH values in leaf samples can be explained by the occurrence of organic acids in leaves, which-depending on the concentration of ligands (e.g., oxalate, citrate, malonate, acetate, formate)-can lower Al toxicity by the formation of relatively stable Al complexes with a considerable advantage of the ligand/Al 3+ . Expressed toxic impacts at low contributions of the ligand/Al 3+ are a consequence of low ligand occurrence (e.g., Frankowski et al. 2013). TC of Ca vs. Al in soils and B. pendula The total content of Ca was higher in samples of B. pendula than in soils. The variability of Ca concentrations in particular plant parts was similar to that of Al concentrations (for both the F1 and F2 fractions and PTC). This relationship indicates a strong connection between the occurrence of Ca and Al in soils as well as similar mechanisms of uptake by the plant root system and transport to leaves. Table 3 presents the TC of Ca determined for particular plant parts and the concentration of Ca in soils. To determine and open the discussion on the dependences of the occurrence of Ca and Al in soils and in particular plant parts, correlations are presented for each group of samples (Fig. 9). The results obtained for soil samples showed that concentrations of Al were highly dependent on the concentration of Ca (r=0.969). This allows us to state that the availability of Ca and Al cations was regulated in the soil. Ca is taken up from soils through the root system, first, through the lateral roots and, subsequently, by the tap roots. With regard to the relationship between Al and Ca in lateral roots, it was found that Al 3+ cations were Bblocked,^and as a result, Ca 2+ cations were introduced. First of all, this can be explained by the much lower concentration of Ca in the lateral root system than in tap roots, combined with the retention of Ca in the root system. In this case, lateral roots prevented the introduction of Al to tap roots and with respect to transport, further to the stems and twigs and finally to the leaves. The process was limited by the uptake of higher amounts of Ca 2+ by the system. This was confirmed by the results of the Ca/Al correlation for tap roots. We obtained much higher values of coefficient r=0.736 as compared to later roots. On that basis, it can be assumed that Al does not migrate from soils to roots as Al 3+ but in other speciations, i.e., Al complexes which are both of inorganic and organic nature and with a different charge (e.g., +1, −1, and +2, −2). Also emphasized is that the correlation study results for tap roots showed that B. pendula plants are able (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2) 11 Fig. 7 The percentage of fraction F1 with respect to the total content of aluminum in particular plant parts of (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2) (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2) 11 tap roots lateral roots (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2) (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2 (1) 1 (1) 2 (1) 3 (1) 4 (1) 5 (1) 6 (1) 7 (2) 8 (2) 9 (2) 10 (2) 11 Fig. 9 Graphs representing the correlations of Al and Ca concentrations for twigs, stem, tap roots, lateral roots, leaves, and soil samples (significance level p=0.95) connected with the transport of the cations toward the leaves. The results of Ca and Al concentrations for leaves and the correlation between these elements (r=0.882) showed that Al can easily migrate from tap roots to leaves. A specific amount of Al was built in as a structural element, and a considerable amount was transported to the leaves (see Fig. 5). Taking the pH of the water extracts of leaf samples into account (Fig. 8), it can be noted that Al species can be transformed, especially to the Al 3+ species. The toxic impact of this Al form is probably lowered by the availability of organic ligands (e.g., malate, oxalate, or citrate ions). As it is commonly known, organic complexes of Al are much less toxic or not toxic at all for plants or living organisms. Similar relationships between Al and Ca concentrations were observed for both the F1 and F2 fractions. Kidd and Proctor (2001) conducted research on the impact of Al on growth and mineral composition of B. pendula Roth and concluded that low Al concentrations (2 and 5 mg l −1 ) enhanced growth, whereas higher Al concentrations (10-15 mg l −1 ) reduced growth in less Al-tolerant plant races. Statistical analysis The statistical analysis of Al concentrations in the F1 and F2 fractions as well as the TC of Al in soils and particular plant parts of B. pendula, based on the Kolmogorov-Smirnov test, did not give ground to reject the hypothesis on the equality of means in the studied groups of samples. Similarly, the Shapiro-Wilk test indicated that 11 out of 18 types of soil samples and plant parts (F1, F2, and TC fractions) were characterized by a normal distribution. The samples of tap root F1 and soil F1 fractions as well as tap root F2 and the TC fractions of twig, tap root, leaf, and soil samples (in total, 7 out of 18 types) were not normally distributed (level of significance p<0.05). To compare the concentration of Al in the study sites (LU vs. WNP), the U Mann-Whitney test was executed. For Al in soils and B. pendula, the obtained values of p were lower than α=0.05, except for twig F1 fraction and twig, stem, and tap root F2 fractions. These results led to the conclusion that the Al concentrations in the F1, F2, and the TC fractions of Al were statistically significantly different for both the investigated sample sites (LU and WNP). Conclusions The application of a new procedure, based on the simple sequential extraction of water-soluble fractions (F1 and F2), can be used as an effective tool for the estimation of soil Al toxicity in plants. Moreover, it can be emphasized that data on total (plants) and pseudo total (soil) content of Al are important indeed and should always be taken into account when performing Al (toxicity) research. Additionally, it can be concluded that the proposed procedure is useful in evaluation of the distribution of Al in soils and plants. It was elicited that in the samples originating from the LU site, binding of Al by particular plant parts is much higher than in the samples taken from the WNP sampling site. This suggests a persistent accumulation of Al during the growing season. The concentration of Ca in plants and soils was used to understand the mechanism of Al migration from soil to leaves through the plant system. It was observed that the variability of Al in particular plant parts and the concentration of Al do not depend on soil contamination. However, based on a statistical analysis, the differences between samples collected from the LU and WNP were indicated. The uptake of Al was evenly distributed in B. pendula plant parts and was limited by the root system as well as strongly connected with the concentration of Al in leaves.

v3-fos

2019-03-19T13:06:37.560Z

2015-06-15T00:00:00.000Z

56078539

s2

β-N-Acetylhexosaminidase (NAHA) as a Marker of Fungal Cell Biomass – Storage Stability and Relation to β-Glucan Background. Laboratory and field studies have demonstrated that the enzyme β-N-acetylhexosaminidase (NAHA) is a marker of fungal biomass. The purposes of this study was to determine, 1) the stability of the NAHA enzyme on stored filters, 2) the effect of air movement during the sampling of particles and resulting NAHA enzyme activity, and 3) the relationship between enzyme activity and β-glucan concentration. Methods. Replicate air, filtered (0.8 μm pore, cellulose acetate) samples were obtained and stored at room temperature. Then 7 to 12 samples were analysed at 0, 10, 20, 30 or 360 days. Air samples were collected in rooms with no activity, walking or with fan use. The NAHA activity on the filters was measured by adding an enzyme activator and the fluorescence was measured. The β-glucan concentrations were measured using a Limulus-based test with and without solubilisation with NaOH. Results. Storage of filters up to 360 days did not influence the content of NAHA. Movements in the room increased the NAHA values but agitation in terms of fan blowing did not increase the potential to detect differences between rooms with or without fungal growth. There was a relation between NAHA and the non-soluble fraction of β-glucan. Comments: Enzyme measurements of fungal biomass are rapid and easy to perform. The sensitivity and specificity of the method is high which makes it suitable for field use. Incorporation of the small fungal fractions in exposure assessment is important from a health point of view as they have a higher penetration rate into the deep parts of the lung. Summary: The evaluation of the enzyme method to determine fungal growth further supports the relevance of this method to relate to medical effects of fungal exposure. Introduction Fungi are present everywhere in the environment and will grow as soon as the air humidity exceeds 70% or the material relative humidity exceeds 23%. The risk factor for fungal growth is water damage, either in terms of flooding from the outside or leaking water pipes [1]. Condensation of water in air ducts or on surfaces in humid environments may also increase the risk of growth and hence dispersion of fungi in the indoor environment. A build-up of fungi in a humid room will increase the risk of transfer to adjacent rooms, particularly during the drying period, when the fungal hyphae and spores crack and small, submicron particles are formed. Exposure to fungi may cause medical problems in terms of irritation in the airways and eyes, difficulties to breathe, itching, and an abnormal tiredness [2,3,4]. Some persons may develop an allergy to fungi but this is quite rare. There is a large difference between individuals -some persons may exhibit strong reactions in a location where others may be without symptoms. Methods to measure fungal contamination are important for house owners, building entrepreneurs, and inhabitants of buildings. Traditional measures of fungal contamination are total spore counts, counting spores on spore traps or air filter samples, or determination of viable fungi on surfaces, air filters or sedimentation plates, using nutrient agar. PCR techniques have also been used, particularly for species determination. Studies have demonstrated important differences between floor dust and air sampling [5]. As the major exposure route is by inhalation, air samples are more representative for risk assessment. Early data on indoor fungi indicated that outdoor levels were often higher than those measured inside in suspect houses. In those studies the dynamics of indoor air was not taken into account. If one places the measuring equipment in a room and leaves it there during the measuring period, the air is still and the particles sediment to the ground. Outdoors there is always wind movements, not surprisingly causing higher levels. Appropriate measuring conditions for indoor sampling should thus comprise some activity in the room during the sampling. There are several biologically active agents in the fungal cell wall which account for the medical effects relating to fungal exposure. β-glucan is a major cell wall constituent and may affect the functioning of the immune system [6]. Chitin and mannan are other agents causing similar effects. Chitin and other agents are allergenic and some fungi produce toxins. Of importance is that the biological activity of these agents remains when the fungal cell is dead. They are also present in fragments of fungal cells that are formed when cells are dried or agitated. The proportion of bioactive agents in such fractions may constitute up 50% of the portion found in larger particles such as whole spores or viable cells [7,8]. This means that determination of viable fungi may have severe limitations in terms of identifying a risk exposure. Techniques to determine total cell biomass are more relevant for dose estimations. Several laboratory and field studies demonstrate that the enzyme β-N-acetylhexosaminidase (NAHA) is a marker of fungal cell biomass. Significant correlations to total spore counts were found in air samples and in dust generated from biomass in a bio fuel plant [9]. Strong correlations were found between fungal biomass (gravimetric weight) and NAHA in fungal species grown on nutrient agar and between ergosterol and NAHA activity on gypsum boards [10]. NAHA is also present in certain bacteria and in cells from humans. Data from a field study demonstrated that indoor air levels were closely related to the presence of mould damage in the buildings [11]. At a cut-off value of 20 U/m 3 , the presence of fungal growth was identified with a sensitivity of 95% and a specificity of 85%. Above 30 U/m 3 the specificity was 100%. No data are available on the influence of storage on NAHA on air sampling filters. Several early studies show the need to maintain some activity in the room during sampling and agitated sampling through the blowing with a fan has been suggested [12]. The relation between NAHA, a substance without an effect after inhalation, and β-glucan, a fungal cell wall agents with important effects on the immune system has not been studied. The present project was set up to answer these questions. Sample Analysis Air samples (300 L, flow rate 15 L/min) were taken using open filter holders, preloaded with cellulose acetate filters (Mixed Cellulose Esters, 25 mm PCM Cassettes, 0.8µm pore size, Zefon International, Inc., Ocala, FL, USA). The filters were analysed for NAHA using a fluorogenic enzyme substrate (4-methylumbelliferyl N-acetyl-β-D-glucosaminide, Mycometer A/S, Horsholm, Denmark) which is added to the filter. After an incubation period of around 30 minutes, set by room temperature, a developer is added, and the fluorescence of the liquid is read in a fluorimeter (Picofluor, Turner Designs, Sunnyvale, CA, USA). The units (U) read are divided by 10 to diminish methodological scatter, rounded off to whole units, and expressed as NAHA U/m 3 . For the βglucan analysis samples were taken with Millipore filters (Millipore 0,8 µm, ATTP, Millipore, Mass USA) 300 L with a flow rate of 15 L/min. Storage Parallel filters were sampled in different rooms and the amount of NAHA was determined on one filter. The remainder were stored indoors in room temperature and humidity around 30% under darkness and were analysed after 10, 20, 30, and 360 days. The results were calculated as percentage of the amount on the filter on day 0. Air Movements Sampling was performed in different rooms in villas and apartments with no mechanical ventilation. It was first done under quiet conditions with no movements in the room, then when a person walked around in the room 5-6 times during the sampling period, and finally after agitation. Agitation was performed by blowing air with a fan (Makita BUB 182, 18 V, 0,043 m 3 /second, Makita Corp, Anjo, Aichi, Japan). The blower, inducing air velocities of 3.3 meters/sec, was directed towards the floor, the ceiling and the walls in the room for two minutes. After a one minute waiting period to let larger particle sediment, air samples were taken. Sampling was also done before and after cleaning of the rooms. β-Glucan Determinations Parallel filters (n=3) were taken in different rooms in villa and apartment buildings to determine NAHA and β-glucan. For determination of β-glucan the filters were placed in a holder and 1 mL endotoxin free water (LAL, Charles River, USA) was added to one filter. To the other filters NaOH (0.05 or 0.3 M) was added to dissolve the non-soluble fraction of β-glucan. After 10 minutes the fluid was sucked through the filter and added to 2 mL LAL. 25 µL of this fluid was placed into a cartridge for measurement of β-glucan, using a Limulus based analysis equipment (Endosafe Pico, Charles River USA). Statistical Analysis The data were stored and evaluated on SPSS. Differences between groups were evaluated using the chi 2 -test and relationships between the groups using Spearman's test. Table 1 reports the amount of NAHA in filters at different times after sampling. There were no indications of a systematic decrease in the NAHA values over time during the first month and a small decline at one year. The variation between different sampling times is probably due to differences in the amount of NAHA on parallel filters -the aerosol is not mono-disperse. Air Movements and Cleaning The NAHA levels during different degrees of movement and the results of cleaning are illustrated in Figure 1. When there was no activity in the room, the values were low without significant difference before-after cleaning. Walking increased the amount of NAHA compared to still conditions (p=0.001, paired sample test) and the use of a fan increased the values in relation to walking (p=0.001, paired sample test).The figure also illustrates that ordinary cleaning is an efficient means to reduce the amount of airborne fungi. After cleaning there was no significant increase in the NAHA values when comparing walking with still and fan with walking. Figure 2 shows the per cent increase in NAHA after fan agitation in relation to the values after walking. Fan Agitation During Sampling The figure illustrates that there was no relation. Amounts lower than 20 U/ m 3 , which has been suggested as threshold value for the presence of fungi [11], had the same proportional increase as values above 30 U/m 3 . At high values there was a relatively small increase after agitation. Agitation thus yields a higher value than walking, but does not improve the possibility to distinguish between rooms with or without fungi. NAHA and β-Glucan The amounts of soluble and non-soluble β-glucan are shown in Table 2. These were no statistically significant relationships between the amount of NAHA and the amount of soluble or with 0.05 M NaOH extracted β-glucan. There was a relationship with the β-glucan extracted with 0.3 M NaOH (p = 0.006, Spearman's test). The relationship is illustrated in Figure 3. measurements, probably related to the non mono-disperse aerosol as earlier referred to, and to methodological variations in the method to determine β-glucan. Comments The main results from the study were the stability of NAHA during prolonged storage, the need to have some air movement during measuring, the absence of an advantage by applying strong agitation during sampling, and a relation between NAHA and the amount of non-soluble β-glucan. The effect of cleaning on the NAHA levels is interesting from an exposure point of view. It is well known that neglected cleaning may induce airway symptoms among inhabitants. Previously this has been referred to as "dust allergy" but the underlying mechanism is probably an inflammatory response induced by β-glucan from fungi accumulated in the house dust. The additional information obtained in this study illustrates the potential of the NAHA method to sample fungal contamination in a building with a high accuracy. Enzyme measurements of fungal biomass are rapid and easy to perform. As with all methods measuring fungi in air, there are certain limitations. The data obtained relate to conditions at the moment of measurement. From a building construction point of view, the method will not detect hidden sources of fungi which are without direct connection to the room where the sampling is performed. Measurements in rooms with a high humidity can also give low values even if there is visible fungal growth. This is due to the adherence of the fungal particles to the surface due to humidity, contrary to the conditions in dry rooms or where air dryers have been used. This will increase the proportion of fungal particles that can be aerosolized. The relation between NAHA and β-glucan is important as it justifies the use of NAHA measurements to investigate the presence of symptoms related to fungal exposure. The results demonstrate that solubilisation with NaOH must be performed to obtain the correct value for β-glucan. Several previous studies have investigated the relation between the presence of symptoms among children and the amounts of βglucan in the dust. Some of these studies reported the exposure in terms of soluble β-glucan [13]. This represents a severe underestimation of the exposure which can explain the weak relation between exposure and symptoms reported. Previous studies have found relationships between NAHA and medical parameters. Higher levels of NAHA have been found in homes of patients with sarcoidosis [14] and nocturnal asthma [15] in comparison to control subjects. A relation has been reported between NAHA levels in bedrooms in bedrooms and the spontaneous secretion of IL-12 from peripheral blood mononuclear cells from patients with sarcoidosis [16]. Another study found a relation between NAHA levels in bedrooms and the amount of β-glucan in broncho-alveolar lavage [17]. In conclusion air sampled NAHA does not decrease in activity during storage of the filters. Agitating room air does not improve the possibility to detect high levels of NAHA, and there is a relation between NAHA and the amount of non-soluble β-glucan.

v3-fos

2016-05-12T22:15:10.714Z

2015-12-23T00:00:00.000Z

17086929

s2

Accuracy and responses of genomic selection on key traits in apple breeding The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval. The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits. The training population comprised 977 individuals derived from 20 pedigreed full-sib families. Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an Illumina 20K SNP array. From these data, a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application full-sib families. The application families had genotypes at 364 SNPs from a dedicated 512 SNP array, and these genotypic data were extended to the high-density level by imputation. These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values. Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19. The accuracies were strongly affected by the phenotypic distribution and heritability of traits. In the largest family, significant selection response was observed for traits with high heritability and symmetric phenotypic distribution. Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability. Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population. The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs. INTRODUCTION Developing new fruit tree cultivars is a time-consuming process for two main reasons. First, the long juvenile phase delays the acquisition of phenotypic data that are necessary to identify genotypes that will produce marketable fruits satisfying both farmer and consumer demands. 1 Second, breeding programmes are often organized in two or more successive steps. The initial large diversity step involves phenotyping a large number of candidates over two or three years at a single location. Those candidates presenting favourable characters are identified and enter the cultivar evaluation step comprising extensive phenotypic evaluation over a longer period at multiple contrasting locations. The early identification of promising genotypes at the large diversity step would enable fruit tree breeders to enhance genetic gain per year and react more efficiently to changing demands by reducing breeding cycle length. 2,3 Molecular markers have been developed to help fruit tree breeders for early identification of interesting genotypes. Indeed, associations between markers and genes underlying agronomic traits are the basis for marker-assisted selection (MAS) 4 which can be performed on young seedlings as well as for selecting well-combining parents. Similar to other crops, 5 MAS has been applied to apple breeding schemes manipulating few major genes including resistance genes for scab, fire blight, mildew, aphids and genes involved in fruit firmness or storability (see e.g. Baumgartner et al. 6 ). However, traditional MAS is ineffective when many genes of small effects are segregating, and reliable markers have not been identified. In this context, Meuwissen et al. 7 proposed to skip the quantitative trait locus (QTL) detection step in favour of using all available markers in a genome-wide prediction approach termed genomic selection. In genomic selection, a training population on which both phenotypic and genotypic data are available is used to construct a prediction model which is subsequently applied to estimate genomic breeding values (GBVs) of individuals that only have genotypic data. Genomic selection often targets additive genetic variation, i.e. estimation of breeding values, but may also account for dominance or higherorder genetic variances in order to estimate genotypic values. Genomic selection could complement MAS for polygenic traits and thus obviate the need of phenotyping at the large diversity step. Genomic selection would strongly enhance breeding efficiency by decreasing generation interval and increasing the accuracy of breeding value estimates and selection intensity. Most genomic selection studies in plants have been conducted on annual crops such as maize, [8][9][10][11][12][13] barley 14 and wheat, 15 where inbred lines are the main focus of selection. A few studies on perennial outbreeding plants have been published, particularly on forest trees, [16][17][18][19] switchgrass, 20 oil palm, 21 Japanese pear 22 and apple. 23 These studies used simulations and/or cross-validation, in a defined set of plant material genotyped at high density and phenotyped in a common set of environments, to evaluate accuracy of genomic selection. An exception is the work of Asoro et al. 24 who compared the results of genomic selection to phenotypic selection and MAS after two selection cycles for the improvement of b-glucan 1 concentration in oats. Based on random cross validation on seven full-sib (FS) families, Kumar et al. 23 reported high accuracies of genomic selection, between 0.67 and 0.89, for six fruit quality traits in apple, and concluded that genomic selection is a credible alternative to conventional selection for these traits. Applicability and success of genomic selection to other traits and to designs commonly used by commercial fruit breeders have not yet been reported. The purpose of this study was to assess the prospects of genomic selection in current apple breeding populations for 10 culling traits that are related to productivity and fruit external appearance. Individuals that do not perform well for culling traits are eliminated prior to any harvest. Genomic selection could provide accurate estimated breeding values of these traits so that breeders could skip phenotypic evaluation. This is the first study in fruit crops where GBVs are calculated for individuals that do not belong to the training population but to additional material developed and studied by breeders. Accuracy of genomic prediction was estimated by comparing predicted GBV and phenotypic data of application individuals. Realized selection differential was assessed on the basis of phenotypic differences between individuals with the highest and lowest GBV in a large full-sib family. The influence of factors such as trait heritability and relatedness between application and training populations on accuracy of genomic prediction was evaluated. The composition of the training population in relation to accuracy of prediction and impact of genomic prediction of culling traits on improving breeding scheme efficiency were discussed. Plant material The training population, developed in the EU-funded HiDRAS project 25 for Pedigree Based QTL analysis, 26 consisted of 20 full-sib (FS) families with a total of 977 individuals. These FS families were obtained from breeding programmes from four research institutes (INRA, France; JKI, Germany; UNIBO and LFW, Italy) at the start of the HiDRAS project (see e.g. Kouassi et al. 27 for more details) and resulted from crosses among 24 parents (Supplementary Table S1) which were related to each other via common ancestors. The parents, intermediate ancestors and founders (individuals with unknown ancestors) were included in pedigree data. The application population consisted of five FS families developed within two European apple breeding programmes, Novadi and Better3Fruit, located in France and Belgium respectively. A total of 1390 individuals from these five families were used in this study, the family size ranged from 109 to 662 (Table 1). The application families resulted from crosses between nine parents where one parent (313) was involved in two crosses ( Table 1). Out of the nine parents, five were also the parents of progenies in the training population (Supplementary Table S1). The pedigree relationships among the parents and FS families of the training and application populations were abundant and were visualized with Pedimap software 28 as shown in Supplementary Fig. S1. Trait phenotypes Phenotypic data for the training population were available from the HiDRAS project and were partly described by Kouassi et al. 27 The individuals of the training population were each evaluated at one location managed by the involved research institutes, and data were collected during at least two seasons over a period of three years, from 2003 to 2005. The individuals were not replicated. Our study focused on culling traits, which are scored before or at harvest. Productivity-related traits namely pre-harvest dropping and fruit cropping were assessed along with external appearance traits such as fruit size, per cent of russet, fruit cracking, attractiveness and four components of skin colour, ground colour, over-colour, per cent over-colour and type of colour. All traits were visually scored on an ordinal scale (1-5, Supplementary Table S2). Twenty-nine reference genotypes (Supplementary Data 1, not part of training population) were scored in all locations and were used to adjust phenotypic data for location and year effects (similar to Bink et al. 29 ). As in Bink et al., 29 the best linear unbiased predictions (BLUPs) of genotypic effects of the individuals in the training population were used as phenotypes for the development of genome-wide prediction model. For the application population, the same traits as in the training population were scored at harvest, except that skin colour was assessed as attractiveness of colour and not as the four component traits scored in the training population. Phenotypic data for the application population were collected, without replication, in 2013 at two sites, i.e. two families in Seiches (FR) and three families in Rillaar (BE), all managed by the involved apple breeders of Novadi and Better3Fruit, respectively. Table 1. Accuracy of prediction for the 10 traits within the application families, and means of these correlations over families and over different sets of traits (all: Mean_10Traits; attractiveness, fruit cropping, fruit size and per cent russet: Mean_4Traits) and mean length by family of 95% confidence intervals of these correlations. Marker genotypes The genotypic data of the training population and their progenitors were obtained from a FruitBreedomics experiment on Pedigree Based Analyses by using the Illumina 20K SNP array 30 . This same experiment provided SNP data on two additional FS families, 'Telamon' 3 'Braeburn' (162 individuals) and 'Jonathan' 3 'Prima' (25 individuals), that were used to improve genotype imputation (see below and Supplementary Table S1). These two latter families did not have phenotypes for the studied traits. This experiment also provided genetic linkage maps, which included a total of 15.8K mapped SNP markers, 30 of the training and additional families. Subsequently, a set of 7651 SNP markers passed the filtering criteria on absence of null-alleles, disturbing additional SNP at the probe set, and genotyping interference from paralogous loci, thus showing robust performance across this germplasm (Van de Weg & Di Guardo, personal communication). The across-families integrated map of these 7651 SNP markers was used here (version of July 4 2014). Twenty-four individuals from the five application families were genotyped with the 20K SNP array following the standard Illumina protocol detailed in the study of Chagné et al. 31 to check parentoffspring consistency and to help phasing the markers in the imputation step (see below). All 1390 individuals of the five application families were genotyped with an array of 512 SNPs using the QuantStudio 12K Flex Real-time PCR system and OpenArray technology (Life Technologies, Carlsbad, CA, USA). These 512 SNPs were a subset of the 15.8 K mapped SNPs. Details on SNP selection process are given in Supplementary Data 2, and the positions of the selected SNPs on the genetic map are shown in Supplementary Fig. S2. Samples consisting in 10 ng DNA were mixed with 2.5 ml of TaqMan OpenArray Genotyping Master Mix (Life Technologies, Carlsbad, CA, USA) in a 384-well plate. Samples were subsequently loaded onto the OpenArray plate using the QuantStudio 12K Flex OpenArray AccuFill System. Following PCR, allelic discrimination results were analysed using the TaqMan Genotyper software v. 1.2 (Life Technologies, Carlsbad, CA, USA). Genotypic data curation The TaqMan OpenArray (512 SNPs) genotypic data resulted in 364 SNPs that could be reliably scored in the application population. These 364 SNPs were checked for Mendelian segregation errors and frequency of observed recombination events using the FlexQTL software 29 (www.flexqtl.nl). The additional curation on the 15.8K SNPs (see previous paragraph) introduced a substantial mismatch between the 364 SNPs scored with the TaqMan array and the 7651 robust SNPs, i.e. 178 out of the 364 SNPs were not considered as robust. The genotypic data on these 178 ''non-robust'' SNPs for the training population were added to those on the 7651 robust SNPs to enhance the accuracy of imputation in the application population. Positions of the robust and non-robust SNPs scored with the TaqMan array are shown in Supplementary Fig. S2. The resulting matrix of genotypic data comprised 7829 SNPs on 2661 individuals. The 1271 individuals genotyped with the 20K array had sporadically missing data, and 1390 individuals from the application FS families had substantially (.95%) missing data. SNP genotype imputation The imputation of genotypic scores for missing SNP data was done in two steps by using AlphaImpute software, 32 which uses pedigree, linkage and linkage disequilibrium information. In both steps, default values were used for all software parameters except for the windows sizes to account for the number of SNPs in the data set (values for CoreAndTailLengths and CoreLengths ranged between 100 and 300 SNPs, and between 50 and 200 SNPs, respectively). In the first step, AlphaImpute was applied to the families of the training population, their progenitors, the two additional FS families and the 24 individuals of the application FS families, all genotyped with the 20K array. In the second step, AlphaImpute was applied to the 1390 individuals of the application families utilizing the completed data from the first step as reference. Variance components and heritability To estimate the heritability of the 10 traits, the phenotypic data were first adjusted for fixed effects, i.e. year and location effects using all available data. Then a linear mixed model (Supplementary Data 3) was used to estimate the additive (s 2 a ) and residual (s 2 e ) variance components using only individuals of the training population. Narrow-sense heritability for each of the Estimates of variance components were obtained with the R package breedR. 33,34 The pedigree-based relationship matrix was obtained with the R package pedigree 35 and the mean pedigree-based relatedness between each application family and the training population was calculated. Genomic relatedness Genomic relatedness between application population and training population were computed using the imputed genotypic data. The matrix of genotypic data (X) with individuals of the training and application population in columns and SNPs in rows was first standardized using means and standard deviations of genotypic data computed for each SNP in the training population. Then the genomic relationship matrix (G) was computed as where W is the standardized version of the matrix X, and p is the number of SNPs. 36 Because of the standardization, the mean of the elements of G pertaining to the pairwise relatedness of an individual of the application population to all individuals of the training population was expected to be zero. 37 Following Clark et al., 38 three fractions of the training population were considered to summarize the relatedness of application individuals and families to the training population. The top 10 relatedness of each application individual was calculated as the mean of the 10 highest values among the elements of G corresponding to the relatedness of an application individual to the individuals of the training population. Likewise, the top 5% and 25% relatedness of each application individual to the training population were calculated. Subsequently, the top 10, top 5% and top 25% relatedness of each application family to the training population was calculated as the mean of these variables within each family. Genomic prediction The BayesCp method, 39 as implemented in GS3 software (Legarra et al., 2011, http://snp.toulouse.inra.fr/,alegarra), was used to estimate GBVs. In this method, the parameter p can be interpreted as the proportion of SNPs that truly affect the trait. Likewise the distribution of estimated SNP effects may reveal information on the genetic architecture of the trait. Once the prediction model (Supplementary Data 3) was established based on the training population, the GBVs in the application population,ĝ, were estimated. Accuracy of predictions and realized selection differential The accuracy of genomic predictions was calculated as the correlation between the GBVĝ and the phenotypic scores in the application population. Pearson correlations were used for all traits and Accuracy and responses of genomic selection in apple H Muranty et al Spearman rank correlations for traits with highly skewed distributions. Accuracy was calculated separately within the five application families due to confounding with locations. As shown in the Appendix, the accuracy calculated in this way is expected to be proportional to the square root of narrow sense heritability. The correlations were calculated with the function cor.test in R software, 34 which also provided estimates for the asymptotic confidence intervals (based on Fisher's z-transformation) for Pearson correlations. The realized selection differential within each application family was estimated as the difference in mean phenotypic scores between the individuals with the highest GBV and the individuals with the lowest GBV. The significance of these differentials was assessed via a Student's t-test. We selected 50 individuals from both tails of the distribution of GBVs, which equated to selected fractions of 7.5% in case of the largest application family, AF1-Da66, which comprised 662 individuals (Table 1). A directional realized selection differential was also estimated as the difference in mean phenotype of the individuals with the most favourable GBV and all individuals within each application family. Note that the trait colour was scored in the application families as attractiveness of colour, while it was scored as four components, i.e. ground colour, over-colour, per cent over-colour and type of colour in the training population. We calculated accuracy of colour predictions using the four components correlated to the same phenotypic scores (on attractiveness of colour). Likewise, we calculated realized selection differential as the difference in mean phenotypic scores for attractiveness of colour between the selected extreme individuals for GBV calculated for the four components of colour. Distribution of trait phenotypes In the training population the distributions of phenotypes (5 genotypic BLUP values) varied greatly among the 10 traits considered in this study ( Figure 1). The skewness was high and negative for fruit cracking, moderate and negative for per cent of russet and preharvest dropping and moderate and positive for type of colour and over-colour. The distributions of the other traits were almost symmetrical. These differences between traits were also present in the distributions of residuals in the quantile-quantile plots ( Supplementary Fig. S3). Due to the pre-adjustment for year and site effects, the range of phenotypes was slightly increased, [0-6] for all traits. However, for fruit cracking, the highest phenotypic value was just above 4, which exemplified the highly negatively skewed distribution. The distributions of phenotypes varied greatly among traits and between the five application families (Figure 1). Highly asymmetric Figure 1. Within-training population distribution of genotypic BLUP (upper row) and within-family distribution of phenotypic data (five lower rows) for traits scored at harvest. Variances are indicated. Non-plotted distributions correspond either to a trait not scored in a family (pre-harvest dropping in AF1_Da66 and AF2_Pi63 families) or, for colour, to components not scored in application families. Accuracy and responses of genomic selection in apple H Muranty et al distributions were observed for fruit cracking, pre-harvest dropping and per cent of russet (except the AF1_Da66 family) and showed the highest frequency in the first, highly desired, class. The distributions for the other traits were almost symmetric, but with narrow ranges as the extreme scores (1 and 5) were hardly present for fruit size in all families and for attractiveness of colour in AF1_Da66 and AF2_Pi63 families. The phenotypic variances in the application population varied greatly over families and over traits, from 0.035 for fruit cracking in AF2_Pi63 family to 1.7 for colour in AF4_31Ga family. Distributions of SNP effects The distributions of estimated SNP effects in the prediction model varied greatly among traits ( Figure 2). More than half of the SNP effects were very close to zero (i.e. less than 10 24 ) for per cent overcolour and over-colour. The distributions of SNP effects were more dispersed for the other traits. The relative SNP effects extended to very large values for per cent over-colour and over-colour, i.e. larger than 0.3, and also quite large values for attractiveness and per cent of russet, i.e. larger than 0.1, whereas the range of relative SNP effects for fruit cracking was very narrow, extending only to 0.0034 ( Figure 2). The estimated probability (p) of marker inclusion in the prediction model varied between 0.007 (over-colour) and 0.397 (ground colour). Furthermore, between 3.7% (fruit size) and 7.0% (fruit cracking) of the markers included in the prediction models were actually genotyped in the application families rather than imputed. Accuracy of genomic prediction Accuracy of predicting phenotypic scores was very low or negative when distributions of traits were very narrow or when these were highly skewed in the training or application populations. This was most apparent for fruit cracking and pre-harvest dropping in all families and per cent of russet in AF5_33Br family (Table 1). For these traits, the Spearman and Pearson correlations were in the same ranges (not shown). Accuracies ranged from 0.02 to 0.38 when distributions on traits were almost symmetrical, setting apart the colour components ( Table 1). The low accuracies for fruit cropping correspond to a flat distribution of relative SNP effects which extended to a small value (less than 0.0069, Figure 2). By contrast, the higher accuracies for attractiveness, fruit size and per cent of russet correspond to distributions where some of the relative SNP effects were above 0.078 ( Figure 2). The accuracies were close to 0 or negative for ground colour and type of colour and were (Table 1). These results suggest that attractiveness of colour is more strongly associated with over-colour and per cent over-colour than with the other two colour traits. Also, the moderate to high accuracies for over-colour and per cent over-colour corresponded to flat distributions of relative SNP effects with a large proportion of effects close to 0 and some extending up to 0.3 or higher. Comparison of the mean accuracy across all traits versus the four traits with almost symmetric phenotypic distribution (see Figure 1) indicate the strong influence of the phenotypic distribution of ordinal traits in the application families on accuracy of prediction. The 95% confidence intervals on the correlations were shorter for the larger families, i.e. varying from 0.16 in AF1_Da66 family (n 5 662) to 0.37 in AF4_31Ga family (n 5 109) ( Table 1). The lengths of the confidence intervals were rather constant within families (not shown). Accuracy and heritability In the training population, the narrow sense heritability of traits varied from 0.03 to 0.67 for fruit cracking and per cent over-colour, respectively. As expected, there was a clear positive trend between heritability and prediction accuracy, which was significant (P ,1%) either considering all traits or considering the four symmetrically distributed traits ( Figure 3). Obviously, this trend is mostly due to the fact that we calculated accuracy of predicting phenotypic scores and not genotypic values (see Appendix). Note that estimation of the heritability in the application population would have been more appropriate, but it was less meaningful here because data of only two or three un-replicated families were available per location. Genomic relatedness between application and training populations Top 10, top 5% and top 25% relatedness between the application families and the training population varied in quite narrow ranges ( Table 2). The ranking of the families was the same for the top 10 and top 5% relatedness and different from the ranking for top 25% relatedness and pedigree-based relatedness, which were also dif-ferent from each other. The standard deviations of these relatedness within application families increased from top 25% to top 10 relatedness and was often close to 10% of the mean ( Table 2). At the individual level, genomic relatedness between individuals of the application population and individuals of the training population varied between 20.31 and 0.59. The highest genomic relatedness were observed between individuals that shared a parent and thus individuals from one application family often had their most closely related individuals in one or a few training families. The levels of highest genomic relatedness for individuals of the AF5_33Br family were lower than those for individuals of the other families (refer to Supplementary Fig. S4). Accuracy and genomic relatedness The relationship between accuracy of prediction and genomic or pedigree-based relatedness varied over traits and over measures of relatedness (Table 3). There was no association for most traits except a significant association for per cent of russet and mean top 25% relatedness. For attractiveness, fruit cropping, per cent of russet and over-colour, the correlation increased when increasing the number of highest values considered to calculate the mean relatedness, e.g. from 0.55 for top 10 relatedness to 0.68 for top 25% relatedness for attractiveness. Realized selection differential The realized selection differential in the (large) AF1_Da66 family was between 0.6 and 0.9 and highly significant for four traits (i.e. attractiveness, fruit size, over-colour and per cent over-colour, Figure 4). Conversely, it was almost absent, i.e. between 20. Points and vertical lines represent the mean and range in accuracy over families, respectively. In blue, the four symmetrically distributed traits (attractiveness, fruit cropping, fruit size and per cent of russet), in black, the two highly skewed traits (fruit cracking and pre-harvest dropping) and in red the four colour components compared to attractiveness of colour. The blue and green lines represent linear regressions without intercept of mean accuracy as a function of square root of heritability on the four symmetrically distributed traits and all traits, respectively. The directional realized selection differential was significant for the same traits in the AF1_Da66 family (Supplementary Table S4). The traits with significant responses also had the highest accuracy estimates, ranging between 0.21 and 0.34 in AF1_Da66 family ( Table 1). The significant response for attractiveness for example implies that out of the 50 individuals with the highest GBV, none had the lowest phenotypic score of 1. Likewise, only one of the 50 individuals with the lowest GBV received a score of 4, and none the highest score of 5 ( Figure 4). Similar trends were observed for fruit size, over-colour and per cent over-colour, but for these traits, very few individuals received the extreme scores of 1 or 5. By contrast, the responses for per cent of russet and fruit cropping were not significant and individuals with the highest and the lowest GBV received the lowest score of 1. Most application individuals with the extreme phenotypic scores for these four traits were in the middle of the distributions of GBV, i.e. neither belonged to the group of 50 individuals with the highest GBV nor to the group of 50 individuals with the lowest GBV. In the other four application families, the realized selection differential was always significant for per cent over-colour, for three of them for attractiveness, per cent of russet and over-colour, for two of them for fruit size and for only one for fruit cropping (Supplementary Table S3). The results were slightly different for the directional realized selection differential, which was always significant for per cent over-colour, for three of them for per cent of russet, for two of them for fruit cracking and for one of them for attractiveness, fruit cropping, fruit size and over-colour (Supplementary Table S4). The realized selection differential was significant for six traits in AF4_31Ga (i.e. attractiveness, fruit cropping, fruit size, per cent of russet, over-colour and per cent over-colour, Supplementary Table S3), whereas it was significant only for three traits in AF2_Pi63 (i.e. attractiveness, per cent of russet and per cent overcolour, Supplementary Table S3). The largest realized selection differentials were observed in family AF4_31Ga for over-colour (2.38) and per cent over-colour (2.63). DISCUSSION This study reports encouraging results on genomic selection for traits that are scored before or at harvest in two European apple breeding programmes. Accuracy of genomic prediction of phenotypic scores varied with traits and families. Heritability was clearly a factor affecting accuracy in this study, whereas the effect of genomic relatedness between application and training population on accuracy was not significant. The realized selection differential in the largest FS family, AF1_Da66, was highly significant for four traits (attractiveness, fruit size, over-colour and per cent over-colour) and negligible for the other five traits. Factors affecting genomic prediction accuracy Relatedness between training and application population. The relatedness between training population and application individuals is a key factor affecting prediction accuracy. 40,41 Our training population was expected to be well-suited for genomic prediction in the application FS families as for each family one or both parents were also parents in the training population, except for AF5_33Br family (Supplementary Table S1, Supplementary Fig. S1). The dense and irregular structure of pedigree relationships between application and training FS families is a plausible explanation why none of the three measures of genomic relatedness provided a regularly spaced sample of relatedness. The later would have been more useful to test the relationship between relatedness and accuracy of genomic prediction. Nevertheless, the three measures of genomic relatedness did not address the same level of relationship. In the application FS families that shared a parent with the training FS families, the 10 most closely related individuals were indeed predominantly present in the training FS families with the shared parents. For individuals from the AF5_33Br family, the 10 most closely related individuals were distributed over 15 of the 20 training FS families (with lower levels of relatedness), but in more than 140 (out of 178) cases most of them were from 'Pinova' 3 'Reanda' and 'Rewena' 3 'Pirol' families, which share recent common ancestors with parent 338 ('Priam' 3 'Reka'). Thus the top 10 relatedness seemed mostly influenced by recent common ancestors. On the contrary, the top 25% most closely related individuals were distributed among 16-20 training FS families suggesting that top 25% relatedness was mostly influenced by more distant common ancestors. The AF5_33Br family was the least related application family, but it did not consistently show the lowest accuracy for all traits. For example, accuracy of genomic prediction in AF5_33Br family was higher than in AF2_Pi63 family for fruit size, per cent over-colour and over-colour (Table 1). The absence of a clear trend between genomic relatedness and prediction accuracy could also be due to the rather large uncertainty of the estimated accuracies ( Figure 3). Despite the large family sizes in the application population, the confidence interval lengths ranged between 0.16 and 0.37. Such large sampling errors of accuracy estimates were also observed by Wolc et al. 42 These results emphasize the importance of the composition of the training population as all QTLs that are segregating in selection candidates of the application populations should also be present at reasonable allele frequency in the training population. The application of genomic selection in a single large bi-parental plant population, phenotyping only a subset, yield high accuracy on unphenotyped full-sibs. 43 In such an application, the generation interval cannot be reduced while this is critical in perennial fruit crops. Thus, a more powerful training population in fruit crops should capture a large and genetically diverse collection of small bi-parental populations to maximize the relatedness of any selection candidate with multiple members of the training population. 41 A larger diversity of the training population and the larger distance between training and application populations will require a higher marker density than for genomic selection in a single bi-parental population. The advantage of using a multi-parental population for training, compared to training and application within a single bi-parental population, is to share the costs of genotyping and phenotyping the training population over a larger number of selection decisions. For fruit trees, this is particularly important as phenotyping costs are high due to the large space needed to grow trees and the long time required to evaluate traits of interest because of the juvenile period and because of the perennial nature of the crops. Genetic architecture of the trait. The genetic architecture of the trait, which can be partly described by the number of QTLs and the distribution of their effects, is another key factor affecting accuracy of genome-wide predictions. This architecture is fixed for a given population-it may change by altering the composition of the population. We used the BayesCp model because of its robustness to a large range of trait genetic architecture in terms of number of QTLs. Although the focus here was not on model inference, the number of QTLs (i.e. non-zero marker effects) influencing a trait may be postulated from the estimated proportion of SNPs (p) from the BayesCp model. Indeed, Habier et al. 39 showed in simulations that estimates of p reflected well the genetic architecture of the trait. For example, the estimated p of 0.007, 0.062 and 0.319 for over-colour, attractiveness and fruit cropping, respectively, would correspond to 55, 470 and 2500 QTLs, respectively. These estimated numbers of QTLs are orders of magnitude larger than what reported in previous QTL mapping studies, 29,[44][45][46][47][48][49][50][51][52][53] which is most likely due to the significance threshold used in QTL mapping studies but omitted in genomic prediction. Low p estimates, and SNPs of large effects (Figure 2), were generally observed for traits with moderate to high accuracies. For traits where the largest SNP effects were small, the size of the training population could have been not large enough to properly estimate SNP effects. The realized selection differential, in the large family AF1_Da66, was significant for four traits (attractiveness, fruit size, over-colour and per cent over-colour). However, most individuals with extreme phenotypic scores for these traits were in the middle of the distributions of GBV, and thus would not have been identified for selection or culling purposes. This shows that the tails of the distributions for these traits were not well predicted, even if accuracies were high. Note that phenotypes were taken as indicators for the individuals' true genotypic values and these phenotypes may have been imprecise for (some) individuals. In addition, the presence of nonadditive genetic effects was ignored in the (additive) prediction model. Further exploration of genomic prediction models including dominance and epistasis would be appropriate as fruit tree crops are often vegetative propagated. 54 Marker density and linkage disequilibrium in training population. The main hypothesis of genomic selection is that all QTLs will be in LD with at least one marker. 55 The marker density in this study (six markers/cM) may be too low to have markers in strong/complete LD with each QTL and consequently the effect for such QTL is diffused over multiple SNPs, thereby increasing the earlier mentioned estimates of p for various traits. The diffusion of QTL effect over multiple (bi-allelic) SNPs may also occur when the QTL is multiallelic. 56 On the other hand, long stretches of LD might be present in the training population that comprised 20 FS families with moderate to large sizes and many recent common ancestors. The number of recombination events was consequently much lower compared to a population of unrelated individuals. The average r 2 between the adjacent markers was 0.3, and the average r 2 between markers separated by 0.2 cM, 2 cM (around 1 Mb) and 20 cM was 0.26, 0.17 and 0.045, respectively ( Supplementary Fig. S5), which were almost identical to those reported by Kumar et al. 23 Optimization of experimental setup. Using deterministic approaches and simplifying assumptions, several formulae have been proposed to predict the accuracy of genomic selection prior to any experiment. [57][58][59] The reliable estimation of the ''number of effective segments in the genome'' as a function of genome size and effective population size was recently questioned. 60 Notwithstanding, all formulae consistently identified heritability as a key factor affecting accuracy of genome-wide predictions, and this was confirmed by our results (Figure 3). The heritability in these formulae pertains to the additive genetic part of the precision of phenotypic data, and this narrow-sense heritability can be very high (o0.95) when data are obtained from progeny testing. 60 Likewise, the heritability of traits in apple and most fruit trees can be increased by averaging phenotypes from clonal replications or from multiple years when trees are not clonally replicated (the latter ignoring permanent environment effects). In all formulae to predict the accuracy of genomic selection, the size of the training population and heritability are mostly used together in a product. Consequently, when establishing a training population, economic parameters, such as costs of plantation, maintenance and phenotyping, must be considered to optimise the size of the training population and the number of replications that affect heritability and eventually maximize accuracy. Another way of raising heritability of traits could be the use of more objective assessment methods instead of visual scoring, for example using digital imaging for traits pertaining to fruit external appearance. Phenotypic distributions. All traits were measured on an ordinal 1 to 5 scale but treated as continuous variables in our analysis. As the phenotypic data used for the training population were averaged over multiple years and also adjusted for year and site effects, we could consider them as continuous variables and we verified that the distributions of the residual terms in the training population were normal for all traits except pre-harvest dropping and fruit cracking ( Supplementary Fig. S3). A more general approach for prediction is the use of an ordinal probit or threshold model 22 that includes fixed effects (e.g. year and location effects and their interaction) influencing the raw phenotypic data. The threshold model holds a continuous latent variable underlying the observed ordinal scores, and this latent variable is described with fixed effects and genetic marker effects. In our case, however, fitting such models for estimation of these fixed effects was not possible because the application FS families were phenotyped in locations and years that were different from those of the training population. Montesinos-Ló pez et al. 61 reported that ordinality of the phenotypic data is not problematic when the number of classes of an ordinal trait is large, i.e. not less than five, and the data approximated a normal distribution. Wang et al. 62 extended the BayesCp method to fit a threshold model for ordinal traits and reported very similar accuracies for the normal and threshold models for simulated traits with four or eight classes and an approximately normal distribution. The threshold model did yield superior accuracies for traits with four classes and highly asymmetric distributions. 63 In our study, several traits, i.e. pre-harvest dropping, fruit cracking and per cent of russet in application family AF5_33Br, showed a very limited phenotypic variation with very skewed distributions (Figure 1), but even for these traits, distribution of genotypic BLUP in the training population was moderately asymmetric. Such asymmetric phenotypic distributions are frequently observed for these traits (Laurens, personal communication). This may be due to experimental conditions that do not favour expression of the defects to evaluate. These distributions gave rise to the very low accuracies obtained for fruit cracking (from 20.09 to 0.13, Table 1), for per cent of russet in AF5_33Br family (accuracy 20.06) or for preharvest dropping (accuracies between 20.06 and 0.02). Fruit cracking also had a very low heritability (0.03, Figure 3 Figure 2), and a short range of relative SNP effects, extending to less than 0.0034, all contributing to very low accuracies. To increase accuracy for this trait, one could consider a presence/absence classification of the defect and fit a binomial model as shown for root vigour in sugar beet by Biscarini et al. 65 However, this approach ignores the intensity of the defect, when present. For binomial traits, Wang et al. 62 showed that the accuracies obtained with the threshold BayesCp method decreased when heritability and/or incidence were lower. Consequently, the low incidence, and heritability, of fruit cracking would probably yield low accuracies when applying the threshold version of the BayesCp method. Accuracies of genomic prediction for fruit cropping were also very low, except in AF4_31Ga (Table 1), while phenotypic variance was large for this trait and phenotypic distributions were almost symmetric in all application FS families, except in AF2_Pi63. Fruit cropping is often affected by biennial bearing and breeders will usually consider multiple years of phenotyping. Consequently, additional phenotypic data on the application population are needed before drawing reliable conclusions on genomic selection for fruit cropping. Genotype by environment interaction. The application FS families and training population were phenotyped in different locations and years. Putative genotype by environment interactions due to differences in years and locations, were not considered and might have affected the prediction accuracy. Only parents were planted in the same plots as the application families, so there was an insufficient number of reference genotypes available to estimate genotype by environment interaction. However, as the training population was evaluated over three years and several locations, the SNP effects estimated to build the genomic prediction model reflect mean effects over years and locations, which would make predictions more robust to genotype 3 environment interaction. Additional phenotyping of the application populations is in progress, and using the average over multiple years may yield more stable estimates of the phenotypic performance (as a proxy for true breeding values), which could further increase the accuracy of the predicted breeding values. To study genotype by environment interactions in the context of genomic selection in perennial fruit crops, a collaborative initiative is underway to establish replicates of large reference populations in apple and peach at multiple sites throughout Europe. Imputation of marker genotypes. Imputation of marker genotypes was seen as a tool to make genomic selection cost effective 66 by genotyping selection candidates with a panel of evenly spaced lowdensity SNPs instead of the high-density panel used in the training population. Results from a simulation study revealed that the loss of accuracy using a low-density panel with markers every 10 cM was limited in a dairy-cattle like population. 66 Likewise, the application of three levels of reduced density SNP panels (approximately one marker every 5, 0.7 and 0.35 cM) in pigs showed that imputation accuracy would be higher than 0.9 provided that both parents of individuals genotyped at low density are genotyped at high density. 67 In our study, the mean interval length between the 364 usable markers was 3.7 cM with 29 intervals being larger than 10 cM and one interval exceeding 20 cM (Supplementary Fig. S2). For these regions the accuracy of imputation might have been reduced. As only 3.7% to 7.0% of the markers with the highest effects were actually genotyped in the application families, reduced imputation accuracy would probably result in a loss of prediction accuracy. Putative confounding factors hampered the assessment of the impact of imputation on prediction accuracy. The accuracy of imputation will be assessed in a forthcoming study. Comparison to previous studies The only previous study concerning genomic selection on apple 23 indicated higher accuracies, ranging between 0.67 and 0.89, for six fruit quality traits. Several factors may explain the discrepancy between the results of our study and those of Kumar et al. 23 Kumar et al. 23 estimated accuracies by cross-validation within a population of seven FS families obtained in a factorial mating design with four female and two male parents, and sampling for Accuracy and responses of genomic selection in apple H Muranty et al cross-validation was performed without taking into account family structure so that each individual in the validation set had full-sibs in the training set. Such a within FS family prediction is expected to result in high accuracies. 41 In the present study, four application FS families shared one or both parents with some of the training FS families. In the work of Kumar et al., 23 the genotypic data were obtained with the 8K SNP array 31 for all individuals under study, so imputation was used only for imputing sporadic missing data and not for a high amount of genotypic data as done in the present study. Based on the imputed datasets, the marker density was lower in Kumar et al., 23 however, the levels of LD were similar to those observed in the present study ( Supplementary Fig. S5). In the study of Kumar et al., 23 the narrow-sense heritability of the traits studied varied between 0.19 and 0.60, thus there was no trait with very low heritability like fruit-cracking in the present study. Finally, in the work of Kumar et al., 23 the phenotypic data in the validation sets used to estimate accuracy of genomic prediction were obtained in the same orchard and with a common adjustment as phenotypic data in the training sets, thus avoiding potential genotype 3 environment interaction that would reduce accuracies. Optimization of apple breeding programmes Genetic bases of apple breeding programmes. The training population represented the major founders of European and worldwide breeding programmes, in order of representation: 'Golden Delicious', 'Delicious', 'McIntosh', F2-26829-2-2, 'Jonathan', 'Cox' and some representation of 'Common Antonovka'. 68 Indeed, in terms of accuracy of genomic prediction or realized selection differential, no major differences were present between the five application FS families derived from breeding programmes in France (AF1_Da66, AF2_Pi63) and Belgium (AF3_31Fu, AF4_31Ga, AF5_33Br). The part of breeding programmes devoted to introgression of new resistance genes, 69 as well as families descending from cultivar 'Braeburn' (that was absent in HiDRAS), could require a more diverse training population. However, as the current training population contained the major founders of the European breeding programmes, genomic prediction seems applicable for many crosses and juvenile FS families in ongoing breeding programmes, allowing selection prior to field-phenotyping. Finally, the static training population can evolve into a dynamic, larger and more diverse representation by adding genotyped individuals with phenotypes as arise from these breeding programmes. Organization of breeding programmes. Breeding programmes in perennial fruit crops may encompass different breeding themes, such as disease resistance, novel flavour and flesh colour, 2 each requiring a separate elite population for each theme. Deploying genomic selection for each breeding theme separately would yield highest accuracy of selection as this maximizes the coincidence of key chromosome segments in training and application populations. However, this challenges the management of inbreeding due to the lower effective population size that arises from a highly related elite population. Simulation experiments on genomic selection indicated lower rates of inbreeding per generation. 70 However, these lower rates per generation may be counteracted by the reduction in generation interval, such that the net outcome of genomic selection schemes will be an increase in inbreeding per year. Relative to trait-targeted training population, the use of a large diverse training population could reduce inbreeding, probably at the expense of prediction accuracy. Note that the high-density genotyping of breeding candidates presents an excellent opportunity to monitor genetic diversity at the genome level and to control inbreeding. The relatively higher efficiency of genomic selection compared to conventional selection in terms of genetic gain per year was estimated considering a reduction of breeding cycle length from seven years in conventional selection to four years when using genomic selection. 23 Apple breeders could work on further reducing generation interval to gain the full advantage of the early availability of GBV by rapid cycling. 3 Finally, breeders could dramatically increase the number of progeny per cross and apply a higher selection intensity among juveniles based on GBV obtained from SNP profiles. The latter will incur higher costs for genotyping, so novel cost-efficient genotyping strategies, such as Genotyping by Sequencing, must be considered. More studies are needed to optimize allocation of resources for phenotyping and genotyping to maximize prediction power for Mendelian, ordinal and complex traits in fruit crops. CONCLUSION This paper reports a substantial range in the accuracy of genomic prediction and realized selection responses for ordinal culling traits in apple. Lower accuracy and response were observed for traits with reduced or skewed phenotypic distributions and with low heritabilities. For symmetrically distributed traits with moderate or high heritability, the genomic predictions could substitute expensive field phenotyping to cull the poorest individuals with moderate intensity of selection. Expectation of correlation between phenotypic scores (y) and GBV The phenotypic scores can be modelled as y~XbzZuze P where y is a vector of phenotypic scores for a given trait, b is the vector of fixed effects (e.g. grand mean), X is the incidence matrix linking observations to fixed effects, Z is the incidence matrix linking individuals to their polygenic additive effect (5 true breeding value) u which has a Normal distribution with V ar(u)~As 2 a , where A is the pedigree-based relationship matrix and s 2 a is the additive genetic variance and e P is a vector of residual terms identically and independently distributed with a variance s 2 e P. GBV (ĝ ) can be considered as an estimation of u, and thus we havê g~uze g where e g is a vector of residual terms with variance s 2 e G . As the GBVĝ are predictions derived from a model fitted to data from the training population while the phenotypic scores pertain to the application population, the residuals terms e P and e g are independent. It should be noted also that the usual quantity of interest is the correlation between the GBV and the polygenic additive effect/true breeding value which is corr(ĝ ,u)~c ov(uze g ,u) ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi var(uze g )var(u) p~s

v3-fos

2016-05-16T04:04:44.519Z

2015-06-05T00:00:00.000Z

10699609

s2

A Major Gene for Bovine Ovulation Rate Half-sib daughters sired by a bull believed to be a carrier of a major gene for high ovulation rate were evaluated for ovulation rate and genotyped in an effort to both test the hypothesis of segregation of a major gene and to map the gene’s location. A total of 131 daughters were produced over four consecutive years at a University of Wisconsin-Madison research farm. All were evaluated for ovulation rate over an average of four estrous cycles using transrectal ultrasonography. The sire and all daughters were genotyped using a 3K SNP chip and the genotype and phenotype data were used in a linkage analysis. Subsequently, daughters recombinant within the QTL region and the sire were genotyped successively with 50K and 777K SNP chips to refine the location of the causative polymorphism. Positional candidate genes within the fine-mapped region were examined for polymorphism by Sanger sequencing of PCR amplicons encompassing coding and 5’ and 3’ flanking regions of the genes. Sire DNA was used as template in the PCR reactions. Strong evidence of a major gene for ovulation rate was observed (p<1x10-28) with the gene localized to bovine chromosome 10. Fine-mapping subsequently reduced the location to a 1.2 Mb region between 13.6 and 14.8 Mb on chromosome 10. The location identified does not correspond to that for any previously identified major gene for ovulation rate. This region contains three candidate genes, SMAD3, SMAD6 and IQCH. While candidate gene screening failed to identify the causative polymorphism, three polymorphisms were identified that can be used as a haplotype to track inheritance of the high ovulation rate allele in descendants of the carrier sire. Introduction Examples of major genes for ovulation rate and litter size in sheep are well known. Currently six genes have been either mapped or identified in sheep that cause profound differences in phenotype including BMPR1B (Booroola) [1], BMP15 (Inverdale) [2], GDF9 [3], B4GALNT2 [4], Fec X2W [5] and Fec D [6]. Characterization of the underlying genes and polymorphisms for several of these [3,[7][8][9][10][11] has led to the determination of the basis for high prolificacy phenotypes in some sheep breeds and has created a new set of candidate genes and gene networks for consideration in examination of prolificacy and ovarian pathology phenotypes in both livestock and humans. Regarding the use of these loci as candidate genes for variation in prolificacy, no less than 29 highly prolific breeds of sheep (in addition to those in which the major genes were originally discovered) and one goat breed have been examined for evidence of polymorphism at these loci [12][13][14][15][16][17][18][19][20][21][22]. In at least thirteen cases, polymorphisms contributing to the high prolificacy phenotype have been identified. Application of these candidate genes to analysis of prolificacy in humans has been more limited [23][24][25], but in two cases evidence was discovered for association of GDF9 mutations with familial dizygotic twinning. A more common focus in humans has been the consideration of these loci as potential candidate genes for ovarian pathologies [26][27][28][29][30][31][32][33][34][35][36][37][38]. In livestock, understanding the genetic basis for high prolificacy is valuable for animal genetic improvement and management programs and provides basic knowledge that may facilitate modification of fertility and prolificacy in the future. The current study examines evidence for segregation of a major gene for ovulation rate in a previously described family of cattle whose matriarch had an exceptional record of prolificacy, having produced three sets of triplets [39]. We hypothesize that this exceptional phenotype is due to the effects of a single locus affecting ovulation rate. Gene mapping studies are reported herein that both support this hypothesis and provide localization of the gene to a genomic region of 1.2 Mb on bovine chromosome 10 (BTA10). Materials and Methods The University of Wisconsin-Madison College of Agricultural and Life Sciences Animal Care and Use Committee approved this research. Animal Resources A son (Trio) of a highly prolific cow (Treble), who had produced three sets of triplets during her lifetime [39], was used by artificial insemination to produce 131 daughters from 2008-2011 (33, 55, 28 and 15 in years 2008-2011, respectively) at a University of Wisconsin-Madison research farm. Trio was born in 1996 as part of Treble's second set of triplets (triplet set consisting of Trio and two sisters); Trio's specific breed composition is unknown though his ancestry likely includes Hereford, Holstein, Angus and Jersey breeds. Trio had himself sired daughters that produced twin and triplet births, providing strong prior evidence of transmission of a genetic factor or factors contributing to high prolificacy. Dams were of mixed breed composition (primarily Angus, Hereford and Holstein-Friesian) with some dams being daughters or granddaughters of sires from the USDA Meat Animal Research Center (USMARC) twinning selection study. Twinning rate among dams at the outset of the study was 5%, so USMARC twinner genetics made only a modest contribution to increased ovulation rate in the Trio daughters. Trio daughters were evaluated for ovulation rate over an average of four estrous cycles from 12-15 months of age by trans-rectal ultrasonography. Estrus was synchronized at initiation of the ovulation rate evaluation by use of a progesterone pessary (eazi-breed CIDR, Zoetis Inc., Florham Park, NJ) for seven days with administration of prostaglandin F2α at the time of CIDR removal. Animals were ultrasonographically scanned at 10-11 day intervals using either an Easi-Scan ultrasound machine with 7.5 MHz probe or an Ibex-ProLite with 6.5 MHz probe. Ovulation rate was determined by counting corpora lutea (CL) during mid-luteal phase of the estrous cycle. Genotyping for Genome Scan and Fine-Mapping Trio and all daughters evaluated for ovulation rate were genotyped with the Illumina (San Diego, CA) Bovine 3K SNP chip to generate genotypes for a within half-sib family linkage analysis. For DNA, a skin biopsy (ear punch) was obtained at birth or blood was drawn from the coccygeal vein from older animals, without anesthesia. DNA was extracted using a standard proteolytic digestion, organic extraction procedure. Subsequently, Trio and three daughters recombinant within the quantitative trait locus (QTL) peak region, along with two daughters each inheriting alternative sire haplotypes across the region, were genotyped with the Illumina Bovine SNP50 (50K) SNP chip to identify marker brackets containing recombination breakpoints and to identify which animals had recombination breakpoints most narrowly bounding a positional candidate gene region. Subsequently, Trio, the two daughters whose recombination breakpoints most narrowly bounded the QTL region, their dams and two Trio daughters each non-recombinant for alternative Trio haplotypes were genotyped with the Illumina Bovi-neHD SNP (777K) chip to further narrow the recombination breakpoints. Samples and SNPs with call rates below 95% were excluded from analyses. Statistical Analyses Paternally inherited haplotypes across autosomal chromosomes were deduced using a Fortran program as described previously [40]. Linkage analysis was conducted by testing association of paternal haplotype for consecutive marker brackets with mean ovulation rate (animal means over 3-5 estrous cycles) using a linear model analysis implemented in R (R project). The model included effects of year of ovulation rate evaluation as a categorical variable and paternally inherited haplotype as a covariate. Results were plotted as minus log 10 of the p-value versus marker bracket location. Haplotypes for the 50K and 777K data within the QTL peak region were deduced by manual inspection of the genotype data. Positional Candidate Gene Analysis Three positional candidate genes (SMAD3, SMAD6 and IQCH) were screened for polymorphisms within their coding regions and 5' and 3' flanking regions (~1 kb) by generation of overlapping PCR amplicons and subsequent Sanger sequencing. Trio DNA was used as template for generation of the PCR amplicons. Sequence traces were visually inspected for putative polymorphisms using Codon Code Aligner software (CodonCode Corporation, Centerville, MA). Putative polymorphisms were validated and linkage phase with the high ovulation rate QTL allele determined by Sanger sequencing of PCR amplicons derived using pooled template DNA from Trio daughters (n = 10) inheriting either high or low ovulation rate Trio haplotypes in the QTL region. Validated polymorphisms were evaluated initially for allele frequency in the Holstein and Angus breeds and also evaluated for functional relevance such as a non-synonymous change in a coding region, alteration of a consensus splice site sequence or alteration of a known regulatory element. Breed allele frequency estimation in the preliminary evaluation was based on Sanger sequencing of PCR amplicons derived from pooled template DNA (n = 20 animals per breed). Relative peak heights from the sequence traces for the alternative alleles were used to estimate allele frequency [41,42]. Given the typical infrequency of twin and particularly triplet birth within common cattle breeds, only polymorphisms for which the minor allele was in association with the high ovulation QTL allele and had a preliminary estimate of allele frequency <0.20 were considered as potentially useful markers for tracking inheritance of the high ovulation QTL allele. Polymorphisms passing these criteria were more precisely evaluated for allele frequency using individuals from the Angus (n = 40), Hereford (n = 23), Holstein (n = 53), Jersey (n = 48) and Simmental (n = 24) breeds by genotyping with PCR-RFLP (Table 1). All PCR reactions were performed with a touchdown protocol that had an initial annealing temperature of 63°C which was reduced by 0.5°C per cycle until an annealing temperature of 58°C was obtained. GoTaq DNA polymerase (Promega Inc., Madison, WI) was used in all reactions per the manufacturer's recommendations. Primer design and expected restriction fragment sizes are indicated in Table 1. Fragment size separation was accomplished by electrophoresis using 4% agarose (1% regular and 3% sieving agarose) gels. Haplotypes were predicted from genotype data using fastPHASE [43] and linkage disequilibrium (LD) was calculated using Haploview [44]. Allele and haplotype frequencies were estimated by counting. Results and Discussion Average ovulation rate across all heifers was 1.67 CL per cycle with a range of one to 3.5 CL per cycle for animal means. Considering individual estrous cycles, the range of observations was from one to five CL per cycle. The distribution of ovulation rate means was not unambiguously bi-modal (Fig 1). Linkage analysis provided strong evidence (p<1x10 -28 ) for segregation of a major gene for ovulation rate (Fig 2). Subsequent analysis of 50K SNP data for recombinant Trio daughters narrowed the region to between 13.2 and 15.1 Mb on BTA10 and identified the two daughters whose recombination breakpoints most narrowly bounded the candidate gene region. Analysis of HD genotype data for these individuals further narrowed the location of the causative polymorphism to a region between 13.6 and 14.8 Mb on BTA10 (Fig 3) which contains eight characterized genes and six uncharacterized loci. The most likely candidate genes within this region are SMAD family member 3 (SMAD3), SMAD family member 6 (SMAD6) and IQ motif containing H (IQCH), at approximately 13.7 Mb, 13.9 Mb and 14.2 Mb, respectively. Analysis of coding and 5' and 3' flanking regions of candidate genes within this region revealed a total of 30 polymorphisms (Table 2), but none were rare and additionally none were alterations of coding or regulatory sequences. However, three polymorphisms with minor alleles in association with the high ovulation rate allele (Table 3) comprised a haplotyping system with a relatively rare haplotype in association with the high ovulation rate allele ( Table 4). The haplotype associated with increase ovulation rate has the insertion allele at locus 13663941, the A allele at locus 14263362 and the A allele at locus 14270483. Linkage disequilibrium between these three loci was variable across breed (Table 5) with a tendency, particularly in the beef breeds, for lower LD between the first and second and first and third loci, and higher LD between the second and third loci, in keeping with the close proximity of the latter two. This relatively infrequent haplotype has utility for tracking inheritance of the high ovulation rate allele in Trio descendants. Frequency of this haplotype ranged from zero to 0.064 within breed (Table 4). Ovulation rate for daughters inheriting alternative haplotypes from Trio were 2.19 ± 0.57 ova for carriers (n = 68) of the high allele versus 1.11 ± 0.22 ova for non-carriers (n = 63). Classification was based on BTA10 haplotypes for non-recombinants within the QTL peak region 1 Haplotypes denoted as "ss1714766385 allele_ ss1714766398 allele _ ss1714766400 allele". "+" denotes the allelic form containing an insertion of TATG, as indicated in Table 2. 2 The "+_A_A" haplotype is associated with increased ovulation rate within the Trio family. doi:10.1371/journal.pone.0129025.t004 and the above-described three polymorphism haplotyping system for daughters recombinant within the QTL peak region. Strong evidence is presented for segregation of a single gene for high ovulation rate within the Treble/Trio extended family. However, the causative polymorphism and gene remain uncertain. Three positional candidate genes residing within the positional candidate gene region were examined for polymorphisms within the coding regions and proximal 5' and 3' flanking regions, but no likely causative polymorphism was identified. This suggests that the causative polymorphism may be within a regulatory sequence, and more distant from the gene than the 1 kb flanking regions considered in the candidate gene screening. Alternatively, the causative polymorphism may be associated with a gene other than the three candidates considered. Initial efforts (unpublished) at a more comprehensive screening of the positional candidate gene region were dissatisfying owing both to the inability to capture and sequence the entire positional candidate gene region and to the presence of duplications within the positional candidate gene region which complicate the identification of true polymorphisms. To overcome these issues individuals homozygous for the high ovulation haplotype are being created through carrier x carrier matings to serve as a source of DNA for a de novo sequence assembly which is expected to provide a comprehensive screening of the candidate region. The genomic region harboring the high ovulation rate polymorphism does not correspond to the location that should be the homologous location of any major genes for ovulation rate or litter size previously identified in sheep (Fig 2). Likewise, while QTL for twinning rate [45] or ovulation rate [46] in cattle have been mapped to the same chromosome, and litter size QTL in mice have been mapped to a chromosome with partial correspondence to the same gene region [47], in neither case was the gene location included within the QTL confidence interval; further, for the mouse the QTL region corresponded primarily to a different bovine chromosome. The closest correspondence in location is for an association with litter size in pigs (number born, number born alive) in which the QTL location at approximately 173.6 Mb on swine chromosome 1 corresponds to the location of FEM1B, mentioned above [48]. However, the failure to also identify an ovulation rate QTL at the corresponding genomic location within the same swine population suggests the litter size QTL may be attributable to something other than an ovulation rate mechanism [49] while the gene mapped here clearly affects ovulation rate. The fact that the gene mapped here does not correspond to any previously identified major gene for ovulation rate does not necessarily imply that the gene is unrelated to a previously identified major gene. Specifically, two of the positional candidate genes considered, SMAD3 and SMAD6, are part of the TGFß signaling pathway which is relevant to one of the known major genes, GDF9. Given the intermediary role of the Smad-3 protein in the high ovulation rate effects of GDF9 variants in sheep, SMAD3 is a strong positional candidate gene. The SMAD6 gene product, Smad-6, is an inhibitor in this signaling pathway that works in an opposing manner to Smad-2 and Smad-3 and is therefore also a strong candidate gene. Two other loci which are unrelated to the TGFß system are either within the candidate gene region or in very close proximity and merit consideration. IQCH, located roughly in the middle of the positional candidate region, has been linked with age at menarche in human females in a whole genome association study meta-analysis [50] and was considered here in screening for polymorphisms. A second locus, FEM1B, has been associated with polycystic ovary syndrome in humans [51,52]. Its location just distal (300 kb) of the positional candidate gene region excluded it from the polymorphism screening effort; however, given the close proximity of FEM1B to the region, it is possible that a regulatory mutation within the candidate gene region could impact its expression. In this regard, reference to a positional candidate gene region is probably a misnomer, and reference should instead be to a positional candidate polymorphism region. In subsequent work, the ovulation rate associated with the high allele has been higher than reported here with an average of four ova for carriers versus one for non-carriers (unpublished). Multiple causes may contribute to the lesser difference between carrier and non-carriers reported here and include possible increase in ovulation rate with age, as has been observed previously for polygenic ovulation rate [53], and possible inaccuracy in ultrasonic evaluation (BWK) leading to understatement of true ovulation rate for carrier females. Corpora lutea diameter in carrier females is significantly smaller than in non-carriers which may have led to some errors in corpora lutea count in the initial group of females (average count rose from 1.51 ± 0.38 to 1.88 ± 0.81 CL from the first to third years of evaluation). One might expect that the presence of MARC twinner genetics within the herd would contribute to an overstatement of ovulation rate, however that contribution would be equivalent for both carrier and non-carrier females, apart from interaction between loci, and MARC twinner genetics comprised a small part of the genetic make-up of the herd as evidenced by the modest twinning rate within the herd in the year preceding the onset of this study (~5%). Anecdotal evidence of the understatement of ovulation rate comes also from an abortion rate among carrier females in the UW herd in excess of 50% with the observable late term abortions typically being triplet and quadruplet pregnancies. For practical application of this allele it will be necessary to modulate ovulation rate. Nutritional, hormonal, or physical approaches may be ways to achieve this. The increase of ovulation rate in response to increased energy and/or protein in the diet of swine and sheep is well known [54] and the opposite treatment might reduce ovulation rate for this allele. Regarding hormonal treatment, research with ewes possessing the BMPR1B allele has demonstrated the ability to reduce ovulation rate through administration of estradiol [55], presumably due to negative feedback effects on follicle stimulating hormone release from the pituitary. Finally, selective ablation of follicles by ultrasound-guided follicular aspiration would be a means of specifically reducing ovulation rate to two ova, preferentially bi-lateral ovulation, maximizing chances for twin pregnancy [56]. Many unanswered questions, besides what are the polymorphism and gene responsible, are raised by this work including what phenotype will be associated with a homozygous genotype, what are the effects of this mutation on male fertility, are there effects of the mutation on reproductive longevity, what is the physiological mechanism for this mutation's effect on ovulation rate, and are there effects of this mutation on non-reproductive characteristics? Some of the major genes for ovulation rate in sheep (BMP15, GDF9) are known to cause infertility in the homozygous genotype [3,7], for some alleles, while others (BMPR1B) lead to even higher ovulation rate in the homozygote versus the carrier [57]. Regarding male fertility and reproductive longevity, there are no reports from previous work with major genes for ovulation rate in sheep that suggest effects on these characteristics. Finally, global gene expression analysis within relevant tissue or cell types, such as granulosa cells, should provide both a test of hypotheses concerning differences in expression of positional candidate genes as well as a picture of downstream effects of the mutation on expression of other genes, helping determine how this mutation ultimately causes alteration of ovulation rate. Regardless of whether this polymorphism can be practically applied or not, identification of the gene and causative polymorphism will advance understanding of the genetic basis for variation in ovulation rate. This information will both deepen understanding of the mechanism underlying variation in ovulation rate and provide a new candidate gene to potentially explain genetic variants for ovulation rate, multiple births and ovarian pathologies. Supporting Information S1 File. Dataset S1. Phenotype data used for linkage analysis. File includes animal ID, average ovulation rate and birth year. (TXT) S2 File. Dataset S2. Genotype data used for linkage analysis. File includes animal ID, SNP ID and location, and numerically coded SNP alleles. (ZIP)

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Cloning and characterization of the pepper CaPAO gene for defense responses to salt-induced leaf senescence Background Pheophorbide a oxygenase (PAO) is an important enzyme in the chlorophyll catabolism pathway and is involved in leaf senescence. It opens the porphyrin macrocycle of pheophorbide a and finally forms the primary fluorescent chlorophyll catabolite. Previous studies have demonstrated the function of PAO during cell death. However, the characterizaton of PAO during leaf senescence induced by environmental factors is not well understood. Methods Homology-based cloning and RACE techniques were used to obtain the full-length cDNA of the CaPAO gene. CaPAO expression was determined by quantitative real-time PCR. Function of CaPAO gene were studied using virus-induced gene silencing and transgenic techniques with tobacco plants (Nicotiana tabacum). Results A novel PAO gene CaPAO was isolated from pepper (Capsicum annuum L.). The full-length CaPAO cDNA is comprised of 1838 bp, containing an open reading frame of 1614 bp, and encodes a 537 amino acid protein. This deduced protein belongs to the Rieske-type iron-sulfur superfamily, containing a conserved Rieske cluster. CaPAO expression, as determined by quantitative real-time PCR, was higher in leaves than roots, stems and flowers. It was upregulated by abscisic acid, methyl jasmonate and salicylic acid. Moreover, CaPAO was significantly induced by high salinity and osmotic stress treatments and also was regulated by Phytophthora capsici. The virus-induced gene silencing technique was used to silence the CaPAO gene in pepper plants. After 3 days of high salt treatment, the chlorophyll breakdown of CaPAO-silenced pepper plants was retarded. RD29A promoter-inducible expression vector was constructed and transferred into tobacco plant. After 7 days of salt treatment, the leaves of transgenic plants were severely turned into yellow, the lower leaves showed necrotic symptom and chlorophyll content was significantly lower than that in the control plants. Conclusions The expression of CaPAO gene was induced in natural senescence and various stresses. The CaPAO gene may be related to defense responses to various stresses and play an important role in salt-induced leaf senescence. Background Leaf senescence is the final stage of leaf development, ultimately leading to the death of the entire leaf. Although governed by the developmental age, it also can be stimulated by diverse environmental factors, including plant hormones, drought, salinity, extreme temperature, darkness, wounding and pathogenic infection [1,2]. Premature leaf senescence can eventually affect the yield of plants under adverse environmental conditions. Therefore, studying leaf senescence will not only strengthen our comprehension of a basic biological process, it also may provide methods to delay plant aging in order to improve agricultural traits of vegetable crops. Pepper (Capsicum annuum L.) is an important vegetable crop that is extensive cultivated worldwide. In recent years, premature senescence of pepper plants caused by various environmental stresses has become a universal phenomenon and considered an important field of research. Loss of green color, induced by degradation of chlorophyll, is the most visible symptom of leaf senescence. Pheophorbide a oxygenase (PAO) has been regarded as a crucial enzyme in chlorophyll degradation [3,4]. It oxygenolytically cleaves the porphyrin macrocycle of pheophorbide (pheide) a and finally forms the primary fluorescent chlorophyll catabolite (FCC). The PAO gene was initially obtained from maize (designated ZmLls1) and then discovered in other higher plants, such as rice, wheat, tomato, soybean and canola [5][6][7][8][9]. Previous studies showed that the expression of PAO is induced by natural senescence and environmental stresses in plants [10][11][12]. In Arabidopsis, AtPAO is encoded by the accelerated cell death 1 (ACD1) gene and is homologous to lethal leaf spot 1 (LLS1) of maize. It belongs to a small family of Rieske-type iron-sulfur oxygenases [13]. The absence of ACD1 has been shown to result in the accumulation of PAO and light-independent cell death when senescence is induced in permanent darkness [14,15]. Tobacco (Nicotiana tabacum) is one of the most important model plants for transgenic research. In previous studies, many new genes from other plants have been transferred into tobacco for further research on their functions [16,17]. The RD29A promoter from Arabidopsis thaliana is a stress-inducible promoter. This promoter contains two dehydration-responsive elements (DREs), which are involved in response to salt, dehydration and low temperature [18]. Using the RD29A promoter instead of the constitutive 35S CaMV promoter for certain genes overexpression minimizes the negative effects on plant growth, which have been widely used in genetic transformation [16]. In recent years, the research on PAO focused on the functional analysis for inhibiting cell death [11,13,14]. However, little is known about CaPAO regulatory role after induction expression of inducible-promoter in pepper. This study was conducted to clone this gene from the pepper plant and analyze its molecular characteristics. Patterns of CaPAO gene expression in specific tissues and in response to various stresses were analyzed by quantitative real-time PCR. Furthermore, virus-induced gene silencing (VIGS) and transgenic technologies were used to study CaPAO gene function. The results suggest that CaPAO may play an important role during leaf senescence and chlorophyll degradation. Cloning and Sequence Analysis of CaPAO The full-length cDNA designated CaPAO was obtained using in silico cloning and RACE techniques. The transcript consists of 1838 nucleotides, including a 5′-untranslated region (UTR) of 32 bp, an ORF of 1614 bp and a 3′-UTR of 192 bp (GenBank accession number KC176709) (Fig. 1). CaPAO was predicted to encode a 537 amino acid protein with a theoretical molecular weight (MW) of 60.8 kDa and calculated isoelectric point (pI) of 6.89. Structural analysis revealed that CaPAO belongs to a Rieske-type iron-sulfur superfamily, containing a conserved Rieske cluster, a mononuclear iron-binding site and a redox-active CxxC motif in the C-terminal end, which are necessary for oxygen activation (Fig. 1). Subcellular analysis localized CaPAO in the chloroplasts. Further sequence analysis indicated that the deduced CaPAO protein contains a chloroplast transit peptide of 50 amino acid residues with a cleavage site located between R 50 and V 51 , but it does not contain a signal peptide region or transmembrane helix. The deduced CaPAO amino acid sequence showed high homology to other plant PAO sequences via multiple alignments using DNAMAN software (Fig. 1) A phylogenetic tree, constructed using MEGA5.05 software, was used to investigate the evolutionary relationship of the CaPAO amino acid sequence with PAO proteins of other plants. Two groups were formed using the 14 PAO protein sequences from C. annuum L., N. tabacum, S. lycopersicum, R. communis, V. vinifera, B. napus, A. thaliana, Medicago truncatula, Aegilops tauschi, Pisum sativum and Brassica rapa var. parachinensis (Fig. 2). CaPAO clustered in the first group, which included SlLLS1, NtPAO, BoPAO, BrPAO and AtPAO. CaPAO was more closely related to SlLLS1, NtPAO than PAO proteins of other plants. All of the above-mentioned bioinformatic analyses demonstrated that CaPAO should function as a PAO. Tissue-Specific Expression of CaPAO In order to investigate the expression levels of the CaPAO gene in different tissues, total RNA was extracted from the roots, stems, leaves and flowers, and quantitative realtime PCR (qRT-PCR) was performed (Fig. 3a). CaPAO transcripts were detected in all of these tissues and found to be higher in leaves than in other tissues. For different leaf developmental stages, a low level of CaPAO transcript was detected in young and fully mature leaves, but CaPAO expression was increased in senescent leaves (Fig. 3b). Induction of signaling molecules, abiotic and biotic stresses In order to study its function in pepper plants, the expression pattern of CaPAO was first analyzed. B12 cultivar seedlings at the six-leaf stage were treated with various stresses, including phytohormones, salt, osmosis and Phytophthora capsici infection, and analyzed by qRT-PCR. To analyze the response of the CaPAO gene to abiotic stresses, pepper plants were exposed to 400 mM sodium chloride (NaCl) and 400 mM mannitol, and then the abundance of CaPAO transcripts was analyzed by quantitative RT-PCR. As shown in Fig. 4a, the CaPAO expression level in plants treated with 400 mM NaCl began to increase gradually at 4 h and peaked (11.9-fold) at 24 h, compared to the control (0 h). With osmotic treatment, CaPAO was induced quickly in pepper plants (Fig. 4b) with a 3.4-fold increase in expression at 2 h and a stronger 10.7-fold elevation at 12 h. The highest transcript level was detected at 24 h (18.7-fold). These results indicate that the increased abundance of the CaPAO gene transcript may be part of the response to abiotic stresses, including high salinity and osmotic stress. To examine whether stress-related signaling molecules can induce CaPAO expression, three phytohormones were used to treat pepper leaves. As shown in Fig. 4c, the expression levels of CaPAO in leaves sprayed with abscisic acid (ABA), methyl jasmonate (MeJA) and salicylic acid (SA) were elevated to different extents. ABA could induce quickly the expression of the CaPAO gene within the first However, the CaPAO expression peaked by 24 h at a 10.1fold greater level than the control. By contrast, the treatment of SA quickly induced the CaPAO transcript abundance at 2 h to 7.6-fold higher than the control and maintained a relatively steady level from 4 h to 12 h before a sharp downregulation at 24 h. At 48 h, the CaPAO transcript decreased to nearly the same levels among all of the plants treated with the three phytohormones. These results indicated that the CaPAO gene could be induced and upregulated by all three stress-related signaling molecules tested (ABA, MeJA and SA). CaPAO expression was enhanced in pepper plants infected with P. capsici as shown in Fig. 4d. The CaPAO transcriptional level was slightly decreased at 3 h and remained at a steady level from 6 h to 24 h, compared with the mock control. This transcript then increased rapidly and peaked (12.8-fold) at 48 h. Subsequently, the CaPAO expression level sharply downregulated at 72 h (5.3-fold) and decreased to 4.9-fold at 96 h, which was the lowest level after infection relative to the control. These results revealed that CaPAO may be involved in the pepper defense response against pathogens. Silencing efficiency of CaPAO gene The results showed that CaPAO participates in the chlorophyll degradation pathway and is involved in the response to various stresses in pepper plants. To further examine the function of CaPAO in pepper, a tobacco rattle virus (TRV)based VIGS technique was used. Pepper plants inoculated with Agrobacterium for 6-7 weeks were used for the following treatments. An empty vector was applied to plants (TRV2:00) as a negative control. TRV2: CaPDS plants, in the endogenous phytoene desaturase (PDS) gene was silenced to cause photobleaching, were used as positive controls for testing VIGS efficiency. Three weeks after the Agrobacterium inoculation, we found that most of the plants clearly showed symptoms of viral infection. Furthermore, the TRV2: CaPDS plants began to exhibit the photobleached phenotype. These results indicated that VIGS was successfully applied in this experiment. As shown in Fig. 5a, no morphological distinction was observed between the CaPAO-silenced plants (TRV2: CaPAO) and the empty vector treated control plants (TRV2:00) 45 d after inoculation. Simultaneously, CaPAO transcript levels in empty vector control plants (TRV2:00) and CaPAO-silenced plants (TRV2: CaPAO) were examined by quantitative RT-PCR to screen the efficiency of CaPAO gene silencing by VIGS (Fig. 5b). The results showed that the CaPAO transcriptional level was reduced remarkably in CaPAO-silenced plants compared to the empty vector control, which demonstrated that the gene silencing was successful. Silencing of CaPAO delay chlorophyll breakdown under high salt treatment In order to analyse whether the CaPAO response to salt stress, the leaf discs from empty vector control-treated (TRV2:00) and CaPAO-silenced (TRV2: CaPAO) plants were exposed to various concentrations (0, 300, 400 and 500 mM) of NaCl solution with continuous lighting for 3 d. As shown in Fig. 6a, the color of the leaf discs of TRV2:00 plants turned yellow under 300 mM NaCl treament and the leaf discs appeared to be a bleached phenotype under treatment with higher NaCl concentrations (400 and 500 mM). However, the leaf discs of TRV2: CaPAO plants slightly shrinked and their color showed little change. Furthermore, chlorophyll breakdown in TRV2:00 leaves was observed to occur faster than that in TRV2: CaPAO leaves 3 d after treatment with high NaCl concentrations (400 and 500 mM) (Fig. 6b). These results suggested that silencing the CaPAO gene can inhibit chlorophyll breakdown during salt stress-induced leaf senescence in pepper plants. Error bars represent SD for three independent replicates. Asterisks indicate a significant difference (p < 0.05) compared to TRV2:00 leaves lower leaves turning yellow but upper leaves remaining green (Fig. 8b-c). Chlorophyll and Malondialdehyde (MDA) contents of transgenic plants after treatment with salt stress Leaf senescence is associated with chlorophyll breakdown and reactive oxygen species (ROS) accumulation [19,20]. ROS-generated lipid peroxidation (reflected by MDA content) is an inherent feature of senescing cells and a source of ROS [21,22]. To further analyze the effect of CaPAO overexpression on salt-induced leaf senescence in tobacco, chlorophyll and MDA contents were measured after salt treatment for 7 and 14 days, respectively (Fig. 8d-e). Before the salt stress, there were few obvious differences in Error bars represent SD for three biological replicates. Asterisks indicate a significant difference (p < 0.05) compared to wild type leaves chlorophyll and MDA content between WT and transgenic leaves. Chlorophyll content of WT and transgenic leaves decreased by 0.37 and 0.84 mg · g −1 after 7 days, and decreased by 0.44 and 0.20 mg · g −1 after 14 days of salt treatment, respectively. The rate of chlorophyll breakdown in WT plants was higher than that in the transgenic plants. Correspondingly, MDA content gradually increased with elongated treated time. MDA content of WT and transgenic leaves increased by 0.32 and 0.55 mmol · g -1 after 7 days, and increased by 2.36 and 2.91 mmol · g -1 after 14 days of salt treatment, respectively. MDA content in WT plants was significantly lower than that in transgenic plants. These results indicated that overexpression of CaPAO could accelerate the chlorophyll breakdown and lipid peroxidation accumulation of transgenic tobacco plants under salt treatment. All these observations suggested that overexpression of CaPAO could accelerate saltinduced leaf senescence in tobacco. Discussion PAO opens the porphyrin macrocycle of pheophorbide a and finally forms FCCs [3]. Here, we identified the CaPAO gene from pepper. CaPAO contained conserved domains that existed in PAO homologues. Furthermore, CaPAO shared high homology to other PAO proteins, especially SlLLS1 and NtPAO. Bioinformatics analyses demonstrated that CaPAO should function as a PAO. Tissue-specific analysis showed that CaPAO was expressed in all tissues, and the expression level in leaves was higher than other tissues. The findings were similar to the previous results in maize and rice [8,23], it was reported that expression of the OsPAO gene was detected in all tissues and at the highest level in leaves. However, the present results were different than those in A. thaliana [12], in which AtPAO transcript was higher in flowers and siliques than other tissues. These results revealed that PAO is important to growth and development of all tissues, although its function may be distinct in different species. Various biotic and abiotic stresses can affect growth and development of pepper plants, causing chlorophyll breakdown, cell death and finally premature senescence [1,6,24,25]. All of these consequences would impact the yield and quality of crop plants. PAO is an important intermediate in chlorophyll degradation, the expression and activity of which can be affected by various stresses. Wang et al. (2012) reported that relative expression of and PAO in drought-stressed leaves was greatly upregulated in apple [26]. Microarray analysis indicated that upregulation of PAO in response to various stress conditions, coinciding with breakdown of Chlorophyll under these conditions [3,27]. Results of the current study showed that transcript levels of the CaPAO gene were upregulated in pepper plants after treatment with various stresses, including high salinity, osmosis and Phytophthora capsici infection. These results suggested that CaPAO may be involved defense response to salt and osmotic stresses as well as Phytophthora capsici in pepper plants. Previous studies have shown that phytohormone signaling pathways played an important role in mediating developmental processes and environmental responses in plants [2,28]. These hormones could cause the expression of stress-related genes, which in turn affect senescence progress of leaf. Many studies have proved that CaPAO gene expression or activity was regulated by hormones [29][30][31][32]. For instance, ABA can enhance the expression of PAO in rice leaves [29]. Rodoni et al. (1998) suggested that the chlorophyll breakdown related to PAO activity in barley detached leaves, a rapid loss of chlorophyll in conjunction with an increase of PAO activity was occurred after treatment with ABA and MeJA [30]. In the current study, treatment with ABA, MeJA or SA was found to increase the expression level of CaPAO. These findings suggested that the CaPAO gene may be involved in ABA-, JA-and SA-dependent signaling pathways. These results were different from those of a study in wheat reporting that ABA and MeJA enhanced the expression of TaPAO, while SA treatment did not cause significant changes in the level of this gene [6]. SA is the hormone involved in pathogen response and abiotic stress tolerance in pepper plant [22,33]. In perennials, SA may be involved in the regulation of drought-induced leaf senescence as SA accumulation preceded chlorophyll breakdown and nitrogen mobilization [34]. Here, high salinity, osmosis and Phytophthora capsici infection induced CaPAO expression in pepper leaves. It is likely that salt, mannitol and Phytophthora capsici-induced SA accumulation may trigger CaPAO transcripts in pepper plants. The function of the PAO gene has been studied in many plants [8,10,35]. Tang et al. (2011) reported that chlorophyll breakdown was delayed compared to controls in leaves detached from leaves of PAO-silenced rice plants during dark-induced senescence [8]. Moreover, leaves with overexpression of PAO in Arabidopsis had lower chlorophyll content and earlier leaf yellowing than the control 4 d after dark treatment [35]. Leaf senescence was involved in chlorophyll degradation and accumulation of ROS. Drought-induced senescence in the leaves of apple was reflected in chlorophyll loss and an increase in the levels of ROS, with the induction of the PAO gene [26]. In this research, the delay of chlorophyll degradation was detectable in the detached leaves from CaPAO silencing pepper plants 3 days after treatment with salt. Conversely, overexpression of CaPAO, induced by the stress-inducible promoter RD29A, could accelerate the rate of chlorophyll breakdown and lipid peroxidation of the transgenic plants under salt stress. The results of Tang et al. (2013) have shown that overexpressing TaPAO caused an accumulation of RCCs in wheat leaves [36]. RCCs have been proved to be phototoxic and caused cell deach, resulting in senescence [8,37]. All of these results demonstrated that CaCP played crucial role in pepper plant defense response to salt stresses, thus delaying leaf senescence. Conclusions Overall, we conclude that CaPAO plays an important role in senescence and chlorophyll degradation, as well as defense responses to various stresses. CaPAO was induced in natural senescence and various stresses. Silence of CaPAO resulted in a stay-green phenotype in pepper plants, and overexpression of CaPAO accelerated the process of salt-induced leaf senescence. In the future, the transgenic plants about overexpression or knockdown of CaPAO gene in pepper would be used for studying detail function of CaPAO. Plant material The B12 pepper cultivar was used for cloning and characterization of the CaPAO gene in this study. This early maturing variety was selected by a pepper research group in the College of Horticulture, Northwest A&F University, China. The seeds were treated with warm water (55°C) for 20 min and then incubated at 28°C to accelerate germination under dark conditions. The seeds were rinsed twice every day until budding. The germinated seeds were sown in pots containing compost. Seedlings were placed in a growth chamber for a 16-h light/8-h dark cycle at 25°C/21°C, respectively. Cloning and sequence analysis of CaPAO gene To clone the CaPAO gene, total RNA was extracted from green mature leaves using the Trizol (Invitrogen) method, and first-strand cDNA synthesis was performed using Smart RACE cDNA amplification kit (Clontech). The reported nucleotide sequence of Nicotiana tabacum PAO (accession number: EU294211.1) was used as the query probe to retrieve homologous expressed sequence tag (EST) sequences of pepper in GenBank using the BLASTN protocol. Four overlapping pepper ESTs (accession numbers: GD077816, GD078012, GD072064 and GD077857) were chosen to be assembled into a splicing fragment without a complete ORF. To confirm the authenticity of the assembled pepper sequence, the EST-PAOF/EST-PAOR primer pair was used ( Table 1). The design of both primers was based on the splicing sequence. The PCR reaction conditions were as follows: 94°C for 5 min; 35 cycles at 94°C for 30 s, 61°C for 30 s, 72°C for 1.5 min; and finally an extension at 72°C for 10 min. The product was obtained, subcloned into a pMD19-T vector (TaKaRa) and sequenced. To isolate a full-length cDNA of the putative CaPAO gene with complete 5' and 3' regions, the RACE method was used. Gene-specific primers (5′-GSP, 5′-NGSP, 3′-GSP, and 3′-NGSP) were designed according to the partial cDNA sequence ( Table 1). The 5′-GSP (external) and 5′-NGSP (internal) primers were used to isolate 5'-end sequences, while the 3'-GSP (external) and 3'-NGSP (internal) primers were used for isolation of 3'-end sequences. Nested PCR was performed in the 5′RACE and 3′RACE procedures. The amplified PCR products were ligated into the pMD19-T vector and sequenced. Finally, all acquired sequences were assembled into a single sequence with a complete ORF using the Contig Expression software and BLAST online software (http://www.ncbi.nlm.gov/blast). The putative CaPAO cDNA and protein sequences were analyzed by the DNAMAN software 5.2.2 and BLAST online software. Prediction of the subcellular localization of the putative signal peptide, chloroplast transit peptides and its cleavage site were carried out using the CBS prediction server's online program (http://www.cbs.dtu.dk/services/). The pI and MW of the putative protein were analyzed with the pI/MW program (http://www.expasy.org/), and its secondary structure was predicted using the Scratch Protein Table 1). The relative gene expression levels were calculated using the 2 −ΔΔCt comparative threshold method [39]. All samples were performed in triplicate, and each had at least three independent biological replicates. Semi-quantitative RT-PCR was performed for analysis the expression level of CaPAO gene in transgenic tobacco, and the RD29A-F and CaPAO-R primer pair were used. The PCR cycles were 1 min at 95°C followed by 29 cycles at 30 s at 95°C, 30 s at 53°C, and 60 s at 72°C followed by an extension for 10 min at 72°C. The PCR products were separated on 2 % agarose gels stained with ethidium bromide to detect expression degree of CaPAO gene. The NtUBI gene was used as a reference gene. Construction of VIGS Plasmids TRV2-CaPAO and TRV2-CaPDS A CaPAO sequence fragment was amplified using genespecific primers with restriction sites XbaI (forward) and BamHI (reverse) and inserted into the pTRV2 vector to generate TRV2-CaPAO. The primers for VIGS are shown in Table 1. The CaPDS gene (phytoene desaturase from C. annuum, accession number: X68058.1) was used for determining the effectiveness of VIGS in this study, and the TRV2-CaPDS vector was designed by our laboratory. Finally, these plasmids (pTRV1, pTRV2, TRV2-CaPDS and TRV2-CaPAO) were each transformed into the Agrobacterium tumefaciens strain GV3101. Inoculation of VIGS Agrobacterium in pepper plants Preparation of A. tumefaciens harboring pTRV1, pTRV2, TRV2-CaPDS or TRV2-CaPAO vectors were described by Liu et al. [40]. Before inoculation, cultures containing pTRV1 and pTRV2 or their derivatives (TRV2-CaPDS or TRV2-CaPAO) were mixed at a 1:1 ratio. The mixtures of Agrobacterium were inoculated into the fully-expanded cotyledons of the B12 pepper cultivars. Plants were placed in a growth chamber at 18°C and 60 % relative humidity for 2 d. Subsequently, the plants were grown at 23°C under a 16-h light/8-h dark photoperiod cycle and 60 % relative humidity. At 45 days after inoculation, the leaves were used for characterization and analysis of CaPAO. Treatment of CaPAO-silenced plants To analyse salt stress of the gene-silenced plants, the leaf discs from empty vector control-treated (TRV2:00) and CaPAO-silenced (TRV2: CaPAO) plants were floated in various concentrations (0, 300, 400 and 500 mM) of NaCl solution with continuous lighting at 25°C for 3 days. The symptoms of leaf discs were observed during treatment, and the chlorophyll content was determined after 3 d. Tobacco genetic transformation of the CaPAO gene Construction of transgenic vector PVBG2307-RD29A-CaPAO The CaCP sequence with a complete ORF was amplified using a primer pair 2307-CaPAOF/2307-CaPAOR and inserted into PVBG2307 plasmid possessing BamHI and KpnI restriction enzyme sites to yield PVBG2307-CaPAO. Then the RD29A promoter sequence from RD29A-T vector was cloned into PVBG2307-CaPAO vector using digestion of HindIII and XbaI restriction enzymes. PVBG2307-PRD29A-CaPAO vector was constructed successfully. Finally, the plasmid was transformed into the Agrobacterium tumefaciens strain GV3101. Plant transformation and selection of T 2 generation of transgenic tobacco plants Tobacco plants (Nicotiana tabacum cv. Bairihong) were used for all subsequent analyses, the successful transformed plants with leaf disc method were selected and incubated as previously described by Li et al. [41]. The primers RD29A-F and CaPAO-R were used to conform the transgenic tobacco seedlings at genomic DNA level, and a second pair of primers, 2307-CaPAOF and CaPAO-R were used to further confirm the transgenic status of transgenic tobacco plants. Growth conditions of tobacco seedlings and seed selection were followed according to the method of previous research [42]. The T 2 offspring of transgenic tobacco plants were used for all subsequent experiments. Treatment of transgenic tobacco plants Seedlings of WT and one tobacco line (T) at the stage of four true leaves were carefully removed from the pots and their roots washed with tap water prior to solution culture in 1/4 strength Hoagland's solution. After seven to eight true leaves stage, the seedlings were cultured with 1/2 Hoagland's solution supplied with 150 mM NaCl solution. Leaves were harvested at 0, 7, and 14 d after salt treatment, and total chlorophyll and MDA contents were measured. All treatments were repeated three times and arranged in a randomized complete block design. Determination of chlorophyll content and MDA content For determination of chlorophyll content, leaf samples (0.5 g) were grinded into a fine powder in the presence of liquid nitrogen, mixed with 8 ml acetone 80 % (v/v) and kept overnight at 4°C to extract chlorophyll. The supernatant containing chlorophyll was obtained after centrifugation at 10,000 × g for 10 min at 4°C. The chlorophyll content was measured by a spectrophotometric method, and results were expressed in milligrams of total chlorophyll per gram fresh weight of tissues [43]. The MDA content of treated leaves was measured according to the method of Buege and Aust [44]. All experiments were replicated three times. Primers used in this study Primers used for cloning, quantitative real-time PCR analysis, semi-quantitative RT-PCR Analysis, VIGS and transgenosis are listed in Table 1. Statistical analysis All data are presented as the mean ± standard deviation (SD) of three replicates. Quantitative data were analyzed using Statistical Analysis System software (SAS Institute, version 8.2) following one-way analysis of variance (ANOVA). Differences among means were analyzed at a significance level of 0.05.

v3-fos

2016-03-01T03:19:46.873Z

2015-10-01T00:00:00.000Z

6270669

s2

De Novo Sequencing and Analysis of the Safflower Transcriptome to Discover Putative Genes Associated with Safflor Yellow in Carthamus tinctorius L. Safflower (Carthamus tinctorius L.), an important traditional Chinese medicine, is cultured widely for its pharmacological effects, but little is known regarding the genes related to the metabolic regulation of the safflower’s yellow pigment. To investigate genes related to safflor yellow biosynthesis, 454 pyrosequencing of flower RNA at different developmental stages was performed, generating large databases.In this study, we analyzed 454 sequencing data from different flowering stages in safflower. In total, 1,151,324 raw reads and 1,140,594 clean reads were produced, which were assembled into 51,591 unigenes with an average length of 679 bp and a maximum length of 5109 bp. Among the unigenes, 40,139 were in the early group, 39,768 were obtained from the full group and 28,316 were detected in both samples. With the threshold of “log2 ratio ≥ 1”, there were 34,464 differentially expressed genes, of which 18,043 were up-regulated and 16,421 were down-regulated in the early flower library. Based on the annotations of the unigenes, 281 pathways were predicted. We selected 12 putative genes and analyzed their expression levels using quantitative real time-PCR. The results were consistent with the 454 sequencing results. In addition, the expression of chalcone synthase, chalcone isomerase and anthocyanidin synthase, which are involved in safflor yellow biosynthesis and safflower yellow pigment (SYP) content, were analyzed in different flowering periods, indicating that their expression levels were related to SYP synthesis. Moreover, to further confirm the results of the 454 pyrosequencing, full-length cDNA of chalcone isomerase (CHI) and anthocyanidin synthase (ANS) were cloned from safflower petal by RACE (Rapid-amplification of cDNA ends) method according to fragment of the transcriptome. Introduction Safflower (Carthamus tinctorius L.), is a widely used herbal plant in the family Compositae, which are cultured in many countries worldwide. In China, safflower plays an important role in meals, dye and traditional medicine [1,2]. Safflower flowers have important pharmacological effects, such as promoting blood circulation to remove blood stasis and alleviate pain [3,4]. The chemical components of safflower are diverse, including flavonoids [5] such as safflor yellow, alkaloids and fatty acids [6], polysaccharide and others. Safflower yellow pigments (SYPs), which are isolated from safflower petals, as flavonoid compounds, have been extensively applied in many fields, including as a medicine and natural food colorant. Hydroxysafflor Yellow A (HSYA), is the major active component of the flower and has potent and important antioxidative effects in vitro [7,8], an enormous antagonistic impact on platelet activating factor receptor [9] and vascular dementia [10], and an inhibitory effect on platelet aggregation, tumor angiogenesis, thrombosis and oxidative stress [11,12]. In China, HSYA has been used clinically in the cerebrospinal fluid of patients with traumatic brain injuries [13]. Related research [14] showed that the maximal inhibitory action against the proliferation of 3T3-L1 cells was 0.1 mg/L HSYA over 72 h. Although HSYA is the flavonoid component of the safflower yellow pigments, the relationship between the HSYA composition in safflower petals and the key enzymes catalyzing flavonoid biosynthesis have not been demonstrated. With the development of high-throughput next-generation sequencing (NGS) technology, RNA sequencing (RNA-Seq), as an effective alternative technology, has been applied extensively to animals, plants and microorganisms, providing novel candidate genes, and validating and refining gene models for metabolic pathways [15][16][17]. The mass of transcript sequences obtained from RNA-Seq has led to the annotation of functional genes included in biological processes [18,19]. Recently, some sequencing by synthesis (SBS) methods [20] have started using NGS platforms, such as the Roche/454 Genome Sequencer FLX Instrument, the Illumina Genome Analyzer, and the ABI SOLiD System. Of these, the 454 pyrosequencing platform provides a remarkably effective sequencing technology to research the transcriptomes of unknown plant genomes [21,22]. Because of the important pharmacological effects of safflower petals, the aims of this study were to investigate the de novo transcriptome in the early and full flowering stages of safflower using the 454 pyrosequencing platform. More importantly, on gene expression levels and identifications, functional annotations, and functional genomic studies could be explored using these transcripts. Based on the sequencing, the de novo assembly and characterization of the transcriptome of safflower was performed, and key genes involved in flavonoid biosynthesis were isolated, which established a biotechnological platform for further research on safflower. Preparation, Sequencing and de Novo Assembly of the Flower Transcriptome To comprehensively cover the optimal flowering period, which had a higher level of expression for a particular condition, total RNA was extracted from different flowering period libraries (early and full). The phenotypes of different flowering periods are shown in Figure 1. All the flower samples were collected on the 1st and 5th days of the flowering stage. Total RNA were used for the 454 pyrosequencing. The resulting sequencing data was analyzed using bioinformatics methods. A total of 583,440 and 567,884 raw reads were generated from early and full flowers by 454 sequencing, respectively (Table 1). After the removal of low quality reads, short reads (<50 bp), contaminating sequences and vector sequences by Tagdust (http://genome.gsc.riken.jp) [23] and Seqclean (http://compbio.dfci.harvard.edu) [24], 577,664 and 562,930 clean reads remained in the early and full libraries, respectively. The average read lengths of 427 and 436 bp, respectively, were used for assembling. Reads from two samples combined were assembled into 51,591 unigenes with an average length of 679 bp using the MIRA program [25] and CAP3 (http://seq.cs.iastate.edu). The longest read was 5109 bp. The length distribution of the reads is presented in Figure 2. The greatest number of sequences, 13,790, were between 501-600 bp in length. Figure 2. Length distribution of the safflower unigenes. The longest unigene was 5109 bp, and the average length of the unigenes was 679 bp. Comparison of Unigenes between Early and Full Flowering Stages Among the assembled unigenes, 40,139 were from the early flower group, including 11,823 unique unigenes, and 39,768 were from the full flower group, including 11,452 unique unigenes. In total, 28,316 unigenes were shared by the samples (Figure 3). The correlations between gene expression levels were measured using Pearson's correlation values, which represent positive relative correlations as greater than zero and negative correlations as less than zero. The bitmap (scatter diagram) of correlations is shown in Figure 4A. Gene expression levels at different flowering stages were analyzed to estimate the differential expression between the two groups. With the threshold of "'log2 ratio ≥ 1", There were 18,043 up-regulated genes (red dots) and 16,421 down-regulated genes (green dots), with a total of 34,464 differentially expressed genes (DEGs) in the full flower stage when compared with the early stage. The number of unigenes with different expression levels is shown in Figure 4B. Additionally, 29.09% of the unigenes of the DEGs that differed by more than two fold in the early library and less than two fold in full library were up-regulated. Classification of Gene Ontology (GO) and Functional Annotation Gene ontology (GO) was used to functionally categorize annotated genes. In total, these unigenes were classified into 43 main functional groups, belonging to three main GO categories: biological process, cellular component and molecular function ( Figure 5). The dominant GO terms in biological processes were grouped into cellular progress, metabolic progress and response to stimulus. Among cellular component, genes participated in cell, cell part, organelle and organelle part. Within the molecular function category, the assignments mostly involved binding and catalytic activity. There were a high number of genes from the of "cellular process", "cell", and "catalytic activity" and only a few genes from the categories of "pigmentation", "extracellular region", "protein binding transcription factor activity" and "transcription regulator activity". More detailed information on the annotation is shown in Table S1. Clusters of orthologous groups (COGs) were utilized to further evaluate the functional annotation. There were 25 annotated functional COG categories (Table S2) of safflower unigenes ( Figure 6), mostly related to metabolism. The five most represented categories were: "general function prediction only" (24.681%), "posttranslational modification, protein turnover and chaperones" (10.896%), "signal transduction mechanisms" (9.659%), "translation, ribosomal structure and biogenesis" (5.878%), and "carbohydrate transport and metabolism" (5.255%). The majority of genes were linked to transcription, folding, and molecular chaperone functions. In addition, the COG distribution of DEGs up-regulated and down-regulated is shown in Figures S1 and S2. Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Mapping and Analysis of DEGs The KEGG [26] database was used to analyze the metabolic or biological pathways and functions of gene products in the cells. KEGG annotation information provided a standardized pathway annotation of the safflower unigenes. To identify the biological pathways specific to safflower, we annotated and mapped 281 KEGG pathways for 51,591 unigenes ( Figure 7). Based on an enrichment analysis of the DEGs and the KEGG annotation, a total of 189 pathways were estimated as up-regulated and 186 as down-regulated. Table 2 lists the pathways of the 15 most up-regulated and down-regulated DEGs. More detailed information regarding the pathways is shown in Table S3. Quantitative Real Time-PCR (qRT-PCR) Validation of 454 Pyrosequencing To confirm the results of the 454 pyrosequencing, 12 unigenes were selected for qRT-PCR analysis. The relative expression levels of these unigenes were consistent with differential expression patterns in early and full flowering libraries ( Figure 8). Unigene_s48497, unigene_rep_c20979 and unigene_rep_c37723 were confirmed as being more highly expressed at the early flowering stage compared with at the full flowering stage. Other annotated unigenes were confirmed as having their lowest expression levels during the early stage of flowering. Analyses of the Flavonoid Biosynthesis Pathway and Putative Genes in the Transcriptome To identify flavonoid biosynthesis genes, we focused our analyses on KEGG pathways and safflower transcripts that appeared regulated in the two samples ( Figure 9). In flavonoid biosynthesis, we were interested in the three key genes encoding flavonoid biosynthetic enzymes, chalcone synthase (CHS, EC 2.3.1.74), chalcone isomerase (CHI, EC 5.5.1.6) and anthocyanidin synthase (ANS, EC 1.14.11.19). The 22 unigenes, including those that were up-regulated and down-regulated, related to these genes are listed in Table 3. Of these, 9 were annotated as chalcone synthase (2 up-regulated and 4 down-regulated), 12 were annotated as anthocyanidin synthase (8 up-regulated and 4 down-regulated), and only 1 unigene (unigene_c27184) was annotated as chalcone isomerase. Validation and Expression Analysis of Putative Flavonoid Synthesis Genes from the Safflower Transcriptome To validate that the unigenes that obtained from the safflower transcriptome and computational analysis were indeed expressed, qRT-PCR was performed to validate the expression levels of the flavonoid biosynthetic genes, CHS, CHI and ANS, at different flowering stages and in different varieties. In the qRT-PCR analysis (Figure 10), the selected genes showed distinctly different expression patterns in different varieties and during flower development. The CHS gene (unigene 27184) showed very highly expressed in all of the samples and the highest expression level was in the fading flower of Jihongyou, which was ~ 96 times greater than the highest expression of ANS (unigene_s48497) and 38 times greater than the highest expression of CHS (unigene_c16567). However, the lowest CHS expression level occurred in the full flowering stage of Jihongerhao, which was still greater than the expression of CHI and ANS. For the CHI gene, the highest expression level occurred in the full flowering stage of Jihongyou and the bud stage of Jihongerhao, while the lowest CHI expression level was in the bud of Jihongyou. The ANS gene had a lower expression, relative to CHS and CHI, in the four studied stages of flowering. SYP synthesis generally varied during flower development, with the highest amounts of SYP occurring in the full stage and lowest amounts in the bud or early stages, regardless of the variety. Cloning and Sequence Analysis of the Full-Length cDNA of Key Gene in Flavonoid Synthesis To further confirm the results of the 454 pyrosequencing, full-length cDNA of chalcone isomerase (CHI) and anthocyanidin synthase (ANS) were cloned from safflower petal by RACE method according to fragment of the transcriptome, the 1161 bp CHI cDNA contained a 654 open reading frame (ORF) that encoded 217 amino acids ( Figure 11) and phylogenetic tree showed that CHI gene in safflower has high homology ( Figure 12) with other species, Ipomoea batatas, Agastache rugosa, Camellia nitidissima, Paeonia lactiflora and Canarium album were separated into a large groups. The putative protein of CHI gene showed predicted molecular weight of 23.14 kD with a theoretical pI of 5.67, containing typical AATAA tail signal sequence and Poly(A). By similar method, the cDNA sequence of ANS gene which was 1226 bp and included a whole open reading frame of 1050 bp, encoding a polypeptide of 349 amino acids (Figure 13). A phylogenetic tree was drawn to investigate the evolutionary relationship contrasting to previously reported ANSs from other plants and found higher homology between them (Figure 14). The conserved structural domain analysis showed that ANS gene had thetypical functional domains of ANS protein, containing 2-oxoglutarate and iron ion combination sites. Discussion Safflower is an economically important traditional Chinese medicinal crop, which is well-adapted to growth in arid environments [27]. It has significant economic value and pharmacological effects, based on the amount of safflor yellow in curing. High-throughput sequencing technology has been widely used in various plants to obtain transcript coverage even without a reference genome. 454 sequencing is a reasonably low cost [28] transcriptome profiling method, and its novel and efficient high throughput approach has been used on the olive [29], Leymus chinensis [21], orchids [30], Podophyllum hexandrum [31], plum [32], Lonicera japonica Thunb. [33] and Vicia faba L. [34]. Here, 454 sequencing was applied to the safflower transcriptome for the first time, to discover the important genes in flavonoid biosynthesis, which may be related to the synthesis of SYPs during different flower developmental stages. We used this method to generate transcripts and analyzed gene expression and secondary metabolic pathways, demonstrating that 454 sequencing is an important tool in gene discovery, and in the study of gene expression, genetic markers and genomics. Although a previous high-throughput sequencing platform, Solexa/Illumina [9,20], had been applied in safflower, the objective of the present study was to analyze differences in samples based on the database sequencing. The 454 sequencing produced large numbers of clean sequencing reads that were used to de novo assemble and functionally annotate unigenes from different flowering stages. We obtained 1,140,594 clean reads (577,664 and 562,930 clean reads in early and full flowering stage samples, respectively) which were assembled into 40,139 unigenes using de novo assembly. The results contained reads that corresponded to those obtained with 454 pyrosequencing in P. hexandrum [35], Lonicera japonica Thunb. [36] and Vicia faba L. [37]. We mapped 51,591 unigenes to 281 KEGG pathways, which and classified into 43 main functional groups. This data provides a foundation for further studies on secondary metabolism in safflower. In this study, gene expression levels were compared with the Safflor yellow contents in different varieties and flowering. In the full stage of Jihongyou, the expression levels of CHS, CHI and ANS were higher than in the other flowering periods. While in Jihongerhao, the lowest expression levels of the three genes occurred when the pigment levels peaked during the full fade. Our results showed that the increase or decrease in CHS, CHI and ANS expression levels was mainly related to the accumulation of Safflor yellow, but the expression levels and contents of pigments varied in different varieties, suggesting further research on the mechanism of CHS, CHI and ANS in the flavonoid synthesis pathway is required. CHS is the first pivotal enzyme in the flavonoid synthesis pathway [38], and it participates in a series of physiological and biochemical reactions, such as flavonoid biosynthesis, pigment synthesis and resistance. CHS expression levels are different in various plants, tissues and developmental stages. In this study, the expression level of CHS is higher than that of CHI and ANS during flower development, demonstrating that the CHS gene may be important for safflower flavonoid synthesis. This result is consistent with that of Huang [39]. The overexpression of CHI can increase the flavonoids content [22] and CHI expression in safflower shows its regulation is related to flowering. The trends in gene expression are identical to those found in white narcissus [28], indicating that CHI may be involved in the synthesis of flower colors and pigments. An important medicinal aspect of safflower is its tubular flowers [2], and HSYA, and flavonoid compounds, are extracted from safflower petals. Another object of this study was to discover genes related to flavonoid biosynthesis. Using the KEGG database, we mapped unigenes to the flavonoid biosynthesis pathway and identified multiple genes from this pathway. We focus on important enzymes, CHS, CHI and ANS, that contribute to flavonoid compound synthesis according to the previous reports [12,14]. The expression analysis of these genes using qRT-PCR indicated that their relative expression levels in different samples high expression of CHS, demonstrating that the CHS gene is important in safflower flavonoid metabolic synthesis, which is consistent with a previous study [9]. Sample Preparation and RNA Extraction Safflower seeds were purchased from XinJiang (Honghua Yuan Co., LTD), China, and grown in 16 cm diameter pots under greenhouse conditions of 26 °C (day) and 20 °C (night), 80% relative humidity; light for 16 h (intensity of illumination at a constant 30,000 lx) and dark for 8 h [20]. When blooming, the early stage occurred on the first day after flowering and the full stage occurred on the fifth day ( Figure 1). The petals of early and full safflowers were frozen quickly in liquid nitrogen and stored at −80°C. Total RNA was isolated from individual petals using Trizol (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's protocol for cDNA library construction by 454 sequencing. The RNA quality and quantity were determined using gel electrophoresis and a NanoDrop 2000 (Thermo Scientific, Wilmington, DE, USA), respectively. De Novo Assembly and Sequence Analysis High quality total RNA was prepared for 454 sequencing using a GS-FLX sequencer (Roche, Basel, Switzerland). The clean reads were obtained by deleting raw data, including low quality reads, short reads (<50 bp), adaptor reads, polluted reads, and hairpin structural reads, and were assembled into unigenes utilizing the MIRA program [25]. Then, the unigenes from the two samples were used for future analyses. Comparative Analysis between Two Samples The expression abundance in the sample is shown by the number of reads mapped onto unigenes in the sample, as represented by normalized reads, such as Reads Per Million reads (RPM) and Reads Per Kilo bases per Million reads (RPKM) [38], which were used to compare the relative expression levels of the two samples in further analyses. DEGs were deemed to be unigenes with thresholds of "log2 ratio ≥ 1" and "false discovery rate < 0.001" for sequence counts across the early and full samples. Subsequently, a functional enrichment analysis of KEGG and metabolic pathways was performed on the DEGs. qRT-PCR Validation of 454 Pyrosequencing To validate the accuracy of 454 pyrosequencing in different flowering stages, the expression levels of 12 selected date genes were determined using qRT-PCR. Total RNA was extracted from safflower using the Super RT Kit (Takara, Japan). The 18s rRNA gene was used as an internal control [43], and the qRT-PCR was performed according to the SYBR ® Premix Ex Taq protocol (Takara, Japan) using a Stratagene Mx3000P instrument (Agilent, Palo Alto, CA, USA). The final volume of the qRT-PCR reaction was 20 μL, including 2 μL of cDNA, 10 μL SYBR Premix Ex Taq (Tli RNaseH Plus), 0.4 μL ROX Reference Dye II (50×), 0.4 forward and reverse primers (10 mM) and 6.8 μL ddH2O. The relative quantification of gene expression was computed using the 2 −ΔCt method. Analysis of Putative Flavonoid Synthesis Genes in the Safflower Transcriptome The flavonoid biosynthetic pathway was mapped in the KEGG database using the relative expression levels in different samples. Putative genes involved in the flavonoid biosynthetic pathway were used as query to search the NCBI databases, and unigenes of the highest similarity with other species were selected to confirm the sequencing results. qRT-PCR Analysis and the Isolation of Important Genes in Flavonoid Synthesis An expression analysis of the selected putative genes in flavonoid synthesis were determined using qRT-PCR. Total RNA was extracted from tissue samples, including different varieties (Jihongerhao and Jihongyou) and flowering stages (bud, early, full and faded), approximately 1 μg of DNaseI-treated total RNA was converted into single-stranded cDNA using a Super RT Kit (Takara, Japan). Gene specific primers were designed to amplify three genes of interest from the transcriptome, and RT-PCR was performed for preliminary verification before the qRT-PCR analysis. The 18s rRNA gene was used as an internal control, and the qRT-PCR was performed according to the protocol of SYBR ® Premix Ex Taq (Takara, Japan) using a Stratagene Mx3000P instrument (Agilent). The final volume of the qRT-PCR reaction was 20 μL, including 2 μL of cDNA, 10 μL SYBR Premix Ex Taq (Tli RNaseH Plus), 0.4 μL ROX Reference Dye II (50×), 0.4 forward and reverse primers (10 mM) and 6.8 μL ddH2O. The relative quantification of gene expression was computed using the 2 −ΔCt method [29]. The full-length cDNAs of the two genes were isolated and analyzed from Safflower petals using 5′ and 3′ RACE methods in the SMART RACE Amplification kit (Clontech, Japan). The RACE fragments were amplified by specific primers, ligated into the pEASY-T1 vector (TranGene Biotech, Beijing, China) and sequenced. Then, the RACE fragments were used for subsequent verifications and analyses of full length cDNAs. Conclusions In this report, a comprehensive transcriptome database from different safflower flowering stages was obtained using 454 pyrosequencing and produced 577,664 and 562,930 clean reads from the early and full flowering libraries, respectively. The safflower transcriptome provided 34,464 DEGs and a large number of unigenes mapped to 281 KEGG pathways. The qRT-PCR analysis of selected unigenes indicated that the 454 sequencing was accurate. We annotated a large number of genes involved in safflor yellow biosynthesis and studied the expression of putative genes related to safflor yellow synthesis. The data from this study will enrich our knowledge of safflower and provide a theoretical foundation for functional studies of SYP-related genes using transgenic technologies. Full-length cDNA of chalcone isomerase (CHI) and anthocyanidin synthase (ANS) were cloned from safflower petals by the RACE method.

v3-fos

2016-04-04T08:54:49.290Z

2015-01-01T00:00:00.000Z

12347089

s2

Phenolic Composition from Different Loquat (Eriobotrya japonica Lindl.) Cultivars Grown in China and Their Antioxidant Properties China is one of the most important centers of diversity for Eriobotrya japonica Lindl. in the world. In this study, seven loquat cultivars grown in China were evaluated for their phenolic compounds and antioxidant activity. Eleven phenolic compounds, i.e., 3-p-coumaroylquinincacid (3-p-CoQA), 5-caffeoylquinic acid (5-CQA), 4-caffeoylquinic acid (4-CQA), 3-caffeoylquinic acid (3-CQA), 5-feruloylquinic acid (5-FQA), quercetin-3-O-galactoside (Q-3-Gal), quercetin-3-O-glucoside (Q-3-Glu), quercetin-3-O-rhamnoside (Q-3-Rha), kaempferol-3-O-galactoside (K-3-Gal), kaempferol-3-O-rhamnoside (K-3-Rha), and kaempferol-3-O-glucoside (K-3-Glu) were identified and quantified in the peel and pulp of the cultivars tested. 3-CQA and 5-CQA were the predominant components in both fruit parts. 2,2-Diphenyl-1-picrylhydrazyl radicals (DPPH), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate (ABTS), and ferric reducing antioxidant power (FRAP) assays were used for the antioxidant evaluation. Results showed that peel extracts had higher antioxidant activities than their pulp counterparts in all the cultivars tested, which was correlated with their higher total phenolic contents. The antioxidant potency composite (APC) index showed obvious variations ranging from 64.15 to 100 in the peel and from 59.49 to 97.95 in the pulp of different cultivars, where “Dahongpao” (DHP) and “Luoyangqing” (LYQ) had the highest APC index in the peel and pulp, respectively. Overall, loquat cultivars rich in hydroxycinnamic acids (HCAs) such as 3-p-CoQA, 5-CQA, 4-CQA, 3-CQA and 5-FQA showed relatively higher antioxidant activities, and may be excellent sources of phytochemicals and natural antioxidants. Introduction Epidemiological studies have shown that consumption of fruit and vegetables has great health benefits against chronic diseases, such as cardiovascular disease, cancer, and diabetes [1][2][3]. The health-promoting properties of fruit and vegetables are mainly due to the presence of various antioxidants, including phenolics [4]. Phenolic compounds are a large group of plant secondary metabolites. So far, more than 8000 dietary phenolics have been identified, and their distribution and accumulation profiles were affected by both genetic and environmental factors [3,4]. Loquat (Eriobotrya japonica Lindl.) is a subtropical evergreen perennial fruit tree originated in south-eastern China. It has been cultivated for more than 2000 years and is now commercially cultivated in more than 30 countries worldwide, including Japan, Turkey, Italy, Spain, Brazil, etc. Loquat fruit is delicious and is a good resource for dietary phenolics. Loquat is a plant with high medicinal value since different organs have been used historically as folk medicines for thousands of years. Loquat extracts have been used for the treatment of cough, chronic bronchitis, inflammation, diabetes, and cancer in Chinese folk medicine, as recorded by ancient literature such as "Compendium of Materia Medica" [5]. The efficacy of loquat, as used in traditional Chinese medicine, is supported by current scientific evidence regarding the pharmacologically-active compounds in plant extracts and their structure-activity associations. For example, loquat extracts from leaf, flower, and kernel showed various pharmaceutical and health-promoting effects in different experimental models, such as antioxidant [6][7][8][9], anti-inflammation [10,11], anti-diabetic [12], anticancer [13], gastroprotective [14]. However, as the edible part, loquat fruit has been rarely investigated for their bioactive compounds and bioactivities. China is the largest producer of loquat fruit in the world (170,000 ha). However, there is no extensive investigation of the phenolic profile and their antioxidant properties in loquat cultivars grown in China. The objective of the present study was to identify individual phenolic compounds in fruit peel and pulp of seven loquat cultivars and to evaluate their antioxidant properties. Results may useful for the selection of loquat genotypes rich in phenolic compounds and enhanced nutritional value, which may be important for better utilization of loquat genetic resources. Fruit Quality Evaluation All fruit used in the present research were harvested at the ready-to-eat stage. As shown in Table 1, fruit quality indices such as fruit weight (FW), fruit shape index (FSI), soluble solids content (SSC) varied significantly among the seven cultivars tested. The FW ranged from 24.24 (BZ) to 42.19 g (LYQ) among the cultivars tested. Previous studied showed that the FW of Turkey loquat cultivars ranged from 22.55 to 29.54 g [15], and those from Italy ranged from 38.4 to 74.2 g [16]. The cultivars tested showed similar fruit shape, as reflected by the similar FSI. SSC is an important fruit quality trait, which is closely related to consumer acceptance and satisfaction. In our study, the white-coloured cultivar NHB showed the lowest SSC (10.24 °Brix), while the red-coloured cultivar DHP showed the highest SSC (12.08 °Brix). Based on the literature, some Italian loquat cultivars showed higher SSC value up to 14.6 °Brix [16]. Total Phenolic Contents Due to the significant correlations found between the phenolic contents and various bioactivities including antioxidant activity, numerous studies have been carried out to select new genotypes rich in phenolic compounds [17,18]. Total phenolic contents of the peel and pulp extracts of seven loquat cultivars were measured using a modified colorimetric Folin-Ciocalteu method [19]. Total phenolic contents showed obvious variations among the cultivars tested, ranging from 30.58 (JJ) to 43.70 mg gallic acid equivalent (GAE)/g DW (DHP) for the peel and from 9.90 (JJ) to 13.73 mg GAE/g DW (LYQ) for the pulp (Figure 1). Total phenolic contents have been evaluated for loquat cultivars in China [20,21], Japan [17], Turkey [22,23] and America [24]. The variation in total phenolic contents of loquat fruit is due to both the genetic and environmental factors. Table 1. Identification of Individual Phenolic Compounds Identification of individual phenolic compounds in loquat fruit were further carried out by HPLC-DAD and LC-ESI-MS/MS. For the identification of hydroxycinnamic acids (HCAs), the fragment ion information from LC-MS/MS were compared with the study of Clifford et al. [25]. As a result, five HCAs were identified in loquat fruit ( Table 2) [25], and together with the confirmation of chemical standards, five HCAs were identified as 3-p-CoQA, 5-CQA, 4-CQA, 3-CQA, and 5-FQA, respectively. For the identification of flavonols, the fragment ion information from LC-MS/MS were compared with the study of Hvattum et al. [26]. As a result, six flavonols were identified ( Table 2) [26], and together with the confirmation of chemical standards, six flavonols were identified as Q-3-Gal, Q-3-Glu, Q-3-Rha, K-3-Gal, K-3-Rha and K-3-Glu, respectively. By comparison with previous report [18], K-3-Gal and K-3-Rha identified in the present study were reported in loquat fruit for the first time. Quantification of Individual Phenolic Compounds Loquat peel extracts contained relatively higher amounts of phenolics than their pulp counterparts. In addition, both HCAs and Flavonols can be detected in the peel extracts, while only HCAs were detected in the pulp extracts. Both 5-CQA and 3-CQA were the main phenolic compounds in both fruit parts (Tables 3 and 4). For HCAs in both fruit peel and pulp, the contents of 3-CQA were relatively higher than those of 5-CQA. The contents of 3-CQA varied from 3.13 (JJ) to 6.75 mg/g DW (NHB) in the peel, and from 2.65 (JJ) to 6.29 mg/g DW (LYQ) in the pulp. The contents of 5-CQA varied from 1.92 (JJ) to 5.10 mg/g DW (LYQ) in the peel, and from 0.46 (BZ) to 1.42 mg/g DW (LYQ) in the pulp. The contents of 3-p-CoQA, 4-CQA, and 5-FQA were much lower compared with those of 3-CQA and 5-CQA. In both the fruit parts, 3-p-CoQA varied from ND to 0.52 mg/g DW, 4-CQA varied from 0.02 to 0.55 mg/g DW, and 5-FQA varied from 0.13 to 0.98 mg/g DW. For the total individual hydroxycinnamic acids (TIHCAs), i.e., the sum of five individual hydroxycinnamic acids identified in the present study, the cultivar NHB and LYQ showed the highest content in the peel (12.8 mg/g DW) and pulp (8.08 mg/g DW), respectively, while JJ showed the lest contents both in the peel (5.66 mg/g DW) and in the pulp (3.49 mg/g DW) (Tables 3 and 4). For the six flavonols detected in the fruit peel, DHP showed the highest contents of all three quercetin glucosides (Q-3-Gal, Q-3-Glu, and Q-3-Rha), while JJ contained the highest contents of all three kaempferol glucosides (K-3-Gal, K-3-Rha, and K-3-Glu). For the total individual flavonols (TIFs), i.e., the sum of six individual flavonols identified in the present study, it varied from 0.39 (LYQ) to 1.74 mg/g DW (JJ) in the peel of seven loquat cultivars (Table 3). Antioxidant Activity The antioxidant activities of loquat cultivars were evaluated by DPPH, ABTS and FRAP methods. Generally speaking, these three assays showed consistent results for both the peel and pulp extracts of seven loquat cultivars (Table 5). DPPH values of the different cultivars analysed varied from 25.19 to 36.64 mg trolox equivalent antioxidant capacity (TEAC)/g DW in the peel and from 6.62 to 11.79 mg TEAC/g DW in the pulp (Table 5). DHP showed the highest DPPH values in both the peel and pulp tissues, followed by LYQ. And much higher levels of DPPH• radical scavenging activity were found in the peel fraction when compared with their pulp counterparts. The ABTS values of the different cultivars analyzed varied from 36.11 to 57.32 mg TEAC/g DW in the peel and from 7.30 to 12.77 mg TEAC/g DW in the pulp (Table 5). DHP and LYQ showed the highest ABTS values in the peel and pulp tissues, respectively. There much higher levels of ABTS + radical scavenging activity were found in the peel fraction when compared with their pulp counterparts. The FRAP values of the loquat cultivars varied from 36.25 to 59.71 mg TEAC/g DW in the peel and from 10.65 to 17.79 mg TEAC/g DW in the pulp. The peel of DHP and pulp of LYQ showed the highest FRAP values among all the samples tested (Table 5). Similarly, higher FRAP values were found for extracts from the peel compared to the pulp, which was in accord with the results obtained by Pande et al. [24]. Previous studies also showed the antioxidant activities of loquat fruit grown in different regions, and values of DPPH, ABTS and FRAP values varied from 1.45 to 5.85 μmol TEAC/g FW, from 1.32 to 4.53 μmol TEAC/g FW, and from 2.14 to 5.91 μmol TEAC/g FW, respectively [21,22]. Such variations were results of different chemical compositions, which was affected by variety, stage of maturity and cultivation environment. For a comprehensive comparison of the antioxidant capacities in two fruit parts of loquat of different cultivars, an overall antioxidant potency composite (APC) index was calculated according to the method described by Seeram et al. [27]. The APC index showed obvious variations ranging from 64.15 (JJ) to 100 (DHP) in the peel and from 59.49 (BZ) to 97.95 (LYQ) in the pulp (Table 5). Both DHP and LYQ are the main loquat cultivar in the market, and the high APC values for both these two cultivars indicated they may also have better health promoting values than other cultivars. Correlations Analysis Correlation analysis was carried between the antioxidant capacities and the phenolic contents in different loquat samples (Table 6). Significant correlations between DPPH, ABTS and FRAP were observed, providing validation of these three antioxidant activity evaluation methods, as mentioned above. Total phenolics showed strong correlation with antioxidant activities, indicating thatextracts with higher total phenolics showed higher antioxidant activity, and vice versa. Such data was in accord with previous results [21,22]. In addition, TIHCAs also showed high correlation with the antioxidant activities in loquat fruit, with higher correlation coefficient in the pulp (r ranged from 0.851 to 0.959, p < 0.01). High antioxidant activities of HCAs such as p-hydroxycinnamic acids were reported previously [28,29]. The high correlation between TIHCAs and three antioxidant activities indicated that HCAs may contribute significantly to the antioxidant activities of loquat fruit samples. TIFs, however, did not show a good correlation with the antioxidant activities. This may mainly due to their low contents in the loquat fruit samples. Table 6. Correlation coefficients between phenolic content and antioxidant capacities. All the other reagents of analytical grade were bought from Sinopharm Chemical Reagent Co., Ltd (Shanghai, China). Materials Seven loquat cultivars were harvested at optimum maturity on the basis of uniformity of shape and colour, absence of disease and mechanical damage in Zhejiang Province, China in the fruit season of 2013 (Table 1). In detail, LYQ and RTBS were harvested from Luqiao county; BZ, DHP, DYYD, and JJ from Tangxi county; NHB from Ninghai county. During the experiments, 90 fruits per cultivar, 30 for each of three replicates were kept separately and the fruit were separated into two parts, i.e., peel and pulp, and frozen in liquid nitrogen. After freeze-drying (FM 25EL-85, VirTis, Los Angeles, CA, USA), all the samples were ground into fine powder and stored at −80 °C until extraction and analysis of phenolics. Fruit Quality Analysis Twelve fruits of each cultivar were randomly chosen and quality traits such as FW, FSI, SSC were measured. Pulp colour was recorded as white and red. The height and diameter at the widest point of the fruit were measured with a vernier caliper, and the height/diameter ratio was calculated for FSI. SSC was measured with a digital refractometer (Atago PR-101R, Tokyo, Japan), and data was expressed as °Brix. Preparation of Fruit Peel and Pulp Extracts The ground powder of peel (0.15 g) and pulp (0.30 g) were extracted with 95% aqueous ethanol with 1% formic acid (7 mL) by sonication for 30 min. The ultrasonic frequency and power were 60 kHz and 30 W, respectively. The extracts were centrifuged at 12,879 g for 10 min at 4 °C and the residue was extracted twice as above. Both supernatants were combined and used for the determination of phenolic compounds and antioxidant activity. Determination of Total Phenolics Total phenolics of fruit extracts were measured using a modified colorimetric Folin-Ciocalteu method [19]. Four milliliters of ddH2O and appropriately diluted fruit extracts (0.5 mL) were placed in a test tube. Folin-Ciocalteu reagent (0.5 mol/L, 0.5 mL) was added to the solution and allowed to react for 3 min. The reaction was neutralized with saturated sodium carbonate (1 mL). Absorbance at 760 nm was measured using a spectrophotometer (UV-2550, Shimadzu, Tokyo, Japan) after 2 h. Standard solutions of gallic acid at concentrations of 0.1, 0.2, 0.3, 0.4, 0.5, and 0.6 mg/mL were used to plot the standard curve. Data were expressed as mg GAE/g DW. HPLC-DAD and LC-ESI-MS/MS Analysis of Phenolic Compounds Each individual phenolic compound in the fruit extracts was identified by LC-ESI-MS/MS. HCAs were detected at 280 nm; flavonols at 350 nm. Except 3-p-CoQA and 5-FQA were quantified with p-coumaric acid and ferulic acid, other phenolics were quantified with their own standard curves, and data were expressed as mg/g DW. Mass spectrometric analyses were performed by an Agilent 6460 triple quadrupole mass spectrometer equipped with an ESI source (Agilent Technologies, Santa Clara, CA, USA) that operated in both positive ionization and negative ionization mode. The nebulizer pressure was set to 45 psi and the flow rate of drying gas was 5 L/min. The collision energy was set to 5, 15, 25 and 35 eV. The flow rate and the temperature of the sheath gas were 11 L/min and 350 °C, respectively. Chromatographic separations were done on an ODS C18 analytical column (4.6 × 250 mm) using an Agilent 1290 Infinity HPLC system (Agilent Technologies). The eluent was split and approximately 0.3 mL/min was introduced into the mass detector. An Agilent Mass Hunter Workstation was used for data acquisition and processing. Antioxidant Activity Assays DPPH radical scavenging activity was measured according to Brand-Williams et al. [30] with modifications. The reaction was carried out by adding sample (0.1 mL) to 60 μmol/L DPPH solution (3.9 mL) at room temperature. After 60 min, the absorbance of samples was recorded at 517 nm, by a spectrophotometer. Trolox was used as standard and data were expressed as mg TEAC/g DW. ABTS assay was carried out using a spectrophotometer as reported [31]. ABTS radical cation was generated by reacting 7 mmol/L ABTS with 2.45 mmol/L potassium persulfate, and the mixture was allowed to stand in the dark at room temperature for 16 h before use. Before analysis, the ABTS solution was diluted with ethanol to an absorbance of 0.70 ± 0.05 at a wavelength of 734 nm. The absorbance at 734 nm was recorded for 6 min after mixing of the tested samples (0.1 mL) with ABTS solution (3.9 mL). Trolox was used as standard and data were expressed as mg TEAC/g DW. The FRAP was measured according to Benzie et al. [32] with modifications. A fresh working solution was prepared by mixing 100 mL 300 mmol/L acetate buffer (pH 3.6), 10 mL 10 mmol/L TPTZ solution in 40 mmol/L HCl, and 10 mL 20 mmol/L FeCl3 solution. The reaction was carried out by adding sample (0.1 mL) to the FRAP solution (0.9 mL) for 10 min at 37 °C, and absorbance at 593 nm was recorded. Trolox was used as standard and data were expressed as mg TEAC/g DW. For each of the antioxidant method, an antioxidant index score was calculated according to the formula: Antioxidant index score = [(sample score/best score) × 100], and APC Index was calculated as the average of the antioxidant index score of each method. Statistical Analysis Besides the fruit quality index in Table 1, which was measured for 12 fruits for each cultivar, all the other data were the result of at least three replications and were expressed as the mean ± standard deviation. Statistical analysis was performed using SPSS 17.0 software (SPSS Inc., Chicago, IL, USA) and significant differences among the samples were calculated using one-way ANOVA followed by Duncan's multiple range test at p < 0.05. Pearson correlation coefficients were calculated between antioxidant activity and phenolic contents at p < 0.05. Conclusions In the present study, the phenolic compounds and antioxidant capacities of the peel and pulp of seven loquat cultivars grown in China were investigated. Eleven phenolic compounds were identified and quantified. 3-CQA and 5-CQA were the predominant components in both tissues. Peel contained higher amounts of phenolics than pulp, and flavonols were mainly detected in the peel. In addition, the APC index of different cultivars varied from 64.15 (JJ) to 100 (DHP) in the peel and 59.49 (BZ) to 97.95 (LYQ) in the pulp. Both DHP and LYQ are the main loquat cultivars in the market, and the high APC values for both these two cultivars indicated that they may also have better health promoting values than other cultivars. Correlation analysis showed that loquat cultivars rich in HCAs showed higher antioxidant activities. Thus, these findings may provide useful information for future study and utilization of the loquat germplasm in China.

v3-fos

2019-03-31T13:44:55.989Z

2015-02-01T00:00:00.000Z

88014489

s2

Performance of High Tunnel Tomato Cultivars in Northern New England Tomato (Solanum lycopersicum) growers select cultivars based on a range of performance criteria. Currently, however, information regarding tomato cultivar performance in high tunnels is lacking. We conducted a tomato cultivar trial in an 1800-ft plastic-covered high tunnel in Durham, NH, with 15 indeterminate cultivars using organic fertilizers and pesticides. Tomatoes were grown in-ground in a randomized complete block design (n = 4) using raised beds with plastic mulch and drip irrigation. Marketable and unmarketable yield, several yield components, and susceptibility to two common diseases, leaf mold (Fulvia fulva) and powdery mildew (Oidium lycopersici or Leveillula taurica), were evaluated over a 3-year period. Differences between cultivars existed in all areas of interest, and year-to-year variation in performance was noteworthy in this experiment. ‘Geronimo’ consistently had among the highest yields, ‘Arbason’ and ‘Massada’ produced many individual fruit, and several cultivars including Rebelski, Massada, and Geronimo showed no signs of disease. Some cultivars such as Conestoga appeared susceptible to several different physiological disorders while others were relatively robust against this type of marketable yield reduction. Because we assessed multiple yield and quality variables and observed apparent trade-offs in several of these, we used radar plots to summarize and communicate the performance of each cultivar in an intuitive and comparable manner. Based on these data, several tomato cultivars appear particularly well suited for high tunnel production in northern New England. H igh tunnels improve tomato yields and/or quality over both field production (Martinez-Blanco et al., 2011;O'Connell et al., 2012;Rogers and Wszelaki, 2012) and low tunnels (Waterer, 2003). By enabling earlier planting dates and later harvests, high tunnels can extend the growing season, thereby allowing for enhanced growth and the intensification of tomato production in cool climates (Hunter et al., 2012;Uzun, 2007). High tunnels can also protect crops from rain and wind damage and against some pests and diseases (Blomgren and Frisch, 2007;Wells and Loy, 1993). Because of its high value, tomato has become the principal crop grown in high tunnels in many states (Carey et al., 2009). Cultivar selection remains a critical component to successful tomato production, and many important traits contribute to cultivar performance in all growing environments, including high tunnels. Traits such as consumer preferences (taste), marketable yield, and yield components such as percentage of unmarketable fruit and the total number of fruit are clearly relevant to growers. Other traits, including susceptibility to disease and physiological disorders, are also important and should be included in the overall assessment of cultivar performance (Hutton and Handley, 2006). Fungal diseases present a significant challenge to tomato growers. Two of these, leaf mold and powdery mildew, are more prevalent in greenhouse or tunnel production than in open-field systems (Curtis et al., 1994, Jones et al., 2001, Whipps et al., 1998. Leaf mold tends to occur annually in northeastern U.S. high tunnels, whereas powdery mildew is less common, and does not occur every year. Chemical management of both diseases in high tunnels is challenged by limited fungicide options in greenhouses. However, genetic resistance to both diseases exists in tomato cultivars. Resistance to leaf mold is controlled by single race-specific resistance genes that have been widely deployed in cultivars (e.g., Joosten and de Wit, 1999), but it is not known which of the many pathogen races are found in the northeastern U.S. region. Resistance to powdery mildew has been described in a few cultivars (e.g., Seifi et al., 2014), but the response of tomato cultivars to powdery mildew in our region has not been described. The total marketable yield of a cultivar is governed by the potential to produce fruit and the percentage of that fruit which is damaged to the extent that it is no longer marketable. The reason fruit becomes unmarketable is a function of abiotic and biotic factors driven by genetic susceptibility, management, and environmental conditions, or often combinations thereof. Some of the many physiological disorders affecting tomato include blossom-end rot, yellow shoulder, uneven ripening (parts of fruit remaining yellow), and various forms of fruit cracking (Jones et al., 2014). While environmental factors usually determine whether particular disorders will be seen, cultivars differ in their susceptibility to common disorders, and an improved understanding of these differences would help growers minimize the risk of crop loss by selecting less susceptible cultivars. To our knowledge, there are no data in the peer-reviewed literature from tomato cultivar trials conducted in high tunnels that are applicable to the northeastern United States. There are, however, several informative extension publications available for various regions in the United States (e.g., Bogash, 2011;Monroe et al., 2010). The purpose of this experiment was to evaluate, describe, and communicate the important differences in yield and susceptibility to common diseases and disorders among 15 tomato cultivars in a high tunnel production system under conditions typical for the northeastern United States (i.e., raised beds, plasticulture, and irrigation) (Lamont et al., 2003). Materials and methods The experiment was conducted for three growing seasons from 2011 to 2013 in a 30 · 60 ft high tunnel at the University of New Hampshire (UNH) Woodman Horticultural Farm in Durham. The high tunnel was managed in accordance with U.S. Department of Agriculture organic production standards. Each season, the tunnel was prepared by rototilling, fertilizing, and forming beds using a small tractor-mounted bed former with 36-inch black plastic mulch and drip tape irrigation. Weeds between rows were controlled by hand and mulching with salt marsh hay. The study was a randomized complete block design with plots of four plants of each cultivar replicated in four blocks. In late May, tomatoes were transplanted directly into the ground in single rows and spaced 16 inches between plants with rows 55 inches apart. In Winter 2011, we developed and conducted a survey to solicit input from local growers on cultivars to evaluate, and which variables to measure during the experiment. This information, combined with additional conversations with growers and extension professionals, was used to select 11 indeterminate beefsteak cultivars in 2011. Of all available tomato types grown in high tunnels, indeterminate tomato cultivars were selected to meet growers' interests and ensure between-cultivar observations were comparable. In 2012, three additional cultivars were added, and one was substituted in 2013. All cultivars were hybrids with the exception of Brandywine, an open-pollinated heirloom type. A full list of cultivars and seed suppliers can be found in Table 1. Before each growing season, high tunnel soil tests were submitted through UNH Cooperative Extension to obtain fertility recommendations for commercial tomato production. Fertilizers were applied according to standard production guidelines (Howell and Hazzard, 2012 x Cultivar was not grown in that season (see Table 1 lb/acre sulfate of potash magnesia, and 1650 lb/acre soybean meal. All dry fertilizers were broadcast uniformly across the soil surface and incorporated into the soil before planting. The tomatoes were germinated at the UNH MacFarlane Greenhouses and transferred to seedling trays %1 week after germination. They were moved to the high tunnel to harden off for 2 d and transplanted into the ground on 20 May 2011, 23 May 2012, and 20 May 2013. Plants were trained to a single leader using a string trellis, and side shoots and lower leaves were pruned weekly or as needed throughout the growing season. The high tunnel was irrigated to the approximate equivalent of 1 inch of rain per week. To maintain consistent soil moisture, the high tunnel was irrigated when the soil 1-3 inches underneath the plastic mulch became dry to the touch, generally two to three times per week. Yellow-striped armyworm (Spodoptera ornithogalli) and tomato hornworm (Manduca quinquemaculata) occurred in all 3 years and were controlled by applying Harvest of mature tomato fruit occurred about weekly from mid-July to late Oct. 2011 and 2012. In 2013, tomatoes were harvested until late September. The final year was shorter to accommodate a transition to winter high tunnel vegetable production. The tomatoes were left to fully ripen on the vine and were edible at the time of picking. Fruit quality (marketability), weight, number, and the presence of physiological disorders or disease were recorded for each plot at each harvest date. Fruits with minor fruit defects, such as mild cosmetic cracks or scars, were considered ''marketable.'' Fruits showing evidence of disease, damage, or physiological disorders that could affect postharvest storage of the fruit were considered unmarketable. Several qualitative factors were evaluated during the experiment. Informal taste tests were conducted in each of the growing seasons, but due to the excessive variability observed, the results are omitted from this report. Visual ratings were used to assess cultivar susceptibility to powdery mildew and leaf mold. Each disease was given a leaf infection rating using a scale of 0 (absent) to 4 (severe) during the peak of their respective outbreaks. In both cases, a score of 0 = no symptoms on any leaves and 4 = sporulating lesions on nearly the entire leaf surface throughout the plant. Yield data were converted to total seasonal production of marketable or unmarketable fruit per plant. The total unmarketable weight was used to calculate the percentage of unmarketable fruit. The total number of fruit per plant and average fruit weight were both calculated using marketable yields only. Consistent production between individual plants of the same cultivar (i.e., yield stability) is a desirable trait; as a measure of yield stability, the plot to plot variability of a cultivar's marketable yield was assessed by calculating the CV for each growing season and this metric is reported in radar plots (see below). The frequency of common physiological disorders and other causes of tomato damage are reported as the percentage of harvest dates in which each disorder was present on at least one tomato. Disorders that did not appear on at least 15% of the harvest dates for at least one cultivar were omitted. Disorders that were prevalent in at least 1 year included blossom-end rot, catfacing, radial and concentric cracking, yellow shoulder, splitting, and uneven ripening (Jones et al., 2014). Incidence of each disorder in each year is presented in a simplified 0-4 scale, where 0 = 0%, 1 = 1% to 24%, 2 = 25% to 49%, 3 = 50% to 74%, and 4 = 75% to 100%. Yield and yield component data were checked for normality and analyzed using analysis of variance. The percentage of unmarketable yield was analyzed similarly to the yield data after it was arcsine square root transformed and subsequently tested using the Shapiro-Wilks goodness of fit test for a normal distribution. Cultivar and block were considered fixed effects, and in cases where there was a significant cultivar by year interaction, results are reported separately by year. All analyses were conducted using JMP Pro 11 (SAS Institute, Cary, NC). Cultivar trial data are typically presented in a univariate manner although multiple variables are assessed in such studies. Radar plots (also known as spider plots) provide a convenient and intuitive way of presenting and evaluating multivariate agricultural data (Smith et al., 2011). Radar plots incorporate three or more axes, with each axis representing a particular variable and sharing a common origin. The original data for each axis may have been collected at various scales and often those data are set to a relativized scale to facilitate comparisons across axes and variables. For each variable in this cultivar trial, the maximum observed value was scaled to the maximum axis value of 50, and the minimum observed value was scaled to the minimum axis value of 1, to emphasize differences between cultivars. In this case, the axes represent six variables: the total number of marketable fruit, total marketable yield in weight, average individual fruit weight, the percentage marketable fruit by weight (inverse of percentage of unmarketable fruit), yield stability or the consistency in production between plots (inverse of the CV), and the resistance to leaf mold (inverse of susceptibility). The size and symmetry of the resulting polygon indicates the relative magnitude of each variable and the overall performance of the cultivar. Radar figures were generated using Excel 2013 (Microsoft Corp., Redmond, WA). Results The mean seasonal daily temperatures for the periods from 20 May to 30 Sept. 2011, 2012, and 2013 were 19.7, 19.5, and 19.1°C, respectively. The mean marketable yield of the 10 cultivars present in all 3 years of the experiment declined from 8195 g/plant in 2011 to 3232 g/plant in 2013 (year, P < 0.001). The relative differences between these same cultivars were inconsistent over the 3 years (cultivar · year interaction, P < 0.0001). For these reasons, as well as the substitutions of some cultivars, yield data were analyzed separately by year. 'Geronimo' consistently produced the highest marketable yields or was not significantly different from the highest yielding cultivar for all 3 years of the study; Arbason, Big Beef, Imperial 643, and Rebelski all had among the highest marketable yields in at least 2 of the 3 years (Table 2). In contrast, 'Lola', 'Trust', and 'Conestoga' produced among the lowest yields in at least 2 years of the study. The percentage of unmarketable fruit ranged from 19% to 47% in 2011, 24% to 44% in 2012, and 15% to 52% Mean marketable yield produced throughout the entire season; 1 g = 0.0353 oz. y By weight. x Within a column, means followed by the same letter are not significantly different at P £ 0.05 using Tukey's honestly significant difference test. w Cultivar was not grown in that season (see Table 1 for details). v 'Martha Washington'. Mean number of marketable fruit produced (total per plant) throughout the entire season. y 1 g = 0.0353 oz. x Within a column, means followed by the same letter are not significantly different at P £ 0.05 using Tukey's honestly significant difference test. w Cultivar was not grown in that season (see Table 1 for details). v 'Martha Washington'. in 2013 (Table 2). 'Brandywine' had one of the highest percentages of unmarketable fruit in the first 2 years but not in 2013, and 'Conestoga' had among the highest in the last 2 years of the study. The cultivars with the lowest percentages of unmarketable fruit varied from season to season, but Cobra produced a relatively low percentage of unmarketable fruit throughout the experiment. 'Massada' and 'Arbason' consistently had the highest numbers of individual marketable fruit; 'Brandywine' and 'Trust' and others had low numbers of fruit in 2011 and 2012, as did 'Goliath' and 'Conestoga' in 2013, and several others (Table 3). Relative to yields, average fruit weight was more stable across the 3 years, following a generally decreasing trend as overall yields declined. 'Brandywine', however, increased in fruit size over 3 years, and 'Geronimo', 'Massada', and 'Trust' remained relatively unchanged. Leaf mold was not present in 2011, but incidence of this disease was high in both 2012 and 2013. Powdery mildew was present only in 2012. Qualitative assessments showed that 'Conestoga' and 'Goliath' were the most susceptible to leaf mold, and 'Arbason', 'Big Beef', and 'Martha Washington' were also highly susceptible (Table 1). In contrast, 'Geronimo', 'Massada', and 'Rebelski' appeared resistant both years that leaf mold incidence was high (2012 and 2013). These three cultivars, along with Arbason and Imperial 643, also appeared resistant to powdery mildew in 2012. The observed frequencies of physiological disorders are presented in Table 4. Overall incidence of the different physiological disorders varied from year to year. Generally, 'Conestoga' tended to exhibit a high frequency of several disorders (blossom-end rot, catfacing, and radial cracking) across years, while other cultivars were more closely associated with only one or two disorders. 'Martha Washington', 'Rebelski', and 'Jet Star' had a high incidence of blossom-end rot. 'Brandywine' was particularly susceptible to radial and concentric cracking and splitting; 'Arbason', 'Big Beef', and 'Goliath' frequently suffered from radial cracking. 'Imperial 643' was characterized by uneven ripening in the Percentage of harvest dates where the disorder occurred on at least one tomato within a cultivar is presented as a range: 0 = 0%, 1 = 1% to 24%, 2 = 25% to 49%, 3 = 50% to 74%, 4 = 75% to 100%. y Cultivar was not grown in that season (see Table 1 for details). • February 2015 25 (1) first 2 years when uneven ripening was prevalent. Radar plots were used to present the relative magnitude of differences among the cultivars for the whole suite of response variables that were measured (Fig. 1). This approach allows for an efficient comparison of potential trade-offs between cultivars in terms of multiple performance traits. For example, both 'Arbason' and 'Rebelski' had relatively high yields; however, they differed in the size and number of fruit; 'Arbason' with many smaller fruit and 'Rebelski' with larger but fewer numbers of fruit. Some cultivars, such as Martha Washington, Goliath, or Conestoga, stood out as not having any relative ''strengths'' compared with the others. In contrast, some cultivars, including Cobra, Big Beef, and Arbason, appear generally ''balanced'' by having relatively desirable values for many of the performance variables that were measured. Both 'Geronimo' and 'Rebelski' had high yields, similar percentages of unmarketable fruit, and good leaf mold resistance. Discussion Given its economic and cultural importance, tomato offers a unique connection between growers and consumers, especially in a direct-market context. Cultivar choice, therefore, remains one of the most important decisions that growers make (Williams and Roberts, 2002). Differences among cultivars in growth habit, disease resistance, and a host of other traits means that growers must make decisions based on their willingness to accept trade-offs in performance traits between cultivars. The inconsistency in yield across years and within cultivars was unexpected. Overall, we observed a declining trend in production over the 3 years of the study, possibly due to soil nutrient depletion and increases in pathogen pressure in our high tunnel. However, soil tests and subsequent fertility applications throughout the experiment should have compensated for nutrient deficiencies developing over time. While the third harvest season was shorter than the first two, the marketable yield totals for a standardized season length follow the same trend, declining over the 3 years. Anecdotal evidence suggests that this general decline is common in high tunnels new to tomato production, and we also do not rule out the cumulative effects of disease pressure in the tunnel increasingly affecting at least some of the cultivars. There were several notable deviations from the general trend of decreasing yields. The cultivars Geronimo, Massada, Trust, and Rebelski had consistent yields in the final 2 years of the experiment, while Brandywine, which Fig. 1. Radar plots depicting the relative differences for six performance variables among tomato cultivars grown in a high tunnel cultivar trial from 2011 to 2013 in Durham, NH. Each axis represents a single variable. The data for each variable have been scaled so that the minimum and maximum observed values are set to 1 and 50, respectively. Each axis value represents a mean of three seasons (note exceptions, see Table 1 for details) and the axes represent (A) the total number of marketable fruit, (B) marketable yield, (C) average individual marketable fruit weight, (D) the percentage marketable fruit by weight, (E) the observed severity of leaf mold, and (F) yield stability or the consistency in production between plots (the inverse of the CV). Yield stability (F) was not calculated if a cultivar was grown <3 years (bottom row). Innermost rings represent the ''least'' or ''lowest'' value relative to other cultivars in the study, and outermost rings the ''most'' or ''highest''; M. Washington = 'Martha Washington'. despite having low yields relative to other cultivars in 2011, maintained the most consistent yield of any cultivar over the entire experiment. We observed stark differences among the cultivars in susceptibility to leaf mold (2012 and 2013) and powdery mildew (2012). When considering both disease resistance and marketable yield results, some cultivars such as Geronimo, Rebelski, and Massada performed very well. Whether the cultivar with the highest yield is the most appropriate choice for growers is a matter of debate. Quality could be measured in many ways, and of particular importance is taste. We conducted multiple informal taste tests each year of the experiment, but unfortunately found a high degree of variability in responses between tests. We observed that the variability exhibited between tasting dates, tasters, and individual tomatoes exceeded detectable differences between the cultivars. With physiological disorders of tomato, the relationship between cause and effect is often complex. For example, the underlying cause of blossom-end rot is a calcium deficiency (Taylor and Locascio, 2004); however, environmental factors that can interact with calcium dynamics, such as water stress, salinity, temperature, and nutrient source and availability, play an important role in this disorder (Cimen et al., 2010;Paradikovic et al., 2010;Saure, 2001;Taylor and Locascio, 2004). Similarly, while cracking disorders may fundamentally be driven by water dynamics (Peet and Willits, 1995), other factors also contribute to the condition (Emmons and Scott, 1997). Despite the underlying complexity, changes in management can mitigate disorders and improve marketable yields. Documenting the susceptibility of cultivars to particular disorders when grown under uniform conditions can be a useful contribution of cultivar trials so that growers can appropriately accept risk or adopt mitigating management strategies. We found stark differences in the prevalence of certain disorders among the cultivars, and addressing these through high tunnel management or cultivar selection could improve yields. Researchers who conduct cultivar trials, regardless of the crop species being evaluated, typically collect and report data on several important crop performance traits. These data are often reported in separate tables or figures. The relative importance of each of these performance traits may be valued and interpreted differently by each grower based on their own personal preference and local growing conditions. Displaying the data from such trials in a way that allows growers to quickly and intuitively compare multiple performance traits simultaneously and between many cultivars may facilitate the ability of growers to select cultivars that best suit their particular needs. Radar plots, therefore, may be a particularly valuable tool for communicating results from cultivar or variety trials to farmers and other stakeholders who must base their decisions on the evaluation of multiple performance criteria. As an example, growers prioritizing both leaf mold resistance and marketable yield might choose between 'Massada', which had more smaller fruit, as compared with 'Geronimo', 'Rebelski', 'Panzer', and 'Imperial 643', which produced fewer larger fruit, depending on their market preferences. Growers prioritizing large size and stable performance might select 'Brandywine', though they would be sacrificing marketable yields. Radar plots are best suited to a suite of quantitative metrics; therefore, it should be noted that, for example, factors such as name recognition and ''fruit quality'' can be equally important as yield to a grower and difficult to incorporate into this graphic. Therefore, cultivars such as Brandywine, Jet Star, or others, may appear undervalued. Additionally, it should also be noted that given the nature of the design of this experiment, intercultivar interactions might have led to observations that may not directly scale up to entire tunnels grown into a single cultivar. For example, the expression of disease symptoms would likely change as a function of the susceptibility of the cultivar and the disease load of other cultivars in the same tunnel. Our results suggest that several of the tomato cultivars examined in the study may be well suited for high tunnel production in the northeastern United States. Future trials should include a greater diversity of cultivars and occur under a greater range of high tunnel management environments so as to be more broadly representative of the diversity of growing environments encountered in high tunnel production systems in the northern New England region. Making the data from these trials available in alternative formats, such as radar plots, may help facilitate the selection of cultivars that are beneficial to farmers and consumers alike.

v3-fos

2019-03-30T13:12:38.995Z

2015-09-22T00:00:00.000Z

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Evaluation of Inbred Lines and Hybrid Maize (Zea mays L.) for Tolerance to Striga hermonthica (Del.) Benth in the Guinea Savanna Agro-Ecological Zone of Ghana Corresponding Author: A. Bawa University for Development Studies, Tamale, Ghana Tel: 0262980190/0243483821 Email: [email protected] Abstract: The study was conducted at the experimental field of the Savanna Agricultural Research Institute (SARI) to screen maize inbred and hybrid lines for Striga tolerance. Maize seeds of hybrid and inbred lines were collected from the West and Central African Maize Collaborative Network (WECAMAN), Boake, La Cote d’Ivoire, for the experiment. The experimental design used was the Randomized Complete Block Design (RCBD) with fourteen treatments replicated four times for the hybrids. For the inbred lines, there were twelve treatments replicated three times. The results of the hybrid experiment indicated that varieties including 9914-14 STR, 8425-8 STR, 9925-49 STR, 9916-11 STR, 9925-3 STR, CLH105 STR and CLH109 STR were comparatively better off than the others in terms of field weight and tolerance to Striga. For the inbred lines, the results indicated that GH110-5, 991228-1 and 991233-1 performed better than the rest of the varieties in terms of yield components such as plant height, days to 50% pollen shed, days to 50% silking and Striga plant rating. On Striga infested Agricultural lands, farmers can therefore use cultivars or varieties like, 9914-14 STR, 8425-8 STR, 9925-49 STR, 991611 STR, 9925-3 STR, CLH105 STR and CLH109 STR or their crosses in order to improve yield and hence maximize profit. Introduction Striga hermonthica (Del.) Benth (Striga) is considered to be one of the major biological constraints to food production in sub-Saharan Africa, probably a more agricultural problem than insects, birds or plant diseases . Over the years, the problem of Striga infestation has intensified across regions in Sub-Saharan Africa for a number of reasons, including: deteriorating soil fertility, shortening of the fallow period, expansion of production into marginal lands with little nutrient input and an increasing trend towards continuous cultivation of one crop in place of the traditional rotation and inter-cropping systems. Striga severely affects an estimated 40 million hectares of land devoted to cereal production in West Africa alone, with additional 70 million hectares having moderate levels of infestation (Lagoke et al., 1991). The annual yield losses due to Striga in the savanna regions alone are estimated to be worth US$7 billion and detrimental to the lives of over 100 million people in Africa (Mboob, 1986). The effects are likely to be long lasting as Striga plants produce millions of tiny seeds that can stay viable in the soil for many years. In Ghana, Striga is a serious problem in areas north of latitude 9 o 30'N, which represents about 57% of the total land area (Nyarko, 1986). The estimated yield losses amount to 4.1 million mega grams of grain in a year. The farm household systems in the northern parts of Ghana rank first in the production of the four major cereals across the country; namely: maize, rice, sorghum and millet (PPMED, 1993). But the production of the cereals is menaced by the threat of low productivity as a result of the parasitic weed, Striga hermonthica (Sauerborn, 1991). According to Sauerborn (1991), records of yield losses caused by Striga hermonthica in Northern Ghana in 1988 amount to 16% for maize, 31% for millet and 29% for sorghum, representing a total economic loss of US$25 million for the three crops. Under heavy infestation, maize is more vulnerable to Striga parasitism than upland rice, sorghum and millet, with high losses in excess of 90% (Efron et al., 1989). Striga infestation can cause yield losses of 20-100% in maize, driving some farmers to give up cultivation of the crop entirely. Almost all the farm fields of every district in the northern parts of Ghana are infested with Striga. However, Runge-Metzger et al. (1997) stated that the state of knowledge with respect to the severity of Striga infestation, its geographical distribution in northern Ghana and its current trend is still extremely unsatisfactory. In spite of the problem of Striga infestation, the cultivation of maize cannot be halted, since the crop is a major source of food for the people of Ghana and Africa in general. Maize is a staple food that constitutes the main diet of many people in the tropical and subtropical Africa (Oyekan et al., 1990). Its importance has increased as it has replaced other food staples, particularly sorghum and millet (Smith et al., 1994) and it has also become a major source of cash for smallholder farmers (Smith et al., 1997). Maize is also the widely consumed staple food with increasing production in Ghana since 1965(FAO, 2008Morris et al., 1999). It is an important cereal produced in all the five agroecological zones of Ghana (Obeng-Bio et al., 2011). Analysis based on 1987 maize consumption data in Ghana showed that maize and maize based foods accounted for 10.8% of food expenditure by the poor and 10.3% of food expenditure by all income groups (SARI, 1996). Breeding for Striga tolerance in maize may improve the performance of the crop even under Striga infested conditions and hence, increase the yield of maize. The objective of this study was to screen the inbred and hybrid lines of maize for tolerance to Striga hermonthica in the Northern Guinea Savanna Agroecological Zone of Ghana. Land preparation, Planting and Experimental Design The experiments were conducted at the experimental field of the Savanna Agricultural Research Institute (SARI) in the Northern Region of Ghana. The land was prepared by ploughing, after which all debris were removed. Land demarcation was done using lining and pegs. The prepared land was leveled using a hoe before seeds of the genotypes were planted. Twenty six maize genotypes consisting of 12 inbred lines and 14 hybrids from West and Central African Maize Collaborative Network (WECAMAN), Boake, La Cote d'Ivoire, were obtained from the Savannah Agricultural Research Institute (SARI), Nyankpala of the Council for Scientific and Industrial Research (CSIR) and screened for tolerance to Striga hermonthica during the 2012 cropping season under field experimental conditions. The inbred lines used for the study were: 991222-1, 991222-2, 991228-1, 991226-34, 991233-1, 991233-2, 991233-3, 991238-1, 9030STR, 9450STR, 5057 (SUSC) and GH110-5 (a check), whilst the hybrids used were: CLH105STR = 87036 X 88094,CLH109STR = 87036 X ENTRADA 29,. In this experiment, maize and Striga seeds were both planted at stake on the prepared plots using 1% germinable Striga seed-sand mixture based on predetermined 70% purity and 65% germination of the Striga seed according to the procedure of (IITA, 1991). In the field studies, there were non-striga inoculated plants which served as the control plants. The inbred treatments were replicated three times in each case in the chosen designs, while the hybrid lines were replicated four times. Fine sand, sieved through a 250 µm sieve was used to formulate the 1% germinable Striga seedsand mixture. The sand-Striga mixture was applied at approximately 2,500 germinable Striga seeds to each maize hole. The intensity of Striga infection on the individual maize genotypes was then assessed visually and scores attached to the various maize genotypes. The implication is that a genotype that scores/rates 1 or 2 is tolerant to Striga. A score/rate of 3 or higher indicates susceptibility of genotype to Striga infestation. Cultural Practices Basal fertilizer was applied at 2 weeks after planting at the rate of 30 kg N ha -1 and 60 kg P 2 O 5 ha -1 . Plants were also top-dressed with additional N at 30 kg N ha -1 at 4 weeks after planting. Pre-emergence chemical weed control was used. An application of a combination of Pendimethalin [N-(1-ethylpropyl) -3, 4 -dimethyl -2, 6 -dinitrobenzenamine] and Gesaprim [2-chloro -4 -(ethylamino) -6-(isopropylamino) -5-triazine] at a rate of 1.5 l ha -1 and 1.0 l ha −1 were used at planting. Where there was heavy weed growth prior to planting, Paraquat (1, 1-dimethyl -4, 4 -bipyridinium ion) was also applied at 1.0 l ha -1 in addition to Pendimethalin and Gesaprim. Hand weeding was also carried out to keep the experimental field free of weeds at 4 weeks after planting. Data Collection and Analysis Measurements were made of growing crop parameters between flowering and physiological maturity for the field studies during the 2012 cropping season. These parameters include: plant height, days to 50% pollen shed, days to 50% silking, ear height, Striga count at 8 and 10 weeks, Striga plant rating at 10 weeks, plant stand, stem lodging and grain yield. The data collected were subjected to Analysis of Variance (ANOVA) using Genstat statistical package and means separated using the Least Significant Difference (LSD) at 5% level of probability. The study revealed significant differences (p<0.01) in plant heights among the infested (Table 2) and noninfested inbred lines (Table 3). The differences in plant height may not have been attributed only to differences in levels of soil fertility of the experimental field and variation of host plant resistant mechanisms but also germination or haustorial initiation of Striga. In most infertile soils, Striga number goes down most probably due to fewer attachment sites on a malnourished host to sustain as much parasite (Ikie et al., 2007;Ransom et al., 1999). Stewart and Press (1990) also reported that Striga germination, attachment and haustorial formation all are dependent on Striga seeds receiving chemical cues from host roots. Siame et al. (1993) further observed that the major Striga germinating stimulant from maize and sorghum is sorgolactone and the minor stimulants are structurally related to strigol. It is therefore possible that all these stimulants were produced by some of the cultivars causing Striga seeds to germinate. The results of the study indicated that most of the genotypes grown in the infested plots were shorter than their counterpart in the non-infested plots ( Table 1). The observation made here is a clear manifestation that Striga hermonthica had caused reduction in the growth of the host plants as a result of reduction in photosynthetic capacity to less than half of that occurring in healthy plants (Press and Graves, 1991). It is estimated that this reduction in photosynthesis in the host results in 80-85% growth reduction in infested maize and sorghum, whilst 20% of the damage is as a result of the actual removal of carbon by the parasite (Graves et al., 1989;. Striga might have also acted not only as an additional sink but probably also had a strong 'toxic' or 'pathological' effect on the host and hence causing the reduction in growth and development of the host. Graves et al. (1989) stated that this parasitic plant induces reduction in host photosynthesis and this has been the most important mechanism of growth reduction. The authors also reported that about 80% of the decrease in host growth rate could be attributed to the impact Striga has on host photosynthesis. The results showed that the genotype, 991228-1, took a maximum of 78 days to produce silk among the infested inbred plants, followed by 991233-2 (73 days), 991238-1(73 days) and 991233-1 (71 days). A minimum of 25 days was taken by 9030 STR to silk. The genotypes 991222-1 and 5057 (SUSC) in the infested plot did not produce silk ( Table 1). The failure of some of the genotypes to produce silk might be due to the problem of susceptibility to Striga and/or low soil fertility. For the non-infested inbred lines, the results indicated that the highest number of days for silk production was produced by 5057 (SUSC) (74 days), whilst the lowest number of 24 days was produced by 991226-34 (Table 1). In general, silk production was better in the non-infested inbred lines than their infested counter parts. For the combined analysis of the days to 50% silking, 991228-1 took the highest of 74 days to silk, followed by 991233-2, 991238-1, 991233-1 and GH110-5, with 69 days, 68 days, 68 days and 66 days respectively. The genotype 991226-34 took the lowest days of 26 to produce silk. However, there were no significant differences (p>0.05) among 991228-1, 991233-2, 991238-1, 991233-1, GH110-5, 9450 STR, 991233-3 and 991222-2. Among the Striga-infested hybrids, the observation was that the genotypes 9925-51 STR and 8338-1 (SUSC) took a maximum of 68 days each for 50% silking, followed by 9916-2 STR (67 days), CLH111 STR (67 days), CLH105 STR (67 days) and CLH 109 STR (66 days). However, a minimum of 64 days each was taken by 9925-4 STR and 9914-14 STR to produce silk (Table 4). There were however, no significant differences (p>0.05) among 9925-4 STR, 9914-14 STR, 8425-8 STR, 9925-49 STR, 9916-11 STR, 9925-3 STR, 9922-13 STR and 9914-59 STR. It was also observed that CLH111 STR took a maximum of 66 days for silk production among the non-infested hybrids, whilst a minimum of 63 days each was taken by 9925-4 STR, 9922-13 STR, 9914-59 STR, 9914-14 STR, 8425-8 STR, 9925-49 STR, 9925-3 STR and 9916-11 STR (Table 4). Silk production was generally more encouraging in the entire non-infested plots than in the infested plots. For the combined analysis of days to 50% silking among the hybrids, CLH111 STR and 9925-51 STR took a maximum of 67 days each, whilst a minimum of 63 days each was taken by 9925-4 STR and 9914-14 STR for silk production. (Table 4). Days required for silking along with other maturity traits are commonly used by plant breeders as basis of determining maturity of maize. The study established highly significant differences (p<0.001) in the number of days for silk production among genotypes within the infested (Table 5) and non-infested (Table 6) hybrid maize. The infested genotypes generally took higher number of days to reach silking than non-infested genotypes ( Table 4). The Striga infestation could have induced the prolonged period of silking among the infested plants. The observed trend in silking among the Striga infested genotypes could be attributed to differences in the levels of Striga tolerance among the infested genotypes. Silk production was generally more encouraging in the noninfested plots than in the infested plots. To aid the selection process, it is always essential to have the information on nature of association of characters with economic yield. The data for correlation studies at the phenotypic level showed that grain yield exhibited negative and significant (p<0.01) correlation with days to 50% silking (Table 7). This implies that grain yield is likely to increase with decrease in days to silking. This finding corroborates the observation made by Banziger et al. (1999) that days to silking and anthesissilking interval are important traits that influence maize yield under serious stress. Maximum grain yield is the prime objective in most breeding programs. The results revealed a clear impact of Striga infection on grain yield. There was a significant (p<0.05) variation in grain yield among the non-infested as well as the Striga-infested hybrids. The yields produced in the non-infested plots were generally higher than those in the infested plots. There was also a statistical difference (p<0.05) in grain yield among the non-infested inbred lines. In general, grain yield is determined by the levels of tolerance of the host genotype, by severity of infestation and/or by the levels of soil fertility. Kim et al. (2002) reported that tolerant varieties suffer lower yield reduction and often produce 2 -2.5 times the yield of susceptible varieties, especially under high infestation. Okonkwo (1966) attributed grain yield losses to the diversion of photosynthates, mineral salts and water from the host to the parasite. The data for correlation studies at the phenotypic level showed that grain yield exhibited positive and significant (p<0.01) correlation with plant height (Table 7). This implies that grain yield is likely to increase with increase in plant height. However, the correlation studies established that grain yield exhibited negative and significant (p<0.001) correlation with Striga plant rating. This implies that grain yield is likely to increase with decrease in Striga plant rating. The grain yield for inbred lines grown in the noninfested plots showed that genotype GH110-5 produced the highest grain yield (4.27 tons/ha), this was followed by 5057 (SUSC) (0.99 tons/ha), 991233-2 (0.88 tons/ha), 9938-1 (0.88 tons/ha) and 991233-1 (0.80 tons/ha). Genotype 991226-34 produced the lowest grain yield of 0.19 tons/ha (Table 8). There was a significant difference (p<0.05) between GH110-5 and all the other genotypes. No grain yield was produced from the infested plots. The infestation of the field with Striga might have contributed to the zero grain yields of the inbred lines. Among the inbred maize, genotypes GH110-5 and 991233-1 had equal Striga plant rating of 4 (Table 8). This means that their ability to tolerate Striga was equal. The rating of the other genotypes was 5 each. This indicates that GH110-5 and 991233-1 are more tolerance to Striga than the rest of the genotypes. Results from the mean Striga plant rating of the infested hybrids indicated that ten of the hybrid genotypes: 9916-2 STR, 8338-1 (SUSC), CLH111 STR, were rated 4, whilst the rest of the genotypes were rated 3 ( Table 9). The implication is that all the genotypes that were rated lower are more tolerant to Striga than those with higher rating. Adeosun et al. (2001) had described Striga emergence and Striga count as parameters to assess the tolerance level of crop genotypes. However, Kim (1994) recommended the use of Striga rating in assessing crop genotypes for tolerance to Striga infestation. The study showed a significant variation among Striga infested genotypes for Striga rating, which could have been attributed to variation in the ability of the plants to resist Striga infestation. Ejeta et al. (1999) reported that the development of necrotic lesions on the root of maize causes poor development leading to the death of attached Striga on the host. Lynn and Chang (1990) also observed that the high tolerance to Striga of some genotypes may be due to the low production of host plant root exudate compounds that are essential for Striga seed germination. The study further showed that Striga plant rating was negatively and highly significantly associated (p<0.001) with grain yield ( Table 7). The implication is that grain yield is likely to increase with a decrease in Striga plant rating. ------------------------------------------------ The study indicated that among the Striga-infested hybrid plots, the genotype 9925-51 STR took 65 days to shed pollen, this was followed by CLH111 STR (64 days), CLH109 STR (63 days) and 9916-2 STR (63 days). Whilst the lowest of 61 days each was taken by 9914-14 STR, 8425-8 STR and 9925-4 STR to shed pollen (Table 9). There were no significant differences (p>0.05) among 9914-14 STR, 8425-8 STR, 9925-4 STR, 9925-49 STR, 9916-11 STR, 9925-3 STR, 9914-59 STR, 9922-13 STR, CLH105 STR and 8338-1(SUSC). For days to 50% pollen shed among the non-infested hybrid maize, the genotypes CLH111 STR and 9925-51 STR took a maximum of 63 days each, whilst 9916-11 STR, 9914-14 STR, 9925-49 STR and 9925-4 STR took a minimum of 61 days each to shed pollen. However, there were no significant differences (p>0.05) among , 9925-3 STR, 9916-2 STR and CLH109 STR ( Table 9). The number of days to 50% pollen shed was generally higher for all the hybrids in the Striga-infested plots than in the non-infested plots. The disparity in the number of days to 50% pollen shed could be attributed to the Striga infestation. In the combined analysis of days to 50% pollen shed, 9925-51 STR and CLH111 STR took 64 days to shed pollen, while 9914-14 STR, 9925-4 STR, 8425-8 STR, 9916-11 STR and 9925-49 STR took 61 days each to shed pollen. There were no significant differences (p>0.05) among with regards to days to pollen shed. The data for correlation studies showed that grain yield exhibited negative and significant (p<0.01) correlation with days to 50% pollen shed (Table 7). This implies that grain yield is likely to increase with decrease in number of days to pollen shed. The study established that among the non-infested hybrid maize, the genotype 9925-51 STR produced the highest ear height of 87 cm, whilst the lowest ear height of 59 cm was produced by 9925-4 STR (Table 9). There were however no significant differences among the hybrids 9925-51 STR, 9916-2 STR, 9916-11 STR, CLH105 STR and CLH109 STR for ear height. The study established that the ear heights of the hybrid plants significantly (p<0.05) varied from one genotype to the other among the non-infested plots. Ali et al. (2011) confirmed this and reported that shorter ear heights are generally not desirable. This is because the problem of crowded canopy, aeration and low transmission of sun light to the lower parts may result in drastic reduction in yield. The findings of Menyonga et al. (1987) were on the contrary. They observed that greater ear height is undesirable because the ear placement at a greater height from the ground level exerts pressure on plant during grain filling and physiological maturity and causes lodging, which could ultimately affect the final yield. Conclusion and Recommendations The experiment was conducted to screen maize inbred and hybrid lines for Striga tolerance. From the foregoing results and discussion of the experiment, the following conclusions were deduced: The inbred lines (GH110-5, 991228-1 and 991233-1) produced the best results with reference to plant height, days to 50% silking, days to 50% pollen shed, Striga plant rating and plant stand. Therefore, the three inbred lines are likely to be more tolerant to Striga than their counterparts.

v3-fos

2018-12-27T07:46:25.844Z

2015-09-23T00:00:00.000Z

54752779

s2

Analysis of The Heat Island Phenomenon in Makassar, South Sulawesi, Indonesia Corresponding Author: Rosmini Maru Department of Geography, Faculty of Mathematics and Natural Sciences, State University of Makassar, Indonesia Email: [email protected] Abstract: Urban Heat Island phenomenon (UHI) is one of the city microclimate phenomenon that mostly hit many big cities in the World, including Makassar, Indonesia. Therefore, this study aimed to analyze the phenomenon of UHI and UHII in Makassar and the surrounding areas. The method used in this study is the analysis of primary data through measurements taken directly to the varied station locations. The measurements are determined by purposive sampling toward the variety of different land uses. The measurements were taken at 11:00 am until 1:00 pm Central Indonesian Time (WITA) and at night from 09.00 to 11.00 pm. The results showed that the mean temperature was 31.29°C during the day and 27.4°C at night. Spatially, the day time showed that the high temperatures (32 to 35°C) are generally located in the downtown areas which are crowded with buildings such as residential, offices and shops. Meanwhile, a lower temperature (29 to 31°C) is generally located in countrysides or outside the city in the form of green areas and open land. The results show that a fairly high temperature causes the comfort of the city the temperatures reduced. Therefore, handle UHI phenomenon needs to be done in an integrated and sustainable. Introduction Based on the monitoring results of the Meteorology and Geophysics Agency (BMG), it is known that at the present time, there has been a shift in weather patterns. For example, it has experienced a rainy season during the year which are recognized as La-Nina storms in 2010. In contrast, the prolonged dry season with a high enough temperature caused by the low air temperature in the Pacific Ocean and the lower part of atmospheric temperatures known as El-Nino storms (Sellers and Robinson, 1986). Both are frequent disasters struck Indonesia, especially El-Nino. The phenomenon has several times happened in Indonesia in general and South Sulawesi in particular. Extreme events is different than usual as the influence of meteorological conditions that are not balanced. According to the Purnomohadi (1995) the state meteorological unbalanced can be caused by increased greenhouse gases. The increase in these gases especially CO 2 in the atmosphere and the Earth's surface has led to the change of weather patterns and rising temperatures or global warming. Furthermore, the situation can give effect to an increase in temperature of the Earth's surface. The phenomenon of significant temperature increases mainly occurred in major cities in the World. An increase in temperature the city phenomenon commonly referred to as the Urban Heat Island (UHI). Said to be the UHI because when viewed from above then the phenomenon is shaped like the island with the core at the center of the city (Fig. 1). This phenomenon is not only influenced by greenhouse gases or global warming, however this phenomenon more caused by various properties and the surface shape of the city as an area dominated by buildings made of concrete. The situation is aggravated with increased anthropogenic activity that happened in the city area (Ahmad and Hashim, 2010;Purnomohadi, 1995). This is in line with Auliciems (1997) that global warming also together with anthropogenic heat increases the temperature of the city. The process of urbanization as a result impact of anthropogenic activities to reduced use of natural land into developed regions (Oke 1987;Tso 1994;Vaughan and dan Cracnell, 1992). (Voogt, 2002) This according to the results of the study Kusaka and Kimura (2004) in Tokyo, Memon et al. (2010) in Hong Kong and Jusuf et al. (2007) in Singapore showed that the influence of anthropogenic factors and cover the surface of the soil is very large while the impact rather than just reaching 0.15°C albedo. The amount of anthropogenic influences seemed to give the impression to the less important of the other factors. Therefore, several studies suggest that greenhouse gases which have been referred to as the main cause of global warming, it does not provide influence which is significant to the occurrence of UHI phenomenon, experienced by various cities in this world. Statistical analysis by Ozdemir et al. (2012) in the Anatolian Peninsula, Europe explained that, there was no significant increase in the daily minimum temperature in the period 1965 to 2006 in the rural areas. Whenever, in the city has increased significantly to reach an increase of 5°C. The phenomenon of rising temperatures in urban areas as tangible evidence of the occurrence of the phenomenon of UHI in the region. This study concluded that global warming in this case the emissions of CO 2 in the atmosphere rather than as the main causes of the phenomenon of UHI. Various studies related to the results of the study, including by Borthakur and Nath (2012) at Metropolitan Guwahati, Lo and Quattrochi (2003) in Georgia, Golden (2004) in Phoenix, Arizona and Effendy et al. (2006) in Greater Jakarta Indonesia. Results of their study confirms that the occurrence of UHI phenomenon is caused by changes in land use which is significant in the city area. Changes in land use causing an increase in surface temperature in urban areas. Therefore, the urban area of the temperature becomes higher than the surrounding area commonly referred to as the phenomenon of the Urban Heat Island (UHI). That has been true in many areas in the city such as Kuala Lumpur in 1988, namely a simple pattern of high temperature (29-32°C) scattered about across the study area. Meanwhile, high temperatures exceeding 32°C prevailing around town Kepong-Jinjang (Ahmad and Hashim 2010). The development of UHI phenomenon in many major cities in the World interest in climate experts to study in depth and perform the quantification of the phenomenon. Therefore, various methods are used, including direct measurement and secondary data analysis done by Maru and Ahmad (2014a;2014b) in Jakarta, Kershaw et al. (2010) in the UK. Another method is where the satellite imagery as performed by Liu and Zhang (2011). Although methods is vary, but all show that has a high temperature prevailing in the downtown area while lower temperatures occurred outside the city. UHI phenomenon more widespread causing loss can even cause death. As a study conducted by Johnson and Wilson (2009) in Philadelphia, USA showed that the concentration of the population died in the area of high UHI. He also explained that other variables also showed that there is influence between poverty with UHI phenomenon prevailing in the study area. Although, it has been known that greenhouse gases are not significant influence to the increase of UHI but if it is valid continuously it will provide a greater negative impact. In accordance with the views Intergovermental Panel on Climate Change (IPCC) (IPCC, 2014) that the increase in greenhouse gases will continue to rise causing an increase in temperature continuously and persist for a long time. In addition, the phenomenon of UHI requires serious attention because it affects the various aspects of community life such as changes in cropping patterns, lower levels of comfort, the emergence of various kinds of diseases, the explosion of various pests include locusts wanderer on the island of Sumba, East Nusa Tenggara and Lampung (Ahmad et al., 2014), the explosion of caterpillar population in some areas of Indonesia (Wadrianto, 2015), a giant jelly fish attacks in Japan at the present time. Therefore, this research is important to provide early information on the existence and development of the UHI in Makassar, so the handler can be done quickly and accurately. According to Purnomohadi (1995), unbalanced meteorological conditions can be caused by increasing greenhouse gases. The increase in these gases, especially CO 2 in the atmosphere and the Earth's surface causes the increase in temperature and the changes in weather patterns. The high temperature with an increasingly widespread HI phenomenon causes damages. One element of a highly influential climate change is an increase in temperature. According to Intergovernmental Panel on Climate Change (IPCC) (IPCC, 2014) that the increase in greenhouse gases will continue to rise causing an increase in temperature continuously and persist for a long time. The increase in temperature and UHI phenomenon occurs in various regions in Indonesia and even in various regions on the Earth's surface, but because the vast territory this study will only focus on one area that is thought to have the potential rate of increase in temperature and a very fast UHI phenomenon that is in the Makassar. Moreover, according to Ahmad et al. (2014), Makassar is included in the classification of high drought index (>33.3%). The problem is approached geographically by using an ecological approach and spatial approach. Ecological approach is intended to analyze the increase of the heat island phenomenon with a variety of causes and impacts. While the spatial approach is intended to analyze the areas that experienced the phenomenon of UHI and the intensity of the various land use patterns. Materials and Methods This study focused on the Makassar which is located in the south arm of South Sulawesi, namely on the west coast. Therefore, this region is dominated by a rather gentle topography with a height of between 0 to 20 meters above sea level (msl). Makassar City is the largest and most populous city in eastern Indonesia. Moreover, according to Ahmad at al. (2014), that the City of Makassar belongs to the class of the drought index is high. Therefore, this area has the potential rate of increase in temperature and a very fast UHI phenomenon in Indonesian eastern portion. Studies in this area will be approached to analyze the spatial and ecological areas that experienced the phenomenon of UHI and intensity of the various land use patterns. The tools used in this study, are as follows: A set of computers or laptops that are used to analyze the data both secondary data and primary data, so that the obtained results of the study. Geographic Position System (GPS) MAP62st large type that is used to determine the location or position than the measurement locations making it easy to put in the picture. Subsequently, the temperature was measured at each location by using the mercury thermometer of four pieces. Although the tool is simple but it can be used to measure the temperature with good results in the area of study. Olympus E-500 Kit type digital cameras are used to record the situation rather than the location of measurement. In addition, no less important is the motorcycle as much as four. This type of vehicle is used to facilitate the study reach all locations in a short time, so that measurements can be made at all locations with a predetermined time. Meanwhile, the materials used in this study are: Administrative maps of Makassar and the surrounding areas, landsat imagery, land use maps of Makassar and observation sheet. This is done to analyze the relationship between the type of land use with the UHI phenomenon that occurs Makassar City area. This study involved the collection of primary data and secondary data. Primary data collection was the direct measurement to the air temperature in the study area (Fig. 2) using a mercury thermometer. Based rather than one of the objectives of this study is to see the tops of the heat island in Makassar, the time measurements carried out in June 2014. This is done because of Makassar is one of the town, which is located in eastern Indonesia which has two seasons: The rainy season and dry season in accordance with the rainfall in the region (Fadholi, 2012). The rainy season lasts between August and March, while the dry season lasts from April to July. Keep in mind that the surface temperature also depends on the second season, which in the dry season usually hot reception on the Earth's surface is much higher than during the rainy season. Therefore, the peaks of heat is expected to occur between April and July is the June. In addition, measurements carried out on weekdays because several studies including by Ohashi et al. (2006) states that the waste heat from the air conditioning has led to the increase in temperature of 1-2°C or more on weekdays in the office area of Tokyo. Therefore, to maximize the findings of the tops of the heat the measurements are made on weekdays. This study begins with a review of the literature that is read and studied a variety of related sources such as relevant books, articles and reports the results of research both within and outside the country like in Kuala Lumpur, Tokyo, Singapore and the others. Furthermore, the administrative map making and land use are made based on Landsat imagery and data administration of Makassar. This is done to make it easier to determine the locations of measurement. Based on study results Ahmad at al. (2011) who showed that land use can affect the surface temperature distribution, the measurement locations are set according to different land use that is farmland, ricefield, embankment, settlements, water bodies, shrubs and savannas. Fig. 2. Map location of measurement Determining the location of the measurement is made in proportion purposive sampling, where the number of measurement points is determined based on the breadth of each land use in accordance with the needs and affordability. The measurement locations are shown in Fig. 2. In addition to measurements, also conducted interviews with the people of Makassar by using the interview guide. This is done to determine how much public knowledge about the occurrence of an increase in temperature in the city of Makassar. In addition, also known how perceptions and patterns of their lives to comfort temperature in the city of Makassar in everyday life. Various secondary data employed in this research were gained from many instances under the authority of the Province of South Sulawesi and its surroundings, such as administration map in Development Planning Agency at Sub-National Level (BAPPEDA), citra landsat in National Institute of Aeronautics and Space (LAPAN), Earth surface's map in National Land Survey Coordinating Board (BAKOSURTANAL), the land use map in land affairs instance. Those data were used for the need of analysis in order to make accurate conclusion. The data obtained is used as an input for temperature mapping. Furthermore, these data are used to analyze the phenomenon of UHI in Makassar using 'kriging interpolation method' is one method of interpolation that connects the points that have the same temperature on the surface of the Earth. The final result obtained is an isotherm map of Makassar in the afternoon and the evening. The Isotherm of Makassar Isotherm is the line that connects the points on the surface of the Earth that have the same temperature ( Fig. 3 and 4). Figure 3 illustrates the temperature distribution map of Makassar in the day. Temperatures during the day range from 29 to 35°C. It also spatially showed that high temperatures (32 to 35°C) are generally located in the downtown area which are densely filled by buildings such as residences, offices and shops. Meanwhile, lower temperatures (29 to 31°C) in general are in the edge region and outside the city in the form of green areas and open land. Furthermore, the temperature at night time is shown by Fig. 4. The temperature of night time is lower than that of the day. The temperature at night time only range between 24 to 28°C. Temperature distribution pattern shows a similar trend during the day in which high temperatures are generally felt in the city center, while low temperature is from the edge to the outside of Makassar. At night time, temperature of the coastal area is higher than that of the other regions. This phenomenon is caused by onshore winds during the night and the sea breeze during the day. Therefore, the temperature of the beach at night was still warm, otherwise the day was cool. Based on both isotherm either by day or night, it is known also UHII Makassar City is 6.0°C during the day and 0.8°C at night. Temperature and Land Use Urbanization problem is a problem for several major cities in Indonesia, including Makassar. The reputation of Makassar as the administrative capital, the city of commerce and the city of education has attracted the people from outside the city to come into Makassar City. This migration takes place every year causing considerably high population density. As the consequence there was an increase in the number of basic needs to people such as public facility, housing and the other such items. This causes the increase of developing area of the region. One of the results of the study showed that the highest temperature happened in housing areas and savanna (Table 1 and Fig. 5). In general, the temperature during the day is higher than the temperature at night in Makassar. This is in accordance with Table 1 and Fig. 5 that the average air temperature during the day was 31.1°C with high air temperature is 32.5°C in the ponds and 31.5°C in the settlement area/office. Conversely, a low temperature was 29.4°C which occurs on land use bush/shrub and water bodies that is 29°C. In contrast, the average temperature in the city of Makassar at night time was 26.7°C the highest temperature was 27.1°C in the area of water bodies with the lowest temperature was 25.5°C in the savanna region. Discussion Spatially known that there is a difference in temperature between the central region, the edge and the outside the city of Makassar which is commonly known as the Urban Heat Island Intensity (UHII). Based on this, the results of the study indicate that UHII of Makassar is 6.0°C during the day and 0.8°C at night. The results of this study are very high when compared with the opinions (Hidayati, 1990;Kartojo, 1992;Santoso, 1998) that in tropical regions such as Indonesia, Malaysia, Singapore, Thailand, Laos and the others. The results of the studies in various cities in these countries demonstrate the value of UHI between 0.02 to 1°C. The results of this study were higher than the results of the study in the city of Jakarta, namely 2.1°C in the north to the south and 1.6°C for east west direction (Maru and Ahmad, 2014a;2014b). It is appropriate as well the results of the study by Jamei and Ossen (2012) in Melaka, Malaysia. Results of studies find that the core area of the city is hotter than the expansion area. The high level of UHII in Makassar is caused by several factors; among them is the weather. At the time of measuring the temperature, it was raining in outside of the city, but sunny in town. In addition, the density of the buildings in the city caused the sheltering effect. This phenomenon leads to deposits in the heat of the city. This further increased the number of high-rise buildings causing the heat can't escape into the atmosphere. Finally, an increase in heat is called the UHI phenomenon in Makassar. Based on these results the development of the UHI phenomenon in Makassar is already on par with other major cities in the subtropical region. This, according to Givoni (1998) that some of the results of the study in the subtropical region, that UHII can reach 3 to 5°C during the day and 8 to 10°C at night. Similar to the findings Streutker (2003) in Houston, Texas (USA); and Svensson and Eliasson (2002) in the city of Gothenburg; and Zeng et al. (2009) in Nanjing. This study uses satellite data, for the entire period of 13 years (1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999) he received an increase in temperature during the day reaches 0 to 8°C. Currently, the construction of roads, offices and housing in the city of Makassar can no longer be avoided. This situation, of course led to the increasing of UHI pheomenon and the UHII values in the region. Therefore, it needs to get serious attention from government, private institutions and society. Governments need to create policies regarding the development of green technologies such as procurement of Green Open Space (GOS), city parks, parking lots using grass and energy-saving movement. Meanwhile, the public can make a roof curtain, green walls, green gardens and multiply water bodies like showers near the house or the offices. This can increase the moisture in the city and can further reduce the rate of heat and UHI phenomenon in Makassar. UHI phenomenon is one of the microclimate phenomenon in urban area that is happening in several big cities in the World, including in Indonesia, particularly in the city of Makassar. This phenomenon is characterized by higher temperatures in the city if compared to the surrounding area or out of the city. The results of interviews with some respondents also showed that the level of comfort in Makassar have decreased due to the high temperatures. It was proved by the results of measurements done during the day and night which shows that the average temperature of Makassar is 31.29°C at the day time and 27.04°C at night. The study carried out by Maru and Ahmad (2012) showed that the average temperature in Makassar is found lower than in Jakarta, although the UHII of Makassar is higher than that of Jakarta. One result of the study was that the average temperature during the weekdays in Utan Kayu (UK) (settlements) was 32.8°C with the maximum and minimum temperature were 34.9°C which was recorded at 14:00 pm and 29.1°C which was recorded at 06.00 pm., respectively. Wycherley (1967) stated that the most optimum temperature reception in the tropical area is 20.8-22.8°C. Based on the criteria the temperature in the city of Makassar was considered very high and led to the decreasing level of comfort in the area. This phenomenon gives effect to the increased use of Air Conditioner (AC), fans and others. Furthermore, it does not directly have an impact on the increased use of electricity for the community. Some respondents who were in the city center were interviewed and they say that the current temperature is so high that they had to use air conditioning and ceiling fans in both the daytime or night time. Lifestyle like exactly will increase the rate UHII phenomenon in urban areas. This is supported by the results of the study indicate that there is a spatial relationship between land use with the ambient temperature in the city of Makassar. High temperatures in the savannah during the day is the effect of the solar radiation, because the measurement time no shelter. Meanwhile, the area of the settlement is the result of a trap heat in the city that can, t be directly out of buildings or residential buildings or offices even experienced repeated reflection, thus causing an increase in temperature in the region. Instead, the results of the study showed that low temperatures occur in the area of water bodies. This is due to the high evaporation in the region causes the surface to become moist air so as to reduce the phenomenon of islands in the region. Based on this, the few studies have shown that the addition of water bodies is one attempt to address the increasing UHI phenomenon such as the study by Steeneveld et al. (2013) in Rotterdam. The results of the study showed that the water bodies can reduce the UHI phenomenon. In addition, the canopy structure also need to be considered in determining the surface temperature (Tan et al., 2010). Conversely, at night apply a different matter where the highest temperatures prevailing in the area of water bodies. According to Steeneveld et al. (2013) that the nature of the water is slow to accept and slow release heat seem to apply in this area. At night time the water body while releasing heat into the atmosphere causing surface temperatures are still warm at the time of measurement. Another phenomenon is the cloud cover. If the surface temperature is seen as one of the effects of the light of the sun, the cloud cover can reduce the heat on the surface of the Earth, because it is less exposed to sunlight. However, based on some of the results of such studies by Hanson et al. (1967) shows that the temperature of the Earth's surface caused by the reflection of heat from the Earth's surface. Meanwhile, cloud cover in the atmosphere blocking the release of heat or pollution to the atmosphere. Therefore, cloud cover can increase the surface temperature. It can be felt at the time before the rain which at that time the sun was not up to the Earth's surface, but still hot. It shows that the heat emitted by the Earth is not completely escape into the atmosphere causing surface temperatures are lower layers of the atmosphere is increased Today, the results of studies on the phenomenon of rising temperatures, such as the UHI has been much discussed especially in many large cities in the World. But in Indonesia, particularly in Makassar is still very limited. Therefore, this brief study can bring more information to the government and the public to understand about climate change in particular microclimate in the city of Makassar. It is very necessary, because it can be used as an initial or reference information for development planning in the future. As a study conducted by Santeramo et al. (2012) in Syria. The study tries to apply the Delphi method in Farming Systems to prioritize things that are central to risk management in Syria. The study is done to put a proper policy interventions. Finally, the implementation of sustainable development and environmentally friendly. Conclusion Based on the results of the study, then drawn some conclusions as follows, namely: The temperature in the city of Makassar is already relatively high and has exceeded the maximum temperature threshold acceptance. This gives a circumstance reduced impact on the comfort level of the urban community. In addition, the temperature difference daylight to night time in downtown lower than the temperature difference outside the city. This happens because the UHI phenomenon that occurs in the city. Furthermore, an increase in the phenomenon of UHI in Makassar impact to the growing UHII between the center, the edge and outside the city of Makassar. In addition, the study results also showed that there is a spatial relationship between the use of land with the state of the temperature in the city of Makassar. High temperatures occur in residential areas or town centers, conversely low temperatures occur in the area of the water body. However, urbanization in this region very quickly resulting in a change of land use from the original into smaller plots. Therefore, causing the temperature in the region is higher than the surrounding area. Based on the criteria Wycherley show that the temperature in the city of Makassar is considered very high and cause the decreasing level of comfort to the temperature by people in the area. UHI phenomenon is a phenomenon of climate change happened in many cities in the World, including the city of Makassar. This phenomenon should not be underestimated because it can provide an inconvenience for residents of Makassar and the surrounding areas. Therefore, it is necessary to do some efforts in the form of proper mitigation such as maintaining open green spaces, add water bodies, using green technologies like roof curtains, green walls, gardens and others. This study may open up horizons for the government and the community to understand the phenomenon of UHI in Makassar. It can be used as an initial or reference information in development planning in the future, so it can be implemented sustainable development and environmentally friendly.

v3-fos

2017-06-19T09:57:01.444Z

2015-09-24T00:00:00.000Z

16611989

s2

Differential diagnosis of Brucella abortus by real-time PCR based on a single-nucleotide polymorphisms To diagnose brucellosis effectively, many genus- and species-specific detection methods based on PCR have been developed. With conventional PCR assays, real-time PCR techniques have been developed as rapid diagnostic tools. Among them, real-time PCR using hybridization probe (hybprobe) has been recommended for bacteria with high DNA homology among species, with which it is possible to make an accurate diagnosis by means of an amplification curve and melting peak analysis. A hybprobe for B. abortus was designed from a specific single-nucleotide polymorphism (SNP) on the fbaA gene. This probe only showed specific amplification of B. abortus from approximately the 14th cycle, given a melting peak at 69°C. The sensitivity of real-time PCR was revealed to be 20 fg/µl by 10-fold DNA dilution, and the detection limit was 4 CFU in clinical samples. This real-time PCR showed greater sensitivity than that of conventional PCR and previous real-time PCR based on Taqman probe. Therefore, this new real-time PCR assay could be helpful for differentiating B. abortus infection with rapidity and accuracy. Brucellosis is known as a major zoonotic disease that can cause reproductive problems, such as abortion, stillbirth or infertility in livestock and wild animals [14,27]. The genus Brucella consists of ten species; six species (Brucella abortus, B. melitensis, B. suis, B. canis, B. ovis and B. neotomae) considered classic members and four species (B. ceti, B. pinnipedialis, B. microti and B. inopinata) considered atypical types of Brucella. So far, classification of Brucella species has been mainly based on host preferences and classical phenotypic biotyping [14,26]. Moreover, the genus expansion is still being processed, with the recent addition of B. papionis from baboons [26]. In terms of the diagnosis of brucellosis, serological assays and bacterial cultivation have mainly been used. Serologic methods are very sensitive and rapid methods to perform, but sometimes false-positive reactions occur with crossreactive bacteria, such as Yersinia enterocolitica O:9, due to the similar structure of the O-chain in the smooth lipopolysaccharide portion [2,8]. In contrast, bacterial culture is considered a 'gold standard' with high specificity, but it is time-consuming and also requires a highly trained workforce and a well-equipped laboratory due to the biohazard risks with Brucella [25]. To overcome these disadvantages, molecular detection methods have been introduced as an alternative for diagnosing brucellosis. Many genus-or species-specific PCR assays, using 16S rRNA and the bcsp31, IS711 and omp2 genes, have been developed [3-5, 7, 8]. Additionally, various multiplex PCRs that can differentiate at the species level have been established [10,12,13]. All of these molecular detection methods are very effective for detecting Brucella strains [20]. Since the development of conventional PCR assays, real-time PCR and loop-mediated isothermal amplification assay (LAMP)-PCR have been introduced as rapid diagnostic tools. Recently, the application of single nucleotide polymorphisms (SNPs) in the microbiological field has shown some merits for diagnosing bacteria with high homology of their DNA [21]. SNP-based PCR assays have been introduced for differentiating bacterial strains and species [14]. Here, we developed a new real-time PCR assay with a hybprobe from a specific SNP to distinguish B. abortus from other Brucella species. Real-time PCR assay using this hybprobe could diagnose rapidly, using an amplification curve with real-time monitoring, and exactly, using melting peak analysis [7], so it is expected to provide more sensitive, rapid and accurate diagnostic efficiency in detecting B. abortus infection. (17). In addition, all of the Korean B. abortus bv. 1 was obtained from slaughtered cattle with brucellosis beginning in 2008, and the B. canis was from dog-breeding farms during 2002-2011. All of the Brucella isolates were identified by the classical biotyping assay including colony morphology, lysis by phages, oxidase, urease activity, growth on dyes and agglutination with monospecific sera (anti-A, -M and -R) [24] and also confirmed specific bands for Brucella species by the differential multiplex PCR [10]. Genomic DNA for real-time PCR was extracted using a Blood & Tissue kit (Qiagen Ltd., Seoul, South Korea) per the manufacturer's instructions. Bacterial strains and Hybprobe design and real-time PCR conditions: To develop B. abortus-specific real-time PCR assays, comparative sequence analysis, using fbaA gene region in whole genome sequences and/or partial sequences of 22 Brucella reference strains, was performed with the CLC Main Workbench software program version 6.0 (Insillicogen Inc., Aarhus N, Denmark). Based on the new B. abortus-specific SNP sites, the primer and probe sets were designed and developed using BEACON designer (Sigma-Aldrich, St. Louis, MO, U.S.A.). Real-time PCR with hybprobe was performed using 4.0 µl of 5 × genotyping master mix, 0.5 µl of each primer, 0.3 µl of each hybprobe, 13.4 µl of D.W. and 1.0 µl of DNA in a 20 µl total volume. After centrifugation for the removal of bubbles from the PCR plate, amplification and melting curve analysis were conducted using a LightCycler ® 480II (Roche Diagnostic, Mannheim, Germany). The real-time PCR amplification was performed with an initial denaturation step of 95°C for 5 min, followed by 45 cycles of 95°C for 10 sec, 65°C for 15 sec and 68°C for 15 sec. After amplification, melting analysis was performed at between 40°C and 80°C at a rate of increase of 0.1°C. Specificity and sensitivity of real-time PCR assay: The specificity of real-time PCR assay using 22 Brucella reference strains, Brucella isolates and non-Brucella bacteria was assessed (Table 1). Its sensitivity was determined from a DNA concentration of 1 ng/µl to 1 fg/µl by serial 10-fold dilution of the B. abortus 544 reference strain. DNA concentration was measured using a Nanodrop ND-1000 UV/ UVS spectrophotometer (Nanodrop Tech., Wilmington, DE, U.S.A.). These results were compared with those of a 16S rRNA [20] and BaSS-PCR assays [3], which were used to identify Brucella species and B. abortus biovars 1, 2 and 4 conventionally. Detection limits of real-time PCR assay: To compare the analytical sensitivity of real-time PCR assay in the clinical specimens, artificial inoculation using a B. abortus strain in the clinical samples was conducted. Briefly, ten-fold serial dilutions of the B. abortus strain with 0.85% saline were processed into the macerated lymphoid tissue, and then, each spiked sample was cultivated on three tryptic soy agars and was calculated in colony-forming units (CFU). The DNA of the spiked samples was extracted using a commercial blood and tissue kit (Qiagen Ltd.) according to the manufacturer's protocols. Evaluation of real-time PCR assay: To apply real-time PCR assay to the clinical specimens, twelve samples (supramammary, submandibular, inguinal and parotid lymph nodes, testicle and buffy coat) were acquired from seropositive Korean native cattle on a breeding farm ( Table 2). These specimens were ground in 1 ml of PBS buffer and spread onto tryptic soy agar supplemented with 5% bovine serum (GIBCO, Grand Island, NY, U.S.A.) and 5% sheep blood agar for 3-4 days at 37°C and 5% CO 2 . Genomic DNA from 200 µl of ground sample was extracted using a Blood & Tissue kit (Qiagen Ltd.) per the manufacturer's instructions and was submitted to real-time PCR assay. RESULTS B. abortus-specific SNPs were detected at the fbaA gene of B. abortus chromosome II (Genbank accession No. AE 017224), with cytosine changed to thymine at 360432 on B. abortus chromosome II. Based on the sequence of the fbaA gene, a primer set 176 bp in size and a hybprobe with a specific SNP were designed (Table 3). Real-time PCR assay showed a positive reaction only to B. abortus reference strains (biovars 1-6 and 9) and B. abortus organisms from clinical specimens, whereas it yielded negative reactions to other Brucella species and non-Brucella bacterial strains (Table 1 and Fig. 1). Only B. abortus species showed specific amplification from approximately the 14th cycle (Fig. 1a). Additionally, the specific amplification was also confirmed by melting curve analysis. The Tm calling value of B. abortus reference strains and isolates was generated at 69°C. In contrast with this finding, other Brucella species and non-Brucella strains showed less than a low melting peak at a temperature of 62°C (Fig. 1b) Table 1). The sensitivity of real-time PCR was assessed by means of successive 10-fold serial dilution of the genomic DNA of the B. abortus 544 reference strain, and it was revealed to be 20 fg/µl (data not shown). In addition, the detection limit for B. abortus in the clinical samples was 4 CFU/µl. In contrast, the detection limit of conventional BaSS-PCR showed 80 CFU/µl. Our new real-time PCR showed 20 times higher sensitivity than those with BaSS-PCR (Fig. 2), but equal sensitivity to 16S rRNA PCR (data not shown). In addition, the application of the real-time PCR to the clinical specimens was conducted using brucellosis-positive Korean native cattle. Here, B. abortus was isolated from tissue samples, such as various lymph nodes and buffy coats. All of the samples were confirmed as positive by generating a fluorescent signal during real-time PCR ( Table 2). The range of mean Ct ranged between 28 and 30, except for buffy coat, and the Tm values were almost identical to the reference B. abortus 544 strain. DISCUSSION For decades, PCR-based assays have been developed continually as a form of real-time PCR. It is able to detect target microorganisms more sensitively, specifically and rapidly than conventional PCRs [8,23]. Unlike endpoint detection methods, such as agarose gel electrophoresis, real-time PCR is used for the quantitative measurement of amplified products using fluorescence during each PCR cycle. These reactions can be classified into two main types according to the fluorescent dye and the specificity of the PCR [15]. The former uses double-stranded DNA-intercalating dye (e.g., SYBR Green I), and the latter uses fluoroephores that bind to oligonucleotides. This type can be divided into three subtypes depending on the fluorescent molecules: (i) primerprobes; (ii) hydrolysis and hybridization probes; and (iii) analogs of nucleic acids [15]. First, SYBR Green I, as one of the most commonly used DNA-binding dyes, binds to total amounts of DNA generated during PCR, so it can induce specific and non-specific amplification [15,22]. At the same time, Taqman probe is a representative hydrolysis type, and it is designed to bind to a specific site of the target DNA, so it shows greater specificity than SYBR Green I. However, it has the disadvantage that the primer-dimer can be generated even if the primer design is not appropriate. Contrarily, hybprobe-based real-time PCR offers two main advantages: first, it requires two additional probes for binding, so it can show improved specificity to distinguish between closely related strains; second, hybprobe does not rely on the hydrolysis reaction, so melting curve analysis can be applied to differentiate based on the probe Tm [16,17]. Thus, its application has increased in various fields, such as pathogen detection, SNP detection and so on [11,15]. In particular, the application of SNPs in microbial molecular typing has been increasing in the diagnostic field. SNPs in the conserved region can be very strong markers for detecting and differentiating etiological agents specifically. Therefore, we designed a hybprobe from another B. abortusspecific SNP in the conserved fbaA gene, although this gene had been already used in real-time PCR with Taqman probe [6]. With regard to specificity, only B. abortus strains revealed specific amplification curves from the 14th cycle, and Tm was 69°C in our new real-time PCR. Not only other Brucella species but also highly genetically and serologically related bacteria were not amplified. Especially, it yielded a negative reaction from two cross-reactive bacteria by 16S rRNA PCR−O. anthropi and S. aureus [1,9]. In terms of sensitivity using B. abortus DNA, our real time PCR assay was equal to or higher than that of 16S rRNA PCR [20]. In addition, our new real-time PCR showed 20 times higher sensitivity and detected all biovars of B. abortus as compared with BaSS-PCR (Table 1 and Fig. 2). Therefore, this new real-time PCR could be valuable for diagnosing B. abortus infection in terms of its accuracy, specificity and sensitivity. Besides two conventional PCR assays, our new PCR showed improved analytical sensitivity, compared to other real-time PCR assays. Using serially diluted DNA samples, our assay revealed 20 fg, but two previous studies using 5′-nuclease IS711 yielded 150 fg and 250 fg, respectively [18,19]. Additionally, previous real-time PCR based on the same fba gene reported sensitivity of 50 fg or 15 cells [6], which was lower than in our study (20 fg or 4 CFU). However, Bounaadja et al. (2009) [2] reported a 10 times higher detection limit than our assay of 2 fg using three genes (IS711, bcsp31 and per gene), but it was not from clinical samples only from extracted DNA samples. As with clinical specimens, our real-time PCR showed identical results to bacterial isolation with high specificity. Because the genus Brucella is an intracellular bacterium, and the number of bacteria in specimens is usually small [23], a highly sensitive diagnostic technique is required to accurate differential diagnosis. This new real-time PCR could be very useful for directly diagnosing brucellosis caused by B. abortus in infected animals due to the high detection limit. In conclusion, our new real-time PCR based on hybprobe could be an efficient diagnostic technique with high sensitivity and rapidity for B. abortus-infected animals in the field, and it could also be applicable in public health. ACKNOWLEDGMENT. This study was supported by a grant from the Animal and Plant Quarantine Agency (QIA) of the Ministry of Agriculture, Food and Rural Affairs (MA-FRA) of the Republic of Korea during 2012-2014.

v3-fos

2016-06-18T00:14:41.660Z

2015-10-14T00:00:00.000Z

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Review of functional markers for improving cooking, eating, and the nutritional qualities of rice After yield, quality is one of the most important aspects of rice breeding. Preference for rice quality varies among cultures and regions; therefore, rice breeders have to tailor the quality according to the preferences of local consumers. Rice quality assessment requires routine chemical analysis procedures. The advancement of molecular marker technology has revolutionized the strategy in breeding programs. The availability of rice genome sequences and the use of forward and reverse genetics approaches facilitate gene discovery and the deciphering of gene functions. A well-characterized gene is the basis for the development of functional markers, which play an important role in plant genotyping and, in particular, marker-assisted breeding. In addition, functional markers offer advantages that counteract the limitations of random DNA markers. Some functional markers have been applied in marker-assisted breeding programs and have successfully improved rice quality to meet local consumers’ preferences. Although functional markers offer a plethora of advantages over random genetic markers, the development and application of functional markers should be conducted with care. The decreasing cost of sequencing will enable more functional markers for rice quality improvement to be developed, and application of these markers in rice quality breeding programs is highly anticipated. Introduction The important attributes of rice are its cooking and eating qualities, its phytochemicals and its micronutrients. The quality of rice needs to match the preferences of local consumers in order to be acceptable. Generally, Japanese people prefer short and sticky rice, whereas Indians prefer aromatic basmati rice which elongates when cooked. Furthermore, rice quality affects the market value, given that better quality rice is able to fetch a higher premium. Indian basmati rice and Thai jasmine rice are highly priced due to their distinctive aroma when cooked. The growing income and food diversification in Asian countries such as China (Sumner et al., 2001) and some European countries (Ferrero and Nguyen, 2004) have led consumers to prefer better quality rice. While people in some parts of the world seek a better cooking and eating quality of their rice, people in other areas seek improved nutrition. Although micronutrients are only required in small quantities, they are necessary to maintain proper bodily function. In fact, two billion people worldwide suffer from micronutrient deficiencies, particularly in vitamin A, iodine, iron (Fe), and zinc (Zn) (World Health Organization, 2007). Therefore, research has been undertaken to increase the micronutrient content in rice to avert nutrient deficiency in the human diet, especially for populations where micronutrient deficiency is prevalent. Recently, Znbiofortified rice has been developed to avert Zn deficiency in the diet of Bangladeshi people, particularly in children (Ahmad, 2013). The International Rice Research Institute (IRRI) is expected to release Fe-rich rice by the year 2029 to alleviate Fe deficiency anemia in needy countries (David, 2014). Due to consumers' demand for better rice quality, rice breeders all over the world are endeavoring to develop rice varieties with improved qualities that meet local demand. The quality of a rice variety is assessed after harvesting the grains from the plant. Prior to an assessment of the acceptability of the rice variety by panelists, the quality parameters of cooking and eating quality, and phytochemical and micronutrient composition are determined by using standard procedures (Dela Cruz and Khush, 2000). Determination of the quality parameters in each individual plant is laborious and time consuming. Certain chemical analyses might require large grain samples, which can be destructive to the plant material, especially during the early stage of breeding when the breeder's seed supply is limited. The advent of molecular marker technology in genetic analysis has revolutionized the research on rice quality. From the time scientists first ventured into using molecular markers, from the earliest protein markers to the current DNA markers, substantial effort in molecular mapping has identified chromosome regions carrying genes of interest. Undeniably, commonly used DNA markers, such as restriction fragment length polymorphism (RFLP), randomly amplified polymorphic DNA (RAPD), and simple sequence repeats (SSRs) have contributed to the mapping and association studies that led to the discovery of genes of interest. However, these DNA markers are derived randomly from polymorphic sites of the genome, and some can be located far from the gene of interest, which might be independent from the phenotype. Functional markers (FMs, also known as perfect markers) are an alternative to random DNA markers. FMs are developed from polymorphic sites within genes that cause phenotypic trait variation (Andersen and Lübberstedt, 2003). In contrast with random DNA markers, FMs are directly linked to the allele of the trait of interest (Varshney et al., 2005). Therefore, FMs are outcompeting random DNA markers, especially in marker-assisted breeding (MAB). Thus far, numerous FMs have been developed for the breeding of quality rice (Table 1), and some of them have been applied to breeding programs that have delivered desirable quality traits unambiguously (Yi et al., 2009;Jin et al., 2010). Advantages of FMs over Random DNA Markers The advantage of FMs is that they can be applied to any population; random markers discovered from quantitative trait loci (QTL) mapping might be population specific. Parents from the QTL mapping have different genetic backgrounds, and might not be polymorphic when applied to other populations (Lübberstedt et al., 2005;Miklas et al., 2006;Gupta et al., 2010). In contrast, FMs can be used regardless of the genetic background of the population under study and applied to any population without revalidating markers or the QTL relationship (Gupta et al., 2010). FMs are developed from functional gene motifs and, therefore, have complete linkage to the desired allele (Andersen and Lübberstedt, 2003). Due to the complete linkage of an FM with the target gene and the absence of recombination between the marker and the gene, the loss of information and the false selection in MAB can be prevented (Ingvardsen et al., 2008). Phenotypic validation in MAB that uses random DNA markers is essential to ensure that the target gene and marker are transferred together to the progeny; however, using FMs eliminates the need for phenotypic validation (Andersen and Lübberstedt, 2003). Therefore, FMs are more efficient than random DNA markers in MAB applications. Another major concern in MAB is linkage drag. Random DNA markers might be located far from the target genes; therefore, when they are applied in MAB, a larger donor segment will be introgressed into the recipient parent or backcross progeny. Undesirable genes might be transferred along with the target gene, resulting in reduced performance of the phenotypic trait. To minimize linkage drag in MAB, Hospital (2001) suggested the use of flanking markers closely linked to the introgressed gene in a large population size to obtain doublerecombinant genotypes. Alternatively, FMs can reduce linkage drag, particularly in foreground selection by genotyping a smaller population size (Bagge and Lübberstedt, 2008;Gupta et al., 2010). A Brief Review on the Genetics of Rice Quality Eating quality refers to the consumers' sensory perception of cooked rice, which is related to characters such as flavor and texture (Hsu et al., 2014). Cooking quality refers to chemical reactions resulting from the cooking of the grain, such as gelatinization temperature (GT), kernel elongation, and water uptake (Juliano and Perez, 1984;Hsu et al., 2014). Amylose, a constituent of starch which comprises approximately 95% of the grain dry weight (Fitzgerald et al., 2009), is an important determinant of eating and cooking qualities. In addition, amylose content (AC) affects the glycemic index (Juliano and Goddard, 1986;Miller et al., 1992;Fitzgerald et al., 2011). Amylose is synthesized by granule bound starch synthase 1 (GBSSI) (Smith et al., 1997), which is encoded by the Waxy gene. At present, many Waxy alleles that correspond to different AC classes have been reported. The five common alleles are wx, Wx t , Wx g1 , Wx g2 , and Wx g3 , which correspond to glutinous, low, intermediate, high I, and high II classes of apparent AC, respectively (Teng et al., 2012). In addition to these common alleles, a rare allele, Wx op , has been reported by Mikami et al. (2008). The identified alleles have given researchers the ability to develop FMs to develop rice varieties with desired AC by using MAB. The Waxy gene has been reported to affect the gel consistency (GC) and GT of rice (Tan et al., 1999;Wang et al., 2007;Tian et al., 2009). Studies have confirmed that Waxy gene affects both AC and GC (Fan et al., 2005;Zhang et al., 2012). Although GT has been reported to be influenced by the Waxy gene, a major QTL corresponding to the alkali degeneration locus (alk) was found to control GT (Tian et al., 2005;Wang et al., 2007). The starch synthase IIa gene (SSIIa), located at the alk locus (Umemoto et al., 2002), is reported to have several functional single nucleotide polymorphisms (SNPs), SNP2, SNP3 (Umemoto and Aoki, 2005;Waters et al., 2006), and SNP4, Waters et al., 2006) that affect GT. Rice grain appearance is an important aspect that affects the visual preference of consumers. A major QTL on chromosome 3 has been found to be responsible for grain length (Aluko et al., 2004;Fan et al., 2006). A comparative sequencing study between short-and long-grain varieties showed that the second exon of the putative grain length gene GS3 has a nonsense mutation that is found in longgrain varieties (Fan et al., 2006). On the other hand, a loss of function mutation in GW2, a QTL located on chromosome 2, affects the grain width and weight (Song et al., 2007). Fragrant rice varieties, such as basmati and jasmine, are of great interest to consumers due to their distinctive flavor. Researchers have identified many chemical compounds that contribute to the fragrance of fragrant rice (Yajima et al., 1979;Petrov et al., 1996). Of the identified chemical compounds, 2-acetyl-1-pyrroline (2AP) has been found to be the most significant compound in conferring fragrance to fragrant rice (Buttery et al., 1983(Buttery et al., , 1988. The elevated levels of 2AP in fragrant rice are thought to be due to a deletion within exon 7 (Bradbury et al., 2005a;Amarawathi et al., 2008) or exon 2 of the gene encoding the enzyme betaine aldehyde dehydrogenase (BADH2), which is located on chromosome 8. These mutations render BADH2 nonfunctional, resulting in the accumulation of 2AP (Bradbury et al., 2005a(Bradbury et al., , 2008. However, the deletions within exon 2 and exon 7 are likely not the only mutations for fragrance because there are varieties without them that accumulate 2AP (Fitzgerald et al., 2008). Fitzgerald et al. (2008) suggest that other mutations could influence BADH2 or that there exist other biochemical pathways, such as the one proposed by Huang et al. (2008), in addition to the pathway proposed by Bradbury et al. (2008), that lead to 2AP accumulation. Hence, the genetics and biochemical pathways of fragrance should be investigated by researchers to further understand fragrance in rice. The micronutrients Zn and Fe are present in low quantities in rice, especially in the polished grain (Mayer et al., 2008). Therefore, biofortification strategies are undertaken to enhance the nutritional quality of rice in order to avert micronutrient deficiencies in populations for whom rice is the staple food and who have limited access to other fortified foods or micronutrient supplements (Bouis and Welch, 2010). However, biofortification in rice is no simple task. Sperotto et al. (2012) stated five constraints for concern in Fe biofortification: uptake from the soil, loading of the xylem, transport through the phloem, unloading at the base of the grain, and grain sink strength. The genetic engineering approach has reported success in increasing Zn and Fe content by overexpression of genes such as ferritin and those of the OsNAS gene family, which encode proteins that serve different purposes such as Fe accumulation or the transport of Fe ions (Johnson et al., 2011;Paul et al., 2012). Many QTLs for Zn and Fe have been reported, and candidate genes and linked markers have also been identified (Lu et al., 2008;Garcia-Oliveira et al., 2009;Sperotto et al., 2010;Anuradha et al., 2012). Based on specific QTLs, linked markers and candidate genes, the development of FMs for Zn and Fe improvement is anticipated for MAB programs. Progression toward FMs for Quality Rice Breeding Before the era of molecular marker technology, grain quality was evaluated on palatability, and the presence or absence of a certain trait, such as aroma. The evaluation of rice quality can also be performed visually, providing morphological data, which can then be represented by a morphological marker. Scientists investigate the proteins or enzymes underlying a specific trait, known as an allozyme marker, to discover the exact cause of the trait. Due to ambiguity and the limited information that can be extracted from enzyme analysis (Murphy et al., 1996), scientists' attention has shifted toward DNA markers. One classic example of DNA markers is the RFLP marker. RFLP is a hybridization based marker that utilizes restriction enzymes to cut the DNA at specific restriction sites. Single nucleotide changes, insertions or deletions cause changes in restriction sites, resulting in different molecular weight restriction fragments and variation between individuals. RFLP markers were used to map genes to chromosomes. Once a RFLP marker has been positively identified as linked to the putative gene controlling the trait under study, further investigation, such as chromosome walking, cloning, or sequencing of the gene, is undertaken. For instance, the gene controlling fragrance was initially mapped by Ahn et al. (1992) using a RFLP marker; using near isogenic lines (NILs), RFLP analysis showed that the fragrance gene (fgr) is linked to marker RG28 on chromosome 8. The introduction of PCR-based markers such as SSR has increased scientists' knowledge of the genetic map. The locus for a certain trait previously mapped with RFLP is saturated with SSR markers, thereby increasing proximity to the gene. In the case of fragrance, the fgr locus was mapped with SSR markers after it was discovered (Chen et al., 1997;Cho et al., 1998). Subsequently, the identified SSR markers have facilitated the development of SSR markers closely linked to the fgr, such as that developed by Garland et al. (2000) which detects changes in the mononucleotide repeat of thiamine, (T) n . This marker was unable to discriminate between genotypes using low-resolution agarose gels and was not polymorphic for some rice variety combinations; therefore, Cordeiro et al. (2002) developed another SSR marker based on the (AT) 40 repeat for fragrance genotyping. Researchers' efforts to identify linked markers have facilitated further exploration into the genes responsible for rice quality traits. Sequencing the rice genome has also facilitated gene discovery (IRGSP, 2005;3K RGP, 2014); now that rice genomic sequence data are available, genotype sequences of rice with and without a desirable trait can be compared, leading to discovery of the sequence underlying the trait. Using a linked SSR marker and a bacterial artificial chromosome (BAC), Bradbury et al. (2005a) identified the sequence polymorphism between fragrant and nonfragrant varieties, that is an 8-bp deletion and three SNPs and found the gene (later known as badh2) that codes for BADH2 whose functionality determines 2AP accumulation in rice. Based on sequence polymorphism and allele variation studies on different fragrant genotypes, researchers have developed FMs for use in genotyping and breeding (Bradbury et al., 2005b;Amarawathi et al., 2008;Shi et al., 2008;Sakthivel et al., 2009;Vanavichit et al., 2010;Myint et al., 2012). The progress of FM development for the example of fragrance is shown in a simplified manner in Figure 1. Some of the FMs developed by researchers for use in quality rice breeding are listed in Table 1. The Development and Applications of FMs in Quality Rice Breeding The development of FMs involves a series of steps (Figure 2). The initial step is discovery of the gene that controls the trait. Forward and reverse genetics approaches facilitate the identification of genes that casually affect phenotypic variation. One method of gene identification is by QTL mapping, which identifies loci that underlie the gene or genes that contribute to the trait. Familybased QTL mapping requires the development of a pedigree from crosses between different genotypes and their resulting progeny. Over the years, many family-based QTL mapping studies, especially bi-parental QTL mapping, have been conducted for rice quality traits. However, in family-based QTL mapping, the recombination events are limited to the generations of the family and therefore provide low resolution (Mitchell-Olds, 2010). To improve the resolution of QTL mapping and promote more recombination events, researchers can opt for multiple-parent advanced generation inter-cross (MAGIC). Bandillo et al. (2013) have developed a MAGIC population from half diallel-mating of eight varieties; conducted genotyping by sequencing (GBS) on 200 indica MAGIC lines and identified major genes and QTLs for many traits that influence grain quality, such as Waxy and GS3. Conversely, population-based QTL mapping and genomewide association studies (GWAS) take into account the historical recombination events that have accumulated over thousands of generations and are, therefore, able to provide higher resolution (Mitchell-Olds, 2010). GWAS utilizes more than 100 genotypes with diverse backgrounds, which leads to a broader genetic base (Mitchell-Olds, 2010). GWAS investigates genome-wide association between SNPs and phenotypes, utilizing an arraybased SNP detection platform or next generation sequencing (NGS). Chen et al. (2014) developed an array-based genotyping tool called RiceSNP50 and identified a locus in the same region as the GS3 locus. Huang et al. (2010) utilized NGS and conducted GWAS on 373 indica lines for 14 agronomic traits important to grain quality and identified major genes such as Waxy and the alk locus, which were similar to those reported by other researchers and other minor genes. Their study showed that GWAS has the potential to identify genes that contribute to natural variation of complex traits. Although the cost for this sequencing platform may be high, with time, it will be made affordable to all researchers. With the marker linked to the loci, target genes can be isolated by map-based cloning (or positional cloning), expression profiling (Duan and Sun, 2005) or transposon tagging, enabling researchers to investigate gene function. FIGURE 1 | A chart of simplified progress of functional marker (FM) development for trait used as an example, fragrance, with reference to Ahn et al. (1992) and Bradbury et al. (2005a). The candidate gene approach has been used in various crop plants to identify genes that contribute to phenotypic variation. Because rice is composed mostly of starch, genes related to starch synthesis are targets of study. Tian et al. (2009) selected 18 starch synthesis-related genes and conducted an association study with AC, GC, and GT. According to Pflieger et al. (2001), genetic transformation is required to determine whether the candidate gene is the gene that causes the trait variation. Tian et al. (2009) have verified the role of each gene in the starch synthesis system by transformation. Their results suggest that selection of a single gene might be insufficient because starch synthesis-related genes cooperate with each other to form a network that determines AC, GC, and GT; therefore, modifying a single gene may alter these three properties. The verified candidate genes from this study can potentially be used in FM development. Currently, the availability of the rice genome sequence (IRGSP, 2005;3K RGP, 2014) facilitates gene discovery. Despite this resource, not all genes have had their functions characterized. Well-characterized gene function is a prerequisite of FM development. There are several methods by which researchers can determine a gene's function, including genetic transformation, RNA interference (RNAi) and mutant characterization. To determine the function of the OsBADH2 gene, Niu et al. (2008) used RNAi combined with Agrobacterium tumefaciens-mediated T-DNA transfer. Their results demonstrated that down-regulated expression of the OsBADH2 gene resulted in increased 2AP, thereby validating OsBADH2 as a gene that affects fragrance in rice. Bradbury et al. (2008) proposed a pathway involving BADH2 that leads to 2AP accumulation; this pathway was supported by Chen et al. (2008), who studied it by transformation. A study by Gross et al. (2003) reported the ferritin genes OsFER1 and OsFER2. An expression profile study on OsFER1 and OsFER2 was then conducted by Stein et al. (2009), who showed that treatment with copper, excess Fe, and other metals causes differential expression of OsFER1 and OsFER2. Paul et al. (2012) showed that overexpression of theOsFER2 gene led to increased Fe and Zn levels in T 3 transgenic plants. Polymorphisms in the alleles that contribute to variation in phenotype can be in the form of SNPs, insertions/deletions (Indels) or SSRs. The relationship between the allelic polymorphism and the phenotypic variation is tested by either indirect or direct proof of allele function (Andersen and Lübberstedt, 2003). Association study is an indirect approach for proving allele function, which provides statistical proof of the relationship between the allele polymorphism and phenotype. Association studies rely on linkage disequilibrium (LD) (Andersen and Lübberstedt, 2003), which plays an important role in association studies because it affects the fine mapping of agronomically important genes. Because rice (Oryza sativa) is an autogamous species, the LD of approximately 75 kb for the indica variety is considered high; therefore it is eligible for genome-wide LD association mapping (Mather et al., 2007;Zhao et al., 2011). Alternatively, reverse genetics approaches such as homologous recombination (HR) or targeted induced local lesions in genomes (TILLING) can be used to directly identify motif function. HR is the locus-targeted integration of alleles to produce isogenic genotypes to obtain direct proof of allele function (Andersen and Lübberstedt, 2003;Hanin and Paszkowski, 2003). Research by Terada et al. (2002) used gene targeting by HR to investigate the Waxy locus in rice with a positive/negative selection vector; these researchers obtained approximately 1% survival of transformants, suggesting that the method can be useful for gene-targeting or gene-knockout. The effects on the phenotypes of organisms generated from HR can, therefore, provide direct proof of allele function. Targeted induced local lesions in genomes approach involves mutagenesis to create variations of mutants which are then subject to high-throughput screening for mutation discovery. By using two Nipponbare populations treated with ethyl methanesulphonate (EMS) or a combination of sodium azide andmethyl-nitrosourea (Az-MNU), Till et al. (2007) reported mutation rates of 1/294 kb and 1/265 kb, respectively. Suzuki et al. (2008) reported a mutation rate of 1/135 kb from a Taichung 65 mutant population treated with MNU, suggesting that a high mutation rate can be used to compliment other mutant resources in rice. EcoTILLING, a variant of TILLING, has been effective at revealing allele polymorphism and acts as a useful marker system for resistant genes in barley (Mejlhede et al., 2006). Recently, Tsai et al. (2011) incorporated NGS with multidimensional pooling into a TILLING protocol for identification of rare alleles. This advent in sequencing, along with researchers' substantial efforts, will lead to the discovery of more alleles. Polymorphisms detected in mutants from TILLING or EcoTILLING provide proof of allele function; when coupled with phenotypic data, these results can facilitate the development of FMs. Plant breeding has benefited from the advent of marker technology. The application of markers in plant breeding is known as MAB. MAB includes marker-assisted recurrent selection (MARS), marker-assisted backcrossing (MABC), and marker-assisted gene pyramiding. MABC is the most commonly used technique in rice breeding. In foreground selection of MABC, markers associated with the QTL or genes for the desired trait are used to identify plants that carry the preferred allele, allowing selection to be conducted at an early stage of the breeding program. Using an FM rather than a linked DNA marker can improve the selection precision. Because the FM is in complete linkage with the target gene, the risk of linkage drag and recombination between the marker and target gene can be minimized, thereby reducing the chance of undesirable alleles being passed down from the donor parent. Jin et al. (2010) applied FMs to select Waxy, badh2, and SSIIa genes in their backcrossing scheme and successfully improved the AC, GT, and fragrance of a maintainer line used for hybrid rice production. Study by Jin et al. (2010) showed that the availability of FMs has made possible the introgression of three traits simultaneously in a breeding program. Moreover, using FMs saves time as it circumvents the phenotypic evaluation on a limited number of seeds at every stage of breeding that would be conducted in conventional breeding. Marker-assisted breeding is particularly useful for traits controlled by major QTLs or genes with large effects; however, it may be ineffective for traits governed by many QTLs with small effects or those influenced by the environment. Genomic selection (GS), an alternative to MAB proposed by Meuwissen et al. (2001), utilizes all marker and phenotypic data to estimate marker effects and makes predictions of which individuals would make the best parents. The genomic estimated breeding values (GEBVs) are calculated from a training population, for which both genotypic and phenotypic data have been collected and then tested on the candidate population (Chen et al., 2013). Recently, Spindel et al. (2015) attempted GS on rice for three traits: flowering time, plant height, and grain yield. Their study reported more accurate predictions of breeding line performance than pedigree data alone. With its many strengths, GS is anticipated to aid researchers in breeding for micronutrients such as Fe and Zn where many QTLs or genes are involved. Challenges in the Development and Application of FMs in Breeding for Quality Rice Although a plethora of developed FMs are recommended for application in quality rice breeding programs, researchers who have used them have different experiences and opinions on use. Amarawathi et al. (2008) and Sakthivel et al. (2009) reported inconsistency of the allele-specific amplification (ASA) marker system for fragrant rice genotyping developed by Bradbury et al. (2005a). Conversely, Sarhadi et al. (2011) proved the efficacy and efficiency of ASA markers in differentiating fragrant and nonfragrant rice genotypes and the genotype matches the phenotype accurately. These contrary views suggest that proper optimization of the FM assay prior to its use is essential because an optimized assay ensures reproducible results; therefore, optimization is required prior to its application in breeding programs (Poczai et al., 2013). Another concern for the application of FMs is the pleiotropic effects of certain genes on several traits (Chen and Lübberstedt, 2010;Brenner et al., 2013). Understanding the correlation among characteristics or the pleiotropy of major genes allows breeders to decide which traits should be directly or indirectly selected or to compensate for the undesirable traits with favorable alleles (Chen and Lübberstedt, 2010). Although major genes or QTLs that influence GT and GC have been identified [SSIIa (Umemoto et al., 2002), alk2(t) (Shu et al., 2006), and qGC-6 ], the effect of the Waxy gene on GT and GC (Lanceras et al., 2000;Bao et al., 2003;Zhang et al., 2012), has yet to be determined as pleiotropic or gene linkage. This create a challenge to breeders in selecting the traits in breeding programs (Shu et al., 2006). Epistasis is another concern for breeders because it complicates the inheritance of quality traits. If epistatic effects of the genes are not taken into account, the associations for a single gene might be inaccurate or misleading, thereby hindering the development of FMs and causing inconsistency in FM application (Brenner et al., 2013). Epistatic effects among the QTLs controlling quality traits have been reported (Lee and Koh, 2010;Anuradha et al., 2012;Liu et al., 2013); therefore, researchers should discern the epistatic effects of the genes influencing a trait in quality rice breeding. The main advantage of an FM is that it would have complete linkage with the desired allele; therefore, it could be applied to any population, regardless of genetic background, without having to revalidate the QTL relationship. While the above statement is technically correct, there is a subtle complication that needs to be mentioned. If a researcher selects on the basis of an FM, the possibility remains that the phenotype of interest is due to another allele that is in linkage disequilibrium with the FM. However, the effect is small. Although no largescale assessment of linkage disequilibrium has been observed in O. sativa, the seminal work by Garris et al. (2003) indicated a linkage disequilibrium decay of 100 kb around a disease resistance locus in the aus subpopulation. More recently, linkage disequilibrium decays of 50 kb in indica, 5 kb in Oryza rufipogon (Rakshit et al., 2007), 2 Mb in indica and tropical japonica, and 500 kb in O. rufipogon have been reported by using genebased markers and phenotypes . The physical extent of linkage disequilibrium around a gene defines the efficiency of linkage disequilibrium mapping, which is the consequence of several factors, including the degree of artificial or natural selection on the gene or region of the genome, the rate of outcrossing, recombination fraction, the age of the allele under study, chromosomal location, and the population size and structure (Garris et al., 2003). While the costs of development and establishment and application of FMs in MAB might currently be a concern to researchers, the costs of marker development and marker genotyping are expected to drop in the near future (Lau et al., 2014). Monsanto reported that price per molecular marker decreased over sixfold from 2000 to 2006 (Eathington et al., 2007). Cost for marker discovery by sequencing technology is also expected to decrease over time (Wetterstrand, 2014). Therefore, the advancement of sequencing technology is expediting gene discovery and FM development. Conclusion There are more genes involved in eating, cooking, and the nutritional qualities of rice that have not yet been discovered. Whole-genome sequencing of rice has been conducted to identify some of these genes. The discovery of genes and gene function characterization can be conducted using the various approaches of forward and reverse genetics. FMs could revolutionize the selection strategy in quality rice breeding without linkage drag. Because the cost of marker discovery by sequencing technology is decreasing, the adoption of FMs in breeding programs, especially MAB, is greatly anticipated. We envision that the utilization of FMs will enable the incorporation of all genes for cooking, eating, and nutritional qualities into one rice genotype.

v3-fos

2016-05-04T20:20:58.661Z

2015-06-04T00:00:00.000Z

15706679

s2

Mapping a Type 1 FHB resistance on chromosome 4AS of Triticum macha and deployment in combination with two Type 2 resistances Key message Markers closely flanking a Type 1 FHB resistance have been produced and the potential of combining this with Type 2 resistances to improve control of FHB has been demonstrated. Abstract Two categories of resistance to Fusarium head blight (FHB) in wheat are generally recognised: resistance to initial infection (Type 1) and resistance to spread within the head (Type 2). While numerous sources of Type 2 resistance have been reported, relatively fewer Type 1 resistances have been characterised. Previous study identified a Type 1 FHB resistance (QFhs.jic-4AS) on chromosome 4A in Triticum macha. Little is known about the effect of combining Type 1 and Type 2 resistances on overall FHB symptoms or accumulation of the mycotoxin deoxynivalenol (DON). QFhs.jic-4AS was combined independently with two Type 2 FHB resistances (Fhb1 and one associated with the 1BL/1RS translocation). While combining Type 1 and Type 2 resistances generally reduced visual symptom development, the effect on DON accumulation was marginal. A lack of polymorphic markers and a limited number of recombinants had originally prevented accurate mapping of the QFhs.jic-4AS resistance. Using an array of recently produced markers in combination with new populations, the position of QFhs.jic-4AS has been determined to allow this resistance to be followed in breeding programmes. Electronic supplementary material The online version of this article (doi:10.1007/s00122-015-2542-9) contains supplementary material, which is available to authorized users. Introduction F. graminearum mutants that do not produce DON can colonise wheat heads, they are not able to spread from the point of infection through the rachis (Bai et al. 2002). This suggests that DON is not required for initial infection but is a virulence factor that is necessary for disease spread through the head. Crop management and agrochemical measures are only partly effective in controlling the disease and therefore the development of FHB resistant varieties is important for disease control and the prevention of mycotoxin contamination. Resistances have been identified in a variety of sources including from Asia (e.g. Sumai-3) (Bai et al. 1999;Waldron et al. 1999), South America (e.g. Frontana) (Schroeder and Christensen 1963;Steiner et al. 2004) and Europe (e.g. Arina) (Snijders 1990). Inheritance of resistance to FHB in wheat is quantitative with a large volume of literature identifying more than 100 quantitative trait loci (QTL) for resistance (Buerstmayr et al. 2009). Several forms of resistance to FHB have been postulated but resistance is generally differentiated into two types: Type 1 (resistance to initial infection) and Type 2 (resistance to spread within the head) (Schroeder and Christensen 1963). The majority of resistance QTL identified confer type 2 resistance (Buerstmayr et al. 2009). This includes the potent 3BS QTL derived from Sumai-3, Qfhs.ndsu-3BS (Anderson et al. 2001), which was subsequently mapped as a single Mendelian gene termed Fhb1 (Cuthbert et al. 2006), and a QTL identified on chromosome 1B that is thought to be located on or closely linked to the 1BL-1RS wheat-rye translocation (Ittu et al. 2000;Shen et al. 2003;Schmolke et al. 2005). Type 1 resistance is considered to be advantageous, because it confers resistance to colonisation both by toxin producing Fusarium species and non-toxin producing Microdochium species. However, it is difficult to identify and select for Type 1 resistance as the presence of this form of resistance must be inferred following assessment by both single spikelet (point) inoculation to assess Type 2 resistance and spray inoculation to assess both Type 1 and Type 2 resistance (Mesterházy et al. 2008). Type 1 resistance QTLs that have been identified include QTL located on chromosome 5A (Buerstmayr et al. 2003;Lin et al. 2006;Steiner et al. 2004), 4B (Lin et al. 2006) and 4A (Steed et al. 2005). Resistance to FHB has also been described within related species of wheat. In particular, FHB resistance has been identified in T. macha, a hulled hexaploid wheat endemic in the Caucasus region (Dardis and Walsh 2003;Gilbert and Tekauz 2000). FHB resistance QTLs were identified in T. macha on chromosomes 2A, 2B, 5A and 5B using backcross derived recombinant inbred lines (Buerstmayr et al. 2011) and on chromosome 4A using a set of single chromosome substitution lines (Steed et al. 2005). The T. macha 4A resistance was shown to confer Type 1 resistance as it was clearly observed from spray inoculations but was not evident following point inoculation. Importantly, this resistance was shown to reduce both visual disease symptoms and levels of DON, suggesting that it may be useful for deployment in elite varieties to provide protection against FHB. This resistance was mapped as a single gene to 4AS using a double haploid (DH) population, where it co-segregated with the SSR marker Gwm165 and was named QFhs.jic-4AS. However, the limited number of recombinants (43 lines) combined with a lack of polymorphic distal flanking markers prevented accurate localisation of the QTL (Steed et al. 2005). More than 100 QTL for FHB resistance have been identified and reported in wheat, as reviewed by Buerstmayr et al. (2009). To provide a high level of resistance to FHB in wheat, marker assisted selection (MAS) of these QTL can be used to pyramid these resistances into an agronomically desirable background. This approach relies on the selection of resistances that function additively to confer an enhanced level of resistance when combined together. It is possible that combining Type 1 resistances such as the T. macha 4AS resistance with Type 2 resistances such as the 1B QTL (associated with the 1BL-1RS wheat-rye translocation) and the major 3B QTL (Fhb1), may provide an additive effect restricting both initial infection and subsequent spread of the pathogen along the rachis. In the present study, we tested combinations of the 1B, 3B and 4A FHB resistance QTL, as outlined above, in a susceptible UK wheat background (Hobbit-'sib') to examine if pyramiding FHB resistances will confer additional resistance, both in terms of visual disease symptoms and DON content. In addition, we utilised a 288 line F 4 population developed from the susceptible parent Hobbit 'sib' and the resistant line DH81, previously developed by Steed et al. (2005), to refine the localisation of the 4AS T. macha Type 1 resistance and to identify SNP markers to aid MAS and pyramiding with other FHB resistance QTL by plant breeders. Plant material and population development Seed of the highly FHB susceptible UK variety Hobbit 'sib' (HS) was obtained from the John Innes Centre (JIC) wheat collection, and seed of the highly resistant variety WEK0609 ® was provided by Pioneer Hi-Bred International Inc. Previous SSR haplotyping has suggested that this variety has a number of QTL providing FHB resistance, including Fhb1 on chromosome 3B and the 1BL-1RS associated resistance (Gosman et al. 2007). Seed was also obtained of the single chromosome substitution line Hobbit 'sib'/T. macha 4A (HS/Tm4A), and a single chromosome recombinant double haploid line (DH81) previously developed by Steed et al. (2005) from the cross between HS/Tm4A × Hobbit 'sib' and shown to possess the FHB QTL. A single chromosome substitution series was generated for HS × WEK0609 ® in a Hobbit 'sib' background. Single chromosome substitution lines (F 6 ) of chromosomes 1B and 3B were crossed to DH81 and the resulting F 2 progeny were screened for the presence/absence of simple sequence repeat (SSR) alleles associated with the 1B, 3B and 4A resistances (see below). This procedure was used to generate a total of 16 independent 'QTL combination' lines with a common susceptible background with: the 4A (three lines), 3B (one line) or 1B (two lines) resistance QTL in isolation; a combination of 4A and 1B QTLs (three lines); a combination of 4A and 3B QTLs (four lines); or lacking any FHB QTL (three lines). These 'QTL combination' lines were evaluated for FHB resistance in a polytunnel trial and five field trials across 3 years as detailed below. DH81 was backcrossed to HS and a population of 288 F 4 plants was generated. Homozygous recombinant F 4 lines (39 lines) identified within this population were selfed (F 5 ) and then bulked for use in phenotypic evaluations of FHB resistance. F 4 lines that were recombinant but heterozygous for one or more loci were selfed and the resulting F 5 individuals genotyped to identify additional homozygous recombinants (39 lines). Seed of individual plants was then bulked for use in phenotypic evaluations of FHB resistance in three field trials and one polytunnel trial as detailed below. To identify SSR markers for mapping the T. macha 4A resistance, HS and DH81 were screened with 39 publically available SSR markers that were reported to be located on chromosome 4A, to identify polymorphic and co-dominant markers. Polymorphic SSR markers (Table S1) were applied to the HS × DH81 F 4 population and the resulting F 5 recombinant lines. DNA extractions, PCR conditions and product size determination were conducted as described by Burt et al. (2011). Single nucleotide polymorphism (SNP) analysis The parent lines of the population (HS and DH81) and the single chromosome substitution line HS/Tm4A were screened at LGC Genomics (www.lgcgenomics.com) with a wheat SNP panel using their proprietary KBioscience Competitive Allele-Specific Polymerase chain reaction (KASP) genotyping technique. This SNP panel was developed in conjunction with the University of Bristol and contains over 5000 validated SNP assays (Allen et al. 2013). Polymorphic markers were identified to provide an even coverage of chromosome 4AS and primer sets obtained (Table S1) to apply to the HS × DH81 F 4 population and the resulting F 5 recombinant lines. To identify additional 4AS polymorphisms, the parent lines and HS/Tm4A were run on the iSelect 90 k wheat SNP chip (Wang et al. 2014) at the University of Bristol Genomics Facility (http://www.bristol.ac.uk/biology/ research/transcriptomics/). The analysis of alleles was conducted using Genome Studio Data Analysis Software from Illumina (http://www.illumina.com/informatics/sequencing-microarray-data-analysis/genomestudio.ilmn) with a cluster file created by Wang et al. (2014) that was trained on a diversity panel of wheat landraces. The sequence of the polymorphic markers was aligned to the flow-sorted scaffolds from the International Wheat Genome Sequencing Consortium (IWGSC) chromosome survey sequence, [available from EnsemblPlants, release 21 (Kersey et al. 2012)] using BLAT (Kent 2002). A BioRuby script (Goto et al. 2010) was used to select the alignment with the highest score and used to infer the likely chromosomal location. Selected iSelect SNPs on 4AS and other chromosomes containing T. macha introgressions were converted into KASP assays by identifying homoeologue SNPs from the survey sequence data and using these in conjunction with the varietal SNPs to design homoeologue specific KASP assays. QTL combination lines were additionally screened for the presence of the 3B QTL using an Fhb1 linked KASP assay wMAS000008 to confirm the presence of this resistance as determined by SSR markers. This marker was previously developed by Gina Brown-Guedira (USDA) as part of a panel of KASPs for MAS of agronomically important genes in wheat (http://www.cerealsdb.uk.net/cerealgenomics/CerealsDB/kasp_download.php?URL). DNA was extracted from all samples as described by Burt et al. (2011), quantified using a NanoDrop 2000 spectrophotometer (Thermo Scientific) and diluted to 10 ng/ul in sterile distilled water for use in KASP-SNP PCR reactions. An 8.112 µl reaction volume consisted of 4 µl of DNA, 4 µl KASP reaction mix (LGC Genomics), and 0.112 µl assay mix (containing 12 µM each allelespecific forward primer and 30 µM reverse primer). The following PCR conditions were used: 15 min at 94 °C; 10 touchdown cycles of 20 s at 94 °C, 60 s at 65-57 °C (decreasing 0.8 °C per cycle); and 26-35 cycles of 20 s at 94 °C, 60 s at 57 °C. Fluorescence detection of the reactions was performed using a Bio-Rad CFX96 realtime PCR machine to conduct end point allelic discrimination with CFX Manager 3.1 software (Bio-Rad Laboratories). Conserved orthologous sequence (COS), expressed sequence tag SSR (EST-SSR) and SSR marker analysis Sequences for the polymorphic wheat genotyping panel SNPs and the polymorphic iSelect SNPs were aligned to the Brachypodium, rice and Sorghum genomes using Phytozome v9.1 (www.phytozome.net) to identify the orthologous loci in these species, where present. The Brachypodium sequence corresponding to the region of interest on wheat 4AS was visually examined using the Brachypodium (Bd21) Genome Browser (http://www.modelcrop.org/cgibin/gbrowse/brachyv1/) to identify thirty-three COS markers aligned to the region. These markers were previously developed by Dr. Simon Griffiths and Michelle Leverington-Waite at the John Innes Centre. Expressed sequence tag-derived microsatellite (EST-SSRs) for comparative mapping in wheat, barley and rice were previously identified by La Rota et al. (2005). From these, primers for a set of 26 EST-SSRs were identified in the rice region orthologous to 4AS in wheat. The 33 COS and 26 EST-SSR markers were tested on the parent lines (HS and DH81) to identify polymorphisms on 4AS located in the region of the resistance. Polymorphic markers (Table S1) were applied to the HS × DH81 F 4 population and the resulting F 5 recombinant lines. DNA extractions and PCR reactions were prepared as described by Burt et al. (2011). PCR amplification was conducted using a touchdown programme consisting of a denaturing step of 95 °C for 10 min; 16 touchdown cycles of 95 °C for 15 s, 58 °C for 1 min decreasing 0.5 °C per cycle, 72 °C for 1 min; then 30 cycles of 95 °C for 15 s, 50 °C for 15 s and 72 °C for 1 min. Samples were run on an ABI 3700 capillary sequencer (Applied Biosystems) and the output data were analysed using Peak Scanner v1.0 (Applied Biosystems) to determine the product size of the amplicons. If no polymorphism was detected using this method, then products were examined by single-strand conformation polymorphism (SSCP) assay (Martins-Lopes et al. 2001) using Sequa GelMD (National Diagnostics, UK Ltd.) and visualised by silver staining (Bassam et al. 1991). These field experiments were conducted in a randomised complete block design with four and two replicate blocks per line in the UK and Austria, respectively. Trials in the UK were inoculated with a highly virulent DON-producing F. culmorum isolate (Fu42), whilst in the trials in Austria, a highly aggressive F. graminearum isolate (IFA66) was used. In the UK, plants were spray inoculated with a conidial suspension (1 × 10 4 ml −1 ) amended with 0.05 % Tween20 at mid anthesis [growth stage (GS) 65, (Zadoks et al. 1974)] using a knapsack sprayer (150 ml m −2 ). Plants were mist irrigated for a minimum of 72 h post inoculation to maintain high humidity. The inoculation was repeated after an interval of 3 days. Disease was assessed as % infection within each plot at four time intervals post infection (dpi) to follow disease development in each trial. The area under the disease progress curve (AUDPC) was calculated from percentage infection at each time point to provide an integrated measure of disease. Additionally, an experiment was conducted in an unheated polytunnel at JIC in 2010 with 4 replicate plants per line arranged in a randomised block design on capillary matting. Inoculum was prepared as described above and plants were inoculated at GS65 with a conidial suspension (1 × 10 4 ml −1 ) amended with 0.05 % Tween20 at GS65 using a held-held sprayer. Following spray inoculation, plants were visually assessed for disease on the basis of percentage of spikelets infected per head at 10, 14 and 18 dpi (%FHB). Percentage spikelet infection at 18 dpi was used as a measure of disease severity. The area under the disease progress curve (AUDPC) was again calculated to provide an integrated measure of disease development. In Austria, all the plots (2 rows, 80 cm long) were repeatedly sprayed with 100 ml m −2 of a 1 × 10 4 conidia/ ml macroconidial suspension using a backpack sprayer. The first inoculation was done 2 days before the earliest line flowered and the treatment was repeated (in total 6 applications with 2 day time intervals) until the last line reached full anthesis. During and after each inoculation cycle, the crop canopy was kept wet with a computer controlled mist irrigation system for 20 h. GS 65 was assessed for each line individually. Ten days after mid anthesis, visual disease assessment started and was repeated on day 14, 18, 22 and 26 after mid anthesis. The percentage of visually diseased spikelets was recorded with which the AUDPC was calculated. Grain samples were taken from the JIC and Tulln field trials in both 2011 and 2012, and the polytunnel trial in 2010. Samples were milled and DON was extracted in 10 % methanol and DON content was assessed using the Ridascreen Fast DON™ (R-Biopharm Rhone Ltd.) enzyme linked immuno-assay (ELISA) according to the manufacturer's instructions as described previously . FHB resistance phenotyping of the HS × DH81 population In total, 78 recombinant lines were selected from the HS × DH81 F 4 population for use in the current study. Thirty nine stable recombinant F 5 lines initially identified and generated from the F 4 population were assessed for FHB resistance in a field trial at JIC in 2012. The FHB resistance of all 78 recombinant F 5 lines was assessed during the summer of 2013 in two independent field trials; one at CF and one at JIC. These field experiments were conducted in a randomised complete block design with three replicate plots per line. All trials were inoculated with a highly virulent DON-producing F. culmorum isolate (Fu42) and conducted as described above. Disease was assessed as % infection within each plot at 16, 22, 25 and 30 days post infection (dpi). The area under the disease progress curve (AUDPC) was again calculated to provide an integrated measure of disease and % infection at 30 dpi was used as a measure of disease severity (%FHB). The 39 stable recombinant HS × DH81 F 5 lines initially identified and generated from the F 4 population were assessed for FHB resistance in 2013 at JIC in an unheated polytunnel with capillary matting irrigation. Fifteen plants per line were arranged in a randomised complete block design with 4 blocks (3-4 plants per line within each block). Inoculations were conducted and plants were scored as described for the above polytunnel trial. Statistical analysis Analysis of variance (ANOVA) using a general linear model (GLM) was performed on AUDPC scores and DON contents (ppm) from the independent FHB resistance experiments for the 1B, 3B and 4A QTL combination lines to assess variation due to QTL class and experiment × QTL class interaction. Means were predicted across the relevant lines for each QTL class, and were subsequently compared using Fisher's least significant difference test. ANOVA using a GLM was also performed on %FHB and AUDPC scores from the four phenotyping experiments for the HS × DH81 population to assess variation due to line and experiment × line interaction. This was conducted separately for 39 line experiments (using all data: 2012JIC, 2013JIC, 2013CF and 2013 and for the 78 line experiments (2013 JIC and 2013 CF) to provide balanced datasets for analysis. Predicted mean disease scores were calculated for the lines within the GLMs. In addition, GLMs were fitted for each experiment individually and predicted mean scores for each line calculated within the models to account for variation due to field block. Means calculated across experiments and means calculated within experiments were used in subsequent QTL analyses. All GLMs were conducted in Genstat v. 15.2. Broad sense heritability across experiments was estimated from the ANOVA using the formula: GE the genotype × experiment interaction variance, σ 2 e the residual variance, E the number of experiments, and r the number of replicates per genotype (Nyquist 1991). To check for stability of QTL effects across different trials, predicted mean %FHB and AUDPC scores from the field trials and polytunnel experiment of F 5 recombinant lines were used alongside marker data from the same lines in a single marker regression analysis to identify QTL locations for each trait within each experiment. A single marker regression analysis was utilised as there were relatively few markers (21) densely spaced on a single linkage group. Markers were only determined to be associated with the phenotype, where p < 0.01, to reduce the likelihood of false positives. FHB resistance in the 1B, 3B and 4A QTL combination lines SSR haplotype data identified 16 lines with the following combinations of QTL: (i) the 3B QTL alone (1 line), (ii) the 1B QTL alone (2 lines), (iii) the 4A QTL alone (3 lines), (iv) 4A and 3B QTLs (4 lines), (v) 4A and 1B QTLs (3 lines), and (vi) 'Null' lines (3 lines) as susceptible controls that had been through the crossing procedure but lacked any of the QTL according to SSR haplotype data. The presence or absence of the 3B QTL in the QTL combination lines as predicted by the SSR data was additionally confirmed by wMAS000008. Data were combined across the lines for each QTL class and also across the trials to conduct an analysis of variance and to predict means for AUDPC and DON contents. Effects of the QTL combination classes were significant for both AUDPC and DON contents (Table 1). However, there was a significant class by trial interaction for both AUDPC and DON contents (p < 0.001)) suggesting that there were differences in the relative performance of the lines across the trials. Broad sense heritability estimates were relatively high for AUDPC (0.80) suggesting a high level of stability of the effect of the QTL combinations in different environments. However, DON contents were less stable across environments for the QTL combinations with a heritability of 0.60 (Table 1). Predicted means for AUDPC and DON contents demonstrated that the 1B, 3B and 4A QTL individually confer a significant reduction (p < 0.05) in both visual disease scores and DON levels compared to the 'Null' lines without any known resistance QTL (Fig. 1). There was some evidence that combinations of QTLs may have an additive effect on visual disease scores. The combination of 4A and 1B FHB QTLs conferred a significant reduction in visual disease scores compared to either 4A alone or 1B alone (p < 0.05) (Fig. 1a). Although the 3B and 4A combined resistance provided some evidence of enhanced disease control compared to the 4A QTL alone, the reduction was not significant (Fig. 1a). There was no evidence that combining QTL enhances resistance to DON accumulation. Combining the 1B and 4AQTL reduced the amount of DON compared to either QTL in isolation (Fig. 1b), however, these reductions were not significant (p > 0.05). The combination of 4A and 3B QTLs provided a similar level of reduction in DON content compared to the 3B QTL alone. Differences in FHB resistance are often associated with plant height (Srinivasachary et al. 2008). All lines in the current work, however, were of similar height so removing this aspect for consideration. HS × DH81 marker analysis, genotyping and map construction Of the 115 LGC wheat KASP-SNP markers previously shown to be on chromosome 4AS (Allen et al. 2011(Allen et al. , 2013, 20 were polymorphic (Table S2). From these, a sub-set of 14 co-dominant and polymorphic SNPs was identified to provide an even coverage of chromosome 4AS on the basis of published SNP maps of the Avalon × Cadenza and Savannah × Rialto populations (Allen et al. 2011(Allen et al. , 2013. These 14 SNP markers were applied to the HS × DH81 F 4 population and also to the resulting F 5 recombinant lines to confirm the genotypes. The 33 COS and 26 EST-SSR markers were tested on HS and DH81 to identify polymorphisms. Only two EST-SSR markers were polymorphic and these were applied to the HS × DH81 F 3 population and F 4 recombinant lines. No COS markers were polymorphic and were therefore not applied to the population (Table S2). Of the 39 SSR markers tested, 9 were polymorphic of which 3 were codominant (Wmc48, Gwm192 and Gwm165). One of these, Gwm165, was previously identified by Steed et al. (2005). These three SSR markers were applied to the HS × DH81 F 4 population and subsequent F 5 recombinant lines. Eighty-three polymorphic iSelect markers were identified on 4AS. From these, 6 markers were identified by BlastN to have homology to Brachypodium, rice and Sorghum genes within the region orthologous to the QTL location as initially located by the LGC KASP, SSR and EST-SSR markers (Fig. 2). Two markers on 4AS were successfully converted to co-dominant KASP assays (BS00182960 and BS00164805) and were applied to the HS × DH81 F 4 and F 5 lines. In total, 14 LGC wheat KASP SNPs, 2 iSelect derived KASPs, 3 SSRs and 2 EST-SSR markers (Fig. 2) were applied to the 288 lines in the HS × DH81 F 4 population to construct a genetic map totalling 70.6 cM (Fig. 2). These 21 markers were also applied to each of the 78 recombinant F 5 lines to confirm the genotypes. Regions in Brachypodium, rice and sorghum were identified with synteny to the QFhs.jic-4AS region in wheat from BS00022015 to BS00164805 (Fig. 2). Although within this region, there was a high level of gene order conservation between the three reference genomes; this was not completely conserved in the genetic map order from HS × DH81, with the marker pairs BS00164805 and TC90601, TC93568 and BS00113963, and BS00022015and BS00003776 inverted compared to their orthologues. It was not possible to establish co-linearity outside of this region, with only two wheat markers identifying orthologues (BS00022816 orthologous to Bra-di1g11550, BS00003914 orthologous to Bradi4g20120). HS × DH81 trait analysis Line effects were significant for both AUDPC and % FHB traits in both 39 and 78 line experiment sets (Table 2). However, there was a significant line by experiment interaction for AUDPC in the 78 line experiments (p < 0.001) suggesting that there were differences in the relative performance of the lines across the two trials. Broad sense heritability for both AUDPC and %FHB traits were higher in the 39 line experiments (Table 2). This may reflect a better estimate of the genetic effects when using 4 environments, and additionally, may be influenced by a greater level of environmental control and more detailed scoring of disease in the polytunnel experiment of 39 lines. Predicted means of AUDPC and %FHB for the HS × DH81 recombinant F 5 lines were plotted in frequency histograms for all experiments ( Figure S1). It was not possible to detect a bimodal distribution as identified for the T. macha 4A resistance in Steed et al. (2005), with all experiments providing an approximate normal distribution of means. HS × DH81 QTL analysis Significant QTL originating from DH81 and conferring FHB resistance was detected in both the 39 line set and 78 line sets. The peak QTL position was located on the marker BS00011173 for AUDPC in both sets of lines and the same marker was identified as the peak QTL position for %FHB in the 78 line set. A slightly different location at TC93568 was identified as the QTL peak for %FHB in the 39 line set. However, this marker is only 3.1 cM away (Table 3), suggesting that this represents the same genetic effect. The QTL scan shows clear QTL peaks, particularly for %FHB across all 78 lines. It also shows consistent QTL location with LOD scores above the significant threshold for all 4 QTL analyses in the region approximately between 30 and 40 cM (Fig. 3). In addition to the main QTL identified at BS00011173 and TC93568, additional resistance QTL originating from HS were detected in the 39 line set at marker Wmc48 for %FHB and at marker BS00003623 for AUDPC. A single marker regression of individual trial locations identified that the major resistance QTL from DH81 identified in the SIM analysis was consistent across the experiments (Table 4). For AUDPC the single marker regression identified a significant association (p < 0.01) between resistance and markers within 3.5 cM of BS00011173 in all trials. Significant associations with %FHB were detected in a region overlapping BS00011173 and TC93568 in three experiments JIC, 2013CF and Polytunnel 2013. However, the experiment conducted in 2012 at JIC was less consistent, identifying a QTL at Gwm165, which is only 0.4 cM from TC93568, but also identifying a QTL at BS0006885 and BS00022015, which are 5.8 and 7 cM, respectively, from BS0001173 (Table 4). Although a QTL from HS conferring a reduction in %FHB was detected at Wmc48, and a QTL from HS conferring a reduction in AUDPC was detected at BS0003623 in the SIM analysis of the 39 line set, the single marker regression of data from individual trials only identified significant associations between this region and disease traits at markers Wmc48 and BS00036472 in the AUDPC trait from the 2013 JIC trial (Table 4). This suggests that this genetic effect is not consistent across environments. The polytunnel trial found the EST-SSR marker TC93568 accounts for the highest proportion of variation for both AUDPC and %FHB traits, using single marker regression. The greater amount of variation accounted for by markers within the polytunnel trial, compared to the field trials, may be due to a more homogenous environment and/ or the more detailed scoring of individual spikelets in this procedure. Steed et al. (2005) conducted all phenotyping in a polytunnel, and this may have assisted the detection of the resistance as a single gene with Mendelian inheritance. Background effects in the HS × DH81 population The wheat KASP panel and the wheat iSelect chip detected the presence of polymorphisms between HS and DH81 on chromosomes 4B and 7A (Table S3). These are likely to be due to remaining T. macha introgressions in DH81 that have not been removed by backcrossing. To test if these regions were influencing the phenotype, primers were obtained for the polymorphic wheat SNP panel KASP assays on 4B and 7A. On 4B, the wheat SNP BS00022576 provided a clear assay and was applied to the HS × DH81 F 5 recombinants. None of the 7A wheat KASP assays provided clear polymorphisms when tested on the population and therefore the iSelect SNP BS00160015 on 7A was converted into a KASP assay that was also applied to the HS × DH81 F 5 recombinants. Single marker regressions to compare these two markers to AUDPC and %FHB in the three trials did not identify any significant relationships (R 2 = 0-7.4 %, p > 0.05), suggesting that these regions are not influencing the observed phenotypes (Table S3). As for the QTL lines, no difference in plant height were observed within the HS × DH81 population. Discussion Previous genetic studies have suggested that relatively small effect FHB resistances may function additively to confer a higher level of resistance (Anderson et al. 2001;Buerstmayr et al. 2003;Snijders 1990). We combined the Type 2 1B and 3B resistances with the type 1 resistance from T. macha 4A (QFhs.jic-4AS) in a winter wheat background to test for additive effects when combining these resistances. The recurrent parent used in this experiment was Hobbit 'sib', a UK winter wheat with a high level of susceptibility. In particular, it contains Rht-D1b, which has been shown to be highly associated with susceptibility to FHB in numerous studies (Kollers et al. 2013;Srinivasachary et al. 2008Srinivasachary et al. , 2009. Despite the high level of susceptibility in the recurrent parent and the high level of disease pressure applied in inoculated, irrigated trials, the 3 resistances all conferred a high level of resistance when deployed individually, reducing both visual disease symptoms and DON content. Both 4A-3B and 4A-1B combinations demonstrated enhanced resistance in terms of reduced visual disease symptoms compared to the individual QTL suggesting that these resistances may function additively to reduce disease. This may be due to the combination of the Type 1 resistance QFhs. jic-4AS, with the Type 2 resistances Fhb1 (3B) and the 1B QTL. However, there was no evidence that these combined resistances functioned additively to reduce the amount of DON that was present in wheat grain at harvest. It is possible that more than one type 2 resistance, which act to prevent DON mediated disease spread, are required to provide an additive reduction in DON levels. The development of varieties with pyramided FHB resistances will be facilitated by increased mapping accuracy and more markers for selection of resistances. Fhb1 on chromosome 3B and the 1B QTL have been extensively mapped and a number of molecular markers are available for their selection through MAS. However, prior to this study, the map location of QFhs.jic-4AS was imprecise. Previous efforts to map this resistance have been restricted by a lack of polymorphic markers. Steed et al. (2005) utilised existing SSR and developed novel sequence-specific amplified polymorphism (SSAP) markers, but were not able to identify any distal markers to flank the resistance to facilitate marker assisted selection of the resistance by plant breeders. Developments in SNP technology and the availability of wheat SNPs both through the KASP assays (Allen et al. 2013) and the wheat 90 K iSelect genotyping assay (Wang et al. 2014) enabled saturation of the region surrounding the 4AS QTL. It was therefore possible to identify breeder-friendly KASP markers underlying the QTL region such as BS00011173 and BS00113963. It was also possible to identify distal flanking KASP assay markers such as BS0006885 and BS00022015, and proximal flanking markers such as the iSelect derived KASP BS00164805 and the KASP assay BS00036472 that would be suitable for selection of the region containing QFhs.jic-4AS. Although the effect of QFhs.jic-4AS was not potent in trials involving the recombinant lines, it was clear in the QTL combination lines, both alone and in combination with the Type 2 resistances from 1B and 3B. Previously, Steed et al. (2005) located the QFhs.jic-4AS as a single gene using visual disease symptoms observed in a polytunnel using a population 43 DH lines. The genetic effect of the region as a whole appears to be relatively large, providing heritability estimates of 0.55-0.82 for the FHB resistance traits recorded (Table 3), and the effect of the QTL was highly significant when studied in the QTL combination lines (Fig. 1) In contrast, in the present study using 78 F 5 lines from a recombinant population, we were unable to resolve the resistance as a single gene in any experiment or across experiments. However, we were able to locate the resistance quantitatively using SIM and single marker regression, and demonstrate that the effect is consistently identified across the experiments. It is possible that the T. macha 4A resistance is conferred by multiple genes of small effect distributed over the approximately 12.2 cM region between markers BS00011060 and BS00164805. The additional recombinants within the 288 F 4 lines and the high marker density in the present study, compared to the limited recombinants within the 43 DH lines studied by Steed et al. (2005), and in the 4A lines studied in the QTL combination field trials in the present study, may have fractionated QFhs.jic-4AS into multiple QTL within a small region. There is some evidence of this from the results obtained from the polytunnel trial when assessing disease severity, which identified three QTL peaks at BS00182960, TC93568 and Gwm192, and also from the JIC trial in 2012, which indicates two QTL conferring resistance to %FHB at Gwm165 and also at BS00022015-BS00068885. However, failure to resolve the QTL as a single gene may reflect the difficulty of accurately phenotyping FHB using only one score. This possibility is evidenced by the fact that the single-score data support a fractionated QTL while the integrated AUDPC score suggests a single QTL centring on marker TC93568. However, from the current data, it is not possible to determine whether there are multiple QTL or whether different loci have been detected as a consequence of unexplained variation in individual experiments. The generation of further recombinants and more detailed disease phenotyping of the lines using the greater accuracy that can be achieved in polytunnel trials are required to determine whether the phenotype observed from QFhs. jic-4AS is conferred by the additive effect of multiple QTL. Several previous studies have identified large effect QTLs that fractionate into multiple linked QTL when finemapping. This includes resistance against Phytophthora infestans in tomato (Johnson et al. 2012), the maize domestication QTL teosinte branched 1 (Studer and Doebley 2011), and a malting quality QTL complex in barley (Gao et al. 2004). Other factors may have hindered resolution of QFsh.jic-4AS as a single gene. Accurate phenotyping of Type 1 resistance is recognised to be challenging because of confounding effects of Type 2 susceptibility in lines such as Hobbit sib. used in the present study. Furthermore, disease pressure was extremely high in all trials, as revealed by the high levels of DON, and this may have resulted in the fungus overcoming the resistance conferred by QFsh. jic-4AS. Additional, detailed phenotyping using reduced disease pressure may assist in resolving this issue. The QFhs.jic-4AS was detected in approximately the same region, using both disease development (represented by AUDPC) and disease severity (represented by %FHB) measurements, in four independent phenotyping experiments. This suggests that the resistance can be considered to be stable, as it was expressed across different environments. Although previously identified as a Type 1 resistance, with no effect on disease spread following point inoculation, this data suggests that this resistance may have additional effects other than limiting initial colonisation (Type 1 resistance) as the resistance effect can be clearly observed when studying disease development over time (AUDPC). In addition, although the effects of the QFhs.jic-4AS QTL can be observed at earlier scoring times (data not shown), it appeared to have greatest effect when scoring visual symptoms after a relatively long period after inoculation (29-30 dpi) supporting the view that it also functions after initial infection. There are some discrepancies between the trials that should be considered when choosing markers for selection of the QFhs.jic-4AS resistance. For example, BS00164805 would appear to be suitable as a proximal flanking marker based on the AUDPC data from all four trials and from the %FHB data from JIC and the polytunnel trial, providing no evidence of association with the resistance (p < 0.01) and hence suggesting that this marker is located immediately proximal to the resistance. However, BS00164805 provides a significant association with the %FHB scores generated from the CF field experiment, suggesting that this marker may be associated with the QTL based on this analysis. In addition, the % variance accounted for tends to increase for this marker compared to the proximal marker TC90601. It is possible that this marker has been positioned incorrectly by genetic mapping and that it should sit between TC90601 and Gwm192, which would be supported by synteny in the region (Fig. 2). However, it is also possible that this marker is providing further evidence for fractionation of QFhs.jic-4AS. EST-derived SSRs (La Rota et al. 2005) and wheat KASP assay SNPs derived from transcript sequencing (Allen et al. 2011(Allen et al. , 2013 were used to identify orthologues in syntenic regions within the fully sequenced genomes of Brachypodium, rice and sorghum. This enabled the identification of the region in these species that was orthologous to QFhs.jic-4AS. This region was then examined to identify further wheat iSelect SNPs based on their homology with these reference genomes. However, there is some evidence of a breakdown of synteny between the order of loci as determined by the wheat × T. macha genetic map of 4A developed in this study and the physical gene orders in the reference sequences (Fig. 2). A breakdown of colinearity may be anticipated on chromosome 4A because it has undergone a significant number of rearrangements compared to the structure of related species. Previous studies have identified a peri-centromeric inversion involving a portion of the ancient long arm and the complete short arm, and interchanges with chromosomes 5A and 7B (Devos et al. 1995;Miftahudin et al. 2004). More recently, nextgeneration sequencing and synteny with Brachypodium, rice and sorghum was used to construct a chromosome 4A 'genome-zipper' with five syntenic segments (Hernandez et al. 2012). The QTL region in the present study lies partly within the syntenous chromosomal segment 'A' identified by Hernandez et al. (2012) from Bradi1g65190 to Bradi1g72092. The breakdown of gene order conservation within the QTL region and our inability to establish any colinearity outside of the region, suggests that there may be a limitation in the use of synteny for further fine-mapping of QFhs.jic-4AS, particularly as the resistance may be controlled by multiple loci over the region. In conclusion, we have demonstrated that Type 1 and Type 2 resistances can be combined in a highly susceptible background to provide an additive reduction in visual disease symptoms. However, caution should be exercised as this reduction in visual symptoms, may not be translated into a reduction in mycotoxin levels. To enhance the capabilities for marker assisted selection of the FHB Type 1 resistance QFhs.jic-4AS, we have developed additional recombinants and identified a number of SNP markers suitable for use by plant breeders. However, we were not able to locate and map the resistance as a single gene. Author contribution statement CB undertook mapping, genotyping, phenotyping and writing of the manuscript, NG initiated production of QTL materials, AS undertook crossing and field work, ML undertook FHB trials in Tulln, NB and RR-G assisted with marker development, SH undertook mapping population development, and PN conceived and coordinated the work.

v3-fos

2018-04-03T04:20:55.857Z

2015-03-27T00:00:00.000Z

206039979

s2

Effects of blending wheatgrass juice on enhancing phenolic compounds and antioxidant activities of traditional kombucha beverage Traditional kombucha is a fermented black tea extract and sugar. Sweetened black tea (10% w/v) and wheatgrass juice (WGJ) were mixed in various ratios and used as fermentation substrate for enhancing phenolic compounds and antioxidant activity. Starter, comprising of yeast (Dekkera bruxellensis) and acetic acid bacteria (Gluconacetobacter rhaeticus and Gluconobacter roseus), was inoculated at 20% (v/v), and fermented statically at 29 ± 1°C for 12 days. The results showed that the total phenolic and flavonoid contents and antioxidant activity of the modified kombucha were higher than those of traditional preparations. All WGJ-blended kombucha preparations were characterized as having higher concentrations of various phenolic compounds such as gallic acid, catechin, caffeic acid, ferulic acid, rutin, and chlorogenic acid as compared to traditional ones. Addition of WGJ resulted in the 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging ability of kombucha being > 90%, while the oxygen radical absorbance capacity increased from 5.0 μmol trolox equivalents/mL to 12.8 μmol trolox equivalents/mL as the ratio of WGJ increased from 0% to 67% (v/v). The highest antioxidant activity was obtained using a 1:1 (v/v) black tea decoction to WGJ ratio and 3 days of fermentation, producing various types of phenolic acids. These results suggest that intake of fermented black tea enhanced with wheatgrass juice is advantageous over traditional kombucha formulas in terms of providing various complementary phenolics and might have more potential to reduce oxidative stress. Introduction Kombucha is a well-known fermented health beverage popular in many countries [1]. Kombucha is traditionally made by fermenting sugared black tea using a symbiotic culture of acetic acid bacteria (e.g., Acetobacter xylinum, Acetobacter xylinoides, or Bacterium gluconicum) and yeast (e.g., Schizosaccharomyces pombe, Saccharomyces ludwigii, Zygosaccharomyces rouxii, Candida spp., or Pichia spp.) statically for 2 weeks. The fermentation product is comprised of two components: a floating cellulosic pellicle layer and a sour-tasting and slightly sparkling liquid broth [2]. It contains many compounds with antioxidant activity, such as phenolics, water-soluble vitamins, organic acids, and minerals [2,3]. Williamson et al [4] demonstrated that the antioxidant activity of kombucha, which may be attributed to the tea polyphenols, can increase the in vivo antioxidant ability. Oral administration of kombucha to rats exposed to pro-oxidation species also indicated the potent antioxidant properties of the fermented drink such as decrease of the degree of lipid oxidation and DNA fragmentation [5]. The antioxidant activity of kombucha corresponds highly to the fermentation substrate (tea leaves); moreover, some components of tea promote cellulose formation from acetic acid bacteria [6]. Greenwalt et al [7] showed that using green tea as the substrate could minimize the fermentation time; however, to retain its characteristic flavor, black tea is still used as the fermentation substrate in the traditional kombucha [6]. Substances with antioxidant properties offer many benefits to the human body [8]. The antioxidants found in kombucha fermentation substrates originated in tea leaves and mainly include polyphenols, especially catechins, which belong to the flavones group [5,9]. Black tea leaves in substrates used for preparing traditional kombucha account for only 1% (w/v) of the total, and in fact do not play a major role in fermentation compared with sucrose (ca. 10%, w/v). Instead, black tea contributes the sensory attributes such as flavor and taste to kombucha, and with a lesser extent on acting as a source of antioxidant substances. The beneficial effects, particularly in antioxidant activity and phenolic substance content, would be further enhanced if we supplement the traditional kombucha with other substrates such as herbs or vegetables. Wheatgrass juice (WGJ) is an extract squeezed from the mature sprouts of wheat seeds (Triticum aestivum). The therapeutic qualities of WGJ have been attributed to its rich nutrient contents, including chlorophyll, vitamins (A, C, and E), bioflavonoids, minerals (iron, calcium, and magnesium), and phenolics (ferulic acid and vanillic acid) [8]. Kulkarni et al [10] reported that WGJ has high antioxidant activity partly because it contains such antioxidants as phenolic compounds and several flavonoids. Phenolics and flavonoids have been shown to remove superoxide radicals (O 2 À or HO 2 À ) in vivo and decrease the cell damage caused by oxidative stress [9]. Wheatgrass extracts also possess superoxide scavenging and ferric reducing abilities [8,10]. Their ability to inhibit oxidative DNA damage was also demonstrated [11]. Several days of acetic acid bacteria and yeast co-culture have been shown to yield a high antioxidant activity. However, the fermentation process is long and produces a large amount of acetic acid from acetic acid bacteria, which affects the flavor of the drink. Therefore, long fermentation processes are not suitable for health beverage production. In addition, few studies have used materials besides tea leaves as the fermentation substrate for kombucha. The aim of this study is to assess the changes in kombucha's antioxidant activity and phenolic compounds during fermentation as affected by different ratios of sugared black tea decoction and WGJ. Starter culture Starter culture, or kombucha culture, was collected from a local cultivator who grows kombucha periodically in Taichung, Taiwan and maintained in sugared black tea. The culture includes both the upper pellicle layer and the lower liquid. The major bacterial components were identified as Gluconacetobacter rhaeticus and Gluconobacter roseus and the yeast component as Dekkera bruxellensis at Mission Biotech (Taipei, Taiwan). The starter culture was periodically maintained according to method of Chen and Liu [2], except that black tea leaves were used. Sweetened black tea Ten percent (w/v) sucrose was added to deionized water and heated at 100 C for 5 minutes. Next, 1% (w/v) black tea leaves (Ten-Ren Co., Taipei, Taiwan) were added, allowed to steep for 15 minutes, and then filtered through a sterile sieve. WGJ-blended kombucha fermentation Sweetened black tea and WGJ were mixed in various ratios to create six groups of WGJ-blended black tea broth, with five glass jars (capacity 500 mL) in each group (Table 1). To each group, the broth was dispensed equally into five glass jars (each containing 120 mL broth) that had been previously sterilized at 121 C for 20 minutes. Each jar was then inoculated with 30 mL of previously fermented kombucha liquid starter that had been cultured in the sweetened black tea for 10 days. The jars were carefully covered with clean cheesecloth and fastened with rubber bands. The fermentation was j o u r n a l o f f o o d a n d d r u g a n a l y s i s 2 3 ( 2 0 1 5 ) 7 0 9 e7 1 8 carried out in a dark incubator at 29 ± 1 C for 12 days. Sampling was performed by removing one jar from the incubator at 3-day intervals. Changes in functional components of the samples were analyzed. The jar and its content were discarded after sampling to avoid disturbing the static fermentation ascribed to the floating pellicle layer, i.e., each jar was sampled once only. Determination of pH The pH of the samples was measured in triplicate with an electronic pH meter (pH 720; inoLab, Weilheim, Germany) in accordance with AOAC protocols (2005). Total phenolic content The total phenolic content (TPC) was determined using the FolineCiocalteu colorimetric method by Gorinstein et al [12], with modifications. The sample (0.1 mL) was mixed with 2 ml of 2% sodium carbonate. After 2 minutes, 0.1 mL of 50% FolineCiocalteu reagent was added and the solution was allowed to stand for 30 minutes at room temperature. The samples were measured at 750 nm versus a blank using a spectrophotometer (U-2000; Hitachi Ltd., Tokyo, Japan). The results were expressed as mg of gallic acid equivalent (GAE)/ mL of sample. Total flavonoid content The total flavonoid content (TFC) was determined using a crystalline aluminum chloride assay according to the method described by Maksimovi c et al [13]. The sample (1.5 mL) was added to an equal volume of 2% aluminum trichloride and allowed to stand for 10 minutes to allow the formation of a flavonoidealuminum complex, after which the absorbance at 430 nm was recorded. The total flavonoid content was expressed as quercetin equivalents (QE) from the calibration curve. Total anthocyanin content The total anthocyanin content TAC was determined according to the modified method of Ruenroengklin et al [14]. The sample (0.1 mL) was mixed with acidified methanol (1% HCl/ methanol), stored in the dark at 4 C for 30 minutes, and then centrifuged at 9100 g for 15 minutes. The anthocyanin concentration in the supernatant was measured spectrophotometrically at 530 nm and 657 nm, and the absorbance values were indicated as A 530 and A 657 , respectively. The concentration was calculated using the following equation: Anthocyanin concentrationðmMÞ The results are expressed as the average of triplicate measurements. Phenolic composition The phenolic composition was analyzed by high-performance liquid chromatography (HPLC). Filtered samples (2 mL) were passed through a membrane filter (0.45 mm) into HPLC vials. The filtrate obtained was analyzed for gallic acid, catechin, caffeic acid, ferulic acid, rutin, and chlorogenic acid by HPLC. A 10 mL of filtrate sample was separated by a reverse phase column (Mightysil RP-18 GP 250 mm  4.6 mm, 5 mm; Kanto Corporation, Portland, OR, USA) according to the method of Nuutila et al [15]. The HPLC system (Hitachi) was equipped with an autosampler (L-2200; Hitachi) and a photodiode-array detector (L-2455; Hitachi). The injection volume was 10 mL, and the pump (L-2130; Hitachi) applied a gradient of solvent A (0.1% phosphoric acid containing 0.1% acetonitrile and 5% N, N-dimethylformamide) and solvent B (100% acetonitrile) at a flow rate of 0.8 mL/min. The gradient elution started with 100% A (0% of solvent B), linearly up to 100% B at the end of a 50-minute cycle. The analyses were monitored at a wavelength of 280 nm, and the calibration standards used for quantification of the samples were gallic acid, catechin, caffeic acid, ferulic acid, rutin, myricetin, and chlorogenic acid. DPPH scavenging ability The DPPH assay was conducted according to the method of Yamaguchi et al [16]. with some modifications. First, 200 mL of sample or MeOH (control) was mixed with 100mM Tris-HCl buffer (pH 7.4, 800 mL) and then added to 1 mL of 500mM DPPH (1,1-diphenyl-2-picrylhydrazyl) in ethanol (final concentration of 250mM). The mixtures were shaken vigorously and allowed to stand in the dark at room temperature for 20 minutes, after which the absorbance was read at 517 nm using a spectrophotometer. The scavenging capacity of the sample was calculated using the following equation: Trolox equivalent antioxidant capacity The method used was as described by Miller et al [17] based on the capacity of a sample to inhibit the 2,2 0 -azinobis (3ethylbenzothiazoline-6-sulfonate) radical (ABTS þ ) relative to a reference antioxidant standard (Trolox). The ABTS radical cation was generated by the interaction of ABTS (100mM), hydrogen peroxide (50mM), and peroxidase (4.4 units/mL). Fresh ABTS þ solution was prepared for each assay. To measure the antioxidant capacity, 0.25 mL of the sample was mixed with 2.25 mL of the radical solution. The absorbance was monitored at 734 nm for 10 minutes. The decrease in absorption at 734 nm after the addition of reactant was used to calculate the Trolox equivalent antioxidant capacity (TEAC) value. Oxygen radical absorbance capacity The oxygen radical absorbance capacity (ORAC) assay was performed according to the method of Ou et al [18] with some modifications. Analyses were conducted in 75mM phosphate buffer (pH 7.4) at 37 C. A freshly prepared fluorescein (150 mL of a 40nM solution) was mixed with 25 mL of the sample. The mixture was preincubated for 15 minutes at 37 C before rapidly adding 25 mL of 250mM 2,2 0 -azobis(2-amidino-propane) dihydrochloride using a multichannel pipette. After incubation, fluorescence measurements (excitation, 485 nm; emission, 520 nm) were taken every 90 seconds to determine the background signal. The test was resumed, and fluoresence measurements were taken for up to 60 cycles using a microplate reader (FLUOstar Omega, BMG Labtech, Offenburg, Germany). The ORAC values were calculated using Trolox and sample concentrations and the net area under the fluorescein decay curve (AUC). The AUC was calculated as: where, f0 is the initial fluorescence reading and fi is the fluorescence reading at time i. The data were analyzed in Microsoft Excel to calculate the AUC. The net AUC was obtained by subtracting the AUC of the blank from that of the sample. The antioxidant activity of the test samples was expressed as mmol Trolox equivalents (TE)/mL. Statistical analysis Data are presented as the mean ± standard deviation, and all analyses were performed in triplicate. The results were evaluated using one-way analysis of variance and Duncan's multiple range test. The level of significance was set at p < 0.05. SPSS for Windows, version 10.0 (SPSS Inc., Chicago, IL, USA) was used for the analyses. Acidity The pH changes for the six groups of kombucha with or without incorporating WGJ during the fermentation are shown in Fig. 1. During the fermentation, the pH of each group decreased with increasing days of culturing, from pH 4.0 to pH 2.9. The initial pH of the medium was higher for higher ratios of WGJ to sweetened black tea. The difference in the pH is due to the culture medium substrate, which is affected by the chemical composition of black tea and WGJ [1,2]. The different substrate ratios exhibit different changes in pH but with a similar overall tendency (final pH, shape of the pH curve) during the fermentation. The result showed that changing the fermentation substrate did not affect the growth of the starter culture (yeast and acetic acid bacteria), ultimately yielding similar pH values. TPC, TFC, and TAC Vegetables, fruits, and tea contain high TPC, TFC, and TAC levels [19]. The TPC and TFC concentrations for all six groups increase with fermentation time ( Fig. 2A and B). The increase in phenolic compounds may come from polyphenols. The microorganisms in kombucha (mainly acetic acid bacteria and yeasts) release enzymes during fermentation, which can degrade polyphenols into small molecules. Therefore, the antioxidant activity of the sample may be derived from phenolics, including flavonoids. Falcioni et al [11] indicated that wheat sprout extracts inhibit DNA oxidative damage and are effective in suppressing the superoxide radical that can lead to various diseases. Because of their ideal chemical structure for free radical scavenging activities, polyphenols have been shown to be more effective in vitro antioxidants than vitamins E and C [20]. The data in Fig. 2C show that there is not much difference in the TAC among the six groups, with values of approximately 0.53 ± 0.02mM to 0.65 ± 0.03mM. Anthocyanins are phenolic compounds widely present in vegetables and fruits with radical-clearing ability and antioxidant activity. The pH value is the most important factor in determining the stability of anthocyanins; under acidic conditions, anthocyanin retains its chemical structure and becomes more stable [21]. Anthocyanins are water-soluble and the fermentation environment provides high-acid conditions (Fig. 1); moreover, the anthocyanins are less strongly affected by metal ions, temperature, and structural transformations. Free anthocyanins can combine with catechin and phenolic compounds to form anthocyanin polymers, leading to a decrease in anthocyanin monomers along with a subsequent increase in anthocyanin polymers during fermentation [22]. Anthocyanins exhibit antioxidant ability due to their polyphenol-like functional structure. Extensive studies indicate that anthocyanins have strong free radical scavenging and antioxidant activities, reduce DNA mutation from oxidative stress, and reduce lipid peroxidation in colorectal, endothelial, hepatic, and breast cells [23]. Primary identification of phenolic constituents The chromatograms of the major antioxidant component of polyphenolics, namely, phenolics, present in kombucha samples after 3 days fermentation are shown in Fig. 3. Fig. 3A presents a chromatogram of phenolic standards. Fig. 3B and 3CeG represent the chromatograms of traditional kombucha (TK) and kombucha blended at various ratios with wheatgrass juice, as shown in Table 1 (WK1e5), respectively. Some active Fig. 1 e Effects of volume ratios of wheatgrass juice to black tea decoction on changes in pH of WGJ-blended kombucha during fermentation. Data are expressed as mean ± standard deviation of three samples. TK ¼ traditional kombucha; WK1e5 ¼ kombucha blended at various ratios with wheatgrass juice, as shown in Table 1. phenolic acids, such as gallic acid, catechin, caffeic acid, ferulic acid, rutin, and chlorogenic acid, can be resolved in this system ( Table 2). As the results show, caffeic acid is the most prevalent phenolic acid of the TK polyphenols, followed by gallic acid and catechin. As the proportion of WGJ increased, the caffeic acid, gallic acid, and catechin contents decreased, whereas the contents of ferulic acid, rutin, and chlorogenic acid increased. Kombucha made from black tea and WGJ substrates contains many types of phenolic acids. Tea and vegetables contain phenolics, which have been implicated in improving the health of test animals and humans [9]. Tea contains catechins, caffeine, and gallic acid, among other compounds [9]. Wheatgrass contains vitamins C and E, bcarotene, ferulic acid, and vanillic acid [10]. Phenolic acids can be derived from two nonphenolic molecules: benzoic acid and cinnamic acids. Gallic acid, vanillic acid, syringic acid, gentisic acid, and p-hydroxybenzoic acid are hydroxyl derivatives of benzoic acid, whereas caffeic acid, ferulic acid, sinapic acid, and p-coumaric acid are hydroxyl derivatives of cinnamic acid. Regarding the antioxidant structure, the eCH]CHeCOOH in hydroxycinnamic acid has better antioxidant activity than the eCOOH in hydroxybenzoic acid. It is likely that the eCH]CH section gains structural resonance, stabilizing the free radicals [24]. Gallic acid has higher antioxidant activity than hydroxybenzoic acid, and the antioxidant activities of hydroxycinnamic acids are ranked in descending order as follows: ferulic acid > p-coumaric acid > sinapic acid > o-coumaric acid > m-coumaric acid > caffeic acid > chlorogenic acid [25]. In addition, the TEAC and ORAC assays reveal that gallic acid, catechin, caffeic acid, ferulic acid, rutin, and chlorogenic acid also exhibit good antioxidant activity [18]. Some phenolic acids, such as caffeic acid, chlorogenic, ferulic, gallic acid, and ellagic acid, have been found to be pharmacologically active as antioxidant, antimutagenic, and anticarcinogenic agents [26]. The WGJ and black tea substrates provide the kombucha cultures with high contents of various phenolics and combine the high antioxidant activities of two phenolic acids: gallic acid and ferulic acid. DPPH radical scavenging ability The use of DPPH assay is a reliable method for determining the antioxidant ability of biological substrates. The DPPH radical scavenging activity is a general assessment of the inhibition percentage of preformed free radicals by antioxidants. As shown in Fig. 4, the six beverages have good DPPH scavenging activity; the DPPH clearance percentage is as high as 85% and increases with increasing incubation time. By the 3 rd day of fermentation, the beverage with the optimal proportion of WGJ exhibits 90% DPPH scavenging; WK1, WK2, and WK3 had the highest DPPH clearance until the end of the fermentation. Kombucha can be made from green tea, oolong tea, or black tea, all of which have good antioxidant capacities. Wheatgrass extracts also possess superoxide scavenging and ferric reducing power [8]. Their ability to inhibit oxidative DNA damage has also been demonstrated [11]. Brand-Williams et al [27] reported that phenolics have DPPH scavenging ability due to their phenolic content, which can provide hydrogen. Table 1. j o u r n a l o f f o o d a n d d r u g a n a l y s i s 2 3 ( 2 0 1 5 ) 7 0 9 e7 1 8 Table 1. Nishidai et al [28] fermented vinegar using acetic acid bacteria with different substrates, revealing that the vinegar fermented using a phenolic-acid-rich substrate had the highest DPPH clearance. Phenolic compounds easily donate hydroxyl hydrogen due to resonance stabilization [17]. Lu and Foo [29] have more definitively shown that the structure in phenolic compounds can supply hydrogen, specifically in the b chain with 2,3 double bonds as well as 4-oxo and 3,5 site hydroxyl groups. This hydrogen supply confers phenolic compounds with excellent DPPH scavenging capacity. Among the DPPH radical scavenging systems, all phenolic compounds, including caffeic acid, chlorogenic acid, 3,5-dicaffeoylquinic acid, ferulic acid, rosmarinic acid, and protocatechuic acid, have free radical scavenging abilities. In fact, the free radical scavenging ability of many phenolic acids is better than that of dl-a-tocopherol or ascorbic acid [20]. WGJ contains many phenolic compounds that function as antioxidants. Therefore, increasing the proportion of WGJ to black tea in the substrate during kombucha fermentation enhances the antioxidant capacity, as the phenolic compounds supply hydrogen with excellent DPPH scavenging capacity. TEAC assay The TEAC assay is based on the inhibition of the absorbance of the ABTS radical cation by antioxidants. The TEAC results for the six beverages are shown in Fig. 5. The average value of TEAC was 0.6 mmol Trolox/mL. In TK, the TEAC capacity increased slowly with fermentation time. The WK1 sample reached its maximum capacity by the 3 rd day, whereas WK3e5 samples peaked on the 6 th day. This result indicates that the free radical scavenging capacity for ABTS þ was different from that of DPPH Because the phenolic compounds have structural differences, each phenolic compound had a different antioxidant capacity and thus behaved differently in the antioxidant assay. In addition, the polarity, ionic conditions, and stereo structure of an antioxidant should affect its capacity evaluation [17]. The report showed that the antioxidation capacity of Data are expressed as mean ± standard deviation of 3 samples. aef Significant differences within a column (p < 0.05). TK ¼ traditional kombucha; WK1e5 ¼ kombucha supplemented at various ratios with wheatgrass juice, as shown in Table 1. j o u r n a l o f f o o d a n d d r u g a n a l y s i s 2 3 ( 2 0 1 5 ) 7 0 9 e7 1 8 a phenolic compound was related to the amount and position of its hydroxyl groups, and the antioxidant capacity then affects its free radical scavenging ability [24]. The antioxidant determination method is highly dependent upon the substances' reaction or the conditions of the sample during monitoring; therefore, each antioxidant determination method will yield a different result, largely due to the differences between the variables in the analysis method. Perez et al [30] compared the ORAC, TEAC, and TRAP methods in samples of red wine and white wine and did not find any correlations between the methods. When a sample is complex or contains strongly different antioxidants, the correlation between the ORAC and TEAC methods is low because of the different kinetics and reaction mechanisms of the various antioxidants present [31]. ORAC The ORAC assay is one of the methods used to evaluate the antioxidant capacity of various biological substrates, ranging from pure compounds, such as phenolic acids and flavonoids, to complex matrices, such as fruits, vegetables, and teas [9,25]. As shown in Fig. 6 [11] demonstrated that wheatgrass extract exhibits free radical scavenging ability, inhibits membrane injury, and minimizes oxidative DNA damage induced by free radicals. The main reason for this behavior is that wheatgrass contains phenolic compounds with flavonoids, some of which are biologically active Peroxide free radicals, ROO (peroxyl radical), are usually used to estimate biological antioxidant activity because peroxyl radicals have long half-lives second only to those of hydroxyl radicals in toxin, pass freely through cell membranes, and are an intermediate product in cell membrane lipid peroxidation reactions [28]. The performance of WK1e3 in scavenging ORAC ROO indicates that cells can be Fig. 6 e Effects of volume ratios of wheatgrass juice to black tea decoction on changes in oxygen radical absorbance capacity (ORAC) of WGJ-blended kombucha during fermentation. Data are expressed as mean ± standard deviation of three samples. TK ¼ traditional kombucha; WK1-5 ¼ kombucha blended at various ratios with wheatgrass juice, as shown in Table 1. Fig. 5 e Effects of volume ratios of wheatgrass juice to black tea decoction on changes in trolox equivalent antioxidant capacity (TEAC) of WGJ-blended kombucha during fermentation. Data are expressed as mean ± standard deviation of three samples. TK ¼ traditional kombucha; WK1e5 ¼ kombucha blended at various ratios with wheatgrass juice, as shown in Table 1. Fig. 4 e Effects of volume ratios of wheatgrass juice to black tea decoction on changes in DPPH radical scavenging ability of WGJ-blended kombucha during fermentation. Data are expressed as mean ± standard deviation of three samples. TK ¼ traditional kombucha; WK1e5 ¼ kombucha blended at various ratios with wheatgrass juice, as shown in Table 1. constantly protected from oxidative damage by peroxyl radicals. TEAC and ORAC assays have proven that phenolics have peroxyl radical scavenging ability. Phenolics can scavenge the peroxyl radical and stop the lipid oxidation chain reaction [28]. The related antioxidant activities among phenolic compounds are as follows: caffeic acid > isoeugenol > ferulic acid > p-coumaric acid [25]. Tea leaf phenolics include gallic acid, catechin, caffeic acid, and tannins [9]. Wheatgrass contains numerous antioxidant substances, such as ferulic acid, vanillic acid, vitamins C and E, and b-carotene [8]. The kombucha broth co-cultured with black tea and WGJ (WK1-3) contain phenolic compounds, which provide cations to stop the peroxyl radical chain reaction in the antioxidation reaction. Cao et al [9] noted that the ORAC method had greater specificity and was capable of responding to a greater number of antioxidant compounds than the TEAC method and that the total phenol content can affect the total antioxidant ability. Length of culture time affects the composition of the culture broth; antioxidant capacity thus increases during fermentation. Therefore, the antioxidant capacity depends on the hydrogen-bond binding ability, pH, oxidation-reduction potential, solubility, and stereo structure with oxygen of phenolic compounds [20]. These factors help to explain the differences between the antioxidant activities. In addition, the products also have higher antioxidant activity after fermentation [32]. In the present study, the analysis mechanism for the antioxidant assays depends on the reaction components. The appropriate adjustment of the fermentation substrates can shorten the culture time while maximizing the antioxidant capacity. The result shows that not only the total phenol content, total flavonoid content, and total anthocyanidin content, but also the types and contents of phenolic compounds in the culture broth, determine the comprehensive antioxidant activity of a beverage. Conclusion In our study, the culture substrate was adjusted in terms of the ratio of WGJ to black tea. The wheatgrass-blended kombucha fermented from these altered substrates reveals that each formulation presents different free radical scavenging capacity and that incubation with various substrates produces different metabolites and antioxidant activities. The highest antioxidant activity for the 1:1 WGJ:black tea substrate was obtained after 3 days of fermentation. This result clearly shows that the modified kombucha is a better free radical scavenging agent than traditional kombucha. The novel kombucha includes antioxidant activity from not only flavonoids and anthocyanins but also phenolic compounds from the culture broth. The data also showed that the antioxidation capacity of wheatgrass-blended kombucha includes contributions from the main phenolic acids, including gallic acid, catechin, and caffeic acid from the traditional kombucha and ferulic acid, rutin, and chlorogenic acid from the wheatgrass juice. Therefore, the wheatgrass-blended kombucha has higher, more stable antioxidant activity and might be recommended for consumption as a novel beverage.

v3-fos

2017-11-08T18:54:42.361Z

2015-06-03T00:00:00.000Z

15979676

s2

Amplicon-based metagenomics identified candidate organisms in soils that caused yield decline in strawberry A phenomenon of yield decline due to weak plant growth in strawberry was recently observed in non-chemo-fumigated soils, which was not associated with the soil fungal pathogen Verticillium dahliae, the main target of fumigation. Amplicon-based metagenomics was used to profile soil microbiota in order to identify microbial organisms that may have caused the yield decline. A total of 36 soil samples were obtained in 2013 and 2014 from four sites for metagenomic studies; two of the four sites had a yield-decline problem, the other two did not. More than 2000 fungal or bacterial operational taxonomy units (OTUs) were found in these samples. Relative abundance of individual OTUs was statistically compared for differences between samples from sites with or without yield decline. A total of 721 individual comparisons were statistically significant – involving 366 unique bacterial and 44 unique fungal OTUs. Based on further selection criteria, we focused on 34 bacterial and 17 fungal OTUs and found that yield decline resulted probably from one or more of the following four factors: (1) low abundance of Bacillus and Pseudomonas populations, which are well known for their ability of supressing pathogen development and/or promoting plant growth; (2) lack of the nematophagous fungus (Paecilomyces species); (3) a high level of two non-specific fungal root rot pathogens; and (4) wet soil conditions. This study demonstrated the usefulness of an amplicon-based metagenomics approach to profile soil microbiota and to detect differential abundance in microbes. INTRODUCTION Verticillium dahliae Kleb. is a soil-borne fungal pathogen, which penetrates the roots of a wide range of host plant species causing the disease Verticillium wilt 1 . The pathogen colonises the vascular system of the roots and crown depriving the leaves and stems of water. Also, it produces microsclerotia in the host as the infected tissues senesce, which are released into the soil as the plant decays and are the primary inoculum of V. dahliae in the soil for subsequent infection. Microsclerotia may survive for more than 10 years in the soil in the absence of its hosts 1 . Wilt incidence tends to be higher in soils infested with the root lesion nematode, Pratylenchus penetrans, which feed on the roots causing wounds, thus increasing entry sites for the pathogen and affecting fungal infection/ colonisation of vascular tissue 2,3 , although the magnitude of this interaction may vary greatly with individual fungal strains 4 . Chemical treatments, such as methyl bromide and chloropicrin, have been an indispensable tool for the past 40 years because of their excellent efficacy, effectively managing Verticillium wilt in strawberry; however, several of these treatments are already banned (e.g. methyl bromide) or face an uncertain future due to legislation (e.g. chloropicrin) 5 . With the loss of methyl bromide and other fumigants, strawberry (Fragaria 3 annanasa) production has come under increasing threat of losses due to wilt caused by V. dahliae. Some alternative measures have control efficacy similar to that achieved by commercial chemical fumigants, but others are not as good 6 . One of the alternatives being investigated is biofumigation, which uses decay products of green manures [7][8][9][10] . Control of V. dahliae through the use of Brassica species plants is believed to result from the toxic isothiocyanates (ITCs), released into the soil after incorporation of glucosinolate-containing plant tissues 11 . A recent study suggested that biofumigation based on the Brassica species cannot fully control wilt because of the limited amount of the ITC released 9 . Other plant species have also been studied for their biofumigation effects against V. dahliae. For example, biofumigation using Lavandula plant materials can result in large reductions in the numbers of viable microsclerotia recovered 12 . Recently, anaerobic soil disinfestation (ASD) methods have been studied for their effects against a range of soil pests and pathogens. Traditional ASD with grass was less effective than with organic materials; all materials proved to be effective at 16 6 C against P. penetrans, Meloidogyne hapla, Globodera pallida and V. dahliae with V. dahliae being most difficult to control 13 . Control efficacy depends on many factors, including soil characteristics, types of organic material, temperature, dosage and exposure time. Soil organic amendments, especially combined with biocontrol agents, can satisfactorily suppress Verticillium wilt 14 , but the effect is often inconsistent and pathosystem specific, revealed by a metastudy 15 . Rotation with other crops, e.g. Brassica and lettuce, can reduce wilt on strawberry 16,17 , but this management strategy is generally not commercially viable. Specific microbial organisms have been tested against soil-borne pathogens, including V. dahliae. Application of two biocontrol organisms (Paenibacillus alvei K165 and the nonpathogenic Fusarium oxysporum F2) at the transplant stage reduced Verticillium wilt symptom development in aubergine 18 . Both organisms induced the expression of the pathogenesis-related (PR) proteins PR1 and PR4 in the stem of aubergines. Many fungi and bacteria were isolated from rhizosphere of oilseed rape and strawberry and tested against V. dahliae 19,20 . Many bacterial (primarily Pseudomonas and Serratia spp.) and fungal species were found to be antagonistic against wilt. There was also some evidence to suggest that some fungi were specifically enriched in each rhizosphere, which is supported by a recent finding that rhizosphere communities are partially genetically controlled by hosts 21 . Dipping plants in a suspension of Serratia plymuthica prior to planting reduced Verticillium wilt of strawberry and increased yield 22 . Plant growth-promoting rhizobacteria (PGPR) have recently received much attention for their use to increase crop production, including their role in suppressing disease development 23 . Non-pathogenic strains of V. dahliae can also be used as a biological control agent to exploit the concept that preoccupation of the ecological niche rendered strawberry plants immune to infection with pathogenic V. dahliae. Inoculation of non-pathogenic strains of V. dahliae reduced wilt on 20% of treated plants but led to increased wilt development on 50% of treated plants 24 . The monoterpenoids associated with the Lavandula spp., which are of lower volatility than the ITCs associated with brassica decomposition, were detected for more than one week after materials were incorporated in soil 12 . Three of these terpenoids were shown to reduce microsclerotium viability in microcosm tests. Recently, we have conducted field experiments to compare a new product based on microencapsulation of the three terpenes (cineole, camphor and borneol) and several other alternatives for their efficacy against wilt on strawberry with the commercial chemofumigant (chloropicrin) as a standard. Results from the trials showed that overall the terpene-based product reduced wilt development but did not increase fruit yield, compared to the un-treated control. However, at two of the eight trial sites, the chloropicrin treatment led to nearly 25% increase in yield, compared to all other treatments, but the level of wilt was similar among all treatments. Chloropicrin-treated plants had increased growth vigour compared to all other treatments; all other treatments had more or less uniformly stunted growth, which cannot be associated with any obvious biotic and abiotic factors (although strawberry roots were not sampled for assessment). We speculated that this yield decline resulted from interactions among a number of microbial organisms, similar to apple replant disease 25 . Involvement of other beneficial or pathogenic microbial organisms in strawberry was implicated in several other experiments on controlling Verticillium wilt 13,22 . This paper reports the results from studies aiming to identify candidate microorganisms that are responsible for observed yield decline in strawberry of non-chloropicrin-treated plants. This study reports primarily data-driven research, aiming to generate hypotheses on the possible candidate organisms responsible for the observed yield decline, which can then be further tested in future. Specifically, we used an amplicon-based metagenomics approach to profile soils from different treatments at four sites -two with and two without yield-decline phenomenon. Through statistical comparison of individual microbial operational taxonomy units (OTUs), combined with several objective selection criteria, several candidate organisms were identified as candidates that may have played a role in the observed yield decline. Field sites and sample collection Evaluation of the efficacy of a new microencapsulated terpene-based product and other alternatives to control Verticillium wilt was conducted at eight sites: three in 2011, three in 2012 and two in 2013. At two sites in 2012, a yield-decline phenomenon in strawberry was observed. Based on the physical distances between the trial sites, four sites (two in 2012: PV12 and HB12 and two in 2013: HB13 and EM13) were selected for microbial profiling to identify candidate microorganisms that may be involved in the yield-decline phenomenon. HB12 and HB13 were two fields at the same farm (about 1 km apart), about 15 km and 25 km from the PV12 and EM13 sites, respectively; PV12 was about 40 km from the EM13 site. At each site there were three blocks; within each block, there was one plot per treatment. The plot size was 15 m long (a single bed of double rows) with four metres between neighbouring plots. Immediately after soil treatment, all beds were covered with black polythene; beds were planted three weeks after treatment. All plots were automatically irrigated through drip tape. Soil samples from the four sites were obtained in 2013 or 2014; details of samples are given in Table 1. Although there were six (2012) and eight (2013) treatments, only selected treatments were sampled for microbial profiling. For the two yield-decline sites, nearly two years had passed since the treatment when soil samples were taken in 2013. Thus, the chloropicrin effect in preventing yield decline may have significantly reduced -this had to be taken into account when trying to identify causal agents responsible for yield decline at these two sites. Although for the two 2012 sites, soil samples were taken long after the trial cropping was finished, the land was not used for other purposes and hence the plot (bed) structure was still intact at the time of sampling. For each plot, a composite soil sample was obtained, consisting of 10 core soils that were obtained with a sampler (2.5 cm in diameter) from a depth of 20 cm at randomly selected locations and then mixed by sieving (mesh size 2 mm). A subsample (approximately 2 g) of each composite sample was collected in a 2 ml Eppendorf tube and stored at 280 6 C until DNA extraction. DNA extraction and next generation sequencing Total genomic DNA was isolated in triplicate from each soil sample (0.25 g) using the PowerSoil DNA Isolation Kit (MoBio Laboratories) with minor modifications as described below. Before bead-beating, the samples were incubated in lysis solution at 65 6 C for 10 min. Samples were homogenised by two 20-sec cycles at power setting of 5.0 in FastPrep instrument (FP120, Bio 101, Thermo Savant, Qbiogene), with 5 min on ice in between cycles. The DNA was further extracted according to the kit protocol. Triplicate samples were pooled after extraction and purified using GeneClean Turbo Kit (MP Biomedicals) using GNomic salt solution as protocol. After preliminary trial sequencing runs, two primer pairs were selected: one for bacteria (27F/534R 16S rDNA) and one for fungi (ITSI-F/Ek28-R 18S ITS). The two primer sets were modified at the 59 end with adaptors, TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG -forward adaptor and GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA -reverse adaptor. The ITSI-F/Ek28-R primer set was chosen as it gave better amplification when combined with the barcode attachments used in the Illumina sequencing. PCR amplification using these primers gave a product of ,750 bp, which was consistent with the target region of the rRNA genes including the end of the SSU, ITS1, 5.8S and the start of the LSU region plus the adaptor primers. All PCR reactions were carried out in triplicate 13.0 ml reactions with 31 buffer basic (Molezym GmbH and Co. Bremen Germany), 2 mM MgCl 2 (Qiagen, Hielden, Germany), 0.2 mM dNTP (Invitrogen, Life Technologies, USA), 0.25 U Mol Taq basic DNA polymerase (Molezym GmbH and Co. Bremen Germany), 0.2 mM forward and reverse primers each (Integrated DNA Technologies) and about 2 ng template DNA, was made up to 13 ml with molecular biology reagent water (Sigma, UK). Each reaction was performed in a Dyad thermocyler (MJ research), according to the following protocol, thermal cycling consisted of initial denaturation at 94 6 C for 3 min, followed by 35 cycles of denaturation at 94 6 C for 30 s, annealing at 55 6 C for 45 s, and elongation at 72 6 C for Soil microbes causing strawberry yield decline XM Xu et al 60 s, reducing 0.5 6 C per cycle until 50 6 C, with a final extension at 72 6 C for 5 min. Negative control samples were treated similarly with the exclusion of template DNA. PCR products were visualised by agarose gel electrophoresis. Following PCR, DNA amplicons were purified using Agencourt AMPure XP beads (Beckman Coulter, USA), as per manufacturer's instructions. The adapted amplicons were then modified by attaching indices and Illumina sequencing adapters using the Nextera XT Index Kit by PCR as described in the manufacturer's protocol, enabling simultaneous sequencing of multiple samples, i.e. multiplexing. Following the index PCR clean-up step, using the Agencourt AMPure XP beads, as per manufacturer's instructions, PCR products were qualitatively assessed using a Fragment Analyzer (Advanced Analytical, Ames, IA, USA) with the High Sensitivity NGS Fragment Analysis Kit (Advanced Analytical, Ames, IA, USA). PCR products were also quantitatively assessed using a Qubit 2.0 Fluorometer (Life Technologies, USA). DNA from the different samples was then pooled so as to be analysed on the same Illumina run to avoid run-quality bias. The unique DNA barcode indices allowed sequences from all samples to be de-multiplexed in subsequent processing. Samples were pooled in such a way to ensure each of them was equimolar. The final concentration of the pooled library was 4 nM. The amplicon library was denatured using 1 mM NaOH and diluted to 30 pM as per manufacturer's protocol. The diluted and denatured amplicon library was then combined with a denatured PhiX library at an equimolar concentration at a rate of 20% to increase heterogeneity of the sample. These samples were then run on an Illumina MiSeq with 300 bp paired end sequencing (version 3 chemistry). Samples from 2013 were sequenced separately from the 2014 samples; within each sequence run, there were 64 samples (which included samples from other studies). Sequence processing Raw sequences were automatically de-multiplexed by the Illumina MiSeq and then further quality-filtered by the QIIME analysis pipeline: 26 (1) removing primers from sequences, (2) removing low-quality reads, (3) identifying an OTU for each sequence against two international databases: 16S (bacteria) -Silva 27 and the UNITE fungal 18S ITS database 28 at 97% similarity, (4) storing every unique sequence and its frequency in each sample. Finally, we wrote a small utility programme in Delphi to (1) produce summary for OTU frequency for each sample, (2) merge the OTU frequency data over all samples and (3) produce an overall OTU table in the BIOM format, enabling further downstream statistical analysis. We also customised the UNITE fungal ITS database to include ITS sequences for oomycetes and vascular wilts; all oomycete ITS sequences were first obtained from international repositories -if multiple sequences were available for a single species then a consensus sequence was generated with Geneious version 6.1 (Biomatters Ltd). Custom Perl scripts were written to query the Index Fungorum database (http://www.indexfungorum.org/), using the Index Fungorum Fungus API to query the website to return taxonomic information on the additional species, absent from the UNITE database. Both the consensus sequences and the linked taxonomic information were then appended to the UNITE database files. Full scripts are available for download from (https://github.com/eastmallingresearch/ metagenomics). Statistical analysis Two types of statistical analyses were performed: (1) initial exploratory analysis and (2) detecting differential OTU abundance between samples from different sites to identify candidates responsible for the yield-decline phenomenon. Individual sample diversity (i.e., a diversity) was calculated: the number of distinct OTUs observed per sample (Sobs) and Shannon and Simpson indices (both related to the frequency of individual OTUs within a sample). To reduce biases in sequencing depth on these indices, a re-sampling (i.e. bootstrap) scheme was used to estimate a diversity indices for each sample. A bootstrap sample was obtained via randomly sampling a minimum number of sequences from the sequences in each sample (i.e., rarefying). All indices are calculated from each bootstrap sample at the rarefaction point -a total of 25 bootstraps were conducted. Mean indices were calculated from these bootstrap samples. Next, we calculated diversity indices among samples (i.e. b diversity): Morrison-Horn (MH), Bray-Curtis (BC) and ThetaYC (YC) indices. MH measures the similarity between two samples whereas the other two methods measure the dissimilarity between two samples. Both a and b diversity indices were calculated using the Win64 version of the Explicet software 29 . A principal component analysis was conducted to detect overall differences between samples using the STAMP programme 30 . To assess differential OTU abundance among treatments, we used the DESeq2 statistical package in R 31 . DESeq2 was developed for comparing differential gene expressions but is equally applicable to analysis of metagenomic data. DESeq2 provides a new statistical fitting routine to account for variance heterogeneity often observed in sequence data; it uses the negative binomial distribution as an error distribution to compare abundance of each OTU between groups of samples in the framework of generalised linear modelling. This method was superior to other methods commonly used for this purpose 32 ; the same study also showed that rarefying samples is inferior to not rarefying in identifying differences in OTU abundances but with correct distribution assumptions. Thus, in the present study, rarefying was not used when comparing OTU abundance. The median-of-ratios method 33 was used to normalise the data to correct for unequal sequencing depth; this procedure was implemented as a default in DESeq2. To correct false discovery rate associated with multiple testing, DESeq2 uses the Benjamini-Hochberg (BH) adjustment 34 . In addition, DESeq2 also implemented an algorithm to adjust for large variability in log-fold changes for small counts. Candidate OTUs were selected at the 5% significance level (BH adjusted). Any OTU with the total number of reads across all the samples less than three was omitted from differential abundance testing. In comparing OTU abundance, seven different comparisons were made, taking into account the potentially complex nature of candidate organisms, and the persistency of chloropicrin effect in relation to sampling time. The first five comparisons were between sites with and without the yield-decline phenomenon; only samples collected in 2014 were used for these five comparisons since they were sampled at the same time. In these comparisons, chloropicrin-treated soil samples from HB12 and PV12 were excluded because it is not certain whether the chloropicrin effect could last for more than two years. These five comparisons were: Sequencing quality Samples were sequenced in two runs: in February (2013 samples) and July (2014 samples), 2014. Most samples had more than 50 000 high-quality sequences ( Figure 1). The median read length of the first read (P1), after quality trimming in the QIIME pipeline, was greater than 250 bps for all examples except four samples for the fungal sequencing ( Figure 1). About 91% and 85% of total reads were of good quality for bacteria and fungi, respectively. The majority of these high-quality reads are mapped to OTUs in the two international databases. For bacteria, on average 88% of reads were mapped to OTUs (ranging from 83% to 94% for individual samples). For fungi, the percentage of good quality reads mapped to OTUs ranged from 85% to 100% with mean of 96%. The total number of distinct bacterial and fungal OTUs was 2142 and 2022, respectively. Of these OTUs, there were respective 306 and 326 cases where there was only a single read across all samples, i.e. only present in one sample. The two most common bacterial phyla are Proteobacteria and Acidobacteria, accounting for ca. 67% of the total mapped reads ( Figure 2). For fungi, Ascomycota was the most common phylum, accounting for more than 50% of the mapped reads on average, and the next two common phyla were Zygomycota and Basidiomycota ( Figure 2). The relationship between number of OTUs observed (Sobs) and the sequencing depth is shown in Figure 3 for a few samples. Overall, the present sequencing depth appeared to be sufficient since the minimum sampling depth in our samples was not in the part of curve with steep increases -indicating a diminishing return of further sequencing in uncovering new OTUs. a diversity Within sample diversity measures varied greatly with samples (Table 2). Overall, there were more bacterial OTUs in individual samples than fungal OTUs (Table 3). At the rarefaction point ( Only at the EMR site, chloropicrin appeared to consistently reduce the number of OTUs, compared to the control treatment ( Table 2). b diversity Table 3 shows the estimated b diversity measures for bacteria and fungi. In general, b diversity among samples was greater for fungi (i.e. lower similarity, high dissimilarity) than for bacteria. However, these diversity estimates did not show consistent patterns regarding their relationship with site and yield decline. For example, EMR site (no yield decline) showed the least similarity to the two sites with the yield-decline phenomenon (HB12 and PV12). However, HB12 was the least similar to PV12. Samples from HB12 and PV12, as a group, were not clearly separated from other samples based on principal component analysis of all bacterial OTUs (Figure 4) or fungal OTUs ( Figure 5). Differential abundance A total of 452 bacterial and 485 fungal OTUs were omitted from differential abundance testing because of extreme low counts across all samples (total counts f 3), leaving 1690 bacterial and 1537 fungal OTUs for statistical testing. Of all pairwise comparisons, 715 comparisons were statistically significant at the 5% level. Figures 6 and 7 show the density plots of three statistics for these significant comparisons: average abundance for the OTUs, log2fold change (no-yield-decline samples over yield-decline samples) and BH-adjusted p-values. Overall, more bacterial OTUs appeared to be more abundant in the non-yield-decline soils than in the yielddecline soils; the opposite was true for fungal OTUs. There were 591 and 124 significant comparisons for bacterial and fungal OTUs, respectively. Excluding multiple significant comparisons for a single OTU, there were 366 and 88 unique bacterial and fungal OTUs for which there were significant differences in their abundance between the two types of samples (yield-decline vs. non-yield-decline). These fungal OTUs did not include common soil-borne pathogens, e.g. Fusarium, Verticillium, Phytophthora and Pythium. The log2-fold change was greater and less than zero for 326 and 325 bacterial comparisons, respectively; the corresponding values for fungal OTUs were 38 and 86. For bacteria, there were 203, 112, 35, 11 and 3 OTUs for which one, two, three, four and five out of the seven comparisons were statistically significant, respectively. For fungi, there were 63, 15, 9 and 1 OTUs for which one, two, three and four out of the seven comparisons were statistically significant, respectively. To narrow down the number of OTUs for further interpretation of their possible roles in affecting yield decline, the following criteria were applied to these 454 OTUs (366 bacteria and 88 fungi): (1) average abundance should be over 10 and 6 across all samples for bacterial and fungal OTUs, respectively; this was used to exclude those OTUs with low counts since it is reasonable to assume that a high level of an OTU is needed if it was partially responsible for causing yield-decline; (2) the absolute log2-fold change is greater than 2.0 (i.e. the difference in abundance is at least four-fold); (3) there should be at least two statistically significant comparisons (out of the seven) for one single OTU; (4) for a single OTU, its effect sign (i.e. negative or positive) must be consistent among those significant comparisons involving the OTU. In total, 32 bacterial and 17 fungal OTUs met these criteria. Of the 32 bacterial OTUs, log2-fold change was positive for 24 cases, i.e. no-yield-decline samples had greater abundance than the yielddecline samples. In 13 of the 17 fungal OTUs, no-yield-decline samples had lower abundance than yield-decline samples. Statistical test showed that there was significant differential abundance between fungal and bacterial OTUs between the two types of samples (p , 0.001). Table 4 gives the taxonomical information of these 32 bacterial and 17 fungal OTUs. Of the 32 bacterial OTUs, 16 were from the phylum of Proteobacteria and six from Firmicutes. The remaining 10 OTUs were from eight phylum groups (Table 4). Ten fungal OTUs were from the Ascomycota and five from Basidiomycota. Further analysis of these OTUs in Table 4 (based on published research studies or online information) suggested 12 bacterial and 4 fungal OTUs (Table 5) could have played a role in the yield-decline phenomenon. Yield decline may result from one or more (and/or their interactions) of the following four factors: (1) lack of beneficial bacteria, (2) lack of nematode-parasitic fungi, (3) high levels of nonspecific fungal root rot pathogens and (4) wet soil conditions. Figure 8 shows the relative abundance of these 16 candidate OTUs at the four sites. HB13 and EM13 had much higher levels of Bacillus and Pseudomonas OTUs than HB12 and PV12. The level of wet-loving bacterial OTUs was higher at PV12 than at the other sites; the opposite was true for the level of bacterial OTUs related to nitrogen cycling. For fungal OTUs, the level of two Ilyonectria species was the highest and lowest at PV12 and HB13, respectively. There was a higher level of wet-loving fungi at HB12 than at the other three sites. Nematode-parasitic fungi were nearly exclusively found at HB13. DISCUSSION The amplicon-based metagenomic analysis of soil samples utilised in this study identified several groups of microbial organisms that may be involved in causing strawberry yield decline. Many OTUs differ in their abundance between samples from the yield decline and non-decline soils. Based on the comparisons of abundance of each individual OTU and several stringent criteria, we identified up to 51 (34 bacterial and 17 fungal OTUs) that were most likely to be involved in affecting yield decline of strawberry. Of these 51 OTUs, only for 12 bacterial OTUs and four fungal OTUs is there published information about their possible roles (or those of closely related species), which is biologically plausible to explain why the OTUs were implicated in strawberry yield decline. There are two fungal OTUs that had very high abundance at one of the two yield-decline sites (PV12); these two OTUs are Ilyonectria robusta and I. coprosmae. Of these two OTUs, I. robusta is particularly abundant at PV12. Based on recent molecular taxonomy, these two IIyonectria species are closely related to Cylindrocarpon spp; indeed, IIyonectria contains many Cylindrocarpon-like species that have been commonly associated with root and decay of woody and herbaceous plants 35 . Recently, I. robusta has been shown to cause root diseases on grapevine (including vascular invasion) [36][37][38] . Cylindrocarpon-like and Ilyonectria cause diseases on Laurustinus 39 . Potential fungal pathogens other than V. dahliae were frequently recovered from strawberry roots, e.g. Rhizoctonia sp. 40,41 , and Cylindrocarpon destructans, Fusarium oxysporum, Fusarium solani, Pestalotia longiseta and Pythium spp [42][43][44] . Cylindrocarpon destructans can cause variable degrees of crown and root rot in strawberry 45,46 . Collectively these general, non-specific pathogens that cause a root disease are commonly referred to as black root rot, a name that is descriptive of the appearance of the roots 47 . The importance of these non-specific root pathogens may have been masked by two factors. First, broad-spectrum chemo-fumigants (e.g., methyl bromide and chloropicrin) have been used to fumigate soil. Second, unlike V. dahliae these non-specific root pathogens do not usually lead to plant mortality but only lead to reduced plant growth. This reduced plant growth is often difficult to differentiate from nutrient deficiency or other abiotic factors. In non-fumigated soils, strawberry yield reduction between 20-25% 43 and 46% (http://www.mbao.org/altmet00/32martin.pdf, accessed on 26 November 2014) was observed but was not attributable to V. dahliae, similar to the loss observed at HB12 and PV12 (ca. 25%). Based on root isolations, this yield decline was attributed to root rot caused by Pythium, binucleate Rhizoctonia and Cylindrocarpon spp. Of the 12 bacterial OTUs, 2 were from the genus Bacillus and 2 from the genus Pseudomonas, which were more abundant in non-yield-decline soil samples. Many strains from Bacillus and Pseudomonas have been demonstrated to have anti-fungal effects and can promote plant growth [48][49][50][51][52][53][54][55][56] . There are already several commercial products based on the strains from these two genera marketed as biocontrol products against plant diseases and/or as PGPR products. Probably the most widely used biocontrol strain for plant pathogens is B. subtlis, e.g. one formulated commercial product is called Serenade H . Soil suppressiveness against non-specific root pathogens is associated with the high level of total fungi and fluorescent bacteria 42 ; suppressiveness is reduced on sites where a strawberry monoculture without organic input has been grown for several years. Two Bacillus strains reduced ginseng root rot caused by C. destructans 57 . Several Pseudomonas strains isolated from the rhizosphere of oilseed rape and strawberry were antagonistic against V. dahliae 19 . Early and localised root surface and root endophytic colonisation by P. fluorescens PICF7 is needed to impair full progress of Verticillium wilt epidemics in olive 58 . However, these identified beneficial bacterial OTUs in the present study are not likely to have much antagonistic effect against V. dahliae since the wilt incidence was similar between yield-decline and nonyield-decline plots at HB12 and PV12. At the HB13 site, an OTU from the genus of Paecilomyces was much greater in abundance than at the two yield-decline sites. This genus is known to contain nematophagous fungal species, killing nematodes by pathogenesis [59][60][61] . It is also generally accepted that nematodes may exacerbate wilt problems in strawberry by provid- ing wounds as fungal entry sites. The presence of nematodes increased the rate of Verticillium wilt development on strawberry except when the fungal inoculum level was very low 62 . In the presence of V. dahliae inoculum, the tolerance of strawberry to lesion nematodes was reduced by 50% 63 . Wilt in potatoes is more severe in the presence of lesion nematodes 64 . Five bacterial OTUs were more abundant in non-yield-decline soils than in yield-decline soils. They are reported to have been involved in global nitrogen cycles, e.g., Methylophilaceaede-nitrification 65 , Rhizobiaceae -nitrogen fixation 66 and Nitrosomonadaceae -nitrification (oxidising ammonia into nitrite) 67 . Thus, these organisms may improve plant growth due to increased availability of nitrogen in the soil to plants. Several other microbial OTUs were more abundant in yield-decline soils than in non-decline soils and they are usually abundant in water or wet conditions or involved in anaerobic respiration. These OTUs are not likely to directly influence strawberry growth. Rather their abundance may indicate water logging or high levels of soil moisture content, which in general would favour pathogen development and reduce root development in strawberry 68 . Soil physiochemical properties may also affect plant and pathogen development. It is not always clear whether such effects are through their direct influence on plant development or (partially) mediated through their effects on soil microbial populations. The two yield-decline sites have been in continuous strawberry production for many years. In contrast, HB13 site was previously an apple orchard and EM13 site was planted with cereals in previous years. Rotation is one of the cultural practices used to manage diseases, particularly soil-borne pathogens [69][70][71][72] . Rotation was able to reduce the severity of strawberry root rot [73][74][75] . Continuous cropping of a single species for a long period of time often leads to reduced cropping potential in rosaceous species, e.g., apple 25 and almond 76 . Further research is needed to understand which bacterial and fungal OTUs associated with strawberry yield decline are also associated with continuous cropping of strawberry and which of these OTUs are due to the nature of soils. Soil sampling in the present work was unfortunately constrained by the limited number of sites with yield-decline and commercial horticulture. Thus it was not possible to adopt a more controlled sampling plan that could adequately consider other site-specific factors, such as soil type, previous crops and host genotypes. These site-specific factors undoubtedly affect plant health, either contributing to soil disease suppression and nutrient supply/uptake or predisposing plants to pathogens 77,78 . However, they are unlikely to be the determinant of strawberry yield decline because strawberry plants in plots treated with chloropicrin at the same sites did not suffer from the yield decline. The present study, based on the data-driven approach, was able to identify candidate microbes for further studies where some of these site-specific factors could be included. For instance, how do the two candidate fungal pathogens interact with beneficial soil microbiota in different types of soil in relation to strawberry yield? It should be noted that the present approach (relative DNA abundance) will not be applicable to scenarios where a very low level of microbes could cause disproportional effects on plant development, e.g., by producing toxins. Such a problem (linking Table 5. Summary of differential abundance between non-yield-decline and yield-decline samples and had met several other selection criteria (see the text) for a number of bacterial and fungal OTUs, together with the log2-fold change (LFC) and possible roles they played in the yield decline of strawberry, which was inferred from published studies and/or from online resources Table 7) organisms per sample that may have played a role in affecting strawberry yield decline observed at HB12 and PV12; counts data were proportionally adjusted to the total reads of 300 000 per sample. Samples from chloropicrin-treated plots at HB12 and PV12 were excluded. soil microbial functions to plant development) may potentially be dealt with metatranscriptomics (RNA-seq) or metabolomics-based approaches. Recent research reports on the transcriptomes of microbial community in soil 79 and Arctic peat soil 80 highlight the feasibility of applying metatranscriptomics to soil microbes (though still challenging). In summary, this study demonstrated the usefulness of ampliconbased metagenomics to identify candidate organisms involved in affecting strawberry yield decline. Isolation and culture techniques are usually used to obtain microbial organisms from root systems for further pathological studies. But this time-consuming approach suffers from the fact that most microbial organisms cannot be cultured in artificial media. An amplicon-profiling approach provided an efficient way to profile microbiota and identify candidate organisms for further hypothesis testing and confirmatory studies.

v3-fos

2017-06-27T10:34:23.256Z

2015-05-27T00:00:00.000Z

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s2

Comparative pharmacokinetics and bioavailability of albendazole sulfoxide in sheep and goats, and dose-dependent plasma disposition in goats Background The aims of this study were to compare the pharmacokinetics of albendazole sulfoxide (ABZ-SO, ricobendazole) in goats and sheep at a dose of 5 mg/kg bodyweight (BW), after intravenous (IV) and subcutaneous (SC) administrations, and to investigate the effects of increased doses (10 and 15 mg/kg BW) on the plasma disposition of ABZ-SO in goats following SC administration. A total of 16 goats (Capra aegagrus hircus, eight males and eight females) and 8 sheep (Ovis aries, four males and four females) 12–16 months old and weighing 20–32 kg, were used. The study was designed according to two-phase crossover study protocol. In Phase-1, eight sheep were assigned as Group I and 16 goats were allocated into two groups (Group II and Group III). ABZ-SO was applied to Group I (sheep) and Group II (goats) animals subcutaneously, and to Group III (goats) animals intravenously, all at a dose rate of 5 mg/kg BW. In Phase-2, the sheep in the Group I received ABZ-SO intravenously in a dose of 5 mg/kg BW; the goats in Group II and Group III received ABZ-SO subcutaneously at a dose of 10 mg/kg and 15 mg/kg BW, respectively. Blood samples were collected from the jugular vein at different times between 1 and 120 h after drug administrations. The plasma concentrations of ABZ-SO and its metabolites were analysed by high performance liquid chromatography. Results In goats, the area under the curve, terminal half-life and plasma persistence of ABZ-SO were significantly smaller and shorter, respectively, compared with those observed in sheep following both IV and SC administrations at a dose of 5 mg/kg BW. On the other side, dose-dependent plasma dispositions of ABZ-SO were observed following SC administration at increased doses (10 and 15 mg/kg) in goats. Conclusions Consequently, ABZ-SO might be used at higher doses to provide higher plasma concentration and thus to achieve greater efficacy against the target parasites. Background Benzimidazole (BZD) and pro-BZD drugs are used widely to treat gastrointestinal helminthiasis including migrating larvae, liver flukes and lungworm infections in animals with a broad spectrum of activity and low mammalian toxicity [1]. The parent molecules of BZD anthelmintics are extensively metabolised in all animal species and the parent drug is short-lived and metabolic products predominate in systemic circulation. The primary metabolites, usually produced by oxidation and hydrolysis, are all more polar and water soluble than the parent drug. The poor water solubility reduces flexibility for drug formulation of the most potent BZD methylcarbamate anthelmintics such as albendazole (ABZ) and fenbendazole (FBZ), allowing their formulation only as tablets, boluses or suspensions for per os/intraruminal administration in ruminants [1]. After absorption from the intestine in ruminants, ABZ is rapidly metabolized into its anthelmintically active albendazole sulfoxide (ABZ-SO) and inactive albendazole sulfone (ABZ-SO 2 ) metabolites by liver enzymes [2]. ABZ-SO, known as ricobendazole, is chemically the sulfoxide derivative of ABZ being the most important antelmintically active metabolic product found systematically after ABZ treatment in sheep [3][4][5][6] and cattle [7,8]. ABZ-SO is much more water soluble compared with ABZ. An injectable formulation of ABZ-SO has been developed for subcutaneous (SC) administration in cattle and sheep. This formulation has some advantages compared with the other formulations for per os or intraruminal administration, as drug molecules are potentially freely available for absorption from the injection site, avoiding the first-pass effect and actions of the oesophageal groove [8]. The gastrointestinal and the first-pass metabolism are common metabolic pathways for sulfoxide BZDs and they are metabolised into their sulfoxides, which in turn are oxidized into the more polar and less anthelmintically active sulfone metabolites following per os administration in different animal species. Sulfoxide BZDs [ABZ-SO and oxfendazole (OFZ)] which have a chiral centre about the sulfur atom are formed as metabolites of sulfides and are metabolised into sulfones. Pharmacodynamic and pharmacokinetic properties of enantiospecific pairs are commonly different and are of major importance for their effective and safe therapeutic use. The sulfones are anthelmintically inactive, whereas sulfides and sulfoxides are both active [9]. Although the plasma dispositions of two enantiomers of ABZ-SO and OFZ have been investigated in many species after per os administration of the pro-chiral ABZ, FBZ and racemic ABZ-SO and OFZ [10][11][12][13][14][15][16][17][18][19], there is a paucity of data available in the literature on the stereospecific plasma behaviour of the enantiomers of ABZ-SO following intravenous (IV) and SC administration of rac-ABZ-SO in goats. Due to a shortage of registered drugs available for goats in most countries, different classes of drugs, including anthelmintics licensed for sheep are extensively used in goats without optimization of dosing regimens and determination of pharmacokinetic and pharmacodynamic properties [20]. It is generally acknowledged that the plasma disposition and metabolism of anthelmintic drugs are different between sheep and goats [21][22][23][24][25]. Goats metabolise and eliminate anthelmintic compounds more rapidly from blood compared with sheep. The presence of the metabolic differences between two species has been not considered for many years. The high prevalence of anthelmintic-resistant nematodes in goats are probably due to the extensive extra-label use of these compounds at a standard ovine dosage, corresponding to a drug under-dosing and leading to reduced efficacy of the drug [26,20]. Therefore, the present study was designed to compare the pharmacokinetic and bioavailability of ABZ-SO in goats and sheep following IV and SC administrations at a dose rate of 5 mg/kg bodyweight (BW) and to investigate the effects of increased doses (10 and 15 mg/kg) on the plasma disposition of ABZ-SO in goats following SC administration. In addition, the stereospecific disposition of enantiomers [(+) ABZ-SO and (−) ABZ-SO)] was also determined and compared in both species after IV and SC administrations of racemic (rac)-ABZ-SO. Results The analytical procedures for the determination of plasma concentrations of ABZ, albendazole-2-aminosulfone (ABZ-NH 3 ), ABZ-SO and ABZ-SO 2 were validated before analysing of the experimental samples and the validation parameters for all molecules are summarised in Table 1. ABZ and ABZ-NH 3 were not detected in any plasma samples of sheep and goats following either IV or SC administrations. The plasma concentration vs. time curves of ABZ-SO and ABZ-SO 2 are shown in Fig. 1 and the pharmacokinetic data are summarized in Table 2 following IV administration in goats and sheep. Although the absorption phase and peak plasma concentrations (C max ) of ABZ-SO were similar in both species, the area under the curve (AUC), terminal half-life (T 1/2 ) and plasma persistence (MRT) values were smaller and shorter, respectively, in goats compared with those observed in sheep after SC administration at a dose of 5 mg/kg BW. The plasma concentrations of (+) ABZ-SO and (−) ABZ-SO) vs. time curves of ABZ-SO in goats and sheep following IV administrations at a dose rate of 5 mg/kg BW are shown in Fig. 2 and 3, respectively. In addition, the comparative ratio of the percentage of enantiomers in goats and sheep following IV administrations is shown in Fig. 4 and kinetic parameters of each enantiomer are summarised in Table 3. Stereospecific disposition of enantiomers displayed similar disposition in sheep and goats. (+) ABZ-SO were predominant and displayed significantly higher plasma concentrations compared with (−) enantiomer. The AUC of (+) enantiomer was almost two times larger than that of (−) enantiomer in both species after IV administration of rac-ABZ-SO. The plasma concentration vs. time curves of ABZ-SO and ABZ-SO 2 are shown in Fig. 5 and 6, respectively. Mean (±SD) pharmacokinetic parameters of ABZ-SO and its metabolite ABZ-SO 2 in goats and sheep at a dose rate of 5 mg/kg and at increased doses (10 and 15 mg/kg BW) in goats following SC administrations are summarized in Table 4 and 5, respectively. Dose-dependent plasma dispositions of ABZ-SO were observed following SC administration at increased doses (10 and 15 mg/kg BW) in goats. In addition, the mean plasma concentrations of enantiomers vs. time curves of ABZ-SO are shown in Fig. 7. The mean kinetic parameters of both enantiomers in goats and sheep at a dose of 5 mg/kg BW and at increased dose rates (10 and 15 mg/kg BW) in goats following SC administrations are given in Table 6. Discussions The present study showed that the AUC and MRT values of ABZ-SO in goats were significantly smaller and shorter compared with those observed in sheep. Moreover, T 1/2 of ABZ-SO was significantly shorter in goats compared with that observed in sheep following IV and SC administrations at a dose of 5 mg/kg BW. The origin of the lower plasma concentration in goats is unclear. The most likely explanation for the origin of these kinetic differences is that goats have a greater metabolic capacity and elimination capability of ABZ-SO in comparison with sheep. Previous studies indicated that the plasma disposition and metabolism of anthelmintic drugs are different between sheep and goats [21][22][23][24][25]. It has been commonly acknowledged that the anthelmintic drugs are more rapidly metabolised and eliminated from blood in goats compared with sheep. This difference has been shown for different anthelmintic compounds, including BZDs [19,21,[27][28][29] endectocides [24,30,31], levamisole, [25,32] and oxyclozanide [25]. The greater ability to detoxify exogenous compounds, including anthelmintics, has been attributed to the specific feeding behaviour of goats [33], since the feeding behaviour of goats is quite different compared with that of sheep. Sheep are known as grazers, preferring to feed on grass and forbs, whereas goats are described as ingesting substantial amounts of browse (woody plants, vines and brush). Thus, goats are better adapted to tolerate and detoxify plant toxins and exogenous compounds compared with sheep [34,35]. The plasma disposition of ABZ-SO has been previously reported in sheep after IV and SC administration at a dose of 5 mg/kg BW [8]. Some findings in the present study (T [8] in sheep, respectively. The origin of the differences between the studies is unclear. These differences between the studies may be attributable to differences in methodology or experimental conditions such as different feeding type or regime, or even to parasitological status of the animals that may cause differences in absorption, disposition and persistence of anthelmintic drugs in the animals. The results obtained in the present study indicate that an increase in ABZ-SO dosage in goats is associated with elevation in the plasma level of ABZ-SO. Significantly higher AUC and C max values for ABZ-SO were observed after SC administration at both dose rates of 10 and 15 mg⁄ kg compared to the treatment at 5 mg⁄ kg ( Table 2). The AUC of ABZ-SO increased from 29.76 (5 mg/kg) to 62.19 (10 mg/kg) and to 112.66 μg.h/mL (15 mg/kg). These findings are in agreement with the previous study performed by Alvarez et al. [36] who indicated that increasing the dose of ABZ (5, 15, 45 mg/kg BW) is associated with enhanced plasma level and exposure of ABZ metabolites in sheep after intraruminal administration. The plasma dispositions of the two enantiomers of ABZ-SO have been investigated in many species after oral administration of the pro-chiral ABZ [10-12, 15-18, 29], and after IV and per os administration of ABZ-SO in sheep [5,17] which is discussed by Capece et al. [37]. In addition, it has been shown that (+) ABZ-SO was anthelmintically more potent than rac-ABZ-SO and (−) ABZ- Vd ss (L/kg) 0.94 ± 0.09 -1.04 ± 0.14 - SO by using an ex vivo murine model for Trichinella spiralis infection [38]. The current study also showed that the enantiomers of ABZ-SO were never in racemic proportions and the enantiospecific ratio (+/−) of plasma concentration of ABZ-SO changed over time in favour of the (+) enantiomer in sheep and goats after both IV and SC administration of rac-ABZ-SO. The AUC of the (+) enantiomer was almost 2 times larger than that of (−) enantiomer of ABZ-SO, in agreement with the previous studies performed by Capece et al. [5] who indicated that (+) enantiomer represented 85 and 80 % of the total plasma AUC of ABZ-SO in male and female sheep, respectively. This may contribute to the anthelmintic effect of the (+) ABZ-SO enantiomer since it has been shown that (−) ABZ-SO is quickly metabolised into the inactive sulfone [17]. It has been demonstrated that the flavin monooxygenase (FMO) system is enantioselective in favour of the (+) sulfoxide of ABZ, whereas only cytochrome P450 systems specifically produce (−) ABZ-SO which was shown to be the main substrate for the formation of the inactive sulphone metabolite [11,39]. Differences in the interspecies enantioselectivity could be explained by different metabolic enzyme contributions. Conclusion Although the absorption phase and the peak plasma concentration of ABZ-SO were similar in both species, the plasma availability, elimination and persistence of ABZ-SO were significantly lower and shorter in goats compared with those observed in sheep, respectively, following SC administrations at a dose of 5 mg/kg BW. As a consequence, treatment of goats with ABZ-SO at the recommended sheep dose may result in reduced anthelmintic efficacy, which may increase the risk of drug resistance in internal parasites. Moreover, it was also shown that increasing the dose of ABZ-SO in goats was associated with enhanced plasma exposures after SC administration. Therefore, increased doses could be a strategy to provide higher and more persistent plasma concentration and thus to improve the efficacy against the target parasites and to delay the development of anthelmintic resistance in goat parasites. Experimental animals A total of 16 goats (Capra aegagrus hircus, eight male and eight female) and 8 sheep (Ovis aries, four male and four female) 12-16 months old and weighing 20-32 kg, were used. The animals were housed and fed twice daily with an appropriate quantity of feed during the experiment period. Water was supplied ad libitum. This study was approved by the Animal Ethic Committee of University of Adnan Menderes. The animals were allocated into three groups (Groups I, Group II and Group III) of 8 such that the mean weight and sex of animals in each group was similar. Drug administration and sampling The study was designed according to two-phase crossover study protocol. A four-week washout period was allowed between the phases of the study. In both phases, 8 sheep were assigned as Group I, and 16 goats were allocated into two groups (Group II and III). For treatment of the animals, ABZ-SO (ricobendazole; Rizal® injectable, 100 mg/mL, Sanovel, Istanbul, Turkey) was used. In Phase 1, the treatments were as follows: Group I and II (both subcutaneously: 5 mg/kg BW-recommended sheep dose), and Group III (intravenously: 5 mg/kg BW). A fourweek washout period was allowed between the phases of the study. In Phase 2, following treatments were performed: Group I (intravenously: 5 mg/kg BW), Group II and III (both subcutaneously; 10 and 15 mg/kg BW, respectively). Because of the possible irritation at the injection site, each of these doses (10 mg/kg and 15 mg/kg) were divided into two injections and applied to left and right side of the goats. Heparinized blood samples (5 ml) were collected via jugular venipuncture prior to drug administration (time 0) and 1,2,4,8,12,16,24,32,48,72,96, 120 h after SC administration. Additionally, 1, 5, 15, 30 and 90 min samples were collected after IV administrations in goats and sheep of intravenous groups. Blood samples were centrifuged at 2000 X g for 20 min, and plasma was harvested and transferred to plastic tubes. All plasma samples were stored at−20°C until the analyses. Analytical procedures Pure analytical standard compounds of ABZ, ABZ-NH 3 , rac-ABZ-SO, ABZ-SO 2 and internal standard of oxibendazole (OBZ) were obtained from Dr. Ehrenstorfer (Augsburg, Germany). A stock solution (100 μg/mL) of a pure standard mixture was prepared with acetonitrile as the solvent. This was diluted with acetonitrile-water (25:75, v/v) to give 0.5, 1, 5, 10 and 20, 50 standard solutions for calibration as standard curves and to add to the drug-free plasma samples to determine the recovery. Plasma concentrations of ABZ, ABZ-NH 3 , ABZ-SO and ABZ-SO 2 were estimated by high performance liquid chromatography (HPLC) with a liquid-liquid phase extraction procedure adapted from that described by Marriner and Bogan [3]. Briefly, drug-free plasma samples (1 ml) were spiked with standards of ABZ, ABZ-NH 3 , rac-ABZ-SO and ABZ-SO 2 to reach the following final concentrations: 0.05, 0.1, 0.5, 1, 2, 5 and 10 μg/mL. OBZ (0.5 μg/mL) was used as an internal standard. Ammonium hydroxide (100 μl, 0.1 N, pH 10) was added to 10 ml-ground glass tubes containing 1 mL spiked or experimental plasma samples. After mixing for 15 s, 6 mL ethyl acetate was added. The sample tubes were stoppered and shaken for 10 min on a slow rotary mixer. After centrifugation at 3000 g for 10 min, the upper organic phase (4 ml) was transferred to a thinwalled 10 ml-conical glass tube and evaporated to dryness at 40°C in a rota vapour (Maxi-Dry plus, Heto, Denmark). The dry residue was reconstituted with 250 μl mobile phase. Then the tubes were placed in an ultrasonic bath and finally, 50 μl of this solution was injected into the chromatographic system. Chromatographic conditions The mobile phase was a mixture of acetonitrile-water to which glacial acetic acid was added (0.5 %, v/v). It was pumped through the column (Luna nucleosil C 18 , 3 μm, 150 mm × 4.6 mm Phenomenex, Cheshire, UK) with nucleosil C 18 guard column (Phenomenex, Cheshire, UK) in a linear gradient fashion changing from 10:90 (acetonitrile-water) to 85:15 for 11 min; 85:15 to 10:90 for 1 min and the last ratio was maintained for 5 min. The flow rate was 1 ml/min. Samples were processed on a computerized gradient HPLC system (1100 series, Agilent Technologies, GmbH, Germany) comprising a degasser, a quaternary pump (G1354A), an auto sampler (G1313), a column oven (G1316A) and diode-array detector (G1315B) set at 292 nm for all molecules. The extracted samples were re-analysed by a chiral stationary phase to determine the concentration of ABZ-SO enantiomers. The enantiomers were estimated by using chiral chromatography adapted from that previously described by Delatour et al. [11] with some modifications. Briefly, a mobile phase of acetonitrile:water (7:93) was pumped at a flow rate of 1 ml/min through a Chiral-AGP column (5 μm, 150 × 40 mm, ChromTech, MN, USA) with ultraviolet detection at 292 nm for 6 min and then the mobile phase ratio was changed to 100 % acetonitrile and maintained for 4 min to wash column for less polar molecules and impurities and finally the ratio changed to initial proportion and (7:93) maintained for 3 min to prepare for the next injection. Method of calibration The analytic methods used for ABZ, ABZ-NH 3 , rac-ABZ-SO and ABZ-SO 2 in plasma were validated prior to the start of the study. The analyte was identified with the retention times of the pure reference standards. Recoveries of the analytes were measured by comparison of the peak areas from 7 spiked plasma samples with the areas resulting from injection of external and internal standards. The inter-and inra-assay precisions of the extraction and chromatography procedures was The parameters in goats observed after a dose of 10 mg/kg are significantly different from those in goats observed after a dose of 15 mg/kg (&P < 0.05) evaluated by processing replicate aliquots of drug-free sheep and goat plasma samples containing known amounts of the drugs on different days. The limits of detection (LOD) and quantification (LOQ) were determined based on signal to noise ratios of 3 and 10, respectively, taken by measuring the instability of the baseline before and after each molecule signal, using individual injections. Calibration curves were fitted by use of 7 concentrations that ranged from 0.05 to 10 μg/mL for plasma samples. Pharmacokinetics and statistical analysis of data The plasma concentration versus time curves obtained after each treatment in individual animals were fitted with a software program (WinNonlin, version 5.2, Pharsight Corp, Mountain View, California) and reported as mean ± SD. The pharmacokinetic parameters for each animal were analysed via non-compartmental model analysis for both administration routes. The C max and T max were obtained from the plotted plasma concentration-time curve in each animal. The trapezoidal rule was used to calculate the area under the curve (AUC), and mean residence time (MRT) from 0 to last time with a measurable concentration was calculated by use of the following equation: Where AUMC last is the area under the moment curve from 0 to infinity and AUC last is the AUC from 0 to infinity. Terminal half-life (T 1/2λz ) was calculated as: Where λz represent the first order rate constant associated with the terminal (log linear) portion of the curve. The mean absorption time (MAT) was calculated by the following equations: The fraction of dose absorbed (ie, F) was calculated by use of mean AUCs calculated for each route of administration by use of the following equation: The pharmacokinetic parameters are reported as mean ± SD. Pharmacokinetic parameters were statistically compared with a one-way analysis of variance (ANOVA). All statistical analyses were performed by using MINITAB for Windows (release 12.1, Minitab Inc., State College, PA, USA). Mean values were considered significantly different at P < 0.05.

v3-fos

2016-05-04T20:20:58.661Z

2015-09-30T00:00:00.000Z

1790126

s2

Molecular marker assisted gene stacking for biotic and abiotic stress resistance genes in an elite rice cultivar Severe yield loss due to various biotic stresses like bacterial blight (BB), gall midge (insect) and Blast (disease) and abiotic stresses like submergence and salinity are a serious constraint to the rice productivity throughout the world. The most effective and reliable method of management of the stresses is the enhancement of host resistance, through an economical and environmentally friendly approach. Through the application of marker assisted selection (MAS) technique, the present study reports a successful pyramidization of genes/QTLs to confer resistance/tolerance to blast (Pi2, Pi9), gall Midge (Gm1, Gm4), submergence (Sub1), and salinity (Saltol) in a released rice variety CRMAS2621-7-1 as Improved Lalat which had already incorporated with three BB resistance genes xa5, xa13, and Xa21 to supplement the Xa4 gene present in Improved Lalat. The molecular analysis revealed clear polymorphism between the donor and recipient parents for all the markers that are tagged to the target traits. The conventional backcross breeding approach was followed till BC3F1 generation and starting from BC1F1 onwards, marker assisted selection was employed at each step to monitor the transfer of the target alleles with molecular markers. The different BC3F1s having the target genes/QTLs were inter crossed to generate hybrids with all 10 stress resistance/tolerance genes/QTLs into a single plant/line. Homozygous plants for resistance/tolerance genes in different combinations were recovered. The BC3F3 lines were characterized for their agronomic and quality traits and promising progeny lines were selected. The SSR based background selection was done. Most of the gene pyramid lines showed a high degree of similarity to the recurrent parent for both morphological, grain quality traits and in SSR based background selection. Out of all the gene pyramids tested, two lines had all the 10 resistance/tolerance genes and showed adequate levels of resistance/tolerance against the five target stresses. The study demonstrates the potential of MAS for stacking of several genes into a single line with a high degree of parental genome recovery. Introduction The rate of world population growth has exceeded the rate of growth in food-grain production. It is predicted that the world population will exceed 8 billion people by 2025 and to meet these global food demands, the production of grain needs to increase upto 50% more by the year 2025 (Khush, 1999). The emergence of new diseases and pests and the changing climate are the major issues that address the requirement for sustainable crop development and resistance to biotic and abiotic stresses (Hasan et al., 2015). Due to the sustained efforts by conventional breeding approaches, over the years, many significant progresses have been achieved in the development of suitable cultivars to effectively combat different types of the biotic and abiotic constraints that affect the productivity of rice. The occurrences of new biotypes/stresses have demanded stacking of several resistance genes into high yielding cultivar background to confer a wider spectrum of resistance. This enhanced capability will enable them to survive attacks from several pathogens at a time and also survive in unfavorable environmental conditions. A rigorous yield loss that has affected the rice cultivation is accounted to biotic and abiotic stresses. In the recent times, technological innovations and development of DNA based molecular markers has facilitated the transfer of genes that confer resistance to different biotic stresses (BB, blast, and gall midge etc.) and abiotic stresses (Submergence and Salinity etc.). With the advances made in the area of molecular markers, the tracking of the genes for resistance is possible by following the path of markers that are linked/ tagged to each gene for resistance, thus making the identification of plants with two and more genes simple. One of the most serious and widespread diseases in rice production is bacterial blight (BB) caused by Xanthomonas oryzae pv.oryzae. It reduces the yield of rice drastically by partial grain filling because of constraint to the photosynthetic area (Pradhan et al., 2015). There are no effective chemical agents against the bacterial blight pathogen. The only way to protect the crop from bacterial blight is the use of resistant varieties of rice (Khush et al., 1989). So far, more than 30 BB resistance genes have been identified and some of them have been incorporated into modern high yielding rice varieties (Dokku et al., 2013a,b;Suh et al., 2013;Kumar et al., 2014;Pradhan et al., 2015). In the presence of a number of virulent pathogens, the genes may differ in their level of resistance to them. Thus, gene stacking is currently being pursued in an effort to develop more durable and comprehensive resistance rice varieties to combat the effect of BB pathogens Dokku et al., 2013a,b;Suh et al., 2013;Kumar et al., 2014;Pradhan et al., 2015). The Rice blast disease occurs in most of the rice growing areas of the world (Ou, 1985). It is the most important fungal rice disease, which is caused by the fungus Magnaporthe grisea Barr. (Telomorph Pyricularia oryzae Sacc). Yield loss due to blast can be as high as 50%, when the disease occurs in epidemic proportions (Babujee and Gnanamanickham, 2000). In severe cases, yield losses can be 70-80% due to the fungus blast alone. In the wet season, due to encouraging environmental conditions for disease development, this disease arises frequently in the rice cultivars. For blast resistance, closely linked DNA markers to a blast R gene can be effectively used for marker assisted selection, which is comparatively faster than the conventional rice breeding methods (Singh et al., 2015). Till 2015, around 100 distinctive blast resistance genes have been identified. Out of them, minimum 14 number of genes (Pi1, Pi2, Pi9, Pi20 (t), Pi33, Pi39, Pi40 (t), Pi47, Pi48, Pi54rh, Pi56, Piz, Piz-t, and Pigm) have been defined as per their wide scale resistance (Hayashi et al., 2010;Huang et al., 2011;Das et al., 2012;Hua et al., 2012Hua et al., , 2015Liu et al., 2013). The use of different resistant rice varieties in the cultivation of rice, could be the most active, and cost effective way to reduce the adverse effect of the blast disease. Thus, the improvement of resistant varieties against blast disease is one of the most important objectives in the rice breeding plan (Gouda et al., 2013;Divya et al., 2014). The Asian rice gall midge, Orseolia oryzae is a serious pest of rice in certain regions of south, central, and east India, causing significant yield loss, mainly during the kharif season. Gall midge insect causes an annual yield loss of about 477,000 tons of grain or 0.8% of the total production with crop losses in the range of 10-100% in India. The estimate suggested an annual yield loss of US$80 million in India and of $550 million in Asian continent (Biradar et al., 2004). Till now, 11 gall midge resistance genes have been identified in plant and seven biotypes of the pest have been reported (Dutta et al., 2014;Hasan et al., 2015). For control of this pest, development of resistant rice varieties using marker assisted selection can be a sustainable and costeffective approach (Dutta et al., 2014). Gene pyramiding with two or additional active genes in a single variety may lead to strong gall midge resistance rice varieties. Nowadays, the use of molecular markers for improvement of gene pyramids in desired combination is being monitored in different rice cultivars and presently using DNA markers for selection of resistant plants for gene pyramiding has been accepted as an established tool (Sundaram et al., 2008;Dutta et al., 2014). Among the abiotic stresses, submergence is one of the vital issues in the flash flood prone rice cultivating areas (Iftekharuddaula et al., 2015). Submergence tolerance is an important trait for rice (Oryza sativa) in rain-fed lowland conditions. This trait is largely controlled by a major gene designated as Sub1. Indica cultivar FR13A, is a highly tolerant rice variety which can survive upto 2 weeks of complete submergence owing to a major quantitative trait locus designated as submergence1 (Sub1) near the centromere of chromosome 9 (Xu and Mackill, 1996;Xu et al., 2000;Chen et al., 2002;Septiningsih et al., 2013;Manivong et al., 2014). For submergence tolerance the background genetic information was well documented from a number of researches using QTL mapping and map based cloning approaches (Septiningsih et al., 2009;Manivong et al., 2014;Singh et al., 2014a). Salt stress is a major constraint across many rice producing areas because of the high sensitivity of modern rice varieties. It is one of the top most abiotic stresses that, imposes a limitation to the growth and improvement of rice plant, triggering yield losses of more than 50% (Molla et al., 2015). Tolerance to salinity is complex, involving a number of different physiological mechanisms, such as sodium exclusion from roots, controlled sodium transport between root and shoot, and sequestering of sodium in older tissues and in the vacuoles. It has been estimated that over 150 million hectares of current and potential rice land in the tropical and subtropical regions of the world are affected by salinity (Dissanayake and Wijeratne, 2006;Molla et al., 2015). Even though, rice is the major food source for half of the world population, comparatively it is more susceptible to salt stress than other cereals (Vu et al., 2012). To stabilize the biotic and abiotic stresses in rice, the improvement of resistant variety can be considered to be the utmost effective technique. As the cultivars undergo quick collapse in their resistance, there is a requirement of the development of highly resistant varieties. Thus, bringing together several genes conferring resistance to more than one stress into a single genetic background is necessary for its durable resistance (Singh et al., 2014b). DNA Isolation and PCR Analysis for Forward Selection Generally the population size in a breeding program is quite large DNA isolation for PCR analysis can be a limiting step in marker assisted selection (MAS). A technically simple, quick, and reproducible DNA isolation technique was carried out following the standard procedure described by Dellaporta et al. (1983). Leaf sample of (2 cm) was collected from 2 weeks old rice seedlings. The leaf tissue was cut into 0.3 cm and placed in a well on the spot test plate (Thomas Scientific). The CTAB extraction buffer was added and grounded with a thick glass rod. The samples were transferred to the 1.5 ml Eppendorf tube and equal volume of chloroform was added to it and mixed well centrifuged at 17 • C at 12,000 rpm for 5 min. The top aqueous phase was transferred to another 1.5 ml Eppendorf tube, to which two times volume of ethanol (99.9%) was added and mixed well. Furthermore, it was centrifuged at 10,000 rpm for 3 min at 4 • C and the supernatant was decanted. The pellets were washed with 70% ethanol and the DNA was air dried and resuspended in 50 µl of 0.1X TE and stored at −20 • C. The quantification of DNA was accomplished by using UV-VIS spectrophotometer (UV-1201 Schimazu Corp; Japan). Screening Against the Bacterial Blight Pathogen The bacterial blight (BB) isolates of the pathogen available at CRRI, India was used to screen pyramided lines of both genotypes under natural conditions in the field. For testing the reaction of pathogen, the top leaves of the plants were clipinoculated using the clip inoculation method with the bacterial suspension at a density of 10 9 cells/ml at maximum tillering stage (Kauffman et al., 1973). For evaluating the resistance of gene pyramids developed in this study, the isolate produced an average lesion length ranging from 6.0 to 18 cm in susceptible differentials and an average lesion length of 0.1-4.8 cm in the resistant differentials. The pyramids were planted in the field with spacing of 15 cm × 20 cm (between plants and between rows) nine leaves of three different plants (3 leaves per plant) in each of the tested lines were clip-inoculated and the phenotypic reactions of the lines were recorded 20 days after inoculation both by visual scoring and measurement of lesion length (LL). The distinction between resistant and susceptible plants was set at LL of 5 cm. Plants with LL of < 5 cm were scored as resistant and those with > 5 cm were scored as susceptible with slight changes (Dokku et al., 2013a,b). The screening was done with three sets of plants for each line and each set contains 18 plants. Screening Procedure Against Blast Pathogen For screening against blast, the lay-out adopted was a Uniform Blast Nursery (UBN) pattern where each test entry (gene pyramid, parent etc.) are sown in a single row of 50 cm length and successive rows are 10 cm apart. After every 20 test entries, B 40, a susceptible variety was sown. The entire nursery was surrounded all sides by two rows of HR12, a well-known susceptible variety for the spread of the disease in the experiment. High doses of nitrogen (100-120 kg N/ha) were applied. Artificial Inoculation The nursery was sown during the blast favorable weather conditions to facilitate infections and polycyclic development of the disease. To create severe blast incidence, additional inoculum was provided by collecting diseased leaves, chopping them into small pieces and scattering them over the nursery. In addition, infected plants are also being transplanted between border rows. This operation can also carried out during prolonged wet weather. The scoring was based on leaf blast severity on the SES scale and at least two readings on blast severity are recorded at 10 day intervals from 25 to 30 days (Roumen et al., 1997;IRRI, 2002). The screening was done with three sets of plants for each line and each set contains 18 plants. Screening Procedure Against Gall Midge Screening for gall midge resistance was done by following the standard protocol (Vijaya Lakshmi et al., 2006). Ten days old seedlings of all the homozygous lines of Improved Lalat were grown in plastic trays along with resistant controls, i.e., Kavya, Abhaya, and a susceptible control such as T (N) 1. The trays were kept in cages and larvae of gall midge were released. After 20 days, the plants were scored for their reaction to gall midge and the appearance and percentage of galls (silver shoot) was recorded. Seedlings were scored for reaction in terms of percent plant damage. The plants were evaluated when the susceptible plants showed 90-100% plant damage with the appearance of gall. Plants without the appearance of gulls were cut up to detect dead maggots and for the existence of tissue necrosis as an indicator of oversensitive response to confirm as resistant lines. Test seedlings with 0-20% of damage were considered as resistant, whereas others were considered as susceptible. The screening was done with three sets of plants for each line and each set contains 18 plants. Screening Procedure for Submergence Tolerance The 21 days old seedlings from the pyramid lines of Improved Lalat were grown in plastic trays along with resistant controls (FR13A, IR64sub1) and susceptible controls (IR42 and Improved Lalat) were placed in submergence tanks of CRRI, India. The tanks were slowly filled with water, without disturbing the plants. The trays were at the bottom of the tank and the tanks were completely filled with 1.6 m standing water over the top of the leaves. After 15 days of complete submergence, all the water was drained from the tank. The trays were kept in the open air for 8 days (desubmergence) and the scoring for a survival rate percentage (%) was determined after 8 days of desubmergence (Jantaboon et al., 2011). The screening was done with three sets of plants for each line and each set contains 18 plants. Screening Procedure for Salinity Tolerance The salinity screening was carried out following the standard procedure of Fageria (1985) in the Central Rice Research Institute, India, experimental salinity tanks. These tanks are specifically designed for salinity screening. These tanks were filled with soil, and fertilizer was applied to it. A water tank was connected to the salinity tanks for water supply to the experimental tank. The 21 days seedlings of the pyramid lines of Improved Lalat were transplanted in the salinity tanks along with resistant controls, i.e., FL478, SR26B and susceptible controls, i.e., IR29, Improved Lalat (Recurrent parent). At the beginning 2 days the water tank was filled with salt water of EC (Electrical conductivity) 2 dS m −1 and the salt water was supplied to the experimental tanks. Up to 10 days the experimental tanks were maintained to (8-10 dS m −1 ) EC. The E.C. of soil and water was checked every day using conductivity meter. After 10 days, the salt concentration of soil was increased to E.C. 16 dS m −1 . After 60 days, when the susceptible controls were completely died, the pyramids were scored for their survival rates. The survived plants kept in the same condition up to the reproductive stage. The spikelet fertility (%) was recorded during the reproductive stage. The screening was done with three sets of plants for each line and each set contains 18 plants. Characterization for Agronomic Performance and Grain Quality The thirty days old selected promising pyramided lines of Improved Lalat with the parent Improved Lalat were transplanted with 15 × 20 cm spacing in a randomized complete block design with three replications at the experimental farm of the Central Rice Research Institute, India. Data were recorded from 10 plants of each genotype for agronomic traits like days to 50% flowering (DFF) was recorded in the days when about 50% of the tillers in the line exhibited panicle emergence. Plant height (PH) was measured in cm from the base of the hill to the tip of the tallest panicle on the 20th day after flowering, ear bearing tiller (EBT) was recorded as the number of panicles per hill. Panicle length (PL) was measured in cm from the ciliate base of the panicle to the tip of the top most spikelet. Grain number (GN) was recorded as the average number of grains of 10 random panicles, one each of the 10 sample hills. Grain weight (GW) was computed in grams as the weight of 1000-well filled oven dried grains at 13% grain moisture content. The grain and cooking quality were analyzed from the harvested grain. Physico-chemical characters such as hulling, milling and head rice recovery percentage were determined as per the method of Ghosh et al. (1971). Head rice recovery (HRR) of the polished kernels is then passed through rice grader having different (mm) grooves. The whole grains were then separated from the broken grains in order to quantify the head rice recovery. Head rice recovery is the percentage of full length intact kernels after milling. This was calculated as (Weight of whole, polished kernels/Weight of paddy) ×100. Kernel length (KL) was the average of the length of 10 unbroken milled rice measured in mm by dial micrometer. Kernel breadth (KB) was the average of the breadth of 10 unbroken milled rice measured in mm by dial micrometer. L/B ratio was recorded as the length and breadth ratio of the kernel averaged over 10 unbroken kernels. Cooking qualities-5 gm of whole milled rice was cooked for 20 min after pre-soaking in 15 ml water for 5 min. Kernel length after cooking (KLAC) was the average of the length of 10 cooked kernels measured in mm, elongation ratio (VER) was the average ratio of the length of cooked rice to kernel length of milled rice of 10 kernels. Volume expansion, for assessing volume expansion the method of Verghese (1950) was followed, Alkali spreading value (ASV), gelatinization temperature is estimated indirectly by the alkali digestion test (Little et al., 1958). Amylose content, amylose was determined following the method described by Juliano (1971). Statistical Analyses The scoring of amplified bands was done as present (1) or absent (0) for each marker allele-genotype combination. The data entry was done into a binary data matrix as discrete variables. The molecular weight of the bands was estimated using 100 bp DNA ladder as standard. Bands with the same molecular weight and mobility were treated as identical fragments. The total number of bands, distribution of bands across accessions, number of polymorphic bands in a set of accessions, and average number of bands per primer were calculated. The molecular data was analyzed using NTSYS-PC (Numerical Taxonomy and Multivariate Analysis System) computer package (Rohlf, 1990). The genetic similarity between accessions was calculated by Dice (SSR) and Jaccard's (RAPD) similarity coefficient and Euclidian distance coefficient for morphological data. The term polymorphism information content (PIC) refers to the value of a marker for detecting polymorphism within a population, depending on the number of detectable alleles and the distribution of their frequency. In the present study, the PIC value of a marker was calculated according to Anderson et al. (1993). Dendrograms were constructed based on Sequential Agglomerative Hierarchical Nesting (SAHN) based Unweight Pair Group Method with Arithmetic Means (UPGMA) using the software package NTSYS PC 2.01, to infer genetic relationships and phylogeny. The dendrogram obtained was then used for cluster analysis. Results Pyramiding of Blast, Gall Midge, Submergence, and Salinity Resistance/Tolerance Genes The molecular markers used in this study for foreground selection were, according to the published literature (Table 1). Marker assisted backcross breeding approach was practiced and foreground selection was done to select the plants having resistance alleles of all the targeted genes. Only the positive plants having resistance alleles was advanced to the next generation at each stage till BC 3 F 1 generation (Figure 1). Clear polymorphism was observed with all the markers linked to the genes/QTLs under the study between the parents and the donors (Figure 2). The polymorphism was also validated by the phenotyping studies conducted against each stress. The BC 3 F 1 generation hybrids were inter crossed in different combinations so as to stack all the 10 genes together into a single genotype. (Figure 1). These hybrids were intercrossed in different combinations for two more cycles. The BC 3 F 3 generation plants homozygous for five, six, seven, eight, nine, and ten genes were selected in resulting combination (Figure 1). From BC 3 F 3 generation 31 pyramid lines with different gene combination were selected and nine lines were advanced for bioassay and background selection. The study employed three backcrosses to transfer the desired traits from the donors into Improved Lalat followed by three cycles of selfing. Through this approach, we could successfully transfer all the target genes/QTLs of resistance/tolerance into the Improved Lalat background using marker assisted selection in each step starting from BC 1 F 1 generation. Of the two hundred fifty BC 3 F 3 generation lines of Improved Lalat, plants homozygous for alleles associated with the resistance/tolerance were identified through marker analysis (Figures 3, 4). Bioassay of the Gene Pyramids for Biotic and Abiotic Stresses The bioassays confirmed the earlier finding that the recurrent parent, i.e., Improved Lalat having Xa4, xa5, xa13, Xa21 incorporated in an earlier study possess high levels of resistance against BB. All the pyramided lines including the parent, the lesion length was below 3.4 cm ( Table 2). The screening result against blast, the donors C1O1A51 and WHD-1S-75-1-127 were very effective against blast and showed resistant reaction (R) with a score of 0 while the recurrent parent showed a score of 4 showing susceptible (S) reaction. The gene pyramids ILGP5, ILGP17, and ILGP 19 having both the blast resistance genes Pi2 and Pi9 showed a high degree of resistance against blast disease (Table 3, Figure 5). The pyramid lines when screened against gall midge, the donor parents Kavya and Abhaya showed 100% resistance while the recurrent parents showed high susceptibility with 6.4% resistance and the pyramid lines showed resistance to gall midge ranging from 50 to 100% (Table 4, Figure 6). The genotype FR13A, a well-known donor for submergence tolerance, showed 100% regeneration after 15 days of submergence and 8 days of desubmergence while the recipient did not survive the submergence stress. Whereas the pyramid lines having Sub1 QTL showed a different percentage of resistance and three lines showed nearly same as resistant control (Figures 7, 8). The line FL478, a MAS product having saltol transferred from Pokkali was found to be effective against salinity All results are expressed in mean ± SD. Values ≤ 5.00 cm was scored as resistant and values >5.00 cm were scored as susceptible, ILP, Improved Lalat parent. stress by showing 100% tolerance with the score 1 while the recipient parents showed 5.8% survival against the stress and the pyramid lines with Saltol QTL showed a high degree of resistance (Figures 9, 10). The homozygous lines with different gene combination were subjected for field evaluation as the 10 gene combination plants showed enhanced resistance/tolerance to all the biotic and abiotic stresses in the bioassay and selected based on their morphology and grain quality characters for further evaluation in BC 3 F 3 generation (Tables 5, 6). Agro-morphological and Quality Characters of the Improved Lalat Gene Pyramids The BC 3 F 3 generation Improved Lalat gene pyramids were grown in the field for agronomic characterization and evaluation of their performance. The results indicate that the plant height of the lines ranged from 89 cm (ILGP5) to 99 cm (ILGP3), while 99.66 cm in (Improved Lalat) parent and in most of the recombinants, the plant height is nearly equal to the parent. The mean tiller (EBT) number varied from 11.0 to 14.4 and some lines showed slightly lower tiller number than the IL parent (13.0) and three lines showed the higher tiller number than the parent. One line ILGP17 (21) had shorter panicle length (PL) than parent Improved Lalat (24) while in all others; the values were nearer or slightly higher than the parent. The fertility percentage ranged from 78.9 to 84.2%. The 1000-grain weight was higher in ILGP3 and ILGP14 (27.00 g) and lowest in ILGP13 (16.00 g) ( Table 5). Most of the selections were found to be nearer to Improved Lalat (the recurrent parent), in grain quality. The rice kernel length varied from 5.67 to 6.99 cm and the L/B ratio value of most of the lines is in the range of 2.55-2.89 cm except ILGP5 (2.00 cm) while parent Improved Lalat has an L/B ratio of 2.70 cm. Two lines, ILGP13 and ILGP19 (63.50 g) showed the higher HRR value in comparison to Improved Lalat (62.00 g). With respect to ASV, maximum lines are similar to their parental value (4) one line LGP 14 has a slightly higher value (6). The KLAC values in the lines ranged from 9.70 to 11.00 cm and some are better than the Improved Lalat parent (10.60 cm) while one line slightly lesser with 9.70 cm. All Improved lines had amylose content in the range of (20.47-23.88%) and the values are nearer to that of the Improved Lalat parent (23.85%) ( Table 6). Number of Alleles Amplified, Allele Size, and PIC Value The Improved Lalat and the six donor parents were tested with 600 SSR primers which were spread across all the 12 chromosomes of rice. Out of them, 45 primers were selected which were polymorphic between the parent and donors that 45 primers were used for background, selection of Improved Lalat and its 9 pyramided lines with different gene combinations. A total of 61 reproducible bands was obtained from 45 microsatellite markers (SSRs). The number of alleles varied from 1 to 3. The size of the amplified fragments within a range of 50 bp (RM302) to 750 bp (RM440). Most of the fragments varied from 100 to 300 bp. The mean PIC value of all polymorphic primers was 0.07. The maximum numbers of alleles (3) were amplified with three primers RM447, RM4838, and RM490. Ten primers produced 2 alleles whereas maximum primers were produced a single allele. The highest PIC value was shown in RM4838 (0.73) while the lowest PIC value was seen in RM2144 (0.19) ( Table 7). Genetic Similarity Using SSR Data Using the data obtained on the background, selection of Improved Lalat and the gene pyramids, genetic similarities were calculated and the genetic similarity between the pyramid lines and Improved Lalat parent (IL P) had an average value of 0.98. Three pyramid lines ILGP3, ILGP19, and ILGP20 showed highest similarity with parent (1.00). ILGP12 showed 0.99 similarities with parent. Three pyramid lines, ILGP1, ILGP5, and ILGP13 showed 0.98 similarities with parent and ILGP14 showed 0.96 similarities while ILGP17 showed the least similarity with a parent having a value of 0.94. Cluster analysis The dendrogram clearly explains the relationships among the pyramid lines with their parent. Dice genetic similarity index was used to study the genetic relationship toward parents, and based on the dendrogram generated, 9 genotypes, including Improved Lalat parent (IL P) were grouped into two major clusters. Cluster I consisted of ILGP17. The cluster II consisted of all the pyramid lines and Improved Lalat parent (IL P). Cluster II was further grouped into two sub clusters. Cluster II-A and cluster II-B. Cluster II-A was consisted of ILGP1 and ILGP14 while cluster II-B consisted of Improved Lalat parent with rest pyramid lines. Cluster II-B was again divided into two sub clusters, cluster II-B-i and II-B-ii. Cluster II-B-i was again divided into two sub clusters. Cluster II-B-i-a was having ILGP13 while another cluster II-B-i-b was again divided into two sub clusters, one was having ILGP5 while another was again divided into two groups, one was having ILGP12 while in another one ILGP20, ILGP19, ILGP3, and IL P were closer to each other by forming a single line (Figure 11). Distance Matrix Combining values of both agronomic and quality traits, genetic distance of 9 pyramid lines were calculated between each pair of observations. The average genetic distance of IL P to all pyramid lines was with a value of 0.27% distance. The result of pair wise comparisons indicated that ILGP17 was closer (0.23) distance to Improved Lalat parent (IL P) than any other with value of distance. While ILGP3, ILGP14, ILGP5, and ILGP19 were closer to parent with 0.28 and 0.29% distance. ILGP20 was closer to IL parent with 0.31 distance. ILGP1 and ILGP12 were 0.33 and 0.34% distant from the parent. ILGP 13 was seen to be the maximum distance from the IL parent. ILP, Improved Lalat Parent; ILGP, Improved Lalat gene pyramid; HRR, Head Rice Recovery (in g); KL, Kernel length (in cm); KB, Kernel breadth (in cm); KLAC, Kernel length after cooking (in cm); Hulling (in g); Milling (in g); ASV, Alkali spreading value. Cluster Analysis A genetic distance of Improved Lalat (IL P) and 9 pyramid lines were produced a dendogram (Cluster tree analysis) which clearly explains the relationships among all the pyramid lines with their parent. There are two major clusters, cluster I and cluster II. The cluster I was having ILGP13 and the cluster II was having IL P with 8 pyramid lines. Cluster II was divided into two subgroups, i.e., cluster IIA and cluster IIB. Cluster IIA was having ILGP13 and ILGP14, while cluster IIB was again divided into two subgroups, i.e., cluster IIB i and cluster IIB ii. Cluster IIB i was again divided into two groups, one was having ILGP1 and another was having ILGP5 and ILGP19 which formed one cluster. Cluster IIB ii was again divided into two groups. One was having ILGP12 and another one was again divided into two groups, one was having ILGP20 and another one formed a single line consisted of IL P and ILGP17 (Figure 12). Discussion The tightly linked molecular markers for economically significant traits have been identified and used for marker assisted backcross breeding in rice including resistance to biotic stresses BB, blast, gall midge, and abiotic stresses submergence and salinity additionally to some other stresses (Hasan et al., 2015). Markerassisted gene pyramiding of key genes/QTLs has helped in tacking susceptibility for foremost diseases and insects such as bacterial blight Singh et al., 2001;Suh et al., 2011), blast (Hittalmani et al., 2000;Singh et al., 2011Singh et al., , 2012Zhou et al., 2011) and gall midge (Katiyar et al., 2001;Singh et al., 2014b) etc. In India, enhancement of broad scale resistance against BB is a foremost challenge due to the high diversity in agro climatic zones where rice is cultured along with the existence of a numeral of genetically distinct virulent Xoo strains in diverse environmental areas of India. Deployment of a combination of genes can attain strong and broad range resistance in many BB prone rice growing areas (Dokku et al., 2013a,b;Pradhan et al., 2015). Marker assisted foreground selection was also used for effective stacking of abiotic stress traits such as submergence tolerance (Neeraja et al., 2007;Iftekharuddaula et al., 2011;Khanh et al., 2013;Divya et al., 2014) and salinity tolerance (Thomson et al., 2010;Moniruzzaman et al., 2012;Divya et al., 2014). Due to environmental stress or abiotic stress, if rice plants stay submerged for more than 5 days, they start to die and there is almost no chance to recover after the water recedes. The International Rice Research Institute (IRRI) determined to identify and introduced various submergencetolerant rice genotypes since 1970s (Vergara and Mazaredo, 1975). In the 1970s, FR13A was identified as one of the best submergence-tolerant donors and was used extensively by rice breeders. Especially in coastal areas where floodwaters are often saline, the pyramiding of submergence and salinity tolerance is very important. Recently the major salinity QTL has been identified on chromosome 1 and characterized (Thomson et al., 2010). Though, numerous QTLs are possibly essential to attain adequate salinity tolerance in the field, also extra QTLs for seedling and reproductive-stage salinity tolerance may be required to afford defense from salinity stress during the rainy season. The prospect to apply molecular marker technologies as a means of stacking numerous tolerance genes/QTLs into single rice varieties delivers a distinctive opportunity for breeders to develop tolerant cultivars more rapidly for targeted environments (Septiningsih et al., 2013) and different types of biotic stresses. The Sub1 gene positioned on rice chromosome 9 was well-known as a foremost gene conferring submergence tolerance in tolerant rice cultivar FR13A and its derived progenies (Xu and Mackill, 1996;Xu et al., 2000Xu et al., , 2004Toojinda et al., 2003;Manivong et al., 2014). In this study, the improvement of resistance against blast, gall midge including bacterial blight disease and tolerable to submergence and salinity stress with effective foreground and SSR based background selection was achieved by following three back crosses and three generation selfing, resulting the high level of resistance or tolerance to biotic and abiotic stresses. Similar results were reported with gene pyramiding in different rice varieties with different resistance genes for biotic and abiotic stresses (Sanchez et al., 2000;Singh et al., 2001;Dokku et al., 2013a,b;Gouda et al., 2013;Suh et al., 2013;Divya et al., 2014;Kumar et al., 2014;Pradhan et al., 2015). The study employed three backcrosses to transfer the desired traits from the donors into Improved Lalat followed by three cycles of selfing (Figure 1). Through this approach, we could effectively transfer all the target genes/QTLs of resistance/tolerance into the Improved Lalat background using marker assisted selection in each step starting from BC 1 F 1 generation (Figure 1). Clear polymorphism was observed with all the markers linked to the genes/QTLs under the study between the parent and the donors (Figure 2). Of the two hundred fifty BC 3 F 3 generation lines of Improved Lalat, 31 plants homozygous for alleles associated with the resistance/tolerance with the gene combination were selected (Figure 1) through marker analysis. Nine lines with the presence and absence of targeted genes/QTLs were selected with different gene combinations using tightly linked markers (Figures 3, 4). The linked markers used in this study were, according to the published literature ( Table 1). Similar results were obtained in rice using the same strategy for BB resistance by several workers, including our laboratory at CRRI earlier (Dokku et al., 2013a,b;Pradhan et al., 2015). The recovery of the entire target genes/QTLs suggested that the population size employed in the study was enough to recover the desired combinations. However, with higher population levels, higher number of gene pyramids with varied content of the recurrent parental genome could have been obtained and selection options would have been higher. This is evident from the background analysis as in some of the lines; the recovery of the recurrent parent genome was not up to the expected level. The purpose of the program is to fortify the plant defenses without disturbing the recurrent parental genome through marker assisted approach so that the new gene pyramid will be acceptable to the farmers, millers and traders. For ensuring the acceptability of the new genotypes, it is necessary to characterize the gene pyramids and select the ones that are closer to the parent for both morphological and quality traits as this selection add value to the MAS program. These genetic similarity studies conclusively prove the utility of both the molecular and morphological analysis in efficient background selection. The bioassays confirmed the earlier finding that the recurrent parent possess high levels of resistance against BB and all the pyramids developed had all the BB resistance genes and all of them showed high levels of resistance ( Table 2). The recurrent parent along with pyramids of different gene combinations including two gene pyramids having 10 genes that showed a high degree of resistance against the most virulent BB isolates with lesion length below 3.4 cm. Whereas, ILGP1, ILGP14 showed the highest resistance with less than 0.9 cm lesion length ( Table 2) against BB similar with the previously reported results (Rajpurohit et al., 2011;Dokku et al., 2013a,b;Suh et al., 2013;Pradhan et al., 2015). Pyramiding multiple resistance genes in case of blast disease is a necessity as a breakdown of resistance is known against blast disease and of the several available genes that confer resistance against blast, a combination of Pi2 and Pi9 (the gene from O. minuta, a wild species of Oryza family) was considered to be ideal for dealing with blast (Hittalmani et al., 2000;Liu et al., 2002;Qu et al., 2006). In case of Blast in the current study, the pyramids which were having genes Pi2 and Pi9 were screened for the blast in the research institute at Hazaribaag India, and these lines showed a score of "0, " a resistant reaction while some lines were moderately resistant (MR) with a score "3." It was evident from the results that the gene combination Pi2+Pi9 were more effective (ILGP5, ILGP17, ILGP19) by showing resistant reaction while the lines with either Pi2 or Pi9 alone were susceptible or moderately resistant to Blast and the recurrent parent had shown highly susceptible reaction (Table 3, Figure 5). The genetic enhancement of the genotype, Improved Lalat in terms of resistance to blast in a hot spot region confirms the utility of Pi2+Pi9 gene combination in eastern India against blast. Gall midge is a major insect pest on rice (Behura et al., 2000). Several biotypes are known and recent breakdown of resistance in different parts of the country is causing fear. There are 11 gall midge resistance genes reported so far. A combination of Gm1 and Gm4 genes was considered to be ideal to confer resistance against this major pest (Nair et al., 1996;Biradar et al., 2004). In our study, the gene pyramids having the Gm1+Gm4 gene combination expressed a high degree of resistance against gall midge, the levels that are comparable to that of the donor parents. In Improved Lalat genotype, the pyramids which were having both genes Gm1 and Gm4 when screened for their reaction against Gall midge, showed high levels of tolerance against gall midge amongst, ILGP5 and ILGP14 showed the highest degree of resistance with 100 and 94.1% positive plants respectively (Table 4, Figure 6). The present result suggested the utility of this gene combination in the combating gall midge, major insect pest affecting rice cultivation. Among the abiotic stresses in rice, salinity and submergence are the two major stresses that cause severe yield losses year after year. In the changing scenario of climate change, they assume greater importance. With the rising of sea levels, more land area is likely to get inundated and with increasing precipitation, submergence of standing crops is a reality. With the recent identification of major QTLS like Sub 1 (Xu et al., 2006) and Saltol (Bonilla et al., 2002;Nejad et al., 2008Nejad et al., , 2010 conferring tolerance against submergence and salinity respectively is feasible. With the development of Swarna Sub 1 through the transfer of Sub 1 QTL from FR 13A, the utility of the Sub1 QTL was well demonstrated at IRRI, Philippines. The present study also strengthens the utility of Sub1 QTL as the pyramids having the Sub1 did exhibit the expected levels of tolerance to submergence. Among them ILGP5, ILGP19 and ILGP20 showed the highest degree of submergence and the tolerance levels are on par with the level exhibited by FR13A (Figures 7, 8). The Saltol QTL was transferred from Pokkali into different genotypes like FL478 that showed high promise in earlier studies at CRRI, India. The lines having Saltol QTL when screened for tolerance against salinity stress, survived the stress with minor variations in degree of tolerance, but scoring was between 1 and 3 on a scale of 0-9 suggesting a high level of tolerance in several gene pyramids (ILGP1, ILGP3, ILGP5, ILGP13, ILGP14, ILGP17, and ILGP19) while the recurrent parent (Improved Lalat) was susceptible with a score of 9 and did not survive the salinity stress (Figures 9, 10). The results indicated that the genes in combination were more effective than a single gene and significant genetic enhancement was observed in Improved Lalat the recurrent parent, for all the target traits that were transferred in the present study. However, despite achieving a high level of success in both gene transfer and their expression in several gene pyramids, some of the pyramids did not exhibit the desired levels of expression of tolerance/resistance against the stresses suggesting the role of the genetic background in showing the level of expression. Another possibility for this deviation could be a result of recombination between the marker locus and the respective gene conferring resistance if the marker and the gene/QTL are quite distant. Therefore, there is a need to develop a suitable PCR based marker that is physically closer to the target gene and use of gene based markers is the best solution for effective transfer and expression of the transferred gene at the desired level. In the current study, we employed three backcrosses followed by selfing to derive the maximum genetic background of Improved Lalat and the BB resistance genes. The SSR based background selection was employed on the pyramids in BC 3 F 3 generation that revealed the recovery of more than 90% of the recurrent parent alleles (Figure 11) which corroborates with previous researches that employed different markers like AFLP (Chen et al., 2001) and RFLP (Chen et al., 2000). At a single locus, the expected frequencies for individuals to be homozygous for the genotype of the recurrent parent would be 0.5, 0.75, and 0.875, in BC 1 F 1 , BC 2 F 1 , and BC 3 F 1 respectively. These can also be viewed as the expected proportions of loci for individuals to be homozygous for the recurrent parent genotype. The variances of such proportions in these generations would be 0.5 (1 2 0.5)/n, 0.75 (1 2 0.75)/n, and 0.875 (1 2 0.875)/n, respectively, where n is the number of independent recombination units in the genome. Though it is difficult to match the map units that are equivalent to an independent recombination unit in the rice genome, it is clear that the variance in BC 1 F 1 is much larger than those in subsequent generations, indicating a wider frequency distribution in the BC 1 F 1 than the later generations. The desired individual with recombination between the targeted gene locus and either one of the flanking markers is expected to occur at a much higher frequency in BC 1 F 1 than BC 2 F 1 which means that it is feasible to practice background selection in the BC 1 F 1 generation. Thus, in addition to the background selection in the BC 3 F 1 generation, adding one more round of background selection in BC 1 F 1 to the MAS scheme may greatly increase the efficiency of the program and selection for one more cycle for morphological and grain quality traits may result in identification of lines that are much more closer to their parent. In this study the pyramids also evaluated for the intimacy of pyramids for its agro morphological and grain quality traits with the recurrent parent. The dendogram combining both morphological and grain qualities showed that the selected nine pyramids were closest to the recurrent parent with less distance to parent (Figure 12). The current work is aimed to combine multiple genes/QTLs into an elite rice variety Improved Lalat for enhanced resistance/tolerance against several stresses. The results suggested that, the pyramidization of 10 genes into an elite variety have significantly enhanced the level of resistance/tolerance against the target stresses for which they are known to be associated. In addition, with the selection at the morphological level, grain quality and SSR based selection, we could recover most of the recurrent parental genome, which is clear from the dendrograms and some of the gene pyramids are closer to their respective recurrent parents in many morphological and quality traits. Thus, the study has achieved the major objective through successful transfer of six important genes/QTLs to confer resistance/tolerance against the major biotic and abiotic stresses and the four BB resistance genes present in the recurrent parent also displayed a higher level of resistance in the bioassays. Two gene pyramids like (ILGP5, ILGP19) that have all the 10 genes have shown great promise and have the potential with resistance/tolerance against multiple stresses. Identification of genes with similar reactions to two or more races is difficult to identify in conventional breeding making transfer difficult through conventional approaches. However, with the availability of molecular markers that are closely linked with each of the target genes make the identification of plants with more than two genes possible enabling us to incorporate multiple desirable genes into a single elite genotype. The success of the work clearly demonstrates the probability of addressing the problems of bacterial blight, blast, gall midge along with submergence and salinity stresses which is a major challenge to the rice productivity. Conclusion Development of broad-spectrum resistance against diseases like BB and blast and insects like gall midge in the Indian subcontinent is a foremost challenge due to the rich multiplicity of the agro-climatic zones where rice is cultured, as well as the presence of a number of genetically distinct virulent strains/biotypes in different geographical areas of India. In addition, in the climate change scenario, tolerance to submergence, and salinity assume great significance to rice particularly in the rain fed ecologies. The study has demonstrated that deployment of appropriate gene or gene combinations against each stress can achieve durable and broad-spectrum resistance/tolerance in stress prone specific areas of India. The success may also stimulate several such studies to realize the potential of molecular plant breeding as the foundation for crop improvement in the twenty-first century. The future studies planned on these gene pyramids include evaluation against the target trait on a larger scale in a multilocation environment so as to determine the expression of the incorporated genes/QTLs. These studies can provide us additional information on the interaction between the incorporated genes, if any. In addition, with a further selection at both morphological and molecular levels in large populations of these gene pyramids, we wish to recover the recurrent parental genome in full and NILs of each genotype can be established with each one of the nine genes/QTLs. These NILs will be of great use in the future rice breeding programs and breeders can use them suiting to their needs either individually or in desired combinations.

v3-fos

2019-03-19T13:07:21.392Z

2015-06-25T00:00:00.000Z

51749656

s2

ISOLATION, SCREENING AND OPTIMIZATION OF ESTUARY REGION (KHAMBHAT, GUJARAT) MICROALGAE FOR LIPID/OIL PRODUCTION Water and soil samples were collected from gulf of Khambhat region, Gujarat. The cations and anions like calcium, chloride, fluoride, magnesium, sulphate and total hardness as calcium carbonate were analyzed. Collected estuarine samples were cultured in three different media under standard laboratory conditions. These enrichments were then used to isolate pure unialgal culture by conventional method. Thirty four isolates belonging to twelve species of Cyanobacteria, twenty species of Chlorophyta and two taxa of Bacillariophyta were identified and are maintained at SPRERI centre. The Chlorophyta were found better accumulators of lipids than the cyanobacterial species. Five promising strains (SBC 7, SBC 9, SBC 17, SBC 18 and SBC 19) have been selected. In-house isolates SBC19 and SBC 17 showed highest acetyl CoA carboxylase (ACCase) of 55.2 (U/ml) and 51.2 (U/ml) respectively, with 0.375 g l-1 nitrogen concentration in 24 days. Biomass production was highest for 2.4 g/l, (SBC 19) and 2.7 g/l (SBC 17) with 1.5 g l-1 nitrogen concentration. The highest lipid content was 52% and 48% in SBC19 and SBC 17, respectively, with 0.375 g l-1 nitrogen concentration of solvent extraction method. Lipid accumulation was found enhanced by more than 50% on dry mass basis under nitrogen starvation. Introduction The depletion of fossil fuel reserves has caused an increase price of diesel fuel. The uncertainty in their availability is considered to be the important trigger for researchers to search for alternative sources of energy, which can supplement or replace fossil fuels (Harun et al., 2010;Mata et al., 2010). In recent years, researches are busy exploring alternate fuels from various biological renewable sources. Biodiesel is an alternate to diesel fuel, which is produced from oils via transesterification. It is non-toxic, biodegradable and has the potential to replace the conventional diesel fuel. The use of biodiesel will ultimately leads to reduction of harmful emissions of carbon monoxide, hydrocarbons and particulate matter and to the elimination of SOx emissions, which can also help in reducing the greenhouse effects and global warming. Presently, biodiesel is produced from different crops, such as, soybean, rapeseed, sunflower, palm, coconut, jatropha, karanja, used fried oil and animal fats (Khan et al., 2009). There is a limitation in use of these oils as alternate fuels because of its food demand, life span, lower yield/ha, higher land usage and higher price inter alia (Mata et al., 2010). It is therefore necessary to search for non-food alternate feedstocks for biodiesel production. Selection of biodiesel feedstock is based on higher yields, short duration, lower production cost and less land usage. Among various biodiesel feedstocks, the microalgae oil has potential to replace the conventional diesel fuel. Microalgae are desirable for biofuels production as compared to plants because (1) microalgae have fast growth rates, high biomass yield potential using non-fresh water streams as substrate, (2) microalgal based biofuels do not interfere with food security concerns, (3) biofuels generated from microalgal lipids have less emissions and contaminants as compared to petroleum based fuels, therefore, reduced greenhouse gas emissions, and (4) microalgae require non-arable land for their cultivation, can utilize industrial flue gas as carbon source and can be harvested daily (Chisti, 2007). The main objective of this research paper is to focusing on isolation, screening and optimization of microalgae cultivation in laboratory level with the main aim of producing biofuels. Media and Nutrients used for the growth studies Water and soil samples were collected by random sampling method from gulf of Khambhat region, Gujarat. The analyses of cations and anions like (calcium, chloride, fluoride, magnesium, sulphate and total hardness as CaCO3) were done by Vaibhav Analytical Services, using established protocols. Collected samples were observed under light microscope used for observing and images were captured with RADICAL RxLR-3 microscope fitted with Research Article camera and photomicrographic system. The identification was done using keys in standard monographs (Desikachary, 1959;Philipose, 1967;Iyengar and Desikachary, 1981). After observation, samples were enriched in different modified media, Bold's Basal medium (Starr and Zeikus, 1993) at pH 6.6, BG11 medium (Rippka et al., 1979) at pH 7.5, Chu 13 medium (Chu, 1942) at pH 7.4 and F/2 medium (Guillard and Ryther 1962) at pH 8.2 followed by plating and incubated under standard temperature condition of about 25±2 ˚C under a photoperiod of 12:12 h light dark cycle at light intensity of 35 μmol photon m -2 s -1 . The microalgae were isolated and purified through serial dilution followed by plating and regular observation under microscope. The biomass of the entire cultures was measured by weighing dried sample of the culture suspensions. Filter papers (Whatman GF/C 0.7μm, 47mm in diameter) stored in a constant room temperature (23±2°C) were preweighed. Then, samples of 5ml of each alga culture were filtered through the filter papers. They were dried over night at 110°C and then weighed again at room temperature. The biomass content was calculated. Preparation of sample for the determine the acetyl-CoA activities Algae cells were added to an assay mixture containing acetyl-CoA, bicarbonate, magnesium and ATP, and aliquots were removed at set time points and stopped by the addition of trifluoroacetic acid. The level of acetyl-CoA remaining in each aliquot was determined via a citrate synthase assay, in which the formation of the yellow compound dithiobisnitrobenzoic acid-thiophenolate was followed spectrophotometrically at 412 nm. 25 ml of algae cells were harvested by centrifugation (8000 x g, 4°C, 10 min), collect the pellet and dissolve in ice-cold 100 mM KPO4 buffer solution (pH 7.5). The algae suspension were kept under sonication for 15 min, (in ice bath, 20 Hz, 30% Amp) condition. Then again centrifuge the algae suspension (8000 x g, 4°C, 10 min). Finally the supernatant was used for enzyme assay. Acetyl-CoA carboxylase activity was measured using a discontinuous spectrophotometric assay used as Laura Willis et al., 2008 method. Determination of lipid content by Nile red and solvent extraction methods Nile red (9-(Diethylamino)-5H benzo [∞] phenoxazin-5one) has been shown to be quite useful in detecting neutral lipids in many different microalgae. The use of the Synergy™ H4 Multi-Mode Microplate Reader to monitor the high levels of lipid in algal strains using fluorescence. After successful isolation, the microalgae were screened for their lipid accumulation using above method (Fig. 1.) Another method was used as solvents -lipid extraction method. Freeze-dried algal mass was extracted with methanol containing 10% DMSO according to Chiara et al., (2002) but with slight modification. The solvent with the biomass was heated at 45 o C and stirred for 45 minutes and the mixture was centrifuged at 3000 rpm for 10 min. The supernatant removed and the pellet was re-extracted with a mixture of diethyl ether and hexane (1:1 v/v). Added equal volume of water to the solvent mixture and supernatants so as to form a ratio of 1:1 (v/v). The mixture was centrifuged again and the upper phase was collected. The water phase was re-extracted and the organic phases that contain total lipid were combined and evaporated to dryness under nitrogen protection. Thereafter, the total lipids were measured gravimetrically after freeze drying for 24 h. Study the physico-chemical parameters from estuaries of Khambat region, Gujarat. Twenty four samples were collected from six different places comprising various estuary habitats e.g. temporary pool, ditch, main stream of river, estuary region of sea, sand surface of river bed etc. from the gulf of Khambhat, Gujarat on seasonal basis. Temperature and pH was measured using portable thermometer and pH meter at each site respectively. Limnological analyses of sample of cations and anions like (calcium, chloride, fluoride, magnesium, sulphate and total hardness as CaCO3) were done by Vaibhav analytical services, Ahmedabad using established protocols. The values from various sites have been listed in Table 1. Determination of acetyl CoA carboxylase (ACCase) activities from promising strains The fatty acid synthesis is the conversion of acetyl CoA to malonyl CoA, catalyzed by acetyl CoA carboxylase (ACCase). In the chloroplast, photosynthesis provides an endogenous source of acetyl CoA, and more than one pathway may contribute to maintaining the acetyl CoA pool. Two in house isolates i.e. SBC19 and SBC 17 showed highest acetyl CoA carboxylase (ACCase) of 55.2 (U/ml) and 51.2 (U/ml) with 0.375 g/l nitrogen concentration in 24 days respectively. But when algae strains were grown in 1.5 g/L (NaNO3) medium the acetyl CoA carboxylase decreased in terms of U/ml in 24 days. These results were points out that as the specific nitrate concentration (0.375 g/l) in the medium acetyl CoA carboxylase enzyme are increased (Table.3). The enzyme dependent was due to level of stress environment and also varies the enzyme accumulated in the cells. The present study suggested that nitrogen starvation with acetyl CoA carboxylase path way is the effective approach to enhance lipid for biofuel production. Effect of Nitrogen source on microalgae growth and determination of biomass, lipid content from potential strains The above five strains were selected for nitrogen starvation experiment. NaNO3 was used as nitrogen source in the respective medium (1.5, 0.75, 0.375, g l -1 ). The following table shows the effect of nitrogen stress condition. The results indicated that as the nitrogen concentration in the medium decreased, biomass production decreased (Table. 4) and increased the lipid content. The present study indicated that nitrogen starvation is the effective approach to enhance algal lipid content. Two in house isolates i.e. SBC19 and SBC 17 showed highest acetyl CoA carboxylase (ACCase) of 55.2 (U/ml) and 51.2 (U/ml) with 0.375 g l -1 nitrogen concentration in 24 days. These strains were highest biomass and lipid content in respectively Table 4: Effect of chemical stress (NaNO3) on microalgal biomass and lipid production. Conclusions It can be conclude that five promising microalgal strains (SBC 7, SBC 9, SBC 17, SBC 18 and SBC 19) have been selected. Two of the isolates i.e. SBC19 and SBC 17 have given very high biomass production of 2.4 and 2.7 g/l, respectively. Their lipid accumulation was found significantly enhanced by more than 50 % on dry mass basis under nitrogen starvation. The five promising microalgae species will be used for further research and development work for biofuel production

v3-fos

2018-04-03T05:49:46.954Z

2015-10-15T00:00:00.000Z

17173546

s2

High‐density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool Summary In wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheat's secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra‐high‐density Axiom® genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site. Introduction Bread wheat (Triticum aestivum) is an allohexaploid crop derived from the hybridization of diploid Aegilops tauschii with tetraploid wild emmer, Triticum turgidum ssp. dicoccoides (Dubcovsky and Dvorak, 2007;Matsuoka, 2011;Shewry, 2009). This hybridization, subsequent domestication and inbreeding have reduced genetic diversity in cultivated wheat compared with its wild ancestors (Haudry et al., 2007;Tanksley and McCouch, 1997). The lack of genetic diversity is a major issue for wheat breeders and limits their ability to produce new varieties (Roussel et al., 2004;White et al., 2008). Hybridization of wheat with wild relatives, resulting in so-called alien introgression, has been used on numerous occasions to introduce novel diversity into bread wheat's gene pool (Chen et al., 2012;Moln ar-L ang et al., 2014). However, introgression of 'alien' DNA into the wheat genome inevitably leads to the introduction of undesirable traits as genes linked to the target gene are introduced along with it, so-called linkage drag (Klindworth et al., 2013). The negative impact of linkage drag can be minimized by reducing the size of the introgressed fragment to the minimum necessary to retain the desired phenotype (Wulff and Moscou, 2014). This can be achieved through repeated backcrossing to the elite parent but is often a lengthy process (Qi et al., 2007). Until recently, evaluation of introgressions has been conducted using manually intensive cytogenetic techniques which cannot be readily applied to a large number of samples (Friebe et al., 1991(Friebe et al., , 1996Lukaszewski et al., 2005). Molecular markers, on the other hand, which can be adapted for high sample throughput, enable the rapid and costeffective characterization of introgressions (Thomson, 2014). The use of molecular markers, such as single nucleotide polymorphisms (SNPs), is now common place in the genotyping of wheat (Akhunov et al., 2009;van Poecke et al., 2013). The uptake of SNP markers has recently been accelerated by the use of both KASP assays (Allen et al., 2011; LGC, Herts, UK) and the development of a high-density iSelect array Illumina, San Diego, CA). However, while the development of the current hexaploid SNP resources is welcome, the majority of SNP markers developed to date are not suitable for use in wide crosses. The high level of sequence polymorphism between hexaploid wheat and its wild relatives makes it difficult to design polymerase chain reaction (PCR) primers for array-based probes. Recently, Tiwari et al. (2014) overcame this problem by sequencing flow-sorted wheat chromosomes to identify SNPs on the homoeologous group five chromosomes in a cross between Chinese Spring and Aegilops geniculata. Their work, however, also highlighted the high cost and attrition level of developing large numbers of validated SNP markers. To overcome this problem, Wang et al. (2014) used an array-based platform to examine and validate over 81 000 putative SNPs in both tetraploid and hexaploid wheat, and were able to validate 56 388. SNPs derived from Ae. tauschii, the D genome donor of hexaploid wheat, were also included on their array, and of the approximately 4400 SNPs derived from this species, 796 (18%) were also polymorphic in a range of hexaploid wheat accessions . We recently reported the use of a sequence capture targeted re-sequencing approach to characterize a significant proportion of the wheat exome (Winfield et al., 2012), which was then used to identify large numbers of exome-specific SNPs (Allen et al., 2013). Here, we have extended this procedure to include the equivalent exome-captured sequences from a range of species, including members of the secondary and tertiary gene pool, that are a potential source of novel alleles suitable for introgression into the hexaploid genome. We have analysed the resulting captured sequences to identify a large number of putative SNPs between different varieties of hexaploid wheat and between hexaploid wheat and related species, including its putative progenitor species (Ae. tauschii, Aegilops speltoides and Triticum urartu) and various wild relatives. To carry out a large-scale validation of the putative SNP markers, we used the Axiom â high-density genotyping platform (Affymetrix Inc., Santa Clara, CA). The SNP markers and the Axiom â genotyping array described here have resulted in the generation of a large number of validated varietal and species-specific SNPs which can be used to monitor and map introgressions within the hexaploid wheat genome. SNP discovery Using a wheat NimbleGen array (Winfield et al., 2012) to direct the capture and targeted re-sequencing of the wheat exome, we generated~900 million sequences from 43 bread wheat accessions and wheat relatives. These included 14 diploid species including A, B and D genome progenitors as well as representatives of E, J, R and T genomes, five tetraploids (AB and AG), 23 hexaploids (ABD and SJJ) and one decaploid (JJJJ s J s ) (Table S1). Of the sequences generated, 344.5 million (38%) could be mapped back to sequences on the array. To identify polymorphic sequences within the species used, we used the SNP discovery pipeline and experimental procedures described by Winfield et al. (2012) to obtain 921 705 putative varietal SNPs from the mapped sequences (this data set may be downloaded from the CerealsDB web site; http://www.cerealsdb.uk.net/cerealgenomics/CerealsDB/Excel/PutativeSNPs.csv). The NimbleGen array contained 132 606 repeat-masked expressed sequence tags obtained from hexaploid wheat (Winfield et al., 2012). Of these features, 81 132 (61%) were found to have at least one SNP with 64 937 (49%) features having three or more SNPs. As chromosome location is an important consideration when selecting SNPs for genotyping projects, we describe the location of the SNP probes with reference to the recently published IWGSC survey sequences (The International Wheat Genome sequencing Consortium, 2014). We used the 'Exonerate' program (Slater and Birney, 2005) to align the SNP probes to the IWGSC survey sequences. We were able to align 547 167 (66.8%) of the SNP probes to 60 841 of the 10 776 707 IWGSC survey sequence contigs (Table 1). Of these, 491 792 (60% of the probes on the array, or 89.9% of the aligned markers) had an unambiguous, single top hit. For all other sequences, it was not possible to determine which homoeologous chromosome was the source of the original SNP probe as probes aligned with equal scores to two or more IWGSC sequences. Examination of the genome distribution of the 60 841 IWGSC contigs containing the 547 167 SNP probes indicated that they were evenly distributed across the 21 hexaploid wheat chromosomes (Table 1). Further examination of the SNP probe distribution across the 60 841 IWGSC contigs suggested that while 11 210 contigs contained a single SNP probe, the remaining contigs aligned to multiple probes ( Figure 1). SNP validation The Axiom â HD Wheat Genotyping Array (hereafter referred to as the Axiom â Array) was used to screen genomic DNA prepared from 475 accessions (listed in Table S2). These included 108 elite hexaploid accessions of which 48 were suggested by a number of commercial wheat breeders, 27 hexaploid accessions from the Watkins collection (Burt et al., 2014;Miller et al., 2001), eight T. turgidum accessions and 24 wheat relatives including T. urartu, Ae. speltoides and Ae. tauschii (A, B and D genome progenitors, respectively). We included twenty lines from the Chinese Spring nullisomic collection (Devos et al., 1999) and 32 accessions from the Kansas deletion line collection (Endo and Gill, 1996) to allow us to physically assign SNP probes to chromosomes. We also included individuals from the Avalon 9 Cadenza, Savannah 9 Rialto (Limagrain, UK) and Synthetic 9 Opata (Sorrels et al., 2011) mapping populations. Genotype calls were generated as described in Experimental procedures. The sample call rate ranged from 80.1% to 99.6% with an average of 98.4% for the 475 accessions. The average call rate varied depending upon the ploidy and relationship of the accessions screened (Table S3). The lowest call rates were obtained for the wheat relatives with an average of 85.8%. The 14 Ae. tauschii accessions had a higher average call rate (92.3%) than either of the other two representatives of the A and B genomes; T. urartu (83.2%) and Ae. speltoides (85.4%). For the 819 571 SNP probes on the array, the call rate ranged from 4.4% to 100% with an average of 98.4%. Of these, 765 359 (93.4%) had a call rate of greater than 95%. The Axiom â Array was designed to genotype hexaploid wheat as well as species from the secondary and tertiary gene pools. To confirm the array's utility, we considered the 546 299 polymorphic SNP probes. Of these, 99 783 were polymorphic between the 108 elite hexaploid wheat varieties, a figure that increased to 112 723 when the Watkins collection was included and to 453 052 when the elite accessions and their relatives and progenitors were considered. The number of polymorphic probes between the different groups is shown in Figure 3. The complete data set for all 475 accessions can be downloaded as a CSV file from the CerealsDB web site (http://www.cerealsdb.uk.net/). To putatively assign markers to chromosomes, genomic DNA from the eighteen Chinese Spring derived nullisomic/tetrasomic accessions and the 32 Kansas deletion accessions was screened against the array. Through this approach, 161 869 markers (nullisomic/tetrasomic lines) and 127 990 markers (Kansas deletion lines) were physically assigned to a chromosome (Table 2). Genetic mapping The number of polymorphic markers between the parental lines of each populations was 23 740 (Avalon 9 Cadenza), 21 285 (Savannah 9 Rialto) and 38 019 (Synthetic W7984 9 Opata). Markers with more than 20% missing data were removed before map construction. Markers that had a unique pattern of segregation were also removed. The number remaining for each population was 20 536, 19 683 and 34 513, respectively. Avalon 9 Cadenza The 20 536 markers fell into 1447 bins. From each of these bins, one marker was selected as a representative to create a chromosome frame. A chi-square test of these representatives showed that 157 exhibited significant segregation distortion (P < 0.05). These markers were also removed along with the markers in the bin they represented. Thus, there were 1290 markers from which to construct the chromosome frame. Of these, 1286 markers mapped to 21 linkage groups representing the 21 wheat chromosomes, and four markers were unlinked. These four markers, along with the all other markers from the bin for which they were the representative, were also removed. The total map length of this 'frame' was 3663 cM with an average chromosome length of 174 cM and one marker every 2.9 cM. Finally, the markers from the initial bins were reintegrated into the map at the same cM position as their representative 'frame' markers. The complete map contained 18 942 markers (Table 3 and Tables S4 and S5). Savannah 9 Rialto The 19 683 markers fell into 830 bins from each of which a single marker was selected as a representative. A chi-square test identified 62 markers with significant segregation distortion (P < 0.05), and these were removed leaving a core set of 768 markers. A total of 655 markers mapped to 23 linkage groups, while 113 markers were unlinked. These unlinked markers, along with all the markers from the bins they represented, were removed from further analysis. Due to the large genetic distance between markers on the long and short arms of chromosomes 5B and 6D, these were split into two groups, one for the short arm and one for the long arm. The total map length was 2819 cM with an average chromosome length of 136.2 cM and one marker every 4.3 cM. Finally, the markers from the initial bins were reintegrated into the map along with their representative 'frame' markers. The complete map contained 16 039 markers (Table 3 and Tables S4 and S5). Synthetic W7984 9 Opata The 34 513 markers fell into one of 2361 bins and one marker was picked to represent each bin. A chi-square test showed 113 markers with significant segregation distortion (P < 0.05) which, once removed, left a core set of 2248 markers. A total of 2167 markers mapped to 21 linkage groups while 81 markers were unlinked. The total map length was 7745 cM with an average of one marker every 3.6 cM and an average chromosome length of 369 cM. After reintegration of binned markers, the map contained 31 808 markers (Table 3 and Tables S4 and S5). Consensus map In total, we have mapped 56 505 markers to the 21 wheat chromosomes. Of these, 47 069 (83.3%) mapped in only one of the populations, 8588 (15.2%) mapped in two populations and 848 (1.5%) mapped in all three populations. Of the 9436 markers that mapped in more than one of the populations, 729 (7.7%) mapped to different chromosomes on the different maps (Table S6). Of these conflicts, 67.4% were between homoeologous chromosomes, 5.3% were conflicts between chromosomes 5B and 7B, and 5.6% were between chromosomes 4A and 7A. Of the markers in conflict, 67 were mapped in all three of the populations. For these markers, the 'consensus chromosome' was assigned based on 'majority rule' (if a marker mapped to the same chromosome in two of three maps, this location was used). For the remaining 662 SNPs, 48 were assigned to a consensus chromosome using genotype scores from the nullisomic and Kansas deletion lines and 132 were assigned to a consensus chromosome using information from IWGSC survey sequence contigs. Finally, for the 482 markers that had two map positions (964 chromosome positions), but no physical information, one was chosen at random. The final consensus map with 56 505 markers was 3739 cM in length, with an average of 178 cM per chromosome (Table 3 and Table S5). Characterization of hexaploids, progenitors and wheat relatives To date, most genotyping arrays have been designed for use with a single, often diploid, species. Here, we have designed a single array capable of characterizing multiple species with levels of ploidy ranging from diploid, for example Ae. tauschii to decaploid, for example Thinopyrum ponticum and different genomes with varying degrees of similarity. The relationship between the accessions was determined by calculating a pairwise similarity matrix (Table S7) that was used to perform multidimensional scaling (MDS) and create principal coordinate (PCO) plots. Clear groups were evident (Figure 4a). Tight clusters were produced for the T. aestivum, T. turgidum and Ae. tauschii accessions. The wheat relatives, including Ae. speltoides and T. urartu, formed a loose cluster. The Ae. tauschii accessions, for which there were 120 459 polymorphic probes, fell into two distinct groups. One group (Group 1) contained only subspecies tauschii, while the other group (Group 2) contained both subspecies tauschii and strangulata. All but one of the Group 1 individuals were from China, whereas those in Group 2 had a wide geographic distribution but with the strangulata individuals originating from the southern Caspian in Iran or Turkmenistan ( Figure 4b). The Axiom â Array was able to separate the T. turgidum accessions according to subspecies; ssp. dicoccoides accession (TTD140) was clearly distinct from the seven durum wheat accessions (Figure 4c). To confirm that the Axiom â Array was able to dissect the substructure of the hexaploid accessions (elite and Watkins), we examined these in isolation. Two broad groups were evidenced; (i) winter wheats and (ii) spring wheats/Watkins accessions (Figure 4d). Ten accessions, eight winter and two spring, were separated from their main groups; these accessions carry the rye 1RS translocation. To examine this further, we used the 2306 Synthetic 9 Opata chromosome 1B probes to characterize the relationship between the accessions (Figure 5a). This highlighted the distinct nature of the ten accessions known to carry the 1RS translocation and confirmed that this introgression was 1BS specific, ending within the 1B centromere (0-133.5 cM covering 34 bins). In addition to the 1RS accessions, we were able to identify eight accessions as distinct from the remaining hexaploids. These accessions carried a unique haplotype covering a significant portion of 1BS and 1BL including the centromeric region (106.3-220.1 cM covering 42 bins). Given the unique 1B haplotype of these accessions, and the similar characteristics that these accessions share with the ten known 1RS accessions, we hypothesized that these might also carry large introgressions on chromosome 1B. To examine the possibility that the Axiom â Array can be used to detect introgressions in the hexaploid wheat genome, we repeated our analysis using the 1266 markers from 7D, which in some lines is known to carry introgressions (Burt . This analysis identified ten accessions as having a distinct genotype spanning 38 cM on 7DL (Figure 5b). Discussion We have developed a high-density wheat genotyping array using the Affymetrix Axiom â platform. This Axiom â HD Wheat Genotyping Array, which is available as a commercial product (Affymetrix product IDs 550491 and 550492 for the two component arrays; http://www.affymetrix.com/support/technical/data sheets/axiom_wheat_hd_genotyping_array_datasheet.pdf), contains 819 571 exome-captured SNP sequences derived from hexaploid wheat accessions, including both elite and landrace accessions, diploid and tetraploid progenitor accessions and wheat relatives. A major problem with comparing sequences from a range of species is the difficulty in identifying orthologous sequences leading to the generation of a large number of putative SNPs that cannot be validated. To minimize this problem, we used a NimbleGen hexaploid wheat exome capture array such that only likely orthologous sequences were collected and screened for SNPs (Winfield et al., 2012). Based upon the screening conditions employed, we were able to convert 89% of our putative SNPs to probes suitable for the Axiom â Array. We have shown that the SNPs on the Axiom â Array that could be assigned to IWGSC contigs are evenly distributed across wheat's 21 chromosomes. However, the majority of contigs (81.5%) contained two or more SNPs with some containing as many as 73. The reasons for this skewed distribution are unclear, for although larger contigs tended to contain more SNPs, this alone is not sufficient to account for the large differences in SNP frequency between the contigs. The complexity of the wheat genome and its large proportion of non-coding sequences is one possible reason for the biased distribution of polymorphic SNPs in the contigs (Gupta et al., 2008;Voss-Fels et al., 2015). Further detailed investigation will be necessary to de-convolute the effects of gene density, polymorphism rate and contig size on SNP density. Screening the Axiom â Array with 475 accessions resulted in 546 299 (66.7%) 'useful SNP probes' (i.e. SNPs that fall into one of the three categories described in Experimental procedures) being called. As expected, the majority of useful probes on the array were polymorphic (any marker for which there is more than one genotype called; a single individual with a distinct genotype is called a polymorphism) between elite hexaploid accessions and wheat relatives. We identified 112 723 polymorphic markers in the hexaploid accessions. Of these, 16 092 (14.2%) were scored as codominant (genotypes scored as AA or BB) rather than dominant probes (scored as either AA and AB or BB and AB). A further 7005 (6.2%) probes were scored as partially codominant (scored as AA or BB with a subset of accessions having an AB call). Codominant and partially codominant markers are extremely useful for generating genetic maps from F2 populations and for tracking introduced genomic fragments in breeding lines (Mammadov et al., 2012). Although we only included eight tetraploid accessions in our screening, 59 079 SNPs were found to be polymorphic between them. This relatively high number suggests that a considerable amount of diversity exists within the tetraploid genepool as has been indicated by Ren et al. (2013); using the Axiom â Array, or a smaller derivative, it should be possible to screen large collections of tetraploid lines. Of the 59 079 SNPs that were polymorphic between the eight tetraploid lines, 35 943 were also polymorphic within the hexaploid accessions. These may be useful in future breeding programmes involving the two species. Polymorphic SNPs were mapped in three populations, Avalon 9 Cadenza and Savannah 9 Rialto (UK standard reference populations) and Synthetic 9 Opata (standard International Triticeae Mapping Initiative population). As expected for the UK populations, the number of markers that mapped to the D genome was considerably lower than those mapping to either the A or B genomes (Akhunov et al., 2010). This was not the case for the Synthetic 9 Opata population; a larger number of markers mapped with a more even distribution between the three genomes (Sorrels et al., 2011). However, this greater level of polymorphism comes at a price as markers polymorphic on the Synthetic 9 Opata population were of limited value when used to screen elite breeding lines. For instance, the average minor allele frequency of the D genome markers from the Synthetic 9 Opata population was lower (0.1204) than that for SNPs on either Avalon 9 Cadenza (0.2216) or Savannah 9 Rialto (0.2946). This result highlights the drawback of using wide crosses to generate molecular makers; although more markers may be generated, many may not be polymorphic on material used in breeding programmes. However, with the wider use of synthetic lines in breeding (reviewed by Li et al., 2014), this problem might resolve itself. Our goal was to generate a genotyping platform capable of characterizing both wheat and its relatives. The Axiom â Array is capable of doing this. For instance, the Axiom â Array was able to separate the D genome progenitor lines into two distinct groups. Lines from the Far East (Kyrgystan and China), which were exclusively Ae. tauschii ssp. tauschii, formed one group, while lines from the Near East (Armenia, Iran and the west of Turkmenistan), including the three strangulata lines, formed a second group (Figure 4b): this is of interest as it is thought that the D genome of hexaploid wheat is derived from this subspecies (Dvorak et al., 1998). Similarly, the array was able to separate the AB tetraploid accessions according to subspecies. As these polymorphic SNP probes were able to discriminate between all of the lines used (Figure 4c), this subset of probes may be useful in the generation of a tetraploid-specific array. The Axiom â Array also discriminated subgroups among the ABD hexaploid accessions (Figure 4a). The spring and winter wheats clustered separately. The accessions from the Watkins Collection were more similar to the spring accessions than they were to the winter accessions. This agrees with the study by Wingen et al. (2014) which suggests that 86% of accessions in the Watkins collection have a spring growth habit. In addition, ten accessions, two spring wheats and eight winter wheats all of which carry the IRS translocation from rye were identified as being distinct. To examine this further, we used the 2306 chromosome 1B markers on the Synthetic 9 Opata map. These mapped the rye introgression to the short arm of 1B and confirmed that the translocation did not extend beyond the centromere (Figure 5a). An additional eight lines appeared to carry a novel haplotype covering a significant proportion of 1B including the region containing the centromere (Figure 5a). Of these, seven were known to be related via the common progenitor line Cadenza. Our results suggest that Cadenza carries genetic material on 1B distinct from the majority of hexaploid accessions and therefore possibly derived from introgressed material. The eighth line, Batis, is not known to be related to Cadenza, and it is interesting to note that the 1B haplotype for this accession, while being distinct from the remaining hexaploid accessions, is also distinct from Cadenza-derived accessions and hence represents a novel introgression within the hexaploid accessions examined. We next investigated whether the Axiom â Array was capable of identifying introgressed material in the hexaploid genome even when it is not from species used to generate the array. Firstly, we examined the array for SNPs previously identified from a species not used in our original design. For this, we used the SNPs identified by Tiwari et al. (2014) from chromosome 5M of Ae. geniculata. A BLASTN screen of the 104 5M flanking sequences against the 819 571 probes on the array indicated that 48 were present, and of these, 36 were also polymorphic between hexaploid accessions and wheat relatives (Table S8). In addition, ten accessions screened on the array (Azzerti, Battalion, Bermude, Boregar, Lynx, Oratorio, Renan, Revelation, Skyfall and Tuerkis) were known to carry the Ae. ventricosa introgression containing the eye spot resistance gene Pch1 (Doussinault et al., 1983;Worland et al., 1988). Using the 1266 markers from chromosome 7D of the Synthetic 9 Opata map, we mapped the Ae. ventricosa introgression to the long arm of 7D (Figure 5b). Our analysis showed that the ten accessions fell into two groups depending on the size of the introgression: six lines; Battalion, Boregar, Lynx, Renan, Revelation and Skyfall had the introgression from 456.8 to 556.8 cM, a region containing 76 SNP markers organized into 18 bins, while the other four had a smaller introgression (551.7-556.8 cM, a region containing 20 markers in 4 bins), a result that extends the work previously reported by Burt and Nicholson (2011). Examination of the long arm of chromosome 7D also indicated that a further 14 accessions (Apogee, Adhoc, Altigo, Biscay, Cellule, Duxford, Exotic, Fiorello, Humber, Mercato, Panorama, Premio, Santiago and Solstice) carry a telomeric introgression but that this is distinct from the Pch1 Ae. ventricosa introgression. Both of these analyses clearly indicated that the Axiom â Array has utility even when used to screen genotypes and species not used in the original array design. In conclusion, the development of the Axiom â HD Wheat Genotyping Array, which is capable of characterizing a range of wheat-related species, together with the associated automated genotyping call algorithms, high-density maps and public database will provide the wheat community with a valuable resource for the characterization and breeding of hexaploid and tetraploid wheat. In addition, the availability of a high-density array capable of tracking the introgression and subsequent fate of chromosomal fragments from a range of wheat relatives could revolutionize wheat breeding and ensure that such introgressions can be utilized with greater efficiency by targeting further breeding to reduce the size of the fragments and hence reduce linkage drag. Plant material The accessions grown for DNA extraction (listed in Table S2) were grown in peat-based soil in pots and maintained in a glasshouse at 15-25°C with 16-h light, 8-h dark. Leaf tissue was harvested from 6-week-old plants, immediately frozen on liquid nitrogen and then stored at À20°C prior to nucleic acid extraction. Genomic DNA was prepared from leaf tissue using a phenolchloroform extraction method (Sambrook et al., 1989). Genomic DNA samples were treated with RNase-A (New England Biolabs UK Ltd., Hitchin, UK), according to the manufacturer's instructions and purified using the QiaQuick PCR purification kit (QIAGEN Ltd., Manchester, UK). Exome capture and next-generation sequencing Exome capture and next-generation sequencing were performed on 43 accessions (Table S1) according to Winfield et al. (2012). The pipeline removes all within-variety (homoeologous) SNPS which make up the vast majority of variants in hexaploid wheat. Sequencing data can be downloaded from the NCBI Sequence Read Archive (SRA) from the Axiom â 820 Wheat Array Data study PRJNA286098, accession SRP059312 (accession numbers for all the lines included in study are in Table S9). SNP discovery After preprocessing of reads to remove adapter sequences, the data were submitted to a custom pipeline (Winfield et al., 2012). Putative SNPs, together with their flanking sequences, were processed using the Affymetrix design protocol for the Axiom â platform to generate SNP probes for array. Sequence alignment Sequence alignment was carried out using Exonerate version 2.2.0 with parameters-model ungapped, per cent 0 and bestn 3. Genotyping The Axiom â Wheat HD Genotyping Arrays was used to genotype 475 samples (Table S2) using the Affymetrix GeneTitan â system according to the procedure described by Affymetrix (Axiom â 2.0 Assay Manual Workflow User Guide Rev3). Allele calling was carried out using the Affymetrix proprietary software packages Affymetrix Power Tools (APT) and SNPolisher TM (http:// www.affymetrix.com/estore/partners_programs/programs/devel oper/tools/devnettools.affx). A custom software pipeline ADAP (Axiom â Data Analysis Pipeline) was written in perl to simplify the data analysis, following the Axiom â Best Practices Genotyping Figure 5 Heatmaps of genotype scores of 104 hexaploid varieties for loci mapped to chromosome (a) 1B and (b) 7DL. The genotypes are organised horizontically by a dendrogram produced using hierarchical cluster analysis and vertically by centimorgan position along the chromosome according to the Synthetic 9 Opata genetic map. Genotype scores have been coded for each locus as: 1 = least common genotype score; 2 = second most common genotype score and 3 = most common genotype score, and have been coloured according to the legend shown. (a) The heatmap of chromosome 1B shows the distinct haplotypes between those lines carrying the 1RS/1BS substitution (accession names highlighted in red; 0-133 cM) and those lines that do not. This figure also displays the lines belonging to Cadenza derived accessions (accession names highlighted in blue) which have a distinct haplotype on 1B (97.8-198 cM). (b) The heatmap of 7DL highlights accessions carrying Ae. ventricosa introgressions (accession names highlighted in red, 456.8-556.8 cM; accession names highlighted in blue, 551.7-556.8 cM). Workflow (http://media.affymetrix.com/support/downloads/manuals/axiom_genotyping_solution_analysis_guide.pdf). A variant call rate threshold of 80% was used instead of the default value (97%) to account for the lower call rates typically obtained from hybridizing wheat relatives and progenitors to the array. The apt-probeset-genotype program within Affymetrix Power Tools determines genotype calls from Affymetrix SNP microarrays. Following this, the SNPolisher R package calculates SNP performance metrics, such as call rate, cluster separation and deviation from expected cluster position. It then classifies the SNPs into performance categories. These categories were as follows: (i) PHR, which were codominant and polymorphic, with at least two examples of the minor allele; (ii) NMH, which were polymorphic and dominant, with two clusters observed; (iii) OTV, which had four clusters, one representing a null allele; (iv) MHR, which were monomorphic; (v) CRBT, where SNP call rate was below threshold but other cluster properties were above threshold; and (vi) Other, where one or more cluster properties were below threshold. Genetic map construction Individuals from three doubled-haploid mapping populations were genotyped with the Axiom â HD Wheat Genotyping Array. From the Avalon 9 Cadenza population, 130 lines were genotyped, 64 lines from the Savannah 9 Rialto population and 60 lines from the Synthetic 9 Opata population. For each population, markers with more than 20% missing data were removed and markers were binned based on their pattern of segregation in each respective population using the BIN function in ICIMapping V.3.3 (Meng et al., 2015). Markers were placed into the same bin if the correlation coefficient between them was one, and therefore, the recombination frequency between them was estimated as 0. Following binning, all markers which displayed a unique pattern of segregation and did not fall into a bin were removed. Markers that shared their pattern of segregation with at least one other were retained, and one marker was chosen to represent each bin, either one with the least amount of missing data, or in the case where the percentage of missing data was equal, at random. Markers were tested for significant segregation distortion using a chi-square test and those with significant distortion (P < 0.05) were removed. Markers were sorted into groups in MapDisto version 1.7.5 Beta 4 (Lorieux, 2012) with a LOD score of six and recombination fraction of 0.3 using the Kosambi mapping function (Kosambi, 1943). Groups were ordered with the seriation algorithm. These were exported and assigned to chromosomes using information from an Exonerate alignment to the IWGSC wheat survey sequence (The International Wheat Genome sequencing Consortium, 2014), genotype scores from the Kansas deletion lines (Endo and Gill, 1996) and genotype scores from wheat nullisomic/tetrasomic lines (Devos et al., 1999). Where chromosomes were split into multiple linkage groups, these were re-formed into a single linkage group and reordered. Marker order within each chromosome group was optimized with an iterative process of rippling the marker order using a window size of five markers and checking for inversions until the best possible order was found. The long and short arm of each chromosome was identified from the IWGSC wheat survey sequence (The International Wheat Genome Sequencing Consortium, 2014), and groups were orientated to have the short arm above the long arm. Following map construction, the binned markers were integrated back into the map. Generating a wheat consensus map Where there was agreement, all markers were assigned to a 'consensus chromosome' based on information from the genetic maps. In the case of conflicts between two or all the maps, information from the nullisomic lines, the Kansas deletion lines and the IWGSC survey sequences was used to assign markers to a consensus chromosome. The consensus map was generated using the R package 'LPMerge' (Endelman and Plomion, 2014). No weighting was given to the component maps. In the case of duplicates, a marker was retained if its position in the consensus map matched the previously defined 'consensus chromosome' and its duplicate was removed. Where there was no 'consensus chromosome' designation, one of the duplicates was removed at random. Dimensionality reduction The relationship between the lines was determined by calculating a similarity matrix for all the lines (Table S7). This was calculated as number of markers shared by any two lines divided by total number of markers for the two lines; markers that had missing calls for either of the lines were not used to estimate similarity. The matrices were imported into R and used to create principal coordinate plots using the classic MDS method, cmdscale. Graphical genotype visualization and hierarchical clustering were performed using Spotfire software (TIBCO, Boston, MA), using default parameters. Prior to importing into Spotfire, genotype scores were coded for each locus as: 1 = least common genotype score; 2 = second most common genotype score; and 3 = most common genotype score. Supporting information Additional Supporting information may be found in the online version of this article: Table S1 Accessions subjected to NimbleGen targeted re-sequencing. Table S2 Accessions assayed on the Axiom HD Wheat Genotyping Array.

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2015-11-17T00:00:00.000Z

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RNA-seq reveals differentially expressed genes of rice (Oryza sativa) spikelet in response to temperature interacting with nitrogen at meiosis stage Background Rice (Oryza sativa) is one of the most important cereal crops, providing food for more than half of the world’s population. However, grain yields are challenged by various abiotic stresses such as drought, fertilizer, heat, and their interaction. Rice at reproductive stage is much more sensitive to environmental temperatures, and little is known about molecular mechanisms of rice spikelet in response to high temperature interacting with nitrogen (N). Results Here we reported the transcriptional profiling analysis of rice spikelet at meiosis stage using RNA sequencing (RNA-seq) as an attempt to gain insights into molecular events associated with temperature and nitrogen. This study received four treatments: 1) NN: normal nitrogen level (165 kg ha−1) with natural temperature (30 °C); 2) HH: high nitrogen level (330 kg ha−1) with high temperature (37 °C); 3) NH: normal nitrogen level and high temperature; and 4) HN: high nitrogen level and natural temperature, respectively. The de novo assembly generated 52,553,536 clean reads aligned with 72,667 unigenes. About 10 M reads were identified from each treatment. In these differentially expressed genes (DEGs), we found 151 and 323 temperature-responsive DEGs in NN-vs-NH and HN-vs-HH, and 114 DEGs were co-expressed. Meanwhile, 203 and 144 nitrogen-responsive DEGs were focused in NN-vs-HN and NH-vs-HH, and 111 DEGs were co-expressed. The temperature-responsive genes were principally associated with calcium-dependent protein, cytochrome, flavonoid, heat shock protein, peroxidase, ubiquitin, and transcription factor while the nitrogen-responsive genes were mainly involved in glutamine synthetase, transcription factor, anthocyanin, amino acid transporter, leucine zipper protein, and hormone. It is noted that, rice spikelet fertility was significantly decreased under high temperature, but it was more reduced under higher nitrogen. Accordingly, numerous spikelet genes involved in pollen development, pollen tube growth, pollen germination, especially sporopollenin biosynthetic process, and pollen exine formation were mainly down-regulated under high temperature. Moreover, the expression levels of co-expressed DEGs including 5 sporopollenin biosynthetic process and 7 pollen exine formation genes of NN-vs-NH were lower than that of HN-vs-HH. Therefore, these spikelet genes may play important roles in response to high temperature with high nitrogen and may be good candidates for crop improvement. Conclusions This RNA-seq study will help elucidate the molecular mechanisms of rice spikelet defense response to high temperature interacting with high nitrogen level. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2141-9) contains supplementary material, which is available to authorized users. Background Rice (Oryza sativa L.) is the staple food for more than half of the world's population, and a continuous increase in rice production is needed to meet the growing food demand resulted from population growth in the future [1]. In the recent hundred of years, rice is increasingly cultivated in more marginal environmental stresses because of global warming, and heat stress is a major abiotic limitation to plant growth and development [2]. The Intergovernmental Panel on Climate Change (IPCC) predicted that the vulnerability of the crop will be increased with a projected global average surface temperature increase by 0.74 ± 0.18°C [3]. In these environments, the uncontrollable temperature frequently exceed the critical temperature of seed set, resulting in spikelet sterility and reduced yield [4,5]. It was estimated that rice grain yields decline by 10 % for each 1°C increase in minimum temperature [6]. In addition to the temperature, the controllable nitrogen (N) is another factor affecting rice yield. In the past, increased rice production was largely attributed to the elevated application of nitrogen [7]. Moreover, grain yields were challenged by high temperature interacting with other abiotic stresses [8,9]. But few reports are demonstrated the effects of high temperature interacting with nitrogen on rice production at meiosis stage. High temperature beyond the critical threshold at reproductive stage leads to spikelet sterility. Morphological observations revealed that reduced spikelet fertility was mainly due to poor anther dehiscence, low pollen production and pollen viability, and reduced germination rate on the rice stigma under high temperature [4,5,10,11]. The recent studies about the molecular biology of spikelet fertility had shown that many differentially expressed genes (DEGs) played an essential role in heat response. It was reported that high temperature treatment (39°C) at the microspore stage reduced spikelet fertility, DNA microarray analysis revealed that at least 13 genes were designated as high temperature-repressed genes in the anther, and these genes expressed specifically in the immature anther were mainly in the tapetum at the microspore stage and down-regulated after 1 d of high temperature [11]. Zhang et al. [12] provided a gene expression profile of rice panicle grown under 40°C for different durations (0 min, 20 min, 60 min, 2 h, 4 h, and 8 h) during anther development by using a rice microarray, and found that the identified differentially expressed genes were mainly involved in transcriptional regulation, transport, cellular homeostasis, and stress response. Furthermore, the time-dependent gene expression pattern was discovered under heat stress, and the regulation model central to reactive oxygen species (ROS) combined with transcriptome and ROS quantification data in rice panicle indicated the great importance to maintain ROS balance and the existence of wide crosstalk in heat response in their study. It has been reported that 50.4 % of all genes in the rice genome (28,296/56,143) were expressed at 25°C, and a similar number of genes (50.2 %; 28,189/56,143) were expressed in rice grown under 30°C. Furthermore, the temperature markedly stimulated several super-families of transcription factors, including bZIP, MYB, and WRKY [13]. Thus far, little is known about the transcriptional mechanism of rice spikelet in response to heat at meiosis stage. Nitrogen is an essential components of various macromolecules, such as proteins, nucleic acids, many cofactors, and some plant hormones [14]. Nitrogen affects many aspects of plant function, from metabolism to resource allocation, growth, and development [15,16]. In order to meet the high nitrogen requirement of plant growth and crop production, a large quantity of nitrogen fertilizers are applied [14,17]. However, crop plants only use less than half of the applied nitrogen fertilizers [18], and the unused nitrogen (nitrogen pollution) is inevitably becoming a threat to global environment [19,20]. Furthermore, the more application of nitrogen fertilizers has markedly increased the cost in crop production, which greatly affects the income of the farmers. Thus, it is extremely valuable to develop strategies that crops are less dependent on the heavy application of nitrogen fertilizers to create a sustainable and efficient agricultural system while maintaining high yield. Efforts have been directed to understanding the molecular basis of plant responses to nitrogen, and many nitrogen-responsive genes were identified [21]. Ammonium (NH 4 + ) and nitrate (NO 3 − ) are two primary inorganic nitrogen sources available for plants. Nitrate and ammonium are absorbed by the plant via a variety of transporters that are divided into high-affinity transport systems (HATS) and lowaffinity transport systems (LATS) [15,16]. Nitrate is taken up by the low and high affinity nitrate transporter gene family members (NRT1 and NRT2), reduced to nitrite by nitrate reductase (NR), and to ammonium by nitrite reductase (NiR) [22]. It is well known that the members of AMT1 gene family encoded the HATS for ammonium [23]. Ammonium is incorporated into organic molecules, catalyzed primarily by glutamine synthetase (GS) and glutamate synthase (GOGAT) pathway [24]. At the molecular level, nitrogen limitation altered the expression levels of 629 genes with 340 of them up-regulated and 289 of them down-regulated in Arabidopsis, and numerous nitrogen-responsive genes encoded transcription factors, signal transduction components, and proteins required for hormone synthesis and response [25]. It was reported that 10,422 genes at an early stage of low nitrogen stress in rice seedling were identified [26]. Wang et al. [27] studied the response of seedlings grown on ammonium to the addition of low or high levels of nitrate, and identified 25 and 49 nitrogen-responsive genes to low or high nitrate induction, respectively. These studies have provided valuable insights into nitrogen response and its linkage to other biological pathways. However, knowledge about plant genes and pathways in response to nitrogen is still lacking, while such knowledge is essential for formulating strategies for manipulating the genetic architecture of the plants to improve the nitrogen use efficiency. The combination of nitrogen and temperature affects plant growth and development. Weng at al [28] examined the differences between photosynthetic activity and dark respiratory rate as influenced by leaf nitrogen levels and temperatures in rice, and found the photosynthetic rates and respiratory rate were correlated with the leaf nitrogen content. Liu et al. [29] evaluated mycorrhizal rice growth based on treatments at two temperatures (15°C and 25°C) and two nitrogen levels (20 mg pot −1 and 50 mg pot −1 ). The arbuscular mycorrhizal fungi (AMF) colonization of rice resulted in different responses of the plants to low and high nitrogen levels. Satake et al. [30] showed that high nitrogen level from the spikelet differentiation stage to the young microspore stage greatly increased the sensitivity to coolness at the critical stage in rice plants. Hayashi [31] showed that cool temperature (12°C) for 3 days decreased rice spikelet fertility by 36 % under standard-nitrogen and 42 % under high-nitrogen conditions. But there are no reports about the effects of the nitrogen interacting with high temperature on spikelet fertility in rice production. Recently, RNA sequencing technology, based on nextgeneration sequencing technology, provides a platform for measuring differences in gene expression [32]. Unlike microarrays, RNA-seq does not require prior knowledge of gene sequences. Furthermore, RNA-seq provides a far more precise measurement of transcripts and has been successfully used for transcript profiling in many plant species [33,34]. Seed setting rate, one of the most important components of rice grain yields, is significantly affected by high temperature during pollen mother cell meiosis. However, limited information about differentially expressed genes of rice spikelet in response to high temperature is available at meiosis stage. Moreover, no reports demonstrate that nitrogen level can regulate the effects of high temperature at meiosis stage on rice production. In this study, we used Illumina RNAseq technology to profile different gene expression of rice spikelet from a conventional strain Zhong531 treated by high temperature and high nitrogen level at meiosis stage. The overall objective of this study was to increase our understanding of the heat response in rice spikelet and provided good candidate genes for crop improvement. Plant material One rice (Oryza sativa L. ssp. indica) strain, Zhong531, was chosen for this study. The trials were conducted between March and August in 2014, in net house at High-Tech Agricultural Science and Technology Park of Jiangxi Agricultural University (latitude: 28°46′ N, longitude: 115°50′ E, altitude: 48.80 m), Nanchang, Jiangxi Province, China. Seed dormancy was broken by exposure to the sun for 3 d, followed by pre-germination and sown in a rice field. Thirty-day-old seedlings were then transplanted on 25 April at a spacing of 22.5 cm × 24.5 cm with only one seedling per hill. The physical and chemical properties of experimental soil were as follows: soil pH, organic matter, total nitrogen, available nitrogen, available phosphorous (P), and available potassium (K) were 5.94, 28.72 g kg −1 , 1.45 g kg −1 , 92.01 mg kg −1 , 28.31 mg kg −1 , and 221.67 mg kg −1 , respectively. The experimental received four treatments: 1) NN: normal nitrogen level (165 kg N ha −1 , as the control) with natural temperature (30°C, as the control); 2) HH: high nitrogen level (330 kg N ha −1 ) with high temperature (37°C); 3) NH: normal nitrogen level and high temperature; and 4) HN: high nitrogen level and natural temperature, respectively. The amount of nitrogen fertilizer in the form of urea for the normal nitrogen level was recommended by local agricultural extension employees based on experience and target yield. For normal nitrogen level, 66, 33, and 66 kg N ha −1 (as pure N) were applied at basal (2 d before transplanting), tillering (10 d after transplanting), and panicle initiation (30 d after transplanting), respectively. For high nitrogen level, 66, 66, and 198 kg N ha −1 were applied at basal, tillering, and panicle initiation, respectively [35]. Phosphorus (90 kg P ha −1 as P 2 O 5 ) was applied 2 d before transplanting. Potassium (180 kg K ha −1 as K 2 O) was applied in two equal splits at basal and panicle initiation. Weeds in the field were manually removed at early growth stages. Insecticides were used to prevent insect damage. All other agronomic practices referred to the local recommendations to avoid yield loss. High temperature treatment Four temperature-controlled growth cabinets were specifically designed to study the impacts of the high temperature (37°C) and natural temperature (30°C), respectively. Each cabinet (1.91 m × 0.76 m × 1.83 m in length, width and height, respectively) was fixed at a 5 m interval to ensure adequate ventilation. For high temperature analysis, rice plants along with soil at the female stamen primordium differentiation stage were randomly transplanted into plastic pots to adapt for 3 d and then transferred to growth cabinets. The pot with a hole at the bottom has internal diameter of 17 cm and height of 16 cm, and the rice plants transferred into pots grew normally and stably without withered and yellow leaves. Twelve rice plants with each in a pot for each treatment combination at the formation stage of pollen mother cell [11] were randomly exposed to high temperature (from 8:00 o'clock to 18 [5]. Two stand-alone sensors were placed in the rice canopy near the panicle base (few centimeters into the canopy) in each cabinet to measure temperature once 15-min interval, with all the sensors connected to data loggers (HOBO, U22-001, USA) [36,37]. The other controlled environmental conditions (white fluorescent illumination of 540 μmol m −2 s −1 day/ 0 μmol m −2 s −1 night, and relative humidity of 75 % day/ 80 % night) in each growth cabinet were consistent. The four treatments of combining temperature and nitrogen were in two repeats, each repeat with six plants (pots) per growth cabinet. No cabinet or replicate effects were observed, therefore, data collected from different replicates and cabinets for each treatment were pooled. According to the descriptions by Endo et al. [11], Tang et al. [38], and Chen et al. [39], we collected young florets in the same phases of the meiosis stage as samples for further analysis. Features used to distinguish this stage are as follows: a) rice was grown for about 2 months, 13 to19 days before flowering; b) the distance between the auricle of the flag leaf and that of the penultimate leaf was within 1 cm; c) the young panicle length was about 2 cm; d) the floret length was 2 to 3 mm. Young florets during the meiosis of pollen mother cell at the middle of main panicles after 4 d in the high temperature environments were collected, frozen in liquid nitrogen immediately, and stored at −80°C for further use. Each sample represented two replicates (each replicate had 3 plants). After high temperature, the pots were removed and the remaining 6 undamaged rice plants were returned to natural field conditions until seed maturity. The average temperatures in the cabinets were close to the required targets: high temperature (from 8:00 o'clock to 18 Spikelet fertility (seed-set) Spikelet fertility (seed-set) was estimated according to the procedures of Prasad et al. [4]. At physiological maturity stage, 16 randomly selected main tiller panicles (four each from separate plant) were tagged and harvested in each treatment. Spikelet fertility was estimated as the ratio of the number of filled grains to the total number of reproductive sites (florets) and expressed as percentage. Each floret was pressed between the forefinger and thumb to determine if the grain was filled or not. Number of filled grains included both completely and partially filled grains. Statistical analysis Differences among the means of spikelet fertility in the four treatments were analyzed using Student's t-test (SPSS statistical software ver. 17.0). The standard errors of the mean were also calculated and presented in the graphs as error bars. cDNA preparation for Illumina sequencing Total RNA was extracted using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. The total RNA samples from the four treatments were mixed and pooled (with equal amount of RNA from each treatment) as one sample for transcriptome sequencing (paired ends sequencing, 90 bp) to obtain as much gene expression information as possible, but they were subjected individually to conduct digital gene expression (DGE) sequencing. The total RNA samples were first treated with deoxyribonuclease I (DNase I) to degrade any possible DNA contamination. Then the mRNA was enriched by using the Oligo(dT) magnetic beads. Mixed with the fragmentation buffer, the mRNA was fragmented into short fragments (about 200 bp). Then the first strand of cDNA was synthesized by using random hexamer-primer. Buffer, dNTPs, RNase H and DNA polymerase I were added to synthesize the second strand. The double strand cDNA was purified with magnetic beads. End reparation and 3-end single nucleotide A (adenine) addition was then performed. Finally, sequencing adaptors were ligated to the fragments. The fragments were enriched by PCR amplification. During the quality control (QC) step, Agilent 2100 Bioanaylzer, and ABI StepOnePlus Real-Time PCR System were used to qualify and quantify of the sample library. The library products were ready for sequencing via Illumina HiSeq™ 2000 at the Beijing Genomics Institute (BGI, http://www.genomics.cn/index; Shenzhen, China) (Additional file 1: Figure S1). Image data output from sequencing machine were transformed by base calling into sequence data, called raw data or raw reads, and was stored in fastq format. Data filtering and de novo assembly Raw reads produced from sequencing machines contained dirty reads which contain adapters, unknown or low quality bases. These data would negatively affect following bioinformatics analysis. After removal of adaptor sequences along with low quality reads (the rate of reads which quality value < = 10 is more than 20 %), and reads of larger than 5 % unknown sequences (reads with unknown sequences 'N'), the resting clean reads were assembled into unigenes by Trinity [40], a short-read assembly program. Transcriptome de novo assembly was carried out with a short reads assembling program-Trinity. Trinity combined three independent software modules: Inchworm, Chrysalis, and Butterfly, was applied sequentially to process large volumes of RNA-seq reads. The Trinity software first combined reads with a certain length of overlap to form longer fragments without N, forming contigs. Then the reads were mapped back to contigs, with paired-end reads it was able to detect contigs from the same transcript as well as the distances between these contigs. Then, Trinity connected these contigs to get consensus sequences that contained the least N and could not be extended on either end. Such sequences were defined as unigenes. When multiple samples from the same species were sequenced, unigenes from each sample's assembly can be taken into further process of sequence splicing and redundancy removing with sequence clustering software to acquire nonredundant unigenes as long as possible. Then gene family clustering was done. The unigenes would be divided to two classes. One was clusters, which the prefix was CL and the cluster ID was behind. In the same cluster, there were several unigenes with the similarity between them was more than 70 %. And the other was singletons, which the prefix was unigene. In the final step, blastx alignment (evalue < 0.00001) between unigenes and protein databases like NR (NCBI non-redundant protein sequences), Swiss-Prot (A manually annotated and reviewed protein sequence database), KEGG (Kyoto Encyclopedia of Genes and Genomes) and COG (Cluster of Orthologous Groups of proteins) was performed, and the best aligning results were used to decide sequence direction of unigenes. If results of different databases conflicted with each other, a priority order of NR, Swiss-Prot, KEGG and COG should be followed when deciding sequence direction of unigenes. When a unigene happened to be unaligned to any of the above four databases, the software named ESTScan [41] would be introduced to decide its sequence direction. For unigenes with sequence directions, we provided their sequences from 5' end to 3' end; for those without any direction we provided their sequences from the assembly software (Additional file 2: Figure S2). Statistics of digital gene expression (DGE) sequencing After DGE sequencing, clean reads were mapped to reference genes (de novo assembly) and/or reference genome (Indica rice database) using SOAPaligner/ SOAP2 [42]. No more than 2 mismatches were allowed in the alignment. The distribution of reads on the reference genes was used to evaluate the randomness [34]. Genes with similar expression patterns usually indicated functional correlation. We performed a cluster analysis of gene expression patterns with cluster software [43] and Java Treeview software [44]. Further evaluation included quality assessment of reads, and sequencing saturation analysis, gene sequencing coverage, correlation analysis of all genes between every two samples replicates. Functional unigene annotation and COG classification Unigene annotation provides information of expression and functional annotation of a unigene. Information of functional annotation gives protein functional annotation, COG functional annotation and Gene Ontology (GO) functional annotation of unigenes. Unigene sequences were firstly aligned to protein databases like NR, Swiss-Prot, KEGG and COG (e-value < 0.00001) by BLASTX, and NCBI nucleotide sequences database (NT) (e-value < 0.00001) by BLASTN, retrieving proteins with the highest sequence similarity with the given unigenes along with their protein functional annotations (Additional file 3: Figure S3). We can get GO functional annotation with NR annotation. GO is an international standardized gene functional classification system which offers a dynamic-updated controlled vocabulary and a strictly defined concept to comprehensively describe properties of genes and their products in any organism. GO has three ontologies: molecular function, cellular component and biological process. The basic unit of GO is GO-term. Every GOterm belongs to a type of ontology. With NR annotation, we used Blast2GO [45] program to get GO annotation of unigenes. Blast2GO has been cited by other articles for more than 150 times and is widely recognized a GO annotation software. After getting GO annotation for every unigene, we used WEGO [46] software to do GO functional classification for all unigenes and to understand the distribution of gene functions of the species from the macro level. GO enrichment analysis provides all GO terms that significantly enriched in DEGs comparing to the genome background, and filter the DEGs that correspond to biological functions. This method firstly mapped all DEGs to GO terms in the database (http://www.ge neontology.org/), calculating gene numbers for every term, then using hypergeometric test to find significantly enriched GO terms in DEGs comparing to the genome background. The calculating formula is: Where N is the number of all genes with GO annotation; n is the number of DEGs in N; M is the number of all genes that are annotated to the certain GO terms; m is the number of DEGs in M. The calculated P-value goes through Bonferroni Correction, taking corrected P-value < = 0.05 as a threshold. GO terms fulfilling this condition are defined as significantly enriched GO terms in DEGs. KEGG (Kyoto Encyclopedia of Genes and Genomes) is the major public pathway-related database [47,48]. Pathway enrichment analysis identifies significantly enriched metabolic pathways or signal transduction pathways in DEGs comparing with the whole genome background. The calculating formula was the same as that in GO analysis. COG (Cluster of Orthologous Groups of proteins) is a database which classifies orthologous gene product, each COG protein is presumed coming from ancestral protein, the construction of COG database is based on the complete genome encoding protein and phylogenetic relationships of bacteria, algae, eucaryon. We mapped the unigene to the COG database, predicted the possible functions and statistics, understand gene function distribution characteristics of the species from the macro [49]. Screening of differentially expressed genes (DEGs) The expression level of unigene was calculated by using RPKM method [50] (Reads Per kb per Million reads), and the formula is shown as follows: Here RPKM (A) is the expression level of gene A, C is number of reads that uniquely aligned to gene A, N is total number of reads that uniquely aligned to all genes, and L is number of bases of gene A. The RPKM method is able to eliminate the influence of different gene length and sequencing discrepancy on the calculation of gene expression level. Therefore, the RPKM values can be directly used for comparing the difference of gene expression among samples. DEGs analysis included the screening of genes that were differentially expressed among samples, and GO functional enrichment analysis and KEGG pathway enrichment analysis for these DEGs. Referring to the method of Audic and Claverie [51], we had developed a strict algorithm to identify DEGs between two samples. P-value corresponded to differential gene expression test. FDR (False Discovery Rate) is a method to determine the threshold of P-value in multiple tests. Assume that we had picked out R differentially expressed genes in which S genes really showed differential expression and the other V genes were false positive. If we decided that the error ratio Q = V / R must stay below a cutoff (<1 %), we should preset the FDR to a number no larger than 0.01 [52]. We used FDR ≤0.001 and the absolute value of log 2 (Ratio) ≥1 as the threshold to judge the significance of gene expression difference. More stringent criteria with smaller FDR and bigger fold-change value can be used to identify DEGs (Additional file 4: Figure S4). Results Illumina paired-end sequencing and de novo assembly of transcriptome Illumina paired-end sequencing generated a total of 61,733,120 raw reads (Table 1). After filtration, 52,553,536 clean reads with accumulated length of 4,729,818,240 bp were remained for further analysis. The Q20 percentage was 96.13 %, and the GC percentage was 54.24 %. These clean reads were assembled into 101,597 contigs with a mean length of 378 bp. The N50 of contigs was 708 bp. These contigs were further assembled by paired-end joining and gap-filling, and clustered into unigenes. Finally, we obtained 72,667 unigenes, with a mean length of 537 bp. The N50 of unigenes was 747 bp. The size distribution indicated that the lengths of the 148 unigenes were more than 3,000 nt (Fig. 1). The contig and unigene size distributions were consistent, which indicated that the Illumina sequencing solution was reproducible and reliable. Functional annotation and classification of unigenes All of the unigenes were compared to the sequences in public databases, including NR, the Nucleic acid data bank (NT), Swiss-Prot, KEGG, COG, and GO database, using BLASTX with a cutoff e-value of 10 −5 ( In order to annotate the transcriptome, a total of 72,667 unigenes were first examined against the NR database in NCBI using BLASTX with an E-value cutoff of 1e −5 , which showed 58,879 (81.03 %) having significant BLAST hits ( Table 2). The E-value distribution of significant hits revealed that 25,886 (43.97 %) of matched unigenes had strong homology (smaller than 1.0e-60), while the other homologous 32,993 (56.03 %) unigenes had E-values in the range of 1.0e-60 to 1.0e-5 (Additional file 5: Figure S5 (A)). The distribution of unigenes similarities presented that most of the BLASTX hits (48,515; 82.40 %) were higher than 95 %. Only 10,364 (17.60 %) of hits had sequence similarity values less than 95 % (Additional file 5: Figure S5 (B)). Figure S5 (C)). The assembled unigenes were compared against the COG database to phylogenetically analyze widespread domain families. The results revealed 18,255 unigenes and 54,811 sequences with significant homology and assigned them to the appropriate COG clusters. These COG classifications were grouped into 25 functional categories (Fig. 2). Among these COG categories, the cluster "general function prediction only" (6,408; 11.69 %) represented the largest group, followed by "function unknown" (5,451; 9.59 %); "transcription" (4,848; 8.84 %); "translation, ribosomal structure and biogenesis" (4,243; 7.74 %); "cell wall/membrane/envelope biogenesis" (4,225; 7.71 %); "replication, recombination, and repair" (4,165; 7.60 %); "posttranslational modification, protein turnover, chaperones" (3,711; 6.77 %); "cell cycle GO assignments were used to classify the functions of the predicted unigenes. Based on sequence homology, 43,180 unigenes and 299,435 sequences could be categorized into three main categories with a total of 57 functional groups (Fig. 3). In each of the three main categories (biological process, cellular component, and molecular function) of the GO classification, "metabolic process", "cell", and "binding" were dominant. We also noticed a high-percentage of genes in the categories of "cellular process", "cell part", and "catalytic activity". Digital gene expression library sequencing (DGE sequencing) Four DGE profiling libraries (NH, NN, HH, HN) were sequenced, which were tested by Agilent 2100 for quality control (Additional file 6: Table S1), and generated approximately 11 to 13 million high-quality reads for each library ( Table 4). All samples had a RNA integrity number To reveal the molecular events behind DGE profiles, we mapped the sequences of the DGE libraries to our transcriptome reference database generated in the above mentioned Illumina sequencing. The summary of reads mapped to reference genes (de novo assembly of transcriptome) ( Table 4) was similar to the summary of reads mapped to reference genome (Indica rice database) (Additional file 7: Table S2). The percentage of clean reads among the raw reads in each library was above 99 % (Additional file 8: Figure S6). Among the clean reads, the number of sequences that could be mapped to unigenes ranged from 10 to 11 million, and the percentage of clean reads was beyond 84 % in the four DGE libraries. The vast majority of these mapped reads were uniquely matched to unigenes (>71 %), and the percentage of multi-position matched reads was less than 14 % ( Table 4). Assessment of DGE sequencing Sequence saturation analysis is used to measure the sequencing data of a sample. With the number of reads increasing, the number of detected genes is increasing. However, when the number of reads reaches a certain amount, the growth curve of detected genes flattens, which indicates that the number of detected genes has a tendency to saturation. As the Additional file 9: Figure S7 shows, when the sequencing amount of the four DGE libraries reached nearly 10 M, the number of detected genes almost ceased to increase. During the RNA-Seq experiment, mRNA were first broken into short segments by chemical method and then sequenced. If the randomness is poor, reads preference to specific gene region will directly affect subsequent bioinformatics analysis. We used the distribution of reads on the reference genes to evaluate the randomness. Since reference genes have different lengths, the reads position on gene is standardized to a relative position (which is calculated as the ratio between reads location position on the gene and gene length), and then the number of reads in each position is counted. Additional file 10: Figure S8 was the result showing the distribution of reads on the reference genes of all four samples, which indicated that the randomness was good, and the reads in every position were evenly distributed. Gene coverage is the percentage of a gene covered by reads. This value is determined as the ratio of the base number in a gene covered by unique mapping reads to the total bases number of that gene. The percentage of gene coverage above 90 % for all samples was about 40 % (Additional file 11: Figure S9). The expression level of each gene is determined by the numbers of reads uniquely mapped to the specific gene and the total number of uniquely mapped reads in the sample (RPKM). The summary results of gene expression and related information for all examples were given in Additional file 12: Table S3. Good performance of screening group differentially expression genes needs a high correlation among the same replicates. So we used Pearson method to get coefficient of all genes between every two samples just for reference. The coefficient of all genes between every two samples was about 90 %, which indicated the performance of two replicates was excellent (Additional file 13: Figure S10). Differentially expressed genes (DEGs) among all samples The differentially expressed genes (DEGs) were identified in different samples. The following significant DEGs were identified: (a) between samples ZHN and ZHH, 1,072 and 1,637 genes were up-and downregulated, respectively; (b) between samples ZNH and ZHH, 424 and 698 genes were up-and down-regulated, respectively; (c) between samples ZNH and ZHN, 4,638 and 2,824 genes were up-and down-regulated, respectively; (d) between samples ZNN and ZHH, 188 and 813 genes were up-and down-regulated, respectively; (e) between samples ZNN and ZHN, 1,581 and 1,839 genes were up-and down-regulated, respectively; (f ) between samples ZNN and ZNH, 389 and 906 genes were upand down-regulated, respectively (Fig. 4, Additional file 14: Table S4). In these DEGs, we found 151 and 323 DEGs temperature-responsive between ZNN and ZNH, and between ZHN and ZHH, respectively (Additional file 15: Table S5). These genes were principally associated with calcium-dependent protein kinase, cytochrome P450, flavonoid, heat shock protein, peroxidase, ubiquitin, photosynthesis, chlorophyll biosynthetic process, zinc transporter, transcription factor, sporopollenin biosynthetic process, and pollen exine formation and so on (Additional file 15: Table S5). Meanwhile, 203 and 144 DEGs in response to nitrogen were focused between ZNN and ZHN, and between ZNH Note: NH, Normal nitrogen level and high temperature treatment; NN, Normal nitrogen level and natural temperature treatment; HH, High nitrogen level and high temperature treatment; HN, High nitrogen level and natural temperature treatment. "Z" represents Zhong 531, 4 treatment combinations and 2 pooling duplicates. The same as follows and ZHH, respectively (Additional file 15: Table S5). These genes were principally related to glutamine synthetase, transcription factor, anthocyanin, amino acid transporter, leucine zipper protein, and hormone and so on (Additional file 15: Table S5). In order to further illuminate the effects of temperature and nitrogen, we compare the DEGs in different samples. A total of 532 DEGs occurred simultaneously in the two comparisons (ZNN-vs-ZNH and ZHN-vs-ZHH), and 671 DEGs were co-expressed in ZNN-vs-ZNH and ZHN-vs-ZHH, respectively (Additional file 16: Table S6). A total of 114 and 111 DEGs associated with temperature and nitrogen were screened out (Additional file 17: Table S7), and the expression pattern analysis of DEGs under the same nitrogen level and the same conditions of temperature was clustered in Fig. 5, respectively. To understand the functions of these differentially expressed genes, all the DEGs were mapped to terms in the GO database and compared to the whole transcriptome background. The DEGs had a GO ID and can be categorized into small functional groups in three main categories (biological process, cellular component, and molecular function) of the GO classification (Additional file 18: Table S8, Additional file 19: Figure S11). Based on sequence homology, the following significant DEGs annotated by the GO database were identified: (a) in ZNN-vs-ZNH and ZHN-vs-ZHH, 50 and 51 functional groups were categorized, respectively; (b) in ZNN-vs-ZHN and ZNHvs-ZHH, 55 and 44 functional groups were categorized, respectively. Among these groups, "metabolic process" and "cellular process" were dominant within the "biological process" category, the "cell" and "cell part" categories were dominant in the "cellular component" category, and "catalytic activity" and "binding" were dominant in the "molecular function" category (Additional file 19: Figure S11). To further investigate the biochemical pathways of these DEGs, we mapped all of the DEGs to terms in KEGG database and compared this with the whole transcriptome background. The DEGs had a KO ID and could be categorized into small pathways (Additional file 20: Table S9). For ZNN-vs-ZNH and ZHN-vs-ZHH, of the 1,295 and 2,709 DEGs, 716 and 1,410 unigenes had a KO ID and could be categorized into 95 and 109 pathways, respectively. Of those, 26 pathways were significantly enriched (Q value < 0.05), and genes involved in metabolic pathways were the most significantly enriched (Additional file 20: Table S9). For ZNN-vs-ZHN and ZNH-vs-ZHH, of the 3,420 and 1,122 DEGs, 1,902 and 584 unigenes had a KO ID and could be categorized into 116 and 93 pathways, respectively. Of those, 35 and 20 pathways were significantly enriched (Q value < 0.05), and genes involved in metabolic pathways were the most significantly enriched, respectively (Additional file 20: Table S9). The top 20 KEGG pathways of DEGs in these four comparisons mentioned above are showed in Fig. 6. Effects of nitrogen level and high temperature at late spikelet differentiation stage (meiosis) on spikelets fertility of rice To test the effects of high nitrogen level and high temperature, we investigated the spikelet fertility in the four combinations (Fig. 7). High temperature at meiosis stage significantly decreased spikelet fertility of Zhong531 compared with natural temperature at high nitrogen level or normal nitrogen level (p < 0.01). Under high temperature or natural temperature, spikelet fertility decreased at high nitrogen level compared with normal nitrogen level, and the difference under high temperature was significantly (p < 0.05). These results imply that excessive high nitrogen level contributed to increase the effects of high temperature on spikelet fertility. Discussion In recent years, RNA-seq has been used as a powerful and cost-efficient tool for mining gene resources and functions. In this study, we performed de novo assembly of transcriptome in rice spikelet using the platform of Illumina Hiseq 2000, and obtained a total 4.73 Gb of transcriptome data. In the results of assembly, 72,667 unigenes were detected, with the total length 39,029,083 nt, average length 537 nt, and N50 747 nt. For functional annotation analysis, unigenes were annotated with the databases of NR (58,879), NT (72,255), Swiss-Prot (34,661), KEGG (31,242), COG (18,255), and GO (43,180) by using BLASTX with a cutoff e-value of 10 −5 , respectively, and the total annotated unigenes were 72,436. We obtained over 10 million clean reads from the samples of four digital gene expression profiling libraries (NH, NN, HH, HN), respectively. A lot of up-regulated and down-regulated genes were differentially expressed among the four libraries. The DEGs data provided comprehensive information of the gene expression in rice spikelet, facilitating our understanding of the molecular mechanisms of the different physiological aspects of rice spikelet in response to temperature interacting with nitrogen at meiosis stage. Rice growth is challenged by fluctuations in environmental factors specially temperature on almost daily basis. To minimize high temperature damage, rice has developed adaptations and heat tolerance during evolution through the regulation of gene expression and changes in cellular processes. It's well known that heat shock proteins (HSPs) are responsive to heat stress in plants [53][54][55]. In plants, HSPs are encoded by nuclear multigene families and localized in different cellular compartments. HSPs generally function as molecular chaperones, and are divided into HSP100, HSP90, HSP70, HSP60, HSP40 and HSP20 or small heat shock proteins (sHSPs) [56,57]. When plants are exposed to elevated temperature, the protective HSPs have increased levels of protein and gene expression [58][59][60][61]. AtHSP70-15-deficient plants under heat stress resulted in drastically increase in mortality, indicating that AtHSP70-15 played an essential role during normal growth and in the heat response of Arabidopsis [62]. A heat-tolerant rice N22 with 71 % spikelet fertility had a cold (putative) and a heat (unknown) shock protein significantly up-regulated under 38°C during anthesis, indicating that the shock proteins may have a greater contribution to the heat tolerance for N22 [5]. Our results revealed that HSP90, HSP70 and HSP20 in these differentially expressed genes (DEGs) were positively responsive to high temperature (Additional file 15: Table S5). Thus, the Hsps genes play an important part in response to heat stress in rice spikelet. Moreover, there were 19 and 26 DEGs annotated as HSPs in between ZNN-vs-ZNH and ZHN-vs-ZHH (Additional file 15: Table S5), respectively, and 18 HSPs occurred simultaneously in the two comparisons (Additional file 17: Table S7). In these DEGs, the gene expression of CL3468.Con-tig1, Unigene9201, Unigene5315, Unigene5314, and Uni-gene25510 in ZNN-vs-ZNH was extremely significant with log 2 Ratio ≥ 4.0, and CL3468.Contig1, Unigene5315, Unigene5314 in ZHN-vs-ZHH was extremely significant with log 2 Ratio ≥ 5.0. Manwhile, the log 2 Ratio value of Uni-gene9201, Unigene47969, Unigene24821, Unigene24300, Unigene41142, Unigene41141, Unigene41143, and Uni-gene25395 of ZHN-vs-ZHH was greater compared to ZNN-vs-ZNH, and the gene expression of other 7 HSP Fig. 5 Hierarchical clustering of differentially expressed genes. Each column represents an experimental condition, each row represents a gene. For differentially expression genes, its log 2 (RPKM) will be clustered, and red means up regulation and green means down regulation, and the color is more close to red or green, the more highly this gene expresses genes was on the contrary. These results may explain the gene expression difference of rice spikelet in response to high temperature under two different nitrogen levels. The cytochrome P450, ubiquitin protein, flavonoid, and transcription factor genes have been extensively studied in plants in response to heat stresses [12,63,64]. Most of the heat-responsive (P450 family) genes were repressed to some extent, and only 10 P450 family genes were upregulated under 40°C at the stage 8 of anther development [12]. High temperature reduced spikelet fertility of rice, DNA microarray analysis revealed that cytochrome P450 family genes were designated as high temperaturerepressed genes in the anther at the microspore stage [11]. In this study, we found that 17 cytochrome P450 genes were all down-regulated in ZNN-vs-ZNH, but 14 and 8 cytochrome P450 genes were up-regulated and downregulated in ZHN-vs-ZHH, respectively (Additional file 15: Table S5). Furthermore, 6 co-expressed cytochrome P450 genes (Unigene7325, Unigene42477, Unigene42476, Uni-gene45111, CL2270.Contig1, and Unigene42480) showed Fig. 6 Scatter plot of KEGG pathway enrichment statistics. RichFactor is the ratio of differentially expressed gene numbers annotated in this pathway term to all gene numbers annotated in this pathway term. Greater RichFactor means greater intensiveness. Q-value is corrected P-value ranging from 0~1, and its less value means greater intensiveness. We just display the top 20 pathway terms enriched by KEGG database different expression in two comparisons with all genes down-regulated in ZNN-vs-ZNH and 3 genes up-regulated in ZHN-vs-ZHH (Additional file 17: Table S7). Besides, the genes belonging to ubiquitin protein, flavonoid, peroxidase, and transcription factor also showed expression differences between ZNN-vs-ZNH and ZHN-vs-ZHH. Nitrogen is one of the major macronutrients for higher plants and can be served as a signal molecule to regulate plant development, physiology, and metabolism [14,65]. Peng et al. [25] found that nitrogen limitation altered the expression levels of 629 genes with 340 of them upregulated and 289 of them down-regulated in Arabidopsis. The up-regulated group included the genes involved in protein degradation and the biosynthesis of anthocyanin, while the down-regulated group contained the genes functioning in photosynthesis and the synthesis of nitrogenous macromolecules such as chlorophyll, proteins, amino acids and nucleotides. Plant hormone play many biological roles in plants. Hirano et al. [66] analyzed the global expression profiles of genes related to phytohormones in microspore/pollen (MS/POL) development. The genes required for IAA and gibberellin (GA) synthesis were coordinately expressed during the later MS/POL developmental stage. In contrast, genes for GA signaling were preferentially expressed during the early stage. Phenotypic analysis revealed that the GA-deficient mutant reduced pollen elongation was defective in pollen tube elongation, resulting in a low spikelet fertilization frequency, whereas the GA-insensitive semidominant mutant was mainly defective in viable pollen production. Furthermore, the GA biosynthesis genes were preferentially expressed after meiosis during pollen development [67]. It was reported that reduction of gibberellin by low temperature (approximately 19°C) disrupted pollen development and caused severe reduction of seed setting in rice [68]. It was reported that nitrogen responsive genes encoded transcription factors, signal transduction process, and proteins required for plant hormone synthesis and response [69][70][71]. In this study, we found 203 and 144 nitrogen-responsive DEGs in ZNN-vs-ZHN and ZNH-vs-ZHH, respectively (Additional file 15: Table S5). Numerous nitrogen responsive genes encoded plant hormone synthesis and response such as abscisic acid, auxin, gibberellin, cytokinin, and ethylene. Furthermore, a total of 111 DEGs associated with nitrogen co-expressed (Additional file 17: Table S7). WRKY genes encode transcription factors with a WRKY domain that belongs to zinc-finger proteins, which play important roles in responses to abiotic stress in rice [72,73]. In these co-expressed DEGs, 8 WRKY transcription factor genes were all down-regulated, and the log 2 Ratio value of Unigene20481, CL4288.Contig1, CL554.Contig1, CL4639.Contig1, CL1348.Contig1, and Unigene16792 of ZNN-vs-ZHN was greater than that of ZNH-vs-ZHH. High temperature cause comprehensive alterations in transcription, but application of auxin can block the transcriptional alterations, leading to the production of normal pollen grains, and the normal seed setting rate under increasing temperatures [74]. We found that 9 auxin-regulated genes with 4 down-regulated and 5 up-regulated DEGs were co-expressed. Our results revealed the gene expression difference of rice spikelet in response to nitrogen. High temperature during flowering (anthesis and fertilization) greatly reduces spikelet fertility in rice [5]. Pollen viability in rice plants exposed to (39°C) was lower than that in control plants, and the pollen grains were very poorly attached and displayed limited germination on the stigma under high temperature, leading to reduced spikelet fertility. Spikelet fertility is closely related to pollen exine formation, pollen tube growth, pollen germination, and pollen development in plants. An ABC transporter gene (OsABCG15) was identified to be involved in pollen development in rice. Wu et al. [75] showed that OsABCG15 played an essential role in the formation of the rice anther cuticle and pollen exine. Ling et al. [76] identified 291 mature anther-preferentially expressed genes (OsSTA) in rice, and OsSTA genes were associated with pollen fertility, pollen germination and anther dehiscence in rice. The pollen semi-sterility1 (PSS1) encoded a kinesin-1-like protein to regulate anther dehiscence in rice [77]. It was pointed out that a RING-type E3 ubiquitin ligase, POLLEN TUBE BLOCKED 1 (PTB1), positively regulated the rice panicle seed setting rate by promoting pollen tube growth [78]. OsAP65, a rice aspartic protease, was essential for male fertility and played a important role in pollen germination and pollen tube growth [79]. Chueasiri et al. [80] quantified gene expression in anthers of temperature-sensitive rice plants grown in controlled growth rooms (26°C and 32°C) for fertile and sterile conditions, the results indicated that plant orosomucoids-like proteins influenced sphingolipid homeostasis, and deletion of this gene affected spikelet fertility resulting from abnormal pollen development. The transcription factor bHLH142 was identified as a pivotal role in tapetal programmed cell death and pollen development during early meiosis in rice [81]. In our study, the expression profile revealed that 15 spikelet genes annotated to GO database including 3 pollen development, 9 pollen exine formation, 1 pollen germination, 1 pollen tube development, and 1 sporopollenin biosynthetic process (pollen exine formation) were all down-regulated in ZNN-vs-ZNH (Additional file 15: Table S5). Many genes including 4 microsporogenesis, 11 flower development, 13 pollen development, 3 pollen tube growth, 12 pollen germination, 12 pollen exine formation, 9 pollen wall assembly, and 14 sporopollenin biosynthetic process from GO annotation were identified as spikelet genes in response to high temperature interacting with high nitrogen level in ZHNvs-ZHH (Additional file 15: Table S5). Moreover, we found that 8 pollen exine formation, and 8 sporopollenin biosynthetic process DEGs with all genes down-regulated were co-expressed. Interestingly, in these co-expressed DEGs, the log 2 Ratio absolute value of spikelet genes including 1 pollen development gene (CL3271.Contig1), 7 pollen exine formation genes (Unigene45103, Unigene32014, Uni-gene32018, Unigene32017, Unigene42236, Unigene42231, Unigene42234), and 5 sporopollenin biosynthetic process genes (Unigene43852, Unigene32623, Unigene23940, Uni-gene23939, Unigene23941) of ZNN-vs-ZNH was lower than that of ZHN-vs-ZHH (Additional file 17: Table S7). The co-expressed DEGs especially pollen exine formation and sporopollenin biosynthetic process genes may suggest they play important roles in rice spikelet in response to high temperature at high nitrogen level. Accordingly, high temperature at meiosis stage significantly decreased spikelet fertility, and spikelet fertility decreased more significantly under high temperature interacting with high nitrogen level (Fig. 7). Therefore, these genes may be good candidates for crop improvement. In addition, we found 151 DEGs with 40 up-regulated and 111 down-regulated genes, and 323 DEGs with 150 up-regulated and 173 down-regulated genes in response to high temperature were identified in ZNN-vs-ZNH and ZHN-vs-ZHH, respectively (Additional file 15: Table S5), which indicating more DEGs were related to high temperature at high nitrogen level. Conclusions In summary, we performed a combination of RNA-seq and digital gene expression sequencing to identify the genes involved in rice spikelet treated by different temperatures and nitrogen levels. This study produced abundant data for research on the molecular mechanisms of the rice spikelet. We highlight the link between the pollen exine formation, sporopollenin biosynthetic process genes and the decreased spikelet fertility. To the best of our knowledge, the present study is the first to attempt to perform a de novo assembly of transcriptome sequencing of the temperature and nitrogen's interactive effects in rice spikelet, which may extend our understanding of the complex molecular and cellular events in spikelet and facilitate identification of temperature and nitrogen's interactive effects on plants.

v3-fos

2016-05-04T20:20:58.661Z

2015-09-08T00:00:00.000Z

3941086

s2

Assessing developmental toxicity of caffeine and sweeteners in medaka (Oryzias latipes) The use of artificial sweeteners (ASWs) has increased and become more widespread, and consequently ASWs have appeared in aquatic environments around the world. However, their safety to the health of humans and wildlife remains inconclusive. In this study, using medaka embryos (Oryzias latipes), we investigated developmental toxicity of aspartame (ASP) and saccharin (SAC). Since ASWs are often consumed with caffeine (CAF) and CAF with sucrose (SUC), we tested biological activities of these four substances and the mixtures of CAF with each sweetener. The embryos were exposed to ASP at 0.2 and 1.0 mM, SAC at 0.005 and 0.050 mM, CAF at 0.05 and 0.5 mM, or SUC at 29 and 146 mM, starting from less than 5 h post fertilization until hatch. Control embryos were treated with embryo solution only. Several endpoints were used to evaluate embryonic development. Some of the hatchlings were also tested for anxiety-like behavior with the white preference test. The results showed that all four substances and the mixtures of CAF with the sweeteners affected development. The most sensitive endpoints were the heart rate, eye density, and hatchling body length. The hatchlings of several treatment groups also exhibited anxiety-like behavior. We then used the Integrated Biological Response (IBR) as an index to evaluate the overall developmental toxicity of the substances. We found that the ranking of developmental toxicity was SAC > CAF > ASP > SUC, and there was a cumulative effect when CAF was combined with the sweeteners. Electronic supplementary material The online version of this article (doi:10.1186/s40064-015-1284-0) contains supplementary material, which is available to authorized users. Background Artificial sweeteners (ASWs) have been in use for decades, but they are now increasingly added to all kinds of foods, drinks, and pharmaceutical products. As a consequence, ASWs are excreted from our bodies and discharged with sewage treatment effluents to the aquatic environment. Therefore, they have emerged as a class of environmental contaminants. For example, saccharin (SAC) is largely unmetabolized in human body, allowing it to pass unchanged to the environment, mainly through the urine. It is usually degraded by more than 90 % during wastewater treatment (Lange et al. 2012). However, wastewater is not always properly treated, and SAC concentrations may be too high to be efficiently removed. In a Canadian river watershed, SAC at a concentration of 7.2 µg/L was found where both urban population and the consumption of caloriereduced beverages were high (Spoelstra et al. 2013). Concentrations of SAC up to 19.7 µg/L were also found from surface waters in Spain (Ordóñez et al. 2012), and up to 137 µg/L from wastewater in Singapore (Tran et al. 2013). On the other hand, aspartame (ASP) is metabolized to 50 % phenylalanine, 40 % aspartic acid, and 10 % methanol in humans (Ranney et al. 1975). The small amount of methanol has been suggested to be responsible for ASP carcinogenicity (Soffritti et al. 2010). Because these components are absorbed and metabolized as other foods, ASP is usually not detected in environmental water samples (Lange et al. 2012;Ordóñez et al. 2012). Nonetheless, Gan et al. (2013) have reported its presence in surface waters at concentrations up to 0.21 µg/L in China. Unlike other contaminants, ASWs are substances we actively purchase and ingest regularly, sometimes in large quantities. Although many studies have supported the safety and benefits of ASWs (Weihrauch and Diehl 2004;Marinovich et al. 2013), clear evidence of safety in long-term use is still lacking (Wiebe et al. 2011;Shankar et al. 2013;Gardner 2014). In addition, their developmental toxicity is surprisingly inconclusive. For example, prospective studies on pregnant women have found an association of daily intake of ASWs-containing beverages with preterm delivery (Halldorsson et al. 2010;Englund-Ögge et al. 2012) or offspring allergic diseases (Maslova et al. 2013), but Marinovich et al. (2013) have also concluded in their review study that ASWs were not related to preterm delivery. Animal studies on developmental toxicity of ASWs are mostly conducted on rats and mice; studies on fish or aquatic organisms are scarce. Saccharin is usually considered safe and often used as a negative control in toxicological studies, such as the study conducted by Selderslaghs et al. (2009). But the authors actually found that saccharin at 55 mM induced 92 % mortality within 24 h post fertilization in zebrafish embryos. As to ASP, Soffritti et al. (2007) have conducted a study with rats using a dose (100 mg/kg bw/day) higher than the acceptable daily intake value for humans (40 mg/kg bw in the European Union and 50 mg/kg bw in the United States). They found that lifespan exposure to the sweetener is carcinogenic, and exposures beginning from prenatal period further increased the risk. Abd Elfatah et al. (2012) also found that a high dose of ASP at 50 mg daily induced histological lesions and genetic alterations in mother rats and their offspring. But an earlier study found no developmental effect from ASP at much higher doses of 500-4000 mg/kg bw (McAnulty et al. 1989). Due to the need for more information regarding developmental toxicity and ecological impact of ASWs, we used medaka embryos (Oryzias latipes) as a bioassay to tackle both issues at the same time. The fish is an oviparous freshwater teleost. It has become a popular animal model in recent years due to its hardiness, small size (adult 2-4 cm in length), high fecundity (spawn 10-20 eggs daily), and short generational time (2-3 months). Most of all, as medaka embryos are transparent, their development can be easily observed in whole living embryos. These qualities have rendered the fish ideal for developmental toxicity studies. Here, using medaka embryos, we investigated developmental toxicity of two ASWs, ASP and SAC, along with the natural sweetener sucrose (SUC) and the known developmental toxin-caffeine (CAF). As CAF was often ingested with sweeteners, the combinations of CAF with SUC, ASP, or SAC were tested as well. The concentrations used in this study were much lower than those of the above-mentioned studies because they were intended to be more realistic and environmentally relevant. We also used the white preference test (Lee and Yang 2014) to investigate behavioral consequences of this developmental toxicity. Furthermore, a novel approachthe integrated biomarker response (IBR; Beliaeff and Burgeot 2002; was applied to evaluate the overall developmental toxicity of the tested substances. Experimental animals A colony of medaka had been established in the current facility for over 5 years. They were maintained at 28 °C under a constant 14 h light:10 h dark photoperiod in glass tanks filled with flow-through filtered water (pH 7.5-7.8). Medaka embryos were incubated in embryo solution (0.1 % NaCl, 0.003 % KCl, 0.004 % CaCl 2 ·2H 2 O, and 0.016 % MgSO 4 ·7H 2 O, pH 7.5-7.8). All salts in the solution were supplied by J.T.Baker (Phillipsburg, NJ, USA). The fish were fed three times daily with brine shrimp (<24 h after hatching). All procedures were carried out in accordance to the "Guidelines for Animal Experimentation" of Chang Jung Christian University, Taiwan. Chemicals and test solutions Sucrose (PA34230, purity > 99 %) was purchased from Panreac (Barcelona, Spain); ASP (228650050, purity > 98 %), SAC (149001000, purity > 98 %), and CAF (108160100, purity > 98.5 %) were purchased from Acros Organics (Geel, Belgium). A 1000× stock solution of ASP was prepared with DD water. Stock solutions of SAC and CAF were prepared as 10× with embryo solution. All of the stock solutions were then diluted with embryo solution immediately before exposures to make final concentrations of ASP at 0.2 and 1 mM, SAC at 0.005 and 0.05 mM, and CAF at 0.05 and 0.5 mM. The SUC test solutions were prepared at concentrations of 29 and 146 mM. All (stock) solutions were stored at 4 °C and used within a month. The concentrations, abbreviations, and numbers of embryos in each group are listed in Table 1. Embryo exposures Medaka embryos from breeding pairs were collected within 5 h post fertilization. They were randomly assigned to different exposure groups, placed in 24-well plates, one embryo per well, and incubated at 27 °C. Each well contained 1 ml embryo or test solutions, which were replaced every 24 h. Embryos treated with embryo solution served as controls. To limit observation period within 2 h, each exposure experiment contained less than 17 embryos (2-4 per group), and the experiment was repeated 13 times. Obviously the 12 treatment groups could not be all tested at the same time, but the control group was always included in each experiment. The embryos were exposed continuously until hatch. The hatchlings were photographed and then transferred to glass dishes containing embryonic solution only. Observations and image analysis The procedures were as described previously (Lee et al. 2012). Briefly, the heart rate of embryos was first counted for 1 min under a dissection microscope at 27 °C, then the embryos were anaesthetized with 0.06 % MS222 (pH 7.25, Sigma-Aldrich), and their images recorded under a microscope (IX2-SLP, Olympus, Tokyo, Japan) from 1 to 3 days post fertilization (dpf ) and at hatch. The eye length, width, and pigmentation density (eye density), the distance between the eyes (eye distance; representing the head growth), the width of the optic tectum (midbrain width), and the hatchling body length were analyzed from the images with ImageJ image processing and analysis software (http://rsbweb.nih.gov/ij/). All images were obtained and analyzed under identical conditions without any alteration. White preference test The white preference test was conducted as described previously (Lee and Yang 2014). Briefly, individual hatchling (4 days after hatching) was held with a pipet for 30 s and then released in the black area of a rectangular box (L 60 mm × W 40 mm × H 15 mm) with two equal black and white areas. A square pattern of 5 × 5 mm 2 was drawn on the bottom surface. Once released, hatchlings were allowed to explore freely for 2 min. Each hatchling was tested once. The following endpoints of the hatchling movement were analyzed from the video recording: time lapse to white area, time spent in black or white areas, number of squares entered (indicating swimming distance), and time swimming along the sides or around the center of the box. The integrated biomarker response (IBR) The integrated biomarker response (IBR) was calculated as described previously (Beliaeff and Burgeot 2002;. Briefly, measurements from the treatment groups were standardized as a set of indexes, one set for each endpoint. An IBR value was calculated from the indexes of four endpoints (day to hatch, hatchling body length, time lapse to white area in the behavioral test, and total number of squares hatchlings entered in 60 s) from each treatment group. Statistical analysis The statistics software SPSS 17 (SPSS Inc., Chicago, USA) was used for all data analysis. One-way ANOVA was conducted, followed by the LSD post hoc test to compare variables of each endpoint among the treatment groups. Values were considered as significantly different when P <0.05. Effects of exposures on embryonic development Representative images of the embryos from the control and SAC2 groups are shown in Fig. 1, in which the SAC2-treated embryo appeared to be less developed than the control. The responses of each endpoint are described as follows: Heart rate The heart rate appeared to be the most sensitive endpoint for the tested substances. At 2-3 dpf ( Fig. 2; only data at 3 dpf were shown), most of the treatment groups had significantly higher heart rates than the control. The increases of the heart rates ranged widely, from 7.8 % (ASP1) to 26.2 % (CAF2) at 3 dpf. In addition, CAF2 combined with SUC1, ASP1, and SAC1 had significantly lower heart rate than CAF2 alone. In regard to dose-dependence, the pairs of SAC1/2 and CAF1/2 at 3 dpf exhibited such an effect, with higher concentrations causing significantly higher heart rates. Eye width and length The eye width and length were not affected as much as the heart rate. The eye width of SUC1 increased significantly at 1 and 3 dpf, compared to the control, while that of CAF2 decreased at 2 and 3 dpf ( Fig. 2; only data from 3 dpf were shown). However, these differences were small, only up to 6.3 %. A dose dependent effect was found between the pair of CAF1/2 at 3 dpf; CAF2 was 5.1 % smaller than CAF1. As to the eye length, only ASP1 at 2 dpf (not shown) and SAC2 at 3 dpf (Figs. 1, 2) were significantly shorter than the control. The groups of SAC1/2 also exhibited a dose-dependent effect at 3 dpf: SAC2 was 3.9 % shorter than SAC1. Eye distance The exposures did not significantly affect the eye distance until 3 dpf, when SUC2, ASP1, SAC2, CAF2, and CAF2 + SUC1 were significantly shorter than the control (Fig. 2). The differences were also small, only up to 6.9 %. A dose-dependent effect was found between the pairs of SUC1/2 and SAC1/2. Fig. 1 Representative images of medaka embryos exposed to saccharin at 0.05 mM (SAC2) or embryo solution only (control) at 1-3 days post fertilization (dpf). The exposures started from less than 5 h post fertilization until hatch. The images were cropped, but their relative proportion was maintained. No other alteration was made. Bar 100 µm Midbrain width At 1 dpf, the midbrain width of CAF1 and CAF2 increased 14.2 and 10.7 %, respectively, compared to the control (not shown). But this increase disappeared at 2 dpf, and at 3 dpf CAF2 became significantly, though only 3.3 %, shorter than the control (Fig. 2). The midbrain width of SAC2 was also significantly shorter than that of the control at 3 dpf. A dose-dependent effect was found between ASP1/2 at 2 dpf (not shown), and SAC1/2 and CAF1/2 at 3 dpf. Eye density The SAC1 test solution significantly increased (12.9 %) the eye density of the exposed embryos at 3 dpf, compared to the control (Fig. 2). Interestingly, CAF combined with all three sweeteners also raised the eye density significantly; the increases ranged from 12.9 to 27.5 %. A dose-dependent effect was found in SAC1/2; SAC2 averaged 15.2 % lower than SAC1. Day to hatch Both SUC1 and SUC2 took 23.9 and 30.0 %, respectively, less time to hatch, compared to the control, but this difference was only statistically significant in SUC2 (Fig. 2). Conversely, the CAF2 + SUC1 and CAF2 + SAC1 groups took 20.3 and 26.8 %, respectively, longer time to hatch than the control, but these differences were not statistically significant. Hatching rate The groups of SAC2 and CAF1 had significantly lower hatching rates than the control (80.0 ± 11.1 and 71.4 ± 13.0 %, respectively, vs. 100 %). The other groups were comparable to the control (Fig. 2). Hatchling body length The hatchlings from SAC2 and CAF2 were 4.3 and 11.4 %, respectively, shorter than the control. Interestingly, the combinations of CAF2 with the sweeteners caused a 7.2-11.7 % significant reduction in hatchling body length, compared to the control. These hatchlings were also significantly shorter than those exposed to SUC1, ASP1, or SAC1 alone (Fig. 2). A dose dependent effect was seen between the pairs of CAF1/2. Effects of exposures on hatchling anxiety-like behavior As there was no significant difference between pairs of substances at different concentrations, their data were combined for analyses (Fig. 3). Representative recordings of the white preference test from the control and CAF + SUC hatchlings are available as Additional files 1 and 2. The result showed that, compared to the control (29.1 ± 8.9 s), most of the treatment groups took significantly less time crossing to the white area (Fig. 3a). The differences of this time lapse ranged from 13.0 s (ASP at 16.1 ± 3.6 s, p < 0.05) to 24.3 s (CAF + SUC at 4.8 ± 1.4 s, p < 0.01). At 15 s (Fig. 3b), CAF + SUC and CAF + ASP spent significantly less time in the black area (4.8 ± 1.4 and 5.6 ± 1.5 s, respectively, vs. 10.8 ± 1.7 s, p < 0.05) and more time in the white area. During 15-60 s (Fig. 3c), in addition to CAF + SUC and CAF + ASP, the groups of ASP, SAC, and CAF were also significantly different from the control (p < 0.05) in their time distribution in the black and white areas. During 60-120 s (Fig. 3d), none of the treated groups were significantly different from the control. , and CAF combined with each sweetener on medaka development at 3 days post fertilization or at hatch. Data were percents of control values and expressed as mean ± SEM. *Significantly different from the control or between pairs of groups, p < 0.05; **p < 0.01; ***p < 0.001. The abbreviations and concentrations of the substances are listed in Table 1 As to swimming distance, at 15 s (Fig. 3e), total numbers of squares from CAF + SUC and CAF + ASP were significantly higher than that of the control (10.7 ± 1.2 and 10.1 ± 1.6, respectively, vs. 4.8 ± 1.3, p < 0.05). At 120 s (Fig. 3f ), CAF + SUC remained significantly higher than the control (107.0 ± 10.3 vs. 66.3 ± 13.4, p < 0.01), but not CAF + ASP. Interestingly, the hatchlings exposed to CAF + ASP entered significantly more squares than ASP alone (90.8 ± 8.0 vs. 66.0 ± 7.0, p < 0.05), while those exposed to CAF + SUC also entered significantly more squares than SUC or CAF alone (107 ± 10.3 vs. 69.3 ± 7.5 and 66.0 ± 7.0, p < 0.05, respectively). In e and f, no significant difference was found among the black areas, while statistical analyses on the white areas produced identical results to those on the total numbers of squares. Values were expressed as mean ± SEM. *Significantly different from the control, p < 0.05. The abbreviations and concentrations of the substances are listed in Table 1 The cumulative number of squares hatchlings entered during the test period was shown in Fig. 3g, which indicated that CAF + SUC caused the highest increase among the groups. As shown in Fig. 3h, statistical analyses on the slopes of these cumulative curves produced identical results to those in Fig. 3f. Interestingly, when in the white area, the hatchlings spent 65.3 ± 2.9 % of the time swimming along the sides, but when in the black area they spent 91.6 ± 1.6 % of the time swimming around the center. This phenomenon was consistent with our previous study (Lee and Yang 2014), but there was no significant difference in this side/center preference among the groups. However, a dose dependent effect was found in the pairs of SAC1/2: when in the white area, the SAC2 group spent significantly more time along the sides of the box, compared to SAC1 (70.3 ± 9.6 vs. 49.0 ± 5.8 %, p < 0.05). Integrated biomarker response (IBR) of the treatment groups To better assess relative developmental toxicity of the substances, the IBRs of the treatment groups were calculated with four endpoints: day to hatch, hatchling body length, time lapse to white area in the behavioral test, and total number of squares hatchlings entered in 60 s. As shown in Fig. 4, all of the treatment groups had lower IBRs than the control. The lowest values were from the groups of SAC1 and CAF2, only 20-21 % of the control value. In regard to dose dependence, the group of CAF2 had lower IBR values than CAF1, while SAC2 had higher IBRs than SAC1. Lastly, to explore the possibility of producing a cumulative effect when CAF was combined with the sweeteners, we compared the actual IBRs of the CAF mixtures with the sums of IBRs from each corresponding individual substance groups. It turned out that the values were quite similar, resulting in a ratio averaged 0.93 ± 0.05. Effects of CAF and the sweeteners on embryonic development The substances of SUC, ASP, SAC, CAF, and the combinations of CAF with the sweeteners all affected embryonic development and/or behavior, as summarized in Table 2. As expected, CAF affected development in all six categories listed in Table 2. Surprisingly, all the substances and their combinations affected embryonic heart rates (SUC2 significantly increased the heart rate at 2 dpf, not shown in Fig. 2). In addition, the mixtures of CAF with the sweeteners also advanced the eye development, shortened the hatchling body length, and/or modified behavior. Caffeine has been known to have developmental toxicity in fish. It had no effect at less than 0.75 mM in zebrafish embryos, but at 1 mM or higher it produced hatchlings with shorter body length (Chen et al. 2008), an effect consistent with our results. Also using zebrafish embryos, Hermsen et al. (2013) reported that CAF at 0.22-1.75 mM induced scoliosis and head and heart malformations. Selderslaghs et al. (2009) Sum=2.50 Fig. 4 The integrated biomarker response (IBR) values of medaka hatchlings exposed to test substances during embryonic development. The endpoints selected were day to hatch, hatchling body length, time lapse to white area in the behavioral test, and total number of squares hatchlings entered in 60 s. The abbreviations and concentrations of the substances are listed in Table 1 tails, but the hatching rate was only slightly affected. In our study, CAF1 (0.05 mM) caused a 29 % decrease in the hatching rate, but not CAF2 at 0.5 mM. In addition, no apparent malformation was observed from both groups. However, CAF2 significantly shortened the eye and midbrain width and hatchling body length, and raised the heart rates. It is likely that species differences contribute to the inconsistencies, and consequences of CAF biological activities vary with different concentrations and endpoints. Caffeine is a known psychostimulant; it has been found to activate brain activity and cerebral blood flow in humans, and may induce anxiety in higher doses (Chen and Parrish 2009). Nehlig and Debry (1994) also reported that pregnant rats and mice ingested CAF in doses equivalent to tens of cups of coffee per day produced offspring with altered behavior, including learning abilities and anxiety levels. Recently, Silva et al. (2013) demonstrated that female mice exposed to CAF during pregnancy and lactation produced offspring with increased neuronal network excitability, and the offspring grew up to have cognitive deficits. However, Brent et al. (2011), after reviewing epidemiological and animal studies, have reported that evidence for developmental toxicity of CAF in humans is inconclusive. The authors indicated that the plasma level of CAF has to reach 0.3 mM to cause teratogenic effects. It is a level roughly equivalent to consuming more than 30 cups of coffee a day in humans, a fairly unlikely scenario. This plasma level of 0.3 mM was in-between the concentrations of CAF1 and CAF2 of this study. Since CAF1 at 0.05 mM already produced effects on medaka development, such as increasing the heart rate and inducing anxiety-like behavior (the time lapses of CAF1 and CAF2 hatchlings moving to the white area were both significantly shorter than that of the control), apparently for subtler effects the minimum plasma level of CAF is likely to be lower. Other than CAF, SAC was another substance affecting all six categories ( Table 2). As SAC also induced significant differences at much lower concentrations than SUC and ASP, it is likely to be more toxic than the other two. This is consistent with the result from a study by Bandyopadhyay et al. (2008), in which SAC at lower concentrations induced more DNA damage than ASP did in mouse bone marrow cells. Though SAC at 55 mM produced 92 % mortality in zebrafish embryos, it caused no effect at concentrations up to 27.9 mM (Selderslaghs et al. 2009). In another study with zebrafish embryos, SAC at 10 mM did not cause any deformity (Hermsen et al. 2013). In the current study, SAC at a much lower concentration of 0.05 mM caused 20 % mortality, suggesting that, compared to zebrafish, medaka embryos were more sensitive to SAC. Effects of SUC (or glucose) on development have been studied extensively. It is well-known that diabetic mothers are at five-time higher risk of producing offspring with congenital malformation (Chappell et al. 2009). Glucose exposure at 50 and 100 mM induced malformations and higher than 70 % of mortality in cultured chick embryos (Datar and Bhonde 2005), or impaired neuronal development at 25 mM in quail embryos (Chen et al. 2013). Furthermore, preterm infants given repeated high dose of sucrose were more likely to show poorer attention and motor development (Johnston et al. 2002). In this study, SUC at high concentrations (29 and 146 mM) appeared to have a slight effect on medaka development. But it did not significantly affect hatchlings' white preference behavior, unless combined with CAF, an issue to be discussed in next section. Interaction of CAF and sweeteners in anxiety-like behavior Our results suggest that SUC is relatively safe at high concentrations. But when combined with CAF, it surprisingly heightened anxiety-like behavior in hatchlings. Furthermore, the mixture of CAF with ASP also significantly raised the anxiety level. Caffeine has been known to potentiate the reinforcing effects of alcohol through adenosine and dopamine neurotransmission when the two substances are combined (Ferré and O'Brien 2011). Similarly, CAF has been linked to increased additive properties of other abused substances, including cocaine, nicotine, and sugar (Temple 2009). Incidentally, SUC-dependent rats have been shown to have altered dopamine receptors and opioid mRNA levels similar to those in morphine-dependent rats (Spangler et al. 2004). Thus, our result was consistent with the notion that the interaction between CAF and SUC may pose a health risk to younger populations (Seifert et al. 2011). However, whether this interaction represents a synergistic relationship would require further studies using appropriate mixture designs. The potential toxicity of ASP has been investigated extensively for decades, and so far ASP is still considered very safe (Butchko et al. 2002). More recent studies also reported no evidence supporting a risk to human health, including preterm deliveries (Marinovich et al. 2013), nervous system function, learning, and behavior (Magnuson et al. 2007). But in our study, ASP increased the heart rate in medaka embryos, slightly suppressed the head growth, and induced anxiety-like behavior in hatchlings. Therefore, more studies are needed to ensure the safety of ASP consumption. Cumulative effects of CAF and sweeteners From the IBRs, we found a cumulative effect in developmental toxicity when CAF is combined with the sweeteners. However, further studies are required to confirm the result. Caffeine is not very soluble in water, due to its nonpolar ring structure. Consequently, the molecules tend to self-aggregate and stack with each other on their flat surface like coins (Tavagnacco et al. 2011). In the presence of SUC, CAF would be drawn by a weak affinity to stack with SUC instead, which increases CAF solubility (Lilley et al. 1992). Both ASP and SAC also have ring structures, and they might similarly stack with CAF in solutions. But this is just speculation, and there is no evidence indicating that this structurally stacking contributes to the cumulative effect of CAF with the sweeteners. The IBR values of the SAC1 and CAF2 groups were the lowest among the groups, while those of ASP and SUC were at the similar level. Since the concentration of SAC1 was much lower than that of CAF2, and that of ASP1/2 was much lower than that of SUC1/2, the ranking of developmental toxicity should be SAC > CAF > ASP > SUC. We have also demonstrated that the IBR is a useful tool to evaluate developmental toxicity with multiple endpoints. As the concentrations of SAC and ASP tested in this study were at least 10 times higher than those found in the environment, the health risk of these two substances on wildlife may be negligible. However, CAF and other ASWs are increasingly found in aquatic environments. For example, CAF and cyclamate have been found to be at the concentrations of 265-14,418 and 28-1406 ng/L, respectively, in surface water (Tran et al. 2013). Their cumulative activities may amount to significant levels and deserve more investigations. Conclusion We used the medaka embryo as a model system to evaluate developmental toxicity of CAF and three sweeteners: SUC, ASP, and SAC. Several endpoints for development were selected for evaluation, including the heart rate, eye density, time to hatch, and anxiety-like behavior. We found that all four substances and the mixtures of CAF with the sweeteners affected development and/ or behavior. We then used the IBR to better evaluate the overall toxicity of these substances. The result showed that the ranking of developmental toxicity was SAC > CAF > ASP > SUC, and there was a cumulative effect when CAF was combined with the sweeteners. Although the concentrations we tested were higher than those detected from the environment, this study has demonstrated that ASWs may pose a health risk to both humans and wildlife, and the effects may accumulate to significant levels when CAF is combined with ASWs.

v3-fos

2016-03-14T22:51:50.573Z

2015-12-22T00:00:00.000Z

11346576

s2

Nutrition and Health Disparities: The Role of Dairy in Improving Minority Health Outcomes Consuming a balanced diet, such as the food groups represented on MyPlate, is key to improving health disparities. Despite the best of intentions, however, the dietary guidelines can be culturally challenging, particularly when it comes to dairy consumption. Many African and Hispanic Americans avoid milk and dairy products—key contributors of three shortfall nutrients (calcium, potassium and vitamin D)—because many people in these populations believe they are lactose intolerant. However, avoiding dairy can have significant health effects. An emerging body of evidence suggests that yogurt and other dairy products may help support reduced risk of heart disease, hypertension, obesity, and type 2 diabetes—conditions that disproportionately impact people of color. For this reason, the National Medical Association and the National Hispanic Medical Association issued a joint consensus statement recommending African Americans consume three to four servings of low-fat dairy every day. Cultured dairy products could play an important role in addressing these recommendations. Because of the presence of lactase-producing cultures, yogurt is often a more easily digestible alternative to milk, and thus more palatable to people who experience symptoms of lactose intolerance. This was a key factor cited in the final rule to include yogurt in the Special Supplemental Nutrition Program for Women, Infants, and Children. Introduction The 2010 Dietary Guidelines for Americans (DGA) identified nine nutrients-vitamins A, D, E, and C; folate; calcium; magnesium; fiber; and potassium-as "short-fall nutrients": those that are under-consumed by a significant portion of Americans. Because of the association in the scientific literature with adverse health outcomes, four of these-calcium, vitamin D, fiber, and potassium-are classified as "nutrients of public health concern", i.e., nutrients the overconsumption of which may cause health risks in specific populations or populations at large. The DGA also considers sodium and saturated fats nutrients of public health concern because these food components are consumed in excess [1]. The question is: What can be done to address the under-consumption of these important nutrients-particularly in a way that also addresses the related health concerns? Dairy foods such as milk, cheese, and yogurt can be key in that they deliver many nutrients important for good health, including three of the nutrients of public health concern-calcium, potassium, and vitamin D. In fact, according to the 2010 DGA, three servings of vitamin D fortified low-fat and nonfat milk and milk products would provide 70% of the calcium and vitamin D, and 30% of the potassium in the diet [1]. Health authorities such as the American Diabetes Association (ADA), the American Heart Association (AHA), the National Medical Association (NMA), and the National Hispanic Medical Association (NHMA) all recommend three servings of low-fat dairy per day as a means of closing the nutrient intake gap [2][3][4]. It is significant, but not surprising that the latter two organizations, the NMA and NHMA, have addressed this public health concern. As stated in the 2010 DGA evidence rating, moderate evidence shows that the intake of milk and milk products is associated with a reduced risk of cardiovascular disease, type 2 diabetes, and lower blood pressure in adults-disease states affecting African Americans (AA) and Hispanic Americans (HA) at disproportionate rates [1]. The 2015 Dietary Guidelines Advisory Committee (DGAC) reaffirmed this association in their scientific report [5]. This evidence makes a strong case for the inclusion of dairy in the diets of AA and HA. It is understood that health disparities may exist among all racial and ethnic minority groups, however, this article will focus on dairy's role in improving AA and HA health outcomes, and strategies for increasing dairy consumption among these populations. Minority Health Disparities Research shows that the rates of obesity, diabetes and heart disease are higher in AA and HA populations than in white populations (Table 1). From 2011 to 2012, the greatest prevalence of obesity was among AA adults followed by HA adults [6]. In 2011, the prevalence of diabetes among AA adults was nearly twice as great as the prevalence among white adults [7]. Likewise, the prevalence of heart disease was greatest in AA compared with HA and white adults. African Americans not only experience higher prevalence rates of these health conditions, but higher mortality rates as well. For example, in 2013 death rates from heart disease were greatest among AA compared with other racial populations and AA were twice as likely to die from diabetes complications [8,9]. Dairy Intake and Chronic Diseases There is evidence that dairy foods and the important nutrients they contain-namely, calcium, vitamin D and potassium-are linked to reduced risk of heart disease; type 2 diabetes; and metabolic syndrome, which is responsible for obesity and diabetes [3]. These are all conditions that AA and HA populations experience in disproportion-a fact that is perhaps related to the fact that minority populations often have lower intake of key nutrients of concern: calcium, potassium and vitamin D ( Table 2). African Americans fall behind HA and the white populations, consuming only 83% of the daily recommended intake of calcium, 27% of vitamin D, and 50% of the potassium (Table 3) [10]. The connection between the shortfall in nutrient consumption and increased risk of these adverse health conditions can be explained by looking at the ways that these nutrients-or deficiency thereof-impact hypertension, diabetes, and obesity. For example, insufficient potassium is associated with hypertension, but consuming dietary potassium can lower hypertension by blunting the adverse effects of sodium on blood pressure. Evidence suggests that AA and individuals with hypertension especially benefit from increasing intake of potassium [1]. Calcium plays a critical role in nerve transmission, muscle contraction, and the constriction and dilation of blood vessels [1]. Adequate calcium intake may be particularly critical for AA and HA since research among these groups revealed higher diagnoses rates of diabetes and hypertension [1]. A calcium-rich diet (1000 mg or more daily) has been shown to decrease blood pressure and inhibit lipogenesis in the fat tissue, thus additionally improving cardiovascular risk [12]. But to help absorb calcium, Vitamin D is needed and African Americans may be at a higher risk for vitamin D deficiency due to dark pigmentation which blocks absorption of vitamin D from the sun [4]. In the United States, especially in colder zones where people get less daily sun exposure, most dietary vitamin D in the diet comes from fortified foods, especially milk and yogurt [1]. From this evidence, it is clear that fortified dairy foods can play an important role in addressing some of the health conditions that hit Black communities the hardest. Obesity The relationship between dairy and AA/HA health is more complicated when it comes to the impact of dairy on obesity. Dairy foods, particularly full-fat varieties, are often associated with excessive weight gain, which in turn contributes to diabetes, heart disease, and other conditions. However a 2013 prospective population-based cohort study of over 1700 men, aged 40-60 years, concluded a high intake of dairy fat was associated with a lower risk of central obesity (OR 0.52, 95% CI 0.33-0.83) and a low dairy fat intake was associated with a higher risk of central obesity (OR 1.53, 95% CI 1.05-2.24). High consumption of dairy fat was defined as butter, full fat milk and intake of whipping cream daily or several times a week. Low consumption of dairy fat was defined as no butter, low fat milk (1.5% fat or less), and seldom or never ingesting cream [12]. In one prospective study, researchers examined three separate cohorts of more than 120,000 US women and men followed every four years for twenty years. Evidence showed that consumption of yogurt, fruits, vegetables, and whole grains was associated with less weight gain over time, with yogurt having the greatest impact. Weight change was inversely associated as follows: vegetables (´0.22 lb), whole grains (´0.37 lb), fruits (´0.49 lb), nuts (´0.57 lb), and yogurt (´0.82 lb) (p ď 0.005 for each comparison) [13]. Heart Disease Hypertension is another area of critical health concern for minority communities. High-blood pressure increases the risk for cardiovascular disease, including heart attack and stroke [14] and uncontrolled hypertension is higher among AA and HA than whites [15]. It is one of the top health concerns for African Americans. One of the interventions recommended to patients diagnosed with hypertension is the Dietary Approaches to Stop Hypertension (DASH) eating plan. The DASH diet recommends lowering sodium intake; eating foods high in blood-pressure lowering nutrients such as calcium, potassium, and magnesium; and consuming fat-free and low-fat milk and milk products. Clinical trials show that the DASH eating plan is not only effective in lowering blood pressure, benefit of DASH was more pronounced in African Americans. Blood pressure was reduced by 6.9 mmHg systolic and 3.7 mm Hg diastolic in African Americans compared to 3.3 mm Hg and 2.4 mm Hg, respectively, in whites [16]. In a 2013 prospective study of more than 33,000 women in Sweden, researchers examined the association between total, as well as specific, dairy food (milk, cultured milk/yogurt, cheese, cream, crème fraiche, and butter) intakes and the incidence of myocardial infarction (MI). Evidence showed an inverse association between total dairy food intake and risk of MI. No difference was observed between specific dairy foods, nor between low-fat and full-fat dairy foods as it relates to risk of MI [17]. A 2013 literature review published in Nutrition Reviews was conducted to determine whether or not there was sufficient evidence to elucidate or dismiss an association between dairy foods and blood-pressure maintenance. The authors concluded that the preponderance of evidence indicates low-fat, non-fat, and full-fat dairy foods are beneficially associated with lower blood pressure [18]. In one 2013 cross-sectional study of adults in the Framingham Heart Study Offspring and Third Generation cohorts, yogurt consumers had higher potassium intakes, lower levels of circulating triglycerides and glucose, and lower systolic blood pressure and insulin resistance when compared with non-yogurt consumers [19]. The study authors suggest the metabolic changes may be due in part to an association between yogurt consumption and BMI. Diabetes Evidence suggests that dairy consumption may be associated with a reduced risk of type 2 diabetes. A meta-analysis of seven cohort studies showed an overall positive role of dairy consumption on the risk of type 2 diabetes, with authors reporting a 14% reduced risk of the disease associated with highest (>3 serving/day) versus lowest (<1 serving/day) dairy food intake [20]. A subgroup analysis suggested that low-fat milk and yogurt consumption were most strongly associated with diabetes risk reduction when compared to high-fat dairy. One serving of dairy per day was found to reduce the risk of type 2 diabetes by 5%. Adding one additional serving of low-fat dairy reduced risk by 10% [20]. In contrast, low-level dairy consumption, for example in the case of self-perceived lactose intolerance, results in lower intakes of calcium and other nutrients and is associated not only with diabetes but hypertension as well [21]. An August 2013 meta-analysis analyzed 17 cohort studies with data from more than 370,000 men and women to determine the relationship between dairy intake and diabetes risk. Evidence suggests a significant inverse association between intake of dairy products-including low-fat dairy products and cheese-and type 2 diabetes risk. Moreover, a dose-response analysis showed that for every 400 g of total dairy per day, type 2 diabetes risk was reduced by 7% [22]. The type of dairy may also be beneficial for the prevention of type 2 diabetes. A 2014 prospective study found that higher consumption of low-fat fermented dairy products compared to high fat fermented diary was associated with a decreased risk of type 2 diabetes. This response was largely driven by yogurt consumption. Fermented dairy products in the study included yogurt, cheese, sour cream, and crème fraîche [23]. Lactose Intolerance The true prevalence of lactose intolerance is not known as the condition is fairly difficult to diagnose with accuracy. However, perceived lactose intolerance is a major health concern. Research shows that currently 20.1% of AA and 8.8% of HA, compared to 7.8% of non-Hispanic whites, consider themselves to be lactose intolerant [21,24]. Even in cases where there is no definitive diagnosis, patients may assume or believe they are lactose intolerant and modify their diet accordingly-often eliminating a great deal of their dairy intake and, thus, the nutritional benefits that come from eating dairy foods. In order to get to the recommended daily values of calcium, vitamin D, and potassium, public health authorities recommend three servings of dairy every day [1]. For African American and HA adults, age 20 years and over, dairy intake is less than recommended: African Americans 1.19 (SE 0.005) servings daily, HA consume 1.49 (SE 0.063) servings daily and whites consume 1.89 (SE 0.055) servings daily [10]. For those who perceive themselves to be lactose intolerant, milk avoidance is a major obstacle in obtaining adequate calcium and vitamin D from the diet, and it has been shown that avoiding dairy may lead to shortfalls in essential nutrients [4,24]. Because of this nutritional shortfall, the National Institutes of Health identified self-restriction of dairy foods associated with self-diagnosis of lactose intolerance as a public health problem [25]. Health Benefits of Yogurt Lactose intolerant individuals-including those whose intolerance is perceived-can meet their dairy requirement and obtain critical nutrients of concern by consuming yogurt [26]. Many people who avoid dairy products because they are lactose intolerant may find that the live and active cultures in yogurt can improve lactose digestion. Yogurt contains less lactose per serving than milk, making it a more digestible alternative (Table 4) [27]. Yogurt is also rich in the nutrients needed to address many adverse health conditions. For example, a single 8-ounce serving of yogurt provides 6%-14% of the recommended daily intake for potassium [28]. Many fat-free and low-fat yogurts provide approximately 25% more potassium than an equal 8-ounce serving of milk [27]. Overall, yogurt consumers have a higher potassium intake, and are less likely to have inadequate intakes of calcium and magnesium [19]. Increasing the proportionate intake of fat-free and low-fat yogurt and milk would not only increase potassium levels, but also increase levels of magnesium, vitamin A, D, and choline in the USDA Food Patterns, and potentially decrease amounts of sodium, cholesterol, and saturated fat [28]. Studies have shown that regular yogurt consumption is associated with a healthy weight, decreased waist circumference, healthy levels of circulating glucose within the normal range, and decreased blood pressure [13,19]. The American Diabetes Association recommends plain, nonfat Greek yogurt as a good choice for people with diabetes [29]. WIC Program Expansion The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) is a federal program that provides nutrition education and vouchers for nutritious foods to low-income pregnant, breastfeeding, and non-breastfeeding postpartum women, and to infants and children up to age 5 who are found to be at nutritional risk. WIC food packages and nutrition education are the chief means by which WIC affects the dietary quality and habits of participants. Since its inception in 1974, WIC has earned the reputation of being one of the most successful federally funded nutrition programs in the United States [30]. In 2007, the WIC food packages were revised to more closely align with the latest DGAs, and provide WIC participants with a wider variety of food. The changes also gave WIC State agencies greater flexibility in prescribing food packages to accommodate participants with cultural food preferences and address regional food trends and traditions. The revisions largely reflected recommendations made by the Institute of Medicine (IOM) of the National Academies in its report "WIC Food Packages: Time for a Change." To address the nutritional needs of individuals who avoid milk due to cultural food preferences or lactose maldigestion, the IOM recommended yogurt be added as a substitute for part of the milk allowance. Heretofore, yogurt had not been on the list of foods that WIC covered [30]. In order to address this recommendation, the USDA asked states for assistance in exploring how yogurt could be provided and incorporated into the diet [30]. They wanted to determine acceptability and cost implications. In response, the California WIC Program conducted a randomized, controlled intervention pilot study to examine the impact of providing yogurt to women enrolled in WIC. The objective of the study was to document changes in women's preferences for yogurt, perceived barriers to yogurt consumption, and the number of dairy servings consumed overall. The study allowed participants to replace part of the WIC milk allowance with yogurt. It found that over 86% of the 511 women in the study wanted to do so. Among these, 62% reported preferring yogurt to milk. The majority (89%) of women in the study redeemed the yogurt coupons [31]. The study concluded that, when the WIC program allowed it, yogurt was a popular substitute for milk that tackled at least two concerns related to dairy consumption: It addressed the dietary needs, and concerns of WIC participants who were either lactose intolerant or irregular milk drinkers. It also addressed a cost barrier to consuming yogurt that study participants had noted. Yogurt was perceived as being more expensive than other dairy products. Removing this barrier could address income-related disparities that affect diet quality [31]. The final changes to the modified WIC food package, effective April 2015, reflect the results of the California research. In response to the recommendations of the IOM, the WIC food package now includes yogurt as a partial substitute for milk [30]. One quart of yogurt may be substituted for one quart of milk, with no more than one quart of yogurt per month. Recommendations The evidence-based Dietary Guidelines are used by the U.S. government as the basis for its food assistance programs, nutrition-education efforts, and decisions about national food-related health objectives. Urging people to consume a balanced diet-one that includes the food groups represented on MyPlate-is key to improving diet-related health disparities. But despite best intentions, the guidelines can be culturally challenging. For example, people with perceived lactose intolerance-a group that includes a disproportionate number of African Americans-can find it difficult to follow the guidelines for dairy intake. In their joint 2013 consensus statement on lactose intolerance, The National Medical Association and the National Hispanic Medical Association recommended that healthcare providers encourage patients to keep dairy foods in the diet, even if they are lactose intolerant. The NMA and NHMA encouraged providers to help patients employ strategies to help them achieve the recommended dairy food intake levels [4]. One such strategy is to replace milk servings with cultured yogurt. Nutrition programming should include research-based information on yogurt's nutritional quality, purchasing and handling guidelines, and recipes for meals and snacks. Such nutrition programming and communication would help ensure that minorities are provided with options for meeting the recommended nutrient and food group intake. Yogurt provides valuable nutrition contributions and should be considered as the 2015 Dietary Guidelines are implemented. Yogurt should also be included in the revised WIC packages, and education messages should be developed that include the benefits of including yogurt in the diet. Recommendations should be culturally relevant and practical to ensure best outcomes. Conclusions Dairy is an important dietary component, contributing nutrients that address conditions for which minorities are measurably at risk. Because AA and HA populations tend to have less-than-optimal intakes of key nutrients, they could benefit from the inclusion of recommended amounts of dairy in their diet. There are also health-disparity implications that come from increasing dairy intake, given the documented association between dairy consumption and lowered risk of obesity, type 2-diabetes, and hypertension. Among dairy products, yogurt has all the benefits of dairy, plus the benefit of being more easily digestible among people who perceive that they have a problem with lactose intolerance. When given the option, WIC clients demonstrated their preference for yogurt by using their vouchers to purchase this product. As a result, WIC has included yogurt to the list of other healthy foods that are available to WIC recipients. All the benefits and uses of yogurt should be promoted in the implementation phase of the 2015 DGA.

v3-fos

2019-04-02T13:06:37.491Z

2015-06-02T00:00:00.000Z

90731126

s2

Determining β-Galactosidase Activity of Commercially Available Probiotic Supplements Consumer interest in probiotics has dramatically increased in recent years due to improved knowledge of the significant benefits imparted on human health. A specific health issue in which probiotics have been found advantageous is lactose intolerance. Probiotics have demonstrated the ability to act on ingested lactose due to the presence of lactase. The objective of this study was to assess the β-galactosidase (β -gal) activity of commercially available probiotics supplements in the market. Ten supplements were used in this study. Two capsules of each supplement were allowed to activate in MRS broth for 10-12 h. Cultures were then inoculated into TPY broth with lactose (induced) or glucose (uninduced) then incubated at 37°C. After bacterial growth reached the mid log phase (optical density 0.7-0.9; 610 nm), the procedures as outlined by Miller were followed. Activity of β-gal was quantified using the o-nitrophenyl-β-D-galactoside (ONPG) assay. The activity of β-gal in the uninduced group ranged between 0 and 800 Miller unit, whereas there as the induced group ranged from 1 to 1,120 Miller units. When induced, supplement #5 exhibited the strongest enzyme activity at 1,120 Miller units and supplement #10 exhibited the lowest activity. Similarly, supplement #3 exhibited the highest (800 Miller unit) and supplements #1, #2 and #10 did not show any β-gal activity with glucose. These findings indicate that β-gal activity in the ten tested supplements varies. Our results suggest that not all of the commercially available probiotic supplements have the same health benefits. Introduction Bacteria colonize all of the physically available space along the gastrointestinal tract, with varying distribution. These bacteria have invaluable functions in the human body. The relationship between human host and the composition of gut microbiota is primarily mutually beneficial. The metabolic activity of gut microbiota provides the human host with metabolic energy and absorbable substrates and nutrients, while the human host provides the microbiota with a source of energy and nutritious products for growth and development [1]. Health benefits conferred on the host are contingent upon the maintenance of a homeostatic state among the network of the microbiota [2]. However, the microbiota is not indestructible, and the positive attributes provided by the bacteria can be overcome by pathogens and environmental factors, especially after cases of illness and/or medication use. The health conferring microorganisms of probiotics are commercially available to consumers in many forms including probiotic supplements (capsules, gummies, liquids, powders, and tablets). These supplements contain several probiotic bacteria such as Lactobacillus and Bifidobacteria. Probiotics benefit individuals of all ages, and age specific probiotic choices are available. The elderly population is often encouraged to consume probiotics to compensate for the natural decrease of beneficial bacteria in their gut microbiota with increasing age; as well as the increase incident of elderly taking medications [3]. In recent years there has been a dramatic rise in the interest of probiotics due to significant benefits imparted on human health. Scientific evidence supporting the health claims of probiotics stem from in vivo and in vitro studies. Consumer interest in functional foods, including those containing probiotics, has risen in the last 20 years [4]. Despite the predominant presence of probiotic food products available to consumers, probiotic supplements are becoming more popular. A specific health issue in which probiotics have been found advantageous is lactose intolerance. As infants all humans are born with the enzyme lactase (β-galactosidase) which hydrolyses lactose to glucose and galactose in order to be absorbed in the small intestine [5,6]. The prevalence of lactose intolerance varies from population to population. On average, in the United States, 80% of Asian and Native Americans, 75% of African Americans, 51% of Hispanic Americans, and 21% of Caucasian Americans are lactose intolerant [7]. These individuals do not possess the lactase enzyme, and any ingested lactose cannot be digested which leads to the gut microbiota attacking the lactose. Researchers have found the presence of lactase in probiotic products. When the probiotic bacteria reach the intestinal lumen the lactase is lysed by bile, and acts on the lactose that has been ingested. Thus relieving lactose intolerance symptoms [8]. Enzyme activity of probiotic supplements is of interest as a component of the viability of the supplement. In terms of being considered for potential use in alleviating symptoms of lactose intolerance, high β-gal activity is essential. To our knowledge, there are limited studies on this topic. Thus there is a need to determine the presence of β-galactosidase (β-gal) activity in commercial probiotic supplements. We believe this is the first study to determine β-gal activity of commercially available probiotic supplements. Sample Preparation Two capsules of each probiotic supplement were added into individual tubes of fresh deMan, Rogosa and Sharpe (MRS) broth respectively, and then mixed for 15 to 30 s using a vortex. Ten probiotic cultures were then incubated for 10-12 h at 37°C for the recovery of the cells. These samples were then used to test β-gal activity of each probiotic supplement. β-gal of probiotic supplements The activity of β-galactosidase was quantified using the o-nitrophenyl-β-D-galactoside (ONPG) assay as described by Miller [9]. Probiotic supplements were first grown to mid log phase, and an initial O. β-gal of probiotic supplements after exposure to 3% bile (w/v) Two capsules of each probiotic supplement was added into individual tubes of fresh MRS broth respectively, and then mixed for 15 to 30 s using a vortex. All supplements were then incubated for 10-12 h at 37°C, for the recovery of the cells. These samples were then exposed to 3% bile (w/v) for 2h at 37°C. The previously mentioned procedure was followed to determine enzyme activity of the samples. Table 1 shows the β-gal activity of the ten commercial probiotic supplements both in the presence of glucose (uninduced) and lactose (induced). The activity of β-gal in the uninduced group ranged between 0 and 860 Miller unit/mL, and activity in the induced group ranged from 1-1,120 Miller unit/mL. The induction of probiotic supplements with lactose increased the average β-gal activity. Lactose acted as a carbohydrate source on the induction of β-gal activity. Notable increases from uninduced to induced enzyme activity include: supplement #5, 50 to 1,120 Initially, ONPG (colorless) is broken down into galactose (colorless) and o-Nitrophenol (yellow). The bright yellow color signifies the breakdown of lactose; increasing intensity of the yellow color indicates increasing β-gal activity (Figures 1a and 1b). Our results were consistent with previous studies in which the presence of lactose in media enhanced β-gal activity when compared to the presence of glucose. We found that the presence of lactose in the growth medium led to β-gal activity enhancement for bifidobacteria and L. acidophilus specifically, [11,12]. We also examined the effect of bile on β-gal activity and found an increase in enzyme activity when bile was included in the medium ( Table 2). This finding is consistent with that of Zarate et al. who contributed this enzyme activity enhancement to the permeabilization of probiotic strains by bile. This allowed more substrate to enter the cells to be hydrolyzed by β-galactosidase [13]. Conclusions Overall lactose intolerant individuals can be well treated by dietary modification and education once properly diagnosed with the condition. Milk and other dairy products can remain in the diet of lactose maldigesters without experiencing symptoms through this dietary modification. This research tested several probiotic supplements containing L. acidophilus, L. reuteri, and L. rhamnosus strains. The high β-gal activity of these supplements (supplements #5, 6, and 8) suggests that consumers should target not only probiotic supplements, but also Supplement 10 0 1 Table 1: β -gal activity in commercial probiotic supplements.

v3-fos

2016-05-04T20:20:58.661Z

2015-04-01T00:00:00.000Z

10755126

s2

A comparison of different irrigation systems and gravitational effect on final extrusion of the irrigant Background The aim of this study was to compare manual needle irrigation (MNI), RinsEndo (RE), and passive ultrasonic irrigation (PUI), and assess the effect of gravity on extrusion from the apex in vitro. Material and Methods The distobuccal roots of molars were used and the canals were instrumented up to F2. Teeth were mounted on models, which permitted visualization and manipulation of the apices for necessary procedures. The models were placed in articulator to simulate the jaw. Six groups (G) were formed as: G1, G2 and G3 represented mandibular positioning of teeth and were irrigated with MNI, RE, and PUI, respectively, while G4, G5, and G6 represented maxillary positioning of teeth and were also irrigated in same sequence. Prior to the final irrigation, 72 cube-shaped foam pieces covered with aluminum foil were weighed and the values were recorded as the initial weights. The cubes were then placed on the apical part of each sample. Final irrigation was performed with distilled water and the cubes were weighed again to determine their final weight. Data were analyzed using Kruskal-Wallis and Mann-Whitney U post-hoc test (p<0.05). Results Irrespective of the irrigation technique used, the amount of irrigant extruded from the apex showed a statistically significant difference related to the effect of gravity (p<0.05). There was no statistically significant difference between irrigation methods (p>0.05). When the irrigation systems were compared to examine the effect of gravity, the significant difference was found between G2 and G5 (p<0.05). Conclusions Within the limitations of this study, MNI and PUI were found to be reliable irrigation systems. Caution should be exercised when using RinsEndo. Key words:Final irrigation, manual needle irrigation, passive ultrasonic irrigation, RinsEndo. Introduction Chemomechanical debridement is an important part of endodontic treatment. Many different irrigation techniques and devices have been used to improve disinfection of the root canal system. For optimal effectiveness of the irrigation, the irrigant should make direct contact with all parts of the canal wall (1). A flushing action, which is dependent on many factors such as the insertion depth, diameter of the needle (2), and the final size and taper of the prepared root canal (3), is necessary for optimal cleaning of the root canal (4). The conventional endodontic irrigation syringe and needle [manual needle irrigation (MNI)] is the most widely used technique because it is very easy to manipulate and affords good control of needle depth and the volume of irrigant delivered (5). However, it's safety has been questioned because of the positive pressure used to introduce the irrigant into the canal, which could cause the solution to extrude into the periapex despite strict control of the working length (WL) and result in severe tissue damage and postoperative pain (6). RinsEndo® (RE) (Dürr-Dental, Bietigheim-Bissingen, Germany) irrigates the canal by using pressure-suction technology. Employing a hydrodynamic working principle, its components include a handpiece, a cannula with a 7-mm-long exit aperture and a syringe carrying the irrigant. The handpiece is powered by a dental air compressor and has an irrigation speed of 6.2 mL/min. It is well documented that ultrasound enhances the flushing action of irrigant solutions (7). The term 'passive ultrasonic irrigation' (PUI) was first defined by Weller et al. (8) "Passive activation" in this technique implies that the instrument, once inside the canal, does not touch the canal walls. During PUI, a small file or smooth wire (e.g., size 15) is placed at the center of the root canal after shaping the canal, and then activated ultrasonically to induce "acoustic streaming" (9). This increases the efficiency of cleaning by the irrigant inside the canal by means of hydrodynamic cutting power (10). The purpose of this study was to compare the final amount of irrigant extruded apically due to MNI, RE, and PUI and assess the effect of gravity on irrigant extrusion using these techniques. There are limited studies examining the effect of gravity on apical extrusion of the irrigant (11,12). The null hypothesis was that the final amount of apically extruded irrigant would differ according to (i) irrigation technique and (ii) the effect of gravity. Material and Methods -Sample Preparation A total of 30 extracted maxillary molar teeth that had intact apices and had not been subjected to any previous endodontic treatment were collected and cleaned off to remove debris and soft tissue remnants. They then stored in 0.5% thymol solution until use. To reduce the effects of canal size and curvature on the extrusion of the irrigant, the distobuccal roots of all teeth were used as they had straight root canals of similar size. Teeth with a curvature between 0 and 10° were selected (13). To ensure similar lengths, all the teeth were measured and decoronated with a high-speed bur. An access cavity was then prepared in each tooth and the canal openings of the mesiobuccal and palatal roots were sealed with chemical composite resin (Alpha-Dent® Self Cure Composite, Dental Technologies, IL, USA). The WL was determined by introducing a size 10 K file (Mani, Inc., Utsunomiya Tochigi, Japan) into the canal until it was just visible at the foramen and then subtracting 1 mm from this measurement. The size of the minor constriction was controlled by introducing a size 15 K file (Mani, Inc., Utsunomiya Tochigi, Japan) up to the WL. Teeth in which the tip of the file extended beyond the apical foramen were excluded. As a result, the study was conducted with a final sample of 12 specimens. An operator then prepared all the distobuccal canals to the WL, up to size F2 (ISO size 25, taper 0.09-0.05) using ProTaper (Dentsply, Tulsa, OK) instruments. Between each file, the root canals were irrigated with 2 mL of 2.5% NaOCl solution using a syringe and a 27-gauge needle (Endo-Eze; 27-G, Endo-Eze, Ultradent South Jordan, UT). No specific attempts were made to remove the smear layer. Root canals were dried with paper points and the external surfaces of the specimens were carefully dried with air blasts. The study used a matrix design with three different irrigation methods and two positions. The same 12 teeth were used in all 6 groups so as to avoid variations in canal anatomy and apical diameter. First, the teeth were divided randomly into two groups (n=6) and embedded in horseshoe-shaped silicon impression material (Zhermack, BadiaPolesine (RO) -Italy) in a manner such that the roots were positioned inside the material while the crowns remained outside (Fig. 1A). The roots/silicon set-up was then surrounded with acrylic resin (Meliodent, HerausKulzer Ltd. Newbury, UK) up to the cementoenamel junctions of the teeth (Fig. 1B). After polymerization of the resin, the silicon impression material was removed with the help of a box cutter (Fig. 1C). The acrylic models, containing 6 teeth each, were then mounted on a semi-adjustable articulator with plaster so as to simulate the mandible and maxilla (Fig. 2). The mounting plate was parallel to the surface when irrigating the mandibular simulation. During irrigation of the maxillary simulation, the angle between the mounting plate and surface was maintained at nearly 45° in order to imitate the patient's head position in the dental unit. In all groups, irrigation was performed with 10 mL of distilled water delivered to the pulp canal according to manufacturer's instruction. Before irrigation, the operator placed a dental dam on the tooth to prevent observation of the extrusion (Fig. 3C). Immediately after each experiment, all specimens were dried with five size-25 paper points (Diadent;Chungcheongbuk-do, Korea). The six experimental groups (G) were formed as follows: in G1, G2 and G3 acrylic model represented mandibular positioning of teeth and were irrigated with MNI, RE, and PUI, respectively, while in G4, G5, and G6 acrylic model represented maxillary positioning of teeth and were also irrigated in same sequence. -Irrigation procedures MNI: This technique was performed with a syringe and Endo-Eze Needle. The 27-G side-vented needle (Endo- The root/silicon set-up was surrounded with acrylic resin. C) Silicone material was removed and roots were exposed. Eze, Ultradent South Jordan, UT) was placed 2 mm short of the WL without any binding and moved in an up-and-down motion during irrigation. Hence, the root canals were irrigated for 1.5 min and the delivery rate was approximately 6.6 mL/min (14). Control of irrigation pressure was difficult in this group. RE®: The irrigant was delivered at the rate of 6.2 mL/ min and agitated by activation of the RE handpiece (Dürr-Dental, Bietigheim-Bissingen, Germany) using the needle provided by the manufacturer (needle size 45 with a lateral opening of 7 mm). The cannula was placed into the coronal third of the canal without any binding and moved up and down during irrigation. The compressed air pressure supplying the handpiece was adjusted to 3.5 bar to ensure it was within the recommended range (2.3-4.2 bar). The root canals were irrigated for 1.6 min (14). PUI: PUI was performed with a stainless steel #15/.00 file (IrriSafe K15; Satelec, Merignac, France) driven by an ultrasonic device (SuprassonPMax; SatelecActeon, Merignac, France) with in-plane oscillation in the direction of the root canals. An IrriSafe ultrasonically activated file on a Satelec P5 booster ultrasonic unit (Satelec) with power setting 5 was placed 1 mm short of the WL and activated. During PUI, the root canals were irrigated for 1 min with a continuous flush of the irrigant (10 mL/min) (14). Every attempt was made to keep the file centered in the canal so as to minimize contact with the canal walls, as any such contact could dampen the oscillatory motion of the file. A cube-shaped piece of floral foam covered in foil was attached to the root tip of every tooth, so as to simulate the slight resistance of periapical tissues and prevent the loss of extruded water (Fig. 3 A,B) (15). For each measurement (n=72), one piece of floral foam covered with foil was weighed prior to any procedures with the help of a 0.0001 electronic balance (Sartorius basic, Sartorius AG, Gottingen, Germany). Three consecutive measurements were taken and their mean was considered to be the weight of each foam piece. If these 3 readings showed great variability, the process of weighing was continued until 3 similar measurements were obtained (where only the last digits differed by 1-2). The electronic balance was placed in a room without any windows and the door of the room was closed during weighing of the cubes. Only two individuals, who were seated and motionless during the process, were present in the room. To monitor the machine's precision, the same 3 foam pieces were weighed at every stage. During irrigation, the root tips were pressed into the foam. The foam pieces were weighed again after irrigation was completed and the mean of these measurements was considered to be the new weight. The amount of apically extruded irrigant was calculated by subtracting the initial recordings from the final weight of the foil-covered foam cubes. As the experiment was conducted at room temperature with water as the irrigant, no conversion between the weight and volume was performed because the specific gravity of water at 25°C (77°F) is 1.00, up to the second decimal place (16). The differences between groups were analyzed using Kruskal-Wallis and Mann-Whitney U post-hoc test (p<0.05). Results The mean weights and standard deviations for each group are presented in table 1. The results indicated that all of the irrigation techniques caused measurable apical extrusion of irrigant. Irrespective of the irrigation methods, the final amount of irrigant extruded showed a statistically significant difference related to the effect of gravity (p=0.002). Irrespective of tooth position, there was no significant difference between irrigation methods (p=0.090). In contrast to PUI and MNI, RE showed much greater extrusion in both positions. In comparisons within groups, only RE showed a significant difference in the amount of irrigant extruded related with the effect of gravity (p=0.045). In the mandibular and maxillary positions, all the techniques showed the same extent of apical extrusion of irrigant (p>0.05). Discussion During root canal instrumentation, pulp tissue remnants, dentine debris, microorganisms, and intracanal irrigants may be extruded from the apical foramen and induce flare-ups. It is known that inflammatory reactions can cause bone resorption, edema and postoperative pain (6,17). While it is important to ensure that the irrigant penetrates the entire root canal system in order to enable it to exert its favorable actions (18), it is also necessary to ensure that it does not extrude into the periapical tissues. This helps maintain the critical balance between cleaning efficacy and patient safety (19). The results of this study can only be generalized to teeth with fully formed apices and straight root canals. Repeated use of the same specimens had a negligible effect on the results under the experimental conditions used (20). Psimma et al. (20) reported that an increase in the constriction diameter is linked to a slight increase in irrigant extrusion, but the difference was not statistically significant. In the present study, a standardized constriction was created in all the specimens so as to avoid the confounding effect of this factor. In experimental studies, the amount of material extruded from the apex is usually between 0.1 g and 1.2 g. VandeVisse and Brilliant (21) reported that a collectible amount of debris was extruded only when root canal instrumentation was accompanied with irrigation. In this study, NaOCl was used for irrigation during preparation and after drying the canals with paper points; final irrigation was performed with distilled water (16). The root tips were pressed into floral foam only at this stage, and the extruded irrigant values were recorded, which have been presented in table 1. Most of the literature regarding extrusion studies involves teeth that had their apices positioned downwards in the vial, representing a mandibular tooth. However, gravity may have an effect on the amount of solution extruded from the apex as it may influence the accessibility of the irrigation solutions to the apex. Currently, only two studies have investigated the effects of gravity on extrusion from the root apex (11,12). In present study, irrigant extrusion was observed even in the maxillary position despite the fact that it was against gravitational force, similar to the results found in previous studies (11,12). There was a significant difference between extrusions in the two positions irrespective of the irrigation technique used. In the current study, significantly larger quantity of irrigant was extruded in the mandibular position compared to the maxillary position. The results of this study were consistent with those obtained by Williams et al. (11). On the other hand, the effect of gravity on the apical extrusion of irrigant may not be important as the patient is usually in a supine position, except in some special situations such as pregnancy and spinal deformities (kyphosis). It has been recommended that the needle tip be placed 2 mm short of the WL or slightly coronal to the point when resistance is encountered, before the needle tip reaches the desirable distance (22). Therefore, in the present study, the same needle penetration depth was used. A previous study performed using a Computational Fluid Dynamics model showed that a flat needle (open-ended needle) led to a higher mean pressure at the apical foramen than the double side-port needles, at the same depth (23). Thus, side-vented needles were used in this study. The results of this study agreed broadly with those of previous studies in which irrigation with positive pres-sure was observed to result in periapical extrusion (16,24). Several studies examined the efficacy of RE in comparison with manual and ultrasonic irrigation (14,16,25). Desai and Himel (16) reported periapical extrusion of the irrigant for MNI, RE and also PUI. The manufacturer's instructions for RE suggest that the hydrodynamic activation of the irrigant ensures that the apical third of the root canal is effectively irrigated, even though the needle tip is inserted into the coronal third. The results of present study confirmed this. Similar to previous study, it was demonstrated that RE extruded significantly more irrigant from the root canal despite the fact that the needle tip was placed the most coronally (16). Hauser et al. (25) reported that the penetration depth of a colored irrigant into the root canal dentine was higher for RE when compared with syringe irrigation, demonstrating the efficacy of the oscillation in distribution of the irrigant. However, PUI extruded significantly less irrigant than RE in the mandibular position, although the file was 1 mm shorter than the WL. Maximum attention was paid to avoid any contact of the instrument with the canal walls during the PUI procedure. According to the results of a previous study, the amount of irrigant extruded apically during PUI is fairly little (26). Tasdemir et al. (26) reported that the use of a passively activated file with ultrasonics in a canal after instrumentation resulted in a low risk of apical extrusion of the irrigating solution. In the present study, PUI extruded less irrigant than the MNI, although the difference was not significant. In the MNI group, the control of irrigation pressure was difficult and this could have affected the amount of irrigant extruded into the periapical tissues. Martin et al. (27) demonstrated the ability of ultrasonically activated K files to cut dentin. The roots used in the present study were straight and PUI was performed after the root canals had been shaped. As stated previously, every attempt was made to keep the file centered in the canal so as to minimize contact with the canal walls. Moreover, PUI was performed last in all the groups to prevent any alteration of the root canal shape, similar to the procedure used by Rodig et al. (14). Most of the previous studies used a vial attached to the apices of the teeth to collect the extruded debris and irrigant (16,26) and measured the mean extruded debris after evaporation of the irrigating solution. However, in this study, the total amount of extruded material during final irrigation was measured. No special attempt was made to distinguish the amount of debris from the amount of irrigant as they are both responsible for periapical inflammation, postoperative pain, and possible delayed healing (24). Altundasar et al. (15) reported that the resistance provided by the floral foam may be more realistic than the assumption of zero back-pressure, which is common in extrusion studies that use a vial setup with no periapical resistance. No significant differences were found in the weights of the floral foams during the study, which demonstrated that precise measurement was possible with the balance used in the study. However, the results may vary in an in vivo model because of the presence of periapical tissues, which act as a natural barrier to prevent irrigant and debris extrusion. In conclusion, the null hypothesis of the study was accepted. The degree of apical extrusion of irrigant was dependent on the type of irrigation technique and gravity. Greater caution should be taken during irrigation so as to prevent postoperative pain. Among the three techniques used, RE was responsible for the heaviest amount of extruded debris, especially in the mandible.

v3-fos

2017-04-07T04:51:25.447Z

2015-06-09T00:00:00.000Z

1884376

s2

Evaluating the Effect of Three Water Management Techniques on Tomato Crop The effects of three water management techniques were evaluated on subsurface drip irrigated tomatoes. The three techniques were the intermittent flow (3 pulses), the dual-lateral drip system (two lateral lines per row, at 15 and 25cm below soil surface), and the physical barrier (buried at 30 cm below soil surface). Field experiments were established for two successive seasons. Water movement in soil was monitored using continuously logging capacitance probes up to 60 cm depth. The results showed that the dual lateral technique positively increased the yield up to 50%, water use efficiency up to 54%, while the intermittent application improved some of the quality measures (fruit size, TSS, and Vitamin C), not the quantity of the yield that decreased in one season, and not affected in the other. The physical barrier has no significant effect on any of the important growth measures. The soil water patterns showed that the dual lateral method lead to uniform wetting pattern with depth up to 45 cm, the physical barrier appeared to increase lateral and upward water movement, while the intermittent application kept the wetting pattern at higher moisture level for longer time. The cost analysis showed also that the economic treatments were the dual lateral followed by the intermittent technique, while the physical barrier is not economical. The study recommends researching the effect of the dual lateral method on the root growth and performance. The intermittent application may be recommended to improve tomato quality but not quantity. The physical barrier is not recommended unless in high permeable soils. Introduction While the presence of water in the root zone is vital for plants, the soil wetting pattern (WP) has a significant effect on the crop growth [1]. The WP depends on two major factors: the soil properties (texture, hydraulic conductivity, etc.) [2][3][4] and the application scheme (application method, position, rate, and frequency). [4][5][6][7]. To conserve water within the root zone, some researchers suggested placing an impermeable barrier (made of polyethylene or foil) below the dripper lines to limit the downward movement of water [8][9][10]. The application of such technique in soils with high infiltration rates increased Soil properties The soil of this field was sandy loam up to 60 cm depth. At the beginning of the experiment, we took soil samples at 0-20, 20-40, 40-60 cm depths, the samples were air-dried and gently crushed and sieved through a 2 mm sieve, and stored for chemical and physical analysis. Particle size distributions were achieved according to Gee and Bauder [25]. Soil pH and EC values were determined in soil paste using a pH-meter according to Thomas [26] and EC-meter according to Rhodes [27]. Calcium carbonate was determined using a calcimeter according to Loppert and Suarez [28]. The concentration of soluble Cations and anions (Ca 2+ , Mg 2+ , Na + , K + , CO 3 2-, HCO 3 -, Cland SO 4 2-) was determined according to the methods described in Sparks et al. [29]. Finally, the soil organic matter content was determined according to Nelson and Sommers [30]. The soil properties are listed in Table 1. Experimental design The three studied techniques were applied each in two levels; applied {1} and not applied {0}. The physical barrier's levels were P 1 and P 0 for applied and not applied respectively. Similarly, the dual-lateral technique is denoted H 1 and H 0 respectively, and the intermittent application (surge drip) is denoted S 1 and S 0 respectively. The selected experimental design was split splitplot factorial design in 2 3 (8) treatments including interactions, each treatment was applied on nine row crops (replicates). The statistical design details are in section 2.8. Tomatoes planting Seeds of commercial tomato variety Kilele F1 were sown in seedling trays (Jiffy-7 peat pellets, Moerdijk, The Netherlands). The seeds were grown in fiberglass greenhouse under controlled conditions at temperatures of 25±1°C/day and 20±1°C/night. After four weeks of seed sowing, seedlings of uniform size having five true leaves were transplanted outdoor (at the open field) into rows of 7 m length and 0.85 m width. The distance between plants was 50 cm. Fertilization and other cultural practices were applied as commonly recommended in commercial tomato production [31]. Irrigation design and scheduling For all plots in the subsurface drip network, we applied the following parameters: the main lateral line is buried 15 cm below soil surface, with 4L/h built-in emitters ffi33 cm apart (3 emitters/m) (Rhein dripperline, pressure compensating, clogging resistance, Saudi drip, K.S.A). For the dual lateral plots (H 1 ), an additional lateral line is buried 10 cm below the main lateral line (25cm below soil surface); the scheduled amount of water is divided equally between the two laterals. For the continuous flow treatments (S 0 ), all the scheduled irrigation was applied at once. The scheduled water for intermittent flow treatments (S 1 ) was divided into equal amounts according to the selected pulse rate (3 pulses), where the OFF duration is three times as the ON duration (a numerical example is at the end of this section). For the treatments with physical barrier (P 1 ), the barrier was placed 30 below the soil surface. The form of the physical barrier is a semicircular PVC tube, 110 mm width; this is narrower than the physical barrier of Ismail et al. [14] (500 mm width), but it is wider than the size of Brown et al. [10] which was less than 57 mm L shaped strip. The amount of water applied to all plots were adjusted to be the same, the irrigation process was scheduled by calculating the crop evapotranspiration by the method of FAO 56 [32], according to the weather station nearby in the same farm. The values of the crop coefficients were taken from FAO 56 as 0.6, 1.15, and 0.9 for the initial, medium, and end growing stages. According to the numbers of emitters in each plot, the desired amount of water is converted to the equivalent operation time and then programed to automatic controllers, (Rainbird ESP Modular Controller, Rainbird, USA). 2.5.1 A numerical example of the timing calculation. Assume the desired amount of irrigation water is 9.6 mm.d -1 for the control treatment. The required time to apply this amount should be calculated depending on soil properties, emitters properties, number of emitters, and area of the plot [33] by Eq (1). where T: irrigation time, T; A: wetted area (normally considered 50% of the drip irrigated area), L 2 ; d g : gross irrigation depth, L; Q: applied water discharge, L 3 T -1 ). For the irrigated plot if A = 80 m 2 , Q = 1.92 m 3 h -1 , and d g = 9.6 mm.d -1 , then T = 24 minutes. This amount of time will be applied to the control treatment (S 0 H 0 ) and the system will work continuously for 24 minutes. For the plots with dual lateral, S 0 H 1 , the amount of discharge (Q) is doubled, and hence the irrigation time is halved, i.e., the plot will work for 12 minutes continuously. For the pulsed treatments with single lateral, S 1 H 0 , the required operation time will be 24 minutes but it will be divided according to the following timing profile: 8-24-8-24-8 where the eights are the ON times and the 24s are the OFF times. For the pulsed treatments with dual lateral, S 1 H 0 , the operation profile would be as follows 4-12-4-12-4, for total 4×3 = 12 minutes total of ON times and 24 minutes of OFF times. We also apply the same amount of water to the S 0 H 1 plots, since the H 1 plots has double the number of emitters than the H 0 plots, then the required time will be half the initial time, i.e. 12 minutes. Water measures To monitor water movement in the soil we installed capacitance probes, EnviroSCAN probes with 5 TriSCAN sensors each, Sentek technologies, Australia. The probes monitor water continuously, for each treatment we installed 2 probes; one of them bordering the emitters' line, Fig 2, and the other is 20 cm apart (center to center), an additional access tube was installed 25 cm far from the second tube for on-demand measurements using another capacitance probe (Diviner 2000; Sentek technologies, Australia). Each probe consists of five sensors installed at 10, 20, 30, 40, and 60 cm depth. Data were collected manually every 3-5 weeks using a manual data logger. A rigor calibration process was performed according to the manufacturer's manual as described in Elnesr et al. [34], readings were logged every 30 minutes through all the study period. To limit the effect of soil heterogeneity, and to focus on the clear effect of the treatments, we calculated difference curves that show the change in water content from the initial time (before irrigation) to a specific time (0.5, 1, 3, 6, 12, 18 h after irrigation). These curves are easier to be explained than the original curves. The difference values (WC c ) are simply calculated by subtracting the initial water content (WC i ) values from the water content value of a specific time (WC t ); e.g. if at z cm depth WC i = 17.1%, WC t = 19.8% then WC c = 19.8-17.1 = 2.7% this was repeated for all the depths from 10 to 60 cm. To qualify the irrigation process, we measured the irrigation water use efficiency (WUE, kg/ m 3 ), which is the ratio of crop yield to the applied irrigation water, Eq (2), [35]. where n: number of replicates (rows) per treatment; r: counter; Y r : yield of the row (kg); Wa r : applied water to each row (m 3 /row). Additionally, we calculated the water footprint of tomatoes (the amount of applied water per fruit, FP, L/fruit), which was introduced by Allan [36], Eq (3). The reference values of the FP for tomatoes and the methods of determination are obtained from Mekonnen and Hoekstra [37]. where: FC r : fruit count per replicate. Crop pre-and post-harvest measures In the 8th week of tomatoes cultivation, we took one representative plant sample from each crop row to evaluate the growth indicators; We measured its length, counted its number of primary branches, and weighed each of its parts separately; leaves, stems and fruits (if any), and evaluated the water content in each of these parts. The water content evaluation was performed by taking about 100 g of each part (stem, leaves, fruit) then dried it at 70°C oven for 3-5 days (till no weight loss occur between two subsequent weighs); finally we calculated the water content percent as (Initial weight-dry weight)/dry weight à 100. After about 80-90 days of cultivation the harvest process starts, while it is over after 4 to 5 harvests depending on the fruits maturity. For each harvest, each row of the 72 crop rows are weighed individually, the fruits of each row were counted, and then we selected 6 random fruits from each row's yield. Portions of the fruits were sliced and dried at 70°C for 72 h to measure their dry matter and water contents. Other parts were homogenized using a fruit blender to determine the fruit chemical composition and fruit quality parameters. Total Soluble Solids (TSS, %) content were determined using a portable digital refractometer (PR-101, AT AGO, Japan). Titratable acidity, (TA, g 100 g -1 fresh weight), as citric acid was determined by potentiometric titration with 0.1 N NaOH against 9:1 dilution of fruit homogenate juice samples with distilled water. Vitamin C (mg 100 g -1 fresh weight, as ascorbic acid) content was measured by titration of homogenate fruit juice samples using 2,6 dichlorophenol-indophenol solution standardized in a solution of ascorbic acid with an identified concentration [38]. Finally, we measured the color of the fruits as an indicator of lycopene content [39]. Measurements of color were performed on 45 fruits per treatment using Hunter color-measuring instrument (Color Flex Hunter Lab, USA). The color space coordinates (L à , a à , b à ) were directly read and stored by the instrument software. In this coordinate system, L à is a measure of lightness ranging from 0 (black) to 100 (white); a à positive values indicate amounts of red while negative values indicate amounts of green, and b à positive values indicate amounts of yellow while negative values indicate amounts of blue. It was reported that the chromatic index that correlates best with the lycopene content was (a à / b à ) 2 , as the relationship is linear with r 2 = 72-91% [40][41][42]. Cost analysis The treatments that contain either the dual lateral or physical barrier techniques require additional equipment and installation costs than other treatments. Thus, we performed a cost analysis between the eight treatment combinations. The economic analysis is based on the methods of FAO [43], O'Brien et al [44], and Amosson et al [45]. The prices of the hardware and other expenses are based on the local market. The lateral line cost including drippers was 0.8$/m, and the manifold's price was 1.5$/m. The fittings and other installation expenses was considered 30% of the total pipelines cost. The physical barrier price was 1.5$/m and the trenching and installation of the lateral lines was about 1.0$/m; increased 50% for the dual lateral installation, and 200% for the physical barrier installation. The system's life was considered 8 years. The annual interest rate is 4%. The seasonal operation time is the sum of the daily operation time of each treatment according to the irrigation schedule (For the control treatment, the total time for seasons 1 and 2 were 40 and 34 h respectively). The electricity price was 0.08$/kWh. The pumps, tanks, flowmeters, and other seasonal labor, seeds, fertilizers, and land preparation expenses were computed from actual expenses in our field for the whole land and divided by 8 to get the expenses for each treatment. Each year includes two seasons, thus the annual rates are divided by two to calculate the seasonal rates. Finally, the selling cost of the yield was 0.5 $/kg. Statistical design Data were subjected to analyses of variances (ANOVA) according to a factorial split-split plot design, with the intermittent application (S) as whole plots, dual drip (H) as the sub plots and the physical barrier (P) as the sub-sub plots. Means were tested with Fisher's least significant difference method (p<0.05). All the statistical analyses were accomplished using the Statistix package v10.0, Analytical Software. [46]. Crop results According to the selected experimental design, the split-split plot design, we had the whole plot factor S, the sub-plot factor H, the interaction between them S×H, the sub-sub plot factor P, the dual interactions S×P, H×P, and the triple interaction S×H×P. The results are listed in Table 2. It is noticed from this table that most of the studied properties were significantly affected by the one or more of the treatments S, H, S×H, while there is no significant effect of the P treatment nor any of its combinations in most of the properties. 3.1.1 Tomato yield. The total yield of tomato in season 1 was highly affected by S and H treatments (p<0.001), the dual lateral treatment (H 1 ) yielded 53.3 t/ha, which is 49.5% more than the single lateral's yield (H 0 = 35.7 t/h), correspondingly, the application of S treatment caused 21.5% reduction in the yield (S 0 , S 1 = 49.8 and 39.1 t/ha respectively). In the second season, the interaction of S×H was significant, and the highest yield was 60.1 t/h for the S 0 H 1 treatment followed by the S 1 H 1 , S 1 H 0 , and S 0 H 0 respectively, Table 2, where no significant difference between the two H 1 means, nor between the H 0 means. The fruits count per plant was affected by the S×H interaction in both seasons; the highest number of fruits per plant in the two seasons has resulted from the S 0 H 1 , with 73.6 and 56.7 fruits/plant respectively, the results of this treatment is significantly higher than the other treatment combinations, Table 2. Unlike the previous measures that show negative effect of the S treatment, the fruit mass of the S 1 treatments was higher than that of the S 0 treatment for the two seasons, where S 1 yielded 8.5 and 17.3% heavier fruits than S 0 in season 1 and 2 respectively, Table 2. However, the effect of the H treatment was not significant in season 1, unlike season 2 that showed the positive effect of H 1 . 3.1.2 Water use efficiency. The dual lateral technique, H, appears to have the sole effect on increasing the water use efficiency in the two seasons, Table 2, (54 and 45% increase in WUE when applying H 1 in season 1 and 2 respectively). Conversely, the application of the intermittent irrigation, S, reduced the WUE in the first season by about 18%, while its effect was not significant in the second season. Similarly, the water footprint of the tomato was improved by applying H 1 (e.g. the net applied water in season 1 was 9L/Fruit for H 0 , improved to be 6.1 L/fruit), and reduced by applying S 1 (from 6.6 to 8.5 L/fruit for S 0 and S 1 in season 1 respectively). 3.1.3 Vegetative growth. The overall growth of the plant appears to be affected by the H and S treatments as well, Table 2. The H technique increased the plant height from average of 59.4cm to 75.4cm and from 75.5cm to 88.5cm in seasons 1 and 2 respectively. However, the S application, had no significant effect on the plant height for the first season, while it had a positive effect on the second season. Likewise, the green mass was positively affected by H 1 in the two seasons, while the effect of the S is negative in the first season, and positive in the second season. Furthermore, the results showed that the number of primary branches was positively affected by the H 1 treatment and not affected by any other treatments. The water content values in the stems, leaves, and fruits were somehow affected by the H and S treatments, Table 2. The water content is higher in the H 1 than H 0 , and in S 1 than S 0 in the three measures. For the leaves, S×H interaction was significant in season 1 only, where the highest water content was the control (S 0 H 0 ), with no significant difference from S 1 H 1 , then the S 1 H 0 and the S 0 H 1 treatments. 3.1.4 Nutritional and maturity indicators. The analyses of the properties of the tomato juice showed that the titratable acidity was only increased by the S 1 treatment in the first season, Table 2. Moreover, the TSS value was increased by S 1 in both seasons, while decreased by H 1 only in season 2. The maturity index (TSS/TA) was not significant for any of the measured treatments. Never the less, the content of vitamin C showed a significant increase by H 1 in the two seasons and by S 1 in the second season only. Finally, we found that no color indices were significantly changed by any of the studied treatments. Changes in soil water content The curves that represent the change in water content (WC) are illustrated in Fig 4 for all the treatments (charts a to h). Each chart in the figure consists of two sets; the left set is the loggings of the probe located near the lateral line (@ 5 cm distance), while the right set of curves represents the distant probe, (@25 cm distance). The two sets help drawing a complete view of the water lateral, and vertical movement with time. For all the charts in Fig 4, the right sets reflect a very small change in WC (less than 2%), this shows that the lateral movement of water is limited in all the treatments except for the physical barrier's (Fig 4d) where the water approaches 3% increase at 10cm depth. The control treatment (S 0 H 0 P 0 ) , Fig 4a, was the only treatment that shows gradual increase in WC up to 60cm depth which reflects deep percolation. The S treatments Fig 4b, 4e, 4f and 4h show that the maximum values of WC was reached after 1 hour, while the rest of the treatments the maximum water contents were reached sooner (after 0.5 h), this reflects the effect of pulsing. In the P treatment Fig 4d and treatment combinations f-h we notice that water remains in the profile up to 18 hours after irrigation, for example, in chart d, at 10cm depth, WC approaches 3%, while it is almost zero in charts a, b, c, and e where the P is absent. This shows that the physical barrier keeps water in the root zone for a long time. The effect of the H treatment is very clear in Fig 4c, as the two lateral lines unifies the WC vertically almost from 20 to 40 cm depth, this trend continued for each of the following logging times. It can be noticed too that the upward water movement is limited in the existence of the dual lateral (as the WC at 20 cm is much more than its value at 10 cm). On the other hand, we notice that the vertical shape of the WC curves has been reduced in the combined treatments charts (g and h), while it is slightly remains at the S×H treatment (e). The increasing trend of WC near the soil surface appears only at the control and P treatments (a, and d), while the rest of the treatments show decreasing trend from10 to 20 cm depths. The increasing trend is not preferable as it increases the probability of water loss by evaporation. The cost comparison In the current experiment, each treatment occupies 1/8 of the total field area, which is 608/ 8 = 76 m 2 . We have conducted two cost analysis studies, one for the current study's area, and the other was simulated for a four hectares square plot (200 x 200 m 2 ) with the same conditions. The summary of the cost analysis of the current study's area is shown in Table 3, while the details of both the current area and the simulated area are attached in S1 and S2 Tables. The cost analysis in Table 3 showed that the highest profit margin was obtained when using the dual lateral (H) without either P or S (S 0 H 1 P 0 , = 91%) followed by the treatment of H with P only (S 0 H 1 P 1 = 76%) then H with S (S 1 H 1 P 0 ; 64%). On the other hand, the least margin was obtained from S 1 H 0 P 1 treatment, which combines S and P without H (18%). Although the fixed costs of the H treatment are doubled at the dripper lines' item, but the higher yield of the treatment led to more than double of the profit margin comparing to the control treatment (S 0 H 0 P 0 ). Additionally, the small operation time of the H treatment reduced the pumping costs as well. The simulated area of 4 ha showed similar results, S2 Table, as the highest profit margin was 135% for S 0 H 1 P 0 , followed by that of S 0 H 1 P 1 , 120%, and the least value of the profit margin was 47% for S 1 H 0 P 1 . Discussion The physical barrier in our study showed non-significant effects over all the studied properties. These results may be due to one or more of the following conditions: the soil texture, the barrier's layout (width, shape, and depth), or the crop type. The main reason for using the physical barrier is to limit the downward water movement due to high soil permeability [8,10]. As a result, the physical barrier produced higher yields (especially for tomatoes) when applied to sandy textured soils as reported by some investigators [11,12]. Accordingly, since our soil's texture is sandy loam with moderate permeability that it does not have the problem of deep percolation especially with low-flow emission like drip irrigation, then the barrier had no effect on the current soil texture. The barrier's shape, width and depth may also have influence the barrier's performance. Our barrier's was narrow (11 cm) if compared to Ismail et al. [14], 50 cm, but it is wider than that of Brown et al. [10], 8 cm, both of them reported good results of their barriers, hence, it can be concluded that the width was not the reason of our results. Furthermore, the depth of our barrier, 30 cm, was similar to that of the previous works with positive results, e. g. Ismail et al. [14]. With similar concept to the physical barrier, the capillary barrier's effect varies by the crop type, [47] as they reported good results for pepper and lettuce and negligible effects on tomatoes and melons, however, tomato crop was positively affected by the physical barrier in sandy soil [14]. Thus, the negative result of the physical barrier in this study appears to be affected only by the soil texture. Additionally, it is important to bear in mind that physical barriers may increase water loss by evaporation by forcing water to move upward as shown in the current study. Nevertheless, physical barriers have some harmful effects on plat roots and may cause accumulation of unwanted chemicals in the root zone [13], thus it should be avoided unless really necessary. In conclusion, it is only advised to apply this technique for light textured soils when the water is excessively lost by deep percolation. The results showed that the intermittent drip had a negative effect on the yield quantity and the water use efficiency, while it had a positive effect on the fruit size (mass) and on the height of the plant in the second season. This means that applying the irrigation water all-at-once is better to gain higher yields, but with smaller fruits. The intermittent application showed a significant increase in the maturity measures; TSS, and titratable acidity, this improvement in fruit quality combined with the significant increase in the fruit mass is a good indicator of quality improvement. Thus, in cases that the fruit size and ripening signs are marketing aspects, the intermittent application should be considered. On the other hand, we should bear in mind that the intermittent application results are affected by the pulse rate, the soil texture and water content, and the type and age of the crop [20,48,49]. This urged some investigators to believe that the future of this technique is not so promising, as it was tested with many frequencies, many crops, and in many soil-textures, and all the results was not encouraging (Alon Ben-Gal, personal communication, November 6 2014). Correspondingly, the good results of the intermittent application in some published research may be attributed to limiting deep percolation [23], or limiting emitters clogging [16], these two reasons may be the reason of increasing yields and WUE. Consequently, if the intermittent application is applied in some systems that do not suffer of deep percolation and emitters clogging problems it might not enhance the growing conditions. Another factor that should be considered, that we have noticed that each time the valves close, the emitters leak some excess water due to the effect of the air relief valve. Hence, the more valve closing events, the more water is wasted. Since the S 1 treatment requires three valve closes instead of one for S 0 , then more water is wasted in the S 1 treatments. This may explains the increase of water discharged to the S 1 plots, and hence causes the reported decrease of water use efficiency. In conclusion, the intermittent application could be considered only if the soil texture causes deep percolation, or the system is exposed to potential emitter clogging. The dual lateral method showed positive results in almost all the studied indicators. It produced greater yields and plant growth, better WUE, higher values of vitamin C, while it had positive effect on the fruit mass and the TSS in the second season only and no effect on the titratable acidity, in addition to its high profit margin over all the studied combinations. These results showed that this method has a very good effect on yield's quantity (in the two seasons), quality (in the cold season), and economically. The good results of the dual lateral agrees with Ismail et al. [14] when the vertical distance between the two laterals was 10cm, while they reported that if this distance is more, then the dual lateral produced less yield as the water of the secondary lateral escaped out of the reach of the rootzone. This lead to a conclusion that the effect of this technology is related to water distribution along the root system, which is reflected on the water distribution patterns , Fig 4c. In similar setup, Zotarelli et al. [50] placed two lateral lines, one at 15 cm below soil surface, and one at the soil surface (for fertigation), they found that this placement increased the root length distribution 48-54% than surface drip irrigation. Although the dual lateral method involves two subsurface laterals, but their results support our assumption that the placement of two lateral lines one above each other enhances the water distribution patterns leading to higher quantity and quality yields. According to the soil-water distribution patterns, the placement of two lateral lines instead of one leads the water vertical distribution to be uniform up to 40 cm, Fig 4c. this distribution water pattern may be the main reason of this good results of the dual lateral method. However, the effect of the dual lateral on the root distribution needs more research to confirm this hypothesis. As the results showed that none of the treatments had a significant effect on any of the tomato skin color indices, and since the lycopene content is directly proportional to the (a à +b à ) 2 color index [40][41][42], we can conclude that the lycopene content is not affected by any treatment as well. This agrees with the studies that reported that Lycopene is affected by water deficiency [51,52], as in this study all the treatments were subjected to the same amount of water and no water deficiency. This shows that the positive effects of the dual lateral and intermittent techniques are due to the application method not to any difference in the application quantity. This proves that these two techniques are capable of enhancing yield quantity and quality using the same amount of water. Summary and Recommendations Each of the three tested techniques has different effect on the wetting pattern and the crop growth. The major shift in crop yield was caused by the dual lateral technique, where it appears to enhance the wetting pattern; this hypothesis, however, requires more research. The dual lateral technique is recommended for its good yield results especially that it is the most economical treatment above all others despite the increase of its fixed costs. The intermittent application improved the fruits size, ripening degree, and content in vitamin C, while it caused reduction in the total yield of the crop, however, it is more economic than the control treatment. The previous studies showed that the intermittent application limits deep percolation and emitters' clogging, while in this study due to our conditions, we have neither deep percolation nor emitters clogging, and hence the effect of this technique does not appear in this study. The intermittent application improved some of the tomato quality measures, and it is recommended to consider it when the quality is more important than quantity especially on sandy soil. The physical barrier had no effect on any of the important measures, while it appears to increase the lateral and upward movement of water, where it can increase evaporation and reduce water use efficiency, additionally, it is not economic in the current study's conditions. The previous studies who reported positive effect of this technique were of sandy textured soils with high permeability, combining this with the other studies that warn of the physical barrier hazards like causing chemical toxicity or growth inhibition of roots, we can recommend to avoid using this technique unless really needed in extremely high permeable soils. Supporting Information S1 Table. A comparative cost analysis of eight treatments, each of them cultivated in 76 square meters. (XLSX) S2 Table. A comparative cost analysis of eight treatments, each of them cultivated in 40,000 square meters. (XLSX)

v3-fos

2017-03-31T06:54:44.004Z

2015-05-28T00:00:00.000Z

15362816

s2

Council Regulation (EC) No. 1099/2009: State of the Art and Its Application in a Local Health Unit in Piedmont, Italy In the last decade, the European Union has reinforced the concept of animal welfare throughout the food chain, from breeding to slaughtering. Studies and assessments of economic nature led to the adoption of Regulation EC 1099/2009 and at the end of 2014 this regulation will be applied to all the members involved in the food chain. For this reason several local health units organized different initiatives. The local health unit of Turin no. 4 (ASLTO4) has developed a project aimed to train food business operators (FBO) to fulfill all the criteria developed in this Regulation. This initiative was divided into four steps: i) communication to the companies about the criteria of the new regulation; ii) a training course for official veterinarians; iii) slaughterhouse audits in order to get information about animal welfare; iv) and a training course for the personnel involved in slaughterhouses. The purpose of this paper was to report the results of the audits in order to identify critical points of structural, instrumental and documentary facilities. Then, the results can be compared with similar studies in order to develop common strategies and intervention areas. Introduction The concept of animal welfare has grown with time and helps in determining the quality of the food. The European Community has tackled this issue with growing interest and found that the lack of harmonization and uniformity were the factors of greatest difficulty for the application of welfare regulations (European Commission, 2008). For this reason, in the last ten years the European Community ruled out several laws and decisions. With the enforcing of hygiene Package, the responsibility for food safety has been transferred almost completely to the food busi-ness operators (FBOs), but the veterinarians still have in charge monitoring and supervision duties. The Animal Welfare Regulation 1099/2009(European Commission, 2009 has followed this trend. In addition to the improvement of the aspects already introduced above, the Reg. 1099 gave measurable parameters and introduced some substantial innovations such as the role of the animal welfare officer, the certificate of eligibility, the compulsory assessment of stunning and the standard operating procedures (SOP) of the stunning phase. Article 17 states that the FBO must designate a person responsible for animal welfare with the task of ensuring compliance with the provisions of the laws. This employee must be trained in a specific way by the veterinary service. Since the control effectiveness must be done systematically, it becomes necessary that all staff is trained in the field of ethology, knows the parameters of proper stunning and how the stunning device works. Another new feature, as mentioned earlier, provides that the FBOs must verify the effectiveness of stunning in order to ensure the absence of any signs of consciousness and sensibility of a representative number of animals, according to a risk analysis of the structure. Due to the entry into force at full capacity of EC Reg 1099/2009(European Commission, 2009, the local health unit of Turin no. 4 (ASLTO4) in the spring of 2012 settled down a project whose aims were to inform about the new requirements of the standard and to help veterinarians -without distinction of areas -focus their attention on issues of animal welfare and stunning. Another aim of the project was to encourage the communication and the discussion among FBOs and veterinarians from different working areas (animal health, food hygiene, age and geographical origin). The project was organized into four steps: i) official communication to the veterinary service, ii) training on animal welfare during slaughtering process for veterinarians, iii) plants audits to verify the state of the art, iv) specific training courses for FBOs. The aim of this work is to illustrate the problems emerged during the audit phase relating to the application of the Regulation in the territory of ASLTO4. The results will allow comparison with other projects in order to identify weaknesses and develop common strategies and solutions. Materials and Methods The audit involved 31 slaughterhouses located all throughout ASLTO4. The checklist used is presented as Appendix. They were: 15 cattle slaughterhouses, 11 bovine/ovine/goat slau-ghterhouses, 3 pig slaughterhouses, 1 equine slaughterhouse and 1 poultry slaughter. Regarding red meat slaughterhouses, half of them slaughtered equal or less than 5 animals/day. One pig slaughterhouse slaughtered more than 100 animals/week, the poultry slaughterhouse over 400 animals/week. The checklist used during the audit took into account the following parameters. First, structural requirements -considering the flooring, the downloading structures, the possibility to split up animals in different groups, the presence of drinking devices, the conditions of ventilation and lighting, the presence of any disturbing factor and the presence of immobilization devices. Second, stunning devices -considering the different method used (mechanical or electrical stunning), the presence of SOP related to the maintenance and the presence of the instruction manuals, a second device in case of failure of the first one, audible warning systems or a complete control panel showing the electrical parameters, the presence of equipment to increase the degree of welfare such as showers. Third, documents -considering the presence of the checklists, the presence of adequate SOP, certificates of use and maintenance procedures. Fourth, behaviour of operators during the animal handling, introduction in the stunning cage and during stunning phase. Results The inspections in slaughterhouses have revealed a discrete number of problems described below. Structural problems Many shortcomings were highlighted but they were easy to resolve. Ninety percent of the companies did not have water devices in the resting area. The percentage of the plants without suitable roofs of waiting pens was about 16%. Some operators solved this problem by installing systems for curtain blinds. One company stated that it was not willing to provide any coverage. In 15% of the structures, pavements were slippery or could become slippery if wet. The reasons were to be found in the lack of maintenance or in the choice of the material. Almost all slaughterhouses stun cages were found adequate for the size of the animals. When inadequate, this problem sorted out in slaughtering facilities that performed more species very different from each other (e.g. cattle/pig) or companies that were authorized for slaughter according to religious rite where the slaughter was carried out during special holidays (e.g. Feast of Abraham's Celebration). Stunning devices Captive bolt The majority of failures detected in the phase of stunning was related to the type of device used or the type of explosive charge. They were often used guns with caliber 22, instead of 25, for stunning animals of large size. In other cases, were used devices of proper caliber, e.g. caliber 25, but unsuitable considering the animal species. Failures due to inexperience of the FBO or human errors in positioning the device were rare. When observed, was often in companies with higher amount of animal slaughtered and we found that this was due to haste. Other failures were related to devices' wear caused by humidity and repeated use. This situation was highlighted in several works and reports (European Commission, 2004;Grandin, 2012a). Electronarcosis Most of the electrical stunning devices commonly used in abattoirs could not achieve the proper amperage requested by the Regulation. Documentary requirements The highest percentages of non-complaint slaughterhouses were related to the required documents. The producing companies were not able to deal with the changes introduced by regulation in this field. The plants did not have the approval certificate for stunning cage at a rate almost equal to 100%. At similar percentages, similar companies did not have SOPs. Only in one case they were drawn up, but they were quite inadequate. For few companies, a register where to sign how many shots were fired was available; this practice, which aimed to detect non-compliance during stunning, was totally misunderstood by operators who were afraid to run the second shot. Behaviour of food business operator In 90% of the cases, the staff did not have the know-how in order to evaluate properly the correct stunning signs and the behaviour signs of consciousness and insensitivity. This situation led to the inability to recognize situations in which the second shot was necessary. In addition, any stunning operator was able to describe its correct mode of execution. The second shot was commonly applied in the entrance hole of the first, proving completely useless for the presence of the hematoma and acute inflammatory reaction of the tissue (European Commission, 2007). A positive note is that all companies were equipped with a second device during stunning operations. Discussion Currently, there are no reports to compare the situation that emerged from the survey with other territories. For this reason, we will discuss our results with the reports referring the investigations prior to 2009, which provided the basis and rationale for processing the EC Regulation 1099/2009 (European Commission, 2009). First of all, every requested change regarding welfare during stunning operation at the slaughterhouses must cope with the total cost of the slaughtering process. This cost has been quantified as the 20% of total costs of the slaughterhouse. This percentage can have a deep impact in terms of competitiveness in a market like meat market (European Commission, 2007). Due to the European economic situation and the difficulties on red meat market, this situation has been and still is the reason why FBOs hardly accept changes. They always keep in mind how prescriptions will reflect on the final production cost. The lack of adequate parking areas deserves a careful evaluation since the magnitude of the slaughter of the companies was not that high, so we can assume that the time between unloading and slaughtering does not justify larger ones (EC Regulation 853/2004;European Commission, 2004). The presence of slippery floors should be carefully considered for its effect on animal behaviour. It may cause more troubled animals and consequently more difficulties at the stage of stunning (Grandin, 2012b). The low rate observed can be attributed to the fact that this requirement seems to be one of the most considered on the part of the FBOs in the area of animal welfare at slaughter (European Commission, 2007). It was observed that the failure of stunning with captive bolt pistol is mainly due to the incorrect valuation given by the manufacturers of explosive charges. The effectiveness of stunning using a mechanical device is given by the caliber of the device and speed of the captive bolt (EFSA, 2004). In order to get a proper result, in many slaughterhouses, it was decided to change the size or change the explosive charge. This change has been accepted and implemented without problems because it is associated with a fraction of the cost quantified as 0.02% in a previous study (European Commission, 2007). Anyway, a crucial point of the problem is that manufacture companies too must been involved in the training process and their knowledge must be seriously implemented. For example, considering the assessment of unconsciousness and insensibility, they pay attention only to the loss of the upright position without taking into account the presence or absence of other signs. In choosing the charge, other parameters such as race, conformation and habits must also be kept in mind. For example bulls which are used to live in herds and with little contact with humans tend to be very nervous and difficult to manage in the stunning cage and tend to move as soon as they come into contact with it (OIE, 2013). The low percentage of errors in manual processing, as for example the positioning of the captive bolt device, is similar to other studies: Grandin (2012b) recorded percentages of 1% in small slaughtering plants like the ones examined by us. Considering the stunning methods ( equipment is, in fact, equal to 0.1% of production costs in the case of large establishments but this percentage may vary considerably in the case of small slaughterhouses (European Commission, 2007) and FBOs not always are willing to deal with expensive investments. The importance of the economic evaluation of investment was reiterated in the case of poultry slaughterhouses in which only 32% of operators expressed its willingness to change of stunning (European Commission, 2012). Scientific reports show that this change does not really affect the animal welfare (EFSA, 2004). Other studies suggest the use of electrical stunning with application head/body in small slaughterhouses could be another choice (Vogel et al., 2011). The maintenance of the devices, especially the mechanical ones, is very important. The not systematic maintenance has been identified as a major cause of failure in several reports and scientific papers (EFSA, 2004;Grandin, 2012aGrandin, , 2012b. The lacking of manuals, SOP and documentations reflects a situation not very different from the one highlighted in a previous EFSA report (2007). Regarding the behaviour of FBOs, the European Community is developing manuals and SOP that may help FBOs during the assessment of the correct stunning operations (EFSA, 2013). We believe that the training needs to be addressed at all levels: device procedure companies, FBOs and official controllers for professionalism and expertise involved very different between them (European Commission, 2008). Conclusions Animal welfare at slaughter has become an important issue and veterinarians will have to cope with more and more. This issue repre-sents the intersection among the needs of consumers in terms of quality and ethics, the compulsory duties of veterinarians in terms of food hygiene and the economic request of FBOs. It has been pointed out that in many cases improving the protection of animals for slaughter does not necessarily entail expensive investments (Grandin, 2012b). The changes may simply need greater attention, greater sensitivity and a different attitude. Food business operators are not apt to change maybe beacuse they have no knowledge of new technologies or can be assumed that a previous acquisition cost has not yet been not yet fully deferred before doing a new one (European Commission, 2007). The other key aspect is that a change in mentality represents a request to which some FBOs, especially older ones, are not prepared to cope with, while the younger ones turn out to have a more open minded attitude and desire of change. The category still have to comply with these problems and still have to learn to communicate with FBOs and consumers in order to continue to play the central role of ensuring food safety and animal welfare.

v3-fos

2017-06-29T17:55:26.632Z

2015-01-21T00:00:00.000Z

9326186

s2

Abscisic acid negatively interferes with basal defence of barley against Magnaporthe oryzae Background Plant hormones are well known regulators which balance plant responses to abiotic and biotic stresses. We investigated the role of abscisic acid (ABA) in resistance of barley (Hordeum vulgare L.) against the plant pathogenic fungus Magnaporthe oryzae. Results Exogenous application of ABA prior to inoculation with M. oryzae led to more disease symptoms on barley leaves. This result contrasted the finding that ABA application enhances resistance of barley against the powdery mildew fungus. Microscopic analysis identified diminished penetration resistance as cause for enhanced susceptibility. Consistently, the barley mutant Az34, impaired in ABA biosynthesis, was less susceptible to infection by M. oryzae and displayed elevated penetration resistance as compared to the isogenic wild type cultivar Steptoe. Chemical complementation of Az34 mutant plants by exogenous application of ABA re-established disease severity to the wild type level. The role of ABA in susceptibility of barley against M. oryzae was corroborated by showing that ABA application led to increased disease severity in all barley cultivars under investigation except for the most susceptible cultivar Pallas. Interestingly, endogenous ABA concentrations did not significantly change after infection of barley with M. oryzae. Conclusion Our results revealed that elevated ABA levels led to a higher disease severity on barley leaves to M. oryzae. This supports earlier reports on the role of ABA in enhancing susceptibility of rice to the same pathogen and thereby demonstrates a host plant-independent function of this phytohormone in pathogenicity of monocotyledonous plants against M. oryzae. Electronic supplementary material The online version of this article (doi:10.1186/s12870-014-0409-x) contains supplementary material, which is available to authorized users. Background Generally, plant hormones are small molecules derived from different metabolic pathways that act at low concentrations either locally or distantly from the site of synthesis [1]. Apart from being important for development, plants use their hormone network to respond to external stimuli such as abiotic and biotic stresses. Salicylic acid (SA), jasmonic acid (JA) and ethylene (ET), the so-called immunity hormones [2], are best known because of their major function in regulating disease resistance in many plant species against a plethora of pathogens. Importantly, they do not act independently from each other but rather form a multidimensional network with synergistic or antagonistic interactions in response to pathogens with different life-styles [3]. More precisely, the ability of a plant to resist a pathogen depends on hormonal balance rather than on the absolute concentration of individual hormones [4]. Pathogens target this sensitive equilibrium to their advantage for promoting disease. Thus, they either produce plant hormones themselves, like e.g. Agrobacterium tumefaciens (indole-3-acetic acid) or Giberella fujikuroi (gibberellic acid) [4], or synthesize hormone-like substances such as coronatine, a JA-mimic secreted by Pseudomonas syringae [5]. For Arabidopsis it was shown that distinct hormone pathways are effective only against subsets of pathogens, e.g. SA-dependent resistance acts most efficiently against biotrophic pathogens which solely colonize living plant tissue. It was shown that some biotrophs developed the ability to suppress SA-mediated defence by up-regulating the antagonistical JA/ET pathway [3]. The classical plant hormone abscisic acid (ABA) also antagonises SA-mediated defence as shown e.g. in Arabidopsis, where ABA-treatment increased the susceptibility to an avirulent strain of Pseudomonas syringae pv. tomato by suppressing lignin accumulation and defence gene expression [6]. Also for monocotyledonous plants such as rice a negative correlation in resistance against Xanthomonas oryzae pv. oryzae of ABA-and SAsignalling was reported [2]. In turgid plants, ABAbiosynthesis takes place in vascular bundles. Plant ABA is a terpenoid with 15 carbon atoms derived from C 40 carotenoids that are produced via the 2-C-methyl-derythritol-4-phosphate (MEP) pathway [7]. By contrast fungal ABA, produced e.g. by Cercospora spp. or Botrytis cinerea, is derived from the MVA (mevalonic acid) pathway [8]. This difference in biosynthetic pathways suggests independent acquisition of ABA-metabolism in fungi and plants. ABA can affect the outcome of plant disease either negatively, most likely due to its interference with SA-signalling, or positively, e.g. by its involvement in primed callose deposition [9,10]. For hemi-biotrophic pathogens, such as Magnaporthe oryzae, less is known about the function of ABA in plant resistance. M. oryzae is a major fungal pathogen of rice (Oryza sativa L.) but is also able to infect other grasses or sedges including barley and wheat [11][12][13]. Koga and co-workers [14] found that ABA-treatment suppressed resistance of rice plants against M. oryzae. Interestingly, Wiese et al. [15] reported the opposite effect for the barley/powdery mildew (Blumeria graminis f. sp. hordei, Bgh) interaction. M. oryzae invades barley plants by direct penetration of epidermal cells which takes place after germination of conidiospores and formation of dark-pigmented appressoria. Growth of invasive hyphae into epidermal cells can happen without microscopically visible plant reaction ( Figure 1A). However, also an autofluorescent papilla, a fortification formed at the inner site of the epidermal cell wall, may occur beneath appressoria ( Figure 1B The initial infection process, up to the formation of bulbous infection hyphae in the primarily attacked epidermal cell, resembles a biotrophic interaction. Later stages of infection, by contrast, are associated with cell necrosis which is visible at the cellular level as collapsed autofluorescent mesophyll tissue ( Figure 1I) [16,17]. We have investigated the interaction between barley and M. oryzae for about 15 years, elucidating e.g. different aspects of quantitative or nonhost resistance [17][18][19][20]. A so far unexplored aspect was the function of plant hormones in this interaction. In the present study we closed this gap by identifying ABA as a balancing factor which contributes to susceptibility. Consequently, a barley mutant with a defect in ABA biosynthesis exerted enhanced resistance to M. oryzae. Quantification of endogenous ABA revealed differences among cultivars but no substantial changes during infection with M. oryzae. ABA-treatment increased susceptibility of barley against M. oryzae In a first exploratory experiment, we investigated which of the classical plant hormones influences the interaction between barley and M. oryzae. Therefore, primary leaves of barley were sprayed with test-solutions of salicylic acid (SA), abscisic acid (ABA), gibberellic acid (GA 3 ), auxin (IAA) and the ethylene precursor 1-aminocyclopropane-1carboxylic acid (ACC) and inoculated after one hour with the pathogen. Typical disease symptoms developed on mock-treated control plants as spindle-shaped lesions indicating that the fungus had successfully completed its life-cycle and produced conidia ( Figure 2A). Hormoneand mock-treated plants were compared macroscopically after seven days and no substantial differences in disease severity were found for most of the hormone treatments ( Figure 2A). The treatment with ABA, however, led to more frequent and larger disease symptoms on treated leaves. To exclude the possibility of a direct effect of ABA against the pathogen, an additional experiment was performed in which solutions with different ABA-concentrations were applied by soil drench and inoculation with M. oryzae was done after 48 hours (Additional file 1: Figure S1). Quantitative measurement of disease symptoms after seven days revealed that each concentration of ABA significantly increased disease severity. Thus, a treatment with 20 μM ABA doubled the number of lesions, whereas a treatment with 100, 200 or 300 μM caused a three to four time increase. We followed this observation in more depth by quantitative microscopic analysis of the infection process using a combination of bright-field and epi-fluorescence microscopy. Generally, barley can arrest or hinder disease progress of M. oryzae at penetration or postpenetration stages, both of which can be tracked by monitoring the presence or absence of invasive hyphae in attacked epidermal cells and its coincidence with the occurrence of autofluorescent plant material. Accordingly six categories of disease progress were discriminated as depicted in Figure 1. For quantitative assessment, microscopic samples were harvested at 72 h p.i. and individual infection sites were assigned to one of these categories. At most plant-fungus interaction sites (approx. 65-70%) a local deposition of autofluorescent material was observed beneath fungal appressoria and in association with a papilla ( Figure 2B). This was the case for mock-treated, SA, ACC and IAA-treated plants. For this group of plants, autofluorescence of collapsed mesophyll cells, indicating accelerated proliferation of the pathogen, was found at only 5-10% of infection sites. By contrast, the latter category was by trend more frequent (17%) in GA 3 -treated and even more and significantly frequent (20%) in ABA-treated plants ( Figure 2B). Concomitant with the increase in mesophyll colonisation a significantly decreased number of infection sites were found which were assigned to the category "local autofluorescence beneath appressorium", suggesting a more efficient growth of the pathogen from attacked epidermal cells into the underlying mesophyll. Further experiments focused on ABA and its interference with the resistance of barley against M. oryzae; our observations with GA 3 will be followed up elsewhere. Since our results pointed to a potential function of ABA in the initial infection process, we evaluated early penetration events of M. oryzae on barley leaves harvested at different time points after inoculation. Again, individual infection sites were inspected in a quantitative manner and assigned to the categories described above. At 48 h p.i. the number of infection sites grouped into the category "local autofluorescence beneath appressorium" was significantly less in ABA-treated (60%) as compared to mocktreated plants (70%) (Figure 3). This phenomenon was accompanied by more infection sites in the category "infection hyphae in epidermal cell without autofluorescense" for ABA-treated plants. Taken together, these results may be interpreted as if the ABA-treatment negatively interferes with early pathogen recognition by the plant. An alternative interpretation could be that the ABA-treatment directly influenced biosynthesis or accumulation of autofluorescent material. Strikingly, the frequency of interaction sites assigned to category "infection hyphae in epidermal cell without fluorescence" declined dramatically from 48 to 72 h p.i. for ABA-treated plants whereas the frequency of interaction sites found for the category "autofluorescence, collapsed mesophyll cells" increased at the same magnitude ( Figure 3). This indicates a correlation of diminished autofluorescent response in attacked epidermal cells with accelerated pathogen spreading into the mesophyll and is in accordance with observations previously reported by Zellerhoff et al. [13,21]. Concomitantly, the frequency of interaction sites assigned to the Figure 1. Bars represent means and standard deviations of four leaves with at least 100 interaction sites evaluated per leaf. Significant differences were determined for each category using One Way ANOVA (p ≤ 0.05) and marked by different letters. The experiment was repeated once with a similar result. category "local autofluorescence beneath appressorium" was almost equal between 48 and 72 h p.i. for ABAtreated plants (Figure 3), suggesting that at these sites fungal infection was aborted. So far, all experiments on the influence of ABA in the pathosystem barley/M. oryzae were done solely with the cultivar Ingrid. It could not be excluded, therefore, that the observed response to ABA was a specific feature of this particular cultivar. To address this question, we extended the study to seven barley cultivars encompassing spring and winter varieties. All plants were sprayed with a 20 μM ABA solution seven days after sowing and inoculated with M. oryzae isolate TH6772. Disease symptoms developed on leaves of all cultivars, indicating a compatible interaction with the chosen pathogen isolate ( Figure 4). Quantitative differences in the number of lesions per leaf were found on mock-treated plants which revealed that the cultivars exhibited different levels of basal resistance against M. oryzae. Thus, on cv. Ingrid on average only two to five lesions were found per leaf of mock-treated plants. The number of disease symptoms per leaf increased for ABA-treated Ingrid-plants to 26, which was the highest relative rise within this experiment ( Figure 4). For Steptoe, Morex, Golden Promise, Hannah and Sultan5 the number of lesions on ABAtreated plants was twice as high as on mock-treated plants of the same cultivar ( Figure 4). The cultivar Pallas was an exception in this regard, since the overall number of lesions on untreated plants was highest (62 lesions per leaf ) and ABA-treatment did not further increase disease severity. The disproportionately higher numbers of lesions on cv. Pallas may indicate a compromised basal defence of this cultivar against M. oryzae isolate TH6772. In case this impairment affects a resistance pathway that is influenced by ABA, additional ABA would not lead to a further decline in resistance. Reduced ABA-content enhanced resistance of barley against M. oryzae Hitherto, our results accounted for a regulatory function of ABA in resistance of barley against M. oryzae. To further validate this finding in an independent experimental set-up, we evaluated whether reduced levels of ABA would lead to the opposite effect, i.e. an increase in resistance of barley to this pathogen. Therefore, we made use of the existing barley mutant Az34 which is impaired in the ability to produce ABA due to a mutation in a gene controlling a molybdenum cofactor [22]. This mutation results in deficiency in molybdoenzymes such as aldehyde oxidase which e.g. has ABA aldehyde, a putative ABA precursor, as substrate [22]. Az34 was generated in the genetic background of cultivar Steptoe for which we already had shown that it is susceptible to M. oryzae isolate TH6772 and that exogenous application of ABA increased the number of lesions (Figure 4). Macroscopic comparison of inoculated leaves from Steptoe wild type plants with the Az34 mutant indicated a slightly lower disease severity on mutant leaves ( Figure 5A) which was quantitatively confirmed by lesion counting ( Figure 5B). A macroscopically clearer result was obtained by inoculation of both genotypes with M. oryzae isolate BR32 which caused larger lesions on infected leaves ( Figure 5A). Even in this case a significant reduction in the number of lesions was observed on mutant leaves ( Figure 5B). Additionally, a microscopic analysis of cellular defence reactions was performed, using the classification scheme described above (Figures 2 and 3). Significant differences between Steptoe and Az34 mutant plants were observed for the categories "local autofluorescence beneath appressorium" and "autofluorescent, collapsed mesophyll cells" (Figure 5C). The frequency of interaction sites grouped in the first category was higher in the mutant as compared to Steptoe while the frequency of interaction sites assigned to the latter category was lower, indicating more efficient block of penetration and less effective invasion of the pathogen into the mesophyll of mutant plants. This result was found with both M. oryzae isolates TH6772 and BR32, underpinning the general validity of the observation. We verified our finding that the reduced ABA-content in Az34 mutant plants was the cause for a lower degree of susceptibility against M. oryzae by chemical complementation. Therefore mutant plants were sprayed with a 20 μM solution of ABA prior to inoculation. Indeed, exogenous application of ABA slightly but significantly increased the number of lesions on Az34 mutant plants to a level as observed on wild type plants ( Figure 6). Interestingly, the number of disease symptoms on chemically complemented Az34 mutant plants was still lower than observed for ABA-treated Steptoe wild type plants. Endogenous ABA-levels were 3.2 ng per g fresh weight for the cultivar Steptoe and approximately half of that for the Az34 mutant (Figure 7), indicating that ABA-biosynthesis was compromised rather than completely abolished in the mutant. Endogenous ABA-levels correlated with susceptibility of cultivars but were not affected by infection Our experiments revealed a higher susceptibility of barley cv. Steptoe to infection with M. oryzae as compared to cv. Ingrid ( Figure 4) and an increase in susceptibility to infection in both cultivars after ABA treatment. Endogenous ABA level in Steptoe was twice as high as in Ingrid ( Figure 7A), corroborating the role of ABA in susceptibility. ABA analysis in further cultivars and in the mutant Az34 showed that the ABA level in Steptoe was not unique and that the mutant Az34 contained a comparable level of ABA to cv. Ingrid ( Figure 7A). Because ABA is known to suppress the SA-dependent defence pathway [2,9,23,24] as well as SA-mediated induction of systemic acquired resistance [25], we determined the content of free SA in leaf extracts of the same cultivars as used for ABA analysis. Interestingly, SA and ABA concentrations were correlated in the different barley genotypes ( Figure 7B mock-treated cv. Ingrid plants were harvested in a time course and subjected to HPLC-MS analysis. Although some variation in ABA-content did occur during the observation period, no significant differences were found between mock-treated and inoculated plants (Figure 8). Discussion The phytohormone ABA is best known to be involved in seed dormancy and senescence. Also a function of ABA in controlling stomatal aperture and in plant responses to environmental changes such as water deficiency was demonstrated [26]. More recently a new facet was added to this picture by showing that ABA is a modulator of plant pathogen interactions. Depending on the pathosystem under investigation, the ABA-effect can range from promoting disease to increase resistance [9,27]. Our results show that exogenous application of ABA to barley compromises resistance against M. oryzae in a quantitative manner (Figure 2A). We investigated the ABA-mediated increase in susceptibility in detail by a quantitative cytological assessment of early infection stages of M. oryzae. In ABA-treated plants fungal infection sites were significantly less frequently grouped into the category "local autofluorescence beneath appressorium" at 72 h p.i.; instead, the fungus was more frequently able to cause cell collapse in the mesophyll ( Figure 2B). This result suggested an enhanced penetration success and a more rapid transition of M. oryzae from the epidermis into the mesophyll. A similar effect on diminishing the basal defence of barley against M. oryzae was reported for the application of Cytochalasin E, an inhibitor affecting the actin cytoskeleton [17]. Further evidence that ABA supports the invasion of M. oryzae into barley leaves was provided by a comparison of the infection progress at different time points after inoculation. At 48 h p.i. M. oryzae infection hyphae that did not cause accumulation of autofluorescent material in epidermal cells were found more often after ABA treatment than in untreated controls ( Figure 3). This can be accounted for interference of ABA with the recognition of the fungus by its host, facilitating unnoticed penetration, or by direct inhibition of a biochemical process that leads to the accumulation of autofluorescent material. The latter hypothesis is corroborated by a report that ABA down-regulated phenylalanine ammonia-lyase, an enzyme generating autofluorescing phenolic compounds, e.g. in soybean [28]. The effect of ABA on the recognition of a pathogen by its host is also conceivable because ABA-treatment increased the resistance of barley against powdery mildew and enhanced the susceptibility of rice plants to M. oryzae [14,15]. A further example for such ambivalence was shown for the inverse effectiveness of the mlo resistance allele against these pathogens [19]. This phenomenon may be explained by different life-styles, biotrophy versus hemi-biotrophy, of these pathogens. Noteworthy, our results are in accordance with the work published by Koga et al. [14], indicating a host plant-independent mechanism by which ABA enhances susceptibility to M. oryzae. Koga and coworkers found that increased de novo synthesis of ABA under low temperature conditions is responsible for Figure 6 Chemical complementation of Az34 mutant phenotype by ABA-treatment. Leaves of seven-day-old barley plants from cultivar Steptoe or mutant Az34 were sprayed either with abscisic acid (20 μM) or mock solution. Inoculation was done one hour later with M. oryzae isolate TH6772 at a spore density of 200,000 conidia mL −1 . Pictures were taken seven days post inoculation. Quantification of disease severity was done by counting blast lesions. Bars represent means and standard deviations of ten leaves and significant differences (t-test, p ≤ 0.05) are indicated with an asterisk. The experiment was repeated once with a similar result. rendering rice plants more susceptible to M. oryzae. This finding was supported by our results with barley mutant Az34, which is impaired in de novo biosynthesis of ABA after water stress [22], and which we found to be more resistant to M. oryzae ( Figure 5). The role of ABA in these phenomena was confirmed by chemical complementation: application of ABA onto leaves of mutant plants reestablished higher susceptibility against the pathogen ( Figure 6). We could not detect an increase in ABA-levels in barley leaves infected with M. oryzae (Figure 8), presumably because extraction of whole leaves masked effects occurring locally at infection sites. The effect of fungal infection on the ABA level in a host is known to vary even for the same pathogen. For instance, no increase of ABA in xylem of B. napus colonized with V. longisporum was observed [29], though infection of A. thaliana with the same fungus dramatically induced ABA levels in the shoot [30]. Jiang et al. [23] detected ABA in hyphae, conidia and culture media of M. oryzae, suggesting that the fungus might secrete this plant hormone to actively suppress plant defence. In this scenario, ABA most likely acts via its antagonistic interaction against SA-and ethylene-dependent signalling pathways in the resistance of rice against M. oryzae [23,31]. We have not found any negative correlation between basal levels of ABA and SA in barley. Performing Northern blot analysis, we also have not found a down-regulation of the SA marker gene PR1b after ABA-treatment in barley plants inoculated with M. oryzae (Additional file 1: Figure S2). Together this might indicate that suppression of the SA pathway alone might not be responsible for the ABA-mediated enhancement of susceptibility of barley to M. oryzae. Quantitative cytological assessment revealed that application of GA 3 , similar to ABA, led to a lower number of infections sites at which autofluorescence occurred beneath appressoria (Figure 2), a cellular reaction clearly associated with diminished penetration resistance [17]. This observation is in accordance with the results published by Yang and co-workes [32] who demonstrated that rice mutant plants with reduced GA 3 -level showed a higher degree of resistance against M. oryzae. Conclusion Elevated ABA levels function as susceptibility factor during pathogenicity of M. oryzae with different host plants such as barley, as shown in this study, and rice, as known from the literature. This phenomenon most likely depends on antagonistical effects disturbing balancing of the plant hormonal network. With respect to the capability of ABA in increasing resistance against powdery mildew on barley, our results with M. oryzae present an additional example of opposing effects of defence pathways in barley against biotrophic (powdery mildew) and hemi-biotrophic (M. oryzae) pathogens. The M. oryzae isolates TH6772 (obtained from Institute of Biochemistry, Facility of Agriculture, Tamagawa University, Machida-shi, Tokyo, Japan) and BR32 (kindly provided by D. Tharreau, CIRAD, Montpellier, France) were grown on rice leaf agar (water extract from 50 g l −1 rice leaves, 10 g l −1 soluble starch, 2 g l −1 yeast extract (Biolabor, Muenster, Germany), 15 g l −1 agar). Fungal culture plates were incubated at 22°C with a 16/8 h day/ night regime. For stimulation of sporulation black-light (310 to 360 nm) was added for 14 days during the illumination period. From these plates, fungal mycelium was scraped, washed off with distilled water and filtered through three layers of gauze. Conidia present in the filtrate were adjusted to a final concentration of 200,000 spores ml −1 in a solution containing 0.1% gelatine (v/v) and 0.05% Tween 20 (v/v). After spray inoculation with this spore solution, plants were kept in a moist chamber (26°C and nearly 100% relative humidity) for at least 22 hours and thereafter cultivated under growth chamber conditions as described above. Hormone application Solutions containing plant hormones were prepared at the following concentration in distilled water supplemented with 0.01% Tween 20 (v/v): i) 0.1 mM sodium salicylate (SA), ii) 20 μM 1-aminocyclopropane-1-carboxylic acid (ACC), iii) 20 μM indole-3-acetic acid (IAA), iv) 20 μM gibberellic acid (GA 3 ), v) 20 μM abscisic acid (ABA). All solutions except for SA were diluted from 4 mM methanolic stock solutions. For mock treatment a solution of Tween 20 and methanol at similar concentrations was prepared. Solutions were sprayed onto leaves of seven day old barley plants. Thereafter, the plants were incubated for one hour at growth chamber conditions and then inoculated. Microscopic analyses At different timepoints after inoculation, primary leaves were detached and placed in a clearing solution (0.15% trichloracetic acid (w/v) in 4:1 ethanol:chloroform (v/v)) for at least two days and then stored in 50% glycerol until evaluation. Fungal structures were observed by bright-field microscopy using a Leica-DMBRE (Leica Microsystems, Wetzlar, Germany). Deposition of autofluorescent material was observed with epi-fluorescent light using the same microscope (excitation filter 485 nm, dichroic mirror 510 nm, barrier filter 520 nm). Images were taken with a digital camera JVC KYF 750 (JVC Professional Europe Ltd, London, UK). Progress of fungal infection and corresponding plant reactions were assessed by quantitative cytology as described previously [17,19]. Therefore, at least 100 plant-fungus interaction sites were inspected per leaf and assigned to different categories (see Figure 1). Statistical analyses were performed with Sigma-Stat (Systat Software Inc., San Jose, California, USA). Significance of differences among means was determined by Student's t-test or an ANOVA with a Holm-Sidak-analysis (95% confidence) was performed. Phytohormone measurements by high performance liquid chromatography and mass spectrometry Each sample for phytohormone measurements was generated by pooling five primary leaves, immediately freezing them in liquid nitrogen and storing them at −80°C. Leaf material was subsequently ground in liquid nitrogen to homogeneity and 150 mg of this powder was used for extraction. The extraction was done avoiding light exposure to exclude cis-ABA conformation changes into the biological inactive trans-ABA. Samples were extracted as described in Häffner et al. [30] and for each sample 2 ng of the deuteriated internal standard D6-(2Z,4E)-ABA (D6-ABA) (Icon Services, NJ, USA) was spiked into the extraction solution. ABA and salicylic acid (SA) were monitored by HPLC-ESI-MS/MS as described in [30] using the mass transitions of m/z 262.8 → m/z 153 (8 eV) for ABA and m/z 268.9 → m/z 159 (9 eV) for D6-ABA and m/z 136.8 → m/z 93.0 (CE 14.5 eV) for SA. Quantification of ABA was performed with a calibration curve of the ratio of peak areas of the unlabelled standard to the peak area of the deuterium-labelled standard. SA was quantified with an external calibration curve obtained with pure standard. Additional file Additional file 1: Figure S1. Increase of barley susceptibility against M. oryzae after soil drench with ABA in different concentrations. Barley plants (cultivar Ingrid) were grown in soil for seven days and thereafter treated with either mock-solution or solutions containing different concentrations of ABA (20 mL per pot). After 48 hours plants were inoculated with M. oryzae isolate TH6772 (200,000 conidia mL −1 ) and seven days later disease severity was quantitatively evaluated. Therefore, typical lesions were counted per leaf and means and standard deviations were calculated from at least ten individual plants. Significant differences were determined for each treatment between ABA and mock using t-test (p ≤ 0.05) and marked with asterisks. The experiment was repeated once with similar results. Figure S2. Accumulation of barley PR1b-specific transcripts in response to ABA treatment and inoculation with M. oryzae. Seven day old primary leaves of barley cultivar Ingrid were sprayed either with abscisic acid solution (20 μM) or mock-solution and inoculated one hour later with M. oryzae isolate TH6772 (200,000 conidia mL −1 ). Five leaves were harvested per sample at time points indicated (h p.i., hours after inoculation). Total RNA was extracted and subjected to gel blot analysis as reported previously [21]. Equal loading of the gel with 10 μg of total RNA was monitored by ethidium bromide (EtBr) staining. Hybridization of the blot was done with an in vitro transcribed digoxigenin-labelled PR1b-specific probe. The experiment was repeated twice with similar results.

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Effect of Superheated Steam Treatment on Changes in Moisture Content and Colour Properties of Coconut Slices Drying is one of the methods to preserve the quality and prolong the shelf life of food. Coconut meat was sliced and dried using superheated steam oven at 140°C, 160°C and 180°C. Drying was carried out at different drying time (5, 10, 15, 20, 25 and 30 minutes). The effect of drying temperature and time on the moisture content and colour properties (L, a, b and BI) of the coconut slices were studied. The temperature and time significantly (p < 0.05) affected the moisture loss and colour values of coconut slices during superheated steam drying. The moisture content decreased with increased drying temperature and time. The values of L decreased with drying temperature and time. The a and b value of coconut slice dried at 140°C decreased initially then increased with time. Coconut slices dried at 160°C had their a values increased up to 20 minutes then decreased and b values increased up to 20 minutes then fluctuated. The a and b values of coconut slices dried at 180°C showed fluctuation. BI values of coconut slices increased with increasing drying time and temperature. Keywords— Coconut slices; Superheated steam drying; Moisture content; Colour I. INTRODUCTION Coconut (Cocos nucifera Linn) is one of the most widely cultivated and used tree in the world and is regarded as one of the most significant of all palms. Its nut provides a nutritious source of meat, juice, milk, and oil that has fed and nourished populations around the world for generations. At the same time, coconut tree also produce furniture, decorative materials, medicine and many more products [1]. Due to its versatility in many applications especially in the tropical and subtropical regions, the tree is also known as "tree of life" [2]. Similar to all high moisture fruits and vegetables, coconut meat has a very short shelf life and prone to microbial degradation. Hence, drying and preservation of coconut meat is very significant for further processing. Thermal processing is one of the main approaches of food preservation to inactivate enzymes, prevent the growth of deteriorative microorganisms which causes decay and reduce water activity via dehydration. However, during this method of handling, food material may be exposed to temperatures that cause undesirable effects on their quality and organoleptic properties mainly due to physiochemical changes in the tissue during drying [3], [4], [5]. Superheated steam dries materials by adding sensible heat to raise its temperature above the corresponding saturation temperature at a particular pressure. A drop in temperature will not result in condensation of the steam, in condition that the temperature is still higher than the saturation temperature at the operating pressure. The moisture evaporated from the product becomes part of the drying medium and does not need to be drained except when the pressure exceeds a set point, at which the extra steam may be released [6], [7]. Using superheated steam as a drying medium is beneficial since it could lead to energy saving if the exhaust (superheated steam) is used elsewhere in the plant and is not charged by the dryer. The oxygen free drying environment of superheated steam also improves product quality since no oxidation or combustion reaction taken place. In addition, risks of fire or explosion hazard could also be avoided. Closed system of superheated steam dryer enable odours, dust or toxic compounds to be removed and collected before in contact with the environment. Superheated steam also allows sterilization, pasteurization and deodorization of food product during drying [6], [8], [9], [10]. An object's colour is one of the most significant quality factors and plays a major role in processing, appearance and consumer acceptability of food materials. Visual appearance of a food is the first impression made by a consumer at the point of purchase [4]. Colour of fruits and vegetables are derived from natural pigments including water soluble anthocyanins (red, blue), betalains (red), flavonoids (yellow), fat-soluble chlorophylls (green) and carotenoids (yellow, orange, and red) [11]. Colour can be associated with other traits such as nutritional, sensory and visual or non-visual defects and aids to regulate them immediately [12]. Factors such as enzymatic browning and non-enzymatic (maillard reactions), and processing environments like temperature, time, pH, acidity and oxidation, are responsible for the destruction of pigment and colour changes of food during processing [14]. The colour measurements of food could be used as an indirect way to determine the colour change, since they are faster and simpler than chemical analysis. Hunter colour parameters lightness (L), redness(a) and yellowness (b) have been widely used for describing visual colour changes during thermal processing of fruits and vegetables, providing useful information for quality control [3], [4], [5], [13]. For L value which measures the luminosity of sample, the value ranges from 100 for a perfect white to 0 for a perfect black. Positive a value indicates redness while negative value indicates greenness. Positive b value indicates yellowness and negative value points to blueness. Browning index (BI) symbolizes the purity of brown colour and has been reported as a crucial parameter in drying processes where enzymatic and non-enzymatic browning occurs [3], [4], [5]. While there are many literature studies on the quality changes of food processed by superheated steam, no work has been done on coconut slices. The purpose of this work is to study the effect of different drying condition of superheated steam on the moisture content and colour properties of coconut slices. A. Sample Preparation Mature coconut samples were purchased from a wet market in Pulau Penang, Malaysia. They were stored at 4°C in refrigerator. Prior to the drying experiments, the samples were taken out from the refrigerator and left for about 45 minutes at room temperature. Then, they were opened and the mature coconut meat was sliced manually to the size of 1.3-1.5mm thick, length of 60-65mm and breadth of 11-12mm. B. Drying Superheated steam oven (Healsio, AV-1500V, SHARP, Japan) in superheated steam mode was used for drying the coconut slices. The oven was preheated to the drying temperature. The drying was carried out at 140°C, 160°C and 180°C. Drying time of 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes and 30 minutes was used for each drying temperature. Each drying condition was done separately and the dried sample was packed in polyethylene plastic bags before further analysis. C. Moisture Determination Dried coconut slices were subjected to moisture content determination using Mettler Toledo HB43-S Halogen Moisture Analyser immediately after each treatment of drying. The drying temperature operated by the analyser was 115°C, approximately 4g of sample was used for each measurement. Determination for each treatment was done in triplicate. D. Colour Measurement The surface colour of the dried coconut slices were measured using spectrophotometer (CM-3500D Minolta Spectrophotometer, Minolta, Japan). The instrument was calibrated before the experiments with a zero calibration box and a white calibration plate. Pulsed xenon arc lamp with reflectance of d/8 is the light source. 8mm measuring head hole was used and each measurement time lasted 2.5 seconds. The coconut slices was scanned at 3 different locations to determine the average L, a, b values during the measurements. Browning index (BI) were calculated from the Hunter L, a, b values and used to describe the colour change during drying. where E. Statistical Analysis Statistical analysis was conducted using IBM SPSS 21.0 (IBM Corp., Armonk, NY, USA). All data were analysed using analysis of variance (ANOVA). Duncan's test was used for multiple comparisons of mean values. Mean values were considered at 95% significant level (x= 0.05). III. RESULTS AND DISCUSSION The changes in the moisture content of coconut slices during drying by superheated steam at 140°C, 160°C and 180°C as a function of drying time were presented in Fig. 1. It could be clearly seen that drying at 180°C leads to more drastic moisture loss compared to 140°C and 160°C. While drying at 140°C gave a more gradual moisture loss to the coconut slices. At 95% confidence interval, the drying temperature and drying time of superheated steam significantly affect the moisture loss during drying process. L, a, b and BI values of coconut slices dried at different temperature and time respectively. The applied two-ways ANOVA showed that temperature and time significantly (p < 0.05) affected the colour properties of coconut slices during superheated steam drying. L values for superheated steam drying showed relatively moderate decrease as time elapses. The L value of coconut slices dried at higher temperature (180°C) and longer time declined faster. It indicated that, higher processing temperature and longer drying time causes higher level of darkening. Similar results were reported for the L value of the coconut research done by Niamnuy and Devahastin [15]. The a value shows the redness of the products. The variation of a value during drying is shown in Fig. 3. There was gradual decrease in a value at the initial period of superheated steam drying at 140°C and 180°C. No initial decrease in a value was observed in superheated steam drying at 160°C. The a value of coconut slices dried at 160°C increased sharply then start to decrease slightly after drying of 20 minutes. At the same time, different trend was observed in superheated steam drying at 180°C, where the a value decreased slightly after 20 minutes drying time then increase again after 25 minutes. Increased of a value during drying could be due to the formation of browning. The browning pigments formed in this study could be due to nonenzymatic browning caused by Maillard reaction. Maillard reaction occurs when amino acids and reducing sugars, proteins and/or other nitrogen-containing compounds are heated together [12]. The b values which shows the yellowness of coconut slices during superheated steam drying is presented in Fig. 4. Gradual decrease in b value was observed at the initial period of superheated steam drying at 140°C, and then the value increased with extending of drying temperature. No initial decrease in b value in superheated steam drying at 160°C and 180°C. However, the b value of coconut slices dried at 180°C showed fluctuations. Different trend was observed in coconut slices dried at 160°C where the b value after drying time of 20 minutes decreased slightly then increased again. The effects of superheated steam drying temperature and drying time on the browning index of coconut slices are presented in Fig.5. Browning index enable more accurate estimation of drying time at which browning is initiated. The BI increased as drying temperature and time increased. BI of coconut slices dried at 140°C increased in a trend that is persistent while coconut slices dried at 180°C rise sharply. IV. CONCLUSIONS The effects of superheated steam drying temperature and drying time on the moisture content and colour properties of coconut slices were examined in this study. The moisture content of coconut slices decreased with extending of drying time and temperature. The lightness of coconut slices decreased with increased in drying temperature and time. It was observed that the redness and yellowness of coconut slices dried at 140°C decreased initially then increased with time. Coconut slices dried at 160°C had their redness increased up to 20 minutes then decreased and yellowness increased up to 20 minutes then fluctuated. The redness and yellowness of coconut slices dried at 180°C fluctuated. In addition, the browning index values of coconut slices increased with increasing drying time and temperature.

v3-fos

2016-05-04T20:20:58.661Z

2015-03-17T00:00:00.000Z

6587146

s2

Comparative Transcriptome Analysis of Anthurium “Albama” and Its Anthocyanin-Loss Mutant Anthurium is one of the most important tropical ornamental plants in the world. The traded value of anthurium is second only to that of tropical orchids among the tropical flowers. The spathe is the main ornamental organ and its color variation mainly arises from anthocyanin contents. Understanding the molecular regulation of spathe color will accelerate new variety creation of anthurium. To announce gene expression differences between Anthurium andraeanum ‘Albama’ and its one unique anthocyanin-loss mutant, we collected spathes of the wild-type and the mutant from two stages in spathe development (the flower separates protrude from the sheath and the spathe is fully expanded) and extracted total RNAs for transcriptome profiling. Using short read sequencing technology (Illumina), 51,955,564, 53,822,224, 54,221,990 and 52,276,418 sequencing raw reads, respectively, for wild-type and mutant in the two stages were assembled de novo into 111,268 unique sequences (unigenes) with a mean length of 652 bp. 47,563 unigenes had significant hits to the sequences in the Nr database, and 32,768 unigenes showed significant similarity to known proteins in the Swiss-Prot database. 28,350 and 19,293 unigenes had significant similarity to existing sequences in the KEGG and COG databases, respectively. Further, analysis of differentially expressed genes in the comparison between wild-type and mutant and between the two different developmental stages was carried out, indicating that the expression of an extensive set of genes changed as the result of mutation. Taken together, these data demonstrated that the Illumina sequencing allowed de novo transcriptome assembly and could obtain differentially expressed genes between A. andraeanum wild-type and the anthocyanin-loss mutant. The expression differences of AN2 and UFGT might cause the anthocyanin-loss mutation. Introduction found the accumulation of Bronze2 appeared to be limited by stringent posttranscriptional regulation. Anthocyanin production is differently regulated in monocot and dicot species. In the monocot maize, the anthocyanin biosynthesis genes are activated as a single unit by a ternary complex of MYB-bHLH-WD40 transcription factors (MBW complex). In the dicot Arabidopsis, anthocyanin biosynthesis genes can be divided in two subgroups: early biosynthesis genes (EBGs) are activated by co-activator independent R2R3-MYB transcription factors, whereas late biosynthesis genes (LBGs) require an MBW complex. In addition, a complex regulatory network of positive and negative feedback mechanisms controlling anthocyanins synthesis in Arabidopsis had been described [15]. Anthocyanin biosynthesis, glycosylation, transport and accumulation all influence flower color. All the data indicate that, although transcription factors from different species are involved in the same biosynthetic process, they are characterized by a different specificity in their target genes. Bioinformatic analysis may therefore help in selecting the proper heterologous regulators. In this study, we built comparative transcriptomes between anthurium wild-type sample of red spathe and mutant sample of white spathe both in stage 6 and stage 3. As a result, we identified the genes that related to anthocyanin biosynthesis, glycosylation, transport and accumulation from all differential expression genes sequences. At last, we concluded that UFGT, GST and MRP genes expressing in lower level might cause the mutation of anthocyanin-loss, although a lot of genes expressing level had changed. Illumina sequencing and de novo assembly In this study, four cDNA samples from the spathes of wild-type A. andraeanum "Alabama" in stage 6 (WS6) and stage 3 (WS3) and its anthocyanin-loss mutant in stage 6 (MS6) and stage 3 (WS3) were prepared and subjected to Illumina deep sequencing (Fig. 1). The output of sequenced data from WS6, WS3, MS6 and MS3 were 51,955,564, 53,822,224, 54,221,990 and 52,276,418 qualified Illumina reads respectively with 90 bp mean length. Then, using trinity [16], these clean reads were assembled to unigene sequences. Finally, unigenes of the four samples were summarized into an All-unigene with 111,268 sequences with mean size of 652 bp, which including all non-redundant unigene sequences of both four samples (Table 1). Fig. 2 showed the distribution of transcripts length, with the length of transcripts ranges from 200 to 11534. Annotations of sequences For annotation, unigene sequences of A. andraeanum were first searched using BlastX against the non-redundant (Nr) database of NCBI with a cut-off E-value of 1e-5. Using this approach, 47,563 unigenes (43.4% of all unigene sequences) returned an above cut-off BlastX result. The E-vaule distribution of BlastX result was shown in Fig. 3A. Of the search results, 11.4% of the matches were with a E-value of 0, meanwhile, 31.69% of the matches were with a E-value less than 1e-60. Correspondingly, the similarity ditribution of best matches were shown in Fig. 3B, 15.4% of the matches were of high similarity ranging from 85% to 100% and 39.2% of the hits were of similarity ranging from 60% to 80%. Moreover, the species-based distribution of best matches were shown in the Fig. 3C. The result of homology analysis indicated that 32.7% of the sequences of A. andraeanum showed the greatest similarity to proteins of Vitis vinifera, whilst proteins of Amygdalus pesica (7.4%), Ricinus communis (6.5%), Populus balsamifera subsp. tricholarpa (5.3%), Clycine max (4.0%) and Fragaria vesca subsp. Vesca (3.8%) showed a lower similarity to sequences of A. andraeanum. Then, these unigene sequences were second searched using BLASTx against the Swiss-Prot database using a cut-off E-value of 1e-5, with 32,768 unigenes (29.8% of all unigene sequences) returned an above cut-off BLAST result. GO assignments were used to classify the functions of the unigenes based on Nr annotation using blast2go [17]. Of the unigenes with significant hits in Nr database, 28,289 unigenes were categorized into 64 functional groups (S1 Table). Amongst the sub-categories of three main GO categories, cell (10.6%), cell part (10.6%), organelle (8.6%), cellular process (7.9%), metabolic process (7.7%), catalytic activity (7.0%) and binding (7.0%) occupied the major proportion. Rather, only a few unigenes were assigned into categories of virion, viron part, extracellular matrix part, metallochaperone activity, channel regulator activity, protein tag and viral reproduction (Fig. 4). To further evaluate the completeness of our transcriptome library and the effectiveness of our annotation process, we searched the annotated sequences for the genes involved in COG classifications. In total, out of 47,563 Nr hits, 19,293 sequences have a COG classification (Fig. 5). These sequences were classfied into 24 categories, of which the categories included General function prediction only (11.7%), Translation, ribosomal structure and biogenesis (11.2%), Transcription (9.5%), Replication, recombination and repair (8.4%) and Function unknown (8.3%) were the top 5 categories that sequnces be categorized (S2 Table). In the meanwhile, of the 24 categories, Defense mechanisms (13; 0.023%) and Nuclear structure (2; 0.0036%) were the least represented. Furthermore, A. andraeanum unigene sequences were aligned against several protein databases using BlastX (Evalue<1e-5) untill as much as unigene sequences have hits. CDS of unigenes have no hit in blast were predicted by ESTScan [19] and then translated into peptide sequences. In the end, we obtained a "Blast-CDS" data including 47,123 unigene sequences and an "ESTscan-CDS" including 5,243 EST sequences. Unigene expression analysis Genome-wide expression analysis was carried out to study the differences between spathes of wild-type and mutant during different developmental stages. The analysis found that 428, 787, 3,534 and 4,187 genes had different expression levels in the comparisons between WS6 and MS6 (WS6 vs MS6), between WS3 and MS3 (WS3 vs MS3), between MS6 and MS3 (MS6 vs MS3) and betweem WS6 and WS3 (WS6 and WS3) respectively (P-value <0.001; Log2 fold changes2 or -2). Fig. 6A, 6B, 6C and 6D showed the expression pattern for WS6 vs MS6, WS3 vs MS3, MS6 vs MS3 and WS6 vs MS3 respectively. Correspondingly, the Fig. 7 illustrated the gene expression changes: for WS6 vs MS6, there are 199 up-regulated genes and 229 downregulated genes; for WS3 vs MS3, there were 484 up-regulated genes and 303 down-regulated genes; for MS6 vs MS3, there were 1137 up-regulated genes and 2397 down-regulated genes; for WS6 vs WS3, there were 1467 up-regulated genes and 2720 down-regulated genes. Using GO-TermFinder [20], GO functional enrichment analysis was carried out to characterize the functions of differentially expressed genes (DEGs). The result revealed that DEGs were enriched into 30 functional groups (Corrected Pvalue<0.05) (S4 Table). DEGs in WS6 vs MS6 were enriched in the categories of virion part and virion and DEGs in WS3 vs MS3 were enriched in the categories of membrane, metabolic process, catalytic activity and cellular component organization, showing a different functional view of DEGs between wild-type and mutant in spathe developmental stage 6 and stage 3. Furthermore, the DEGs in WS6 vs WS3 and MS6 vs MS3 were both enriched in 14 categories, inlcuding symplast, biological regulation, growth, pigmentation, envelope etc. (S4 Table), indicating that both wild-type and muntant have similar and extensive changes in gene expression level during different developmental stages of spathe. To further explore the functions of DEGs, KOBAS [21] was used for pahtway enrichment annalysis. The DEGs in MS6 vs MS3 and WS3 vs MS3 were both enriched in the Homologous recombination pathway, while the DEGs in MS6 vs WS6 and WS6 vs WS3 were both enriched in the pathways of the Ubiquinone and other terpenoid-quinone biosynthesis, RNA transport, mRNA surveillance pathway, Plant hormone signal transduction, Oxidative phosphorylation, Flavonoid biosynthesis, Regulation of autophagy etc. (Table 2; the complete information were summaried in S5 Table). In this study, we focused on genes involved in anthocyanin biosynthesis and pathways related to anthocyanin biosynthesis such as ABC transporters, Glutathione metabolism, although changes of anthocyanin biosynthesis affected expression of many other pathways. Detection of sequences related to anthocyanin biosynthesis The plant flavonoid pathway lead to flavones and anthocyanins synthesis [2]. According to the flavonoid pathway and all differentially expressed sequences data, we screened 18 fragments which are homologous to the genes related to phenylpropanoid pathyway, flavonoid biosynthesis pathway and anthocyanins transport pathway (Table 3; the complete information of the 18 DEGs was summarized in S6 Table). The analysis of differential gene expression in MS6 vs WS6 showed that c3000005417_g1_i11 (DFR), c30000038819_g1_i1 (UFGT) and c200000509_g5_i1 (UFGT) were down-regulated in MS6. And c200000509_g5_i1 was also down-regulated in differential gene expression analysis of MS3 vs WS3. Especially, c50000092719_g1_i1 (AN2), homologous AN2 gene, only expressed in the full spread spathe of the mutant (MS6) but very low in the unexpanded spathe of the mutant (MS3). We speculated that the expressional difference of AN2 between the wild type and the mutant and between different developmental stages of spathe affected the biosynthesis of anthocyanin, although AN2 were lowly expressed MS6 with FPKM value of 9.39 (25 fragments count). And other genes' expression levels may also be associated with the color mutation. We isolated the full-length cDNA of AN2 from A. andraeanum and designated as AnAN2. Then the function of AnAN2 were confrimed by a inhibition of anthocynains biosynthesis phenotypes in A. thaliana caused by ectopic expression of AnAN2. AnAN2 driven by the CaMV 35S promoter was transformed into A. thaliana ecotype 'Columbia' plants. Independent 35S::AnAN2 transgenic A. thaliana plants were screened on MS medium containing 50 mg/L Hyg. The 35S::AnAN2 transgenic plants appeared significantly anthocyanin biosynthesis phenotypes both in seedlings and adult plants, indicating AnAN2 act as a negative regulator of anthocyanin biosynthetic pathway (S1 Fig.). Verification of comparative transciptome results Several genes whose expression was altered to varying degrees in the mutant were chosen for verification of the comparative transciptome results. The results of qRT-PCR perfomed on RNA prepared from the conserved full spread young spathe and unexpanded at-80℃ were Comparative Transcriptome Analysis of Anthurium "Albama" agreement with the alterations in gene expression detected by the transcriptome analysis. This agreement was seen for the direction of change, and was also generally seen for the magnitude of change, in gene expression (Fig. 8). For these experiments, cDNA aliquots were taken from the same samples used for transcriptome sequencing. These results indicated that transcriptome sequencing accurately reflected genome-wide changes between the wild type and the mutant. For the low expression of AN2 in our transcriptome data, we confirmed especially the qPCR products was specific to AN2 by gel electrophoresis and sequencing (S2 Fig.). Anthocyanin accumulation To examine the accumulation of anthocyanin in the A. andraeanum, spathe, petiole and leaf extracts were subjected to high-performance liquid chromatography (HPLC) analysis. The HPLC data show that the main anthocyanins, including peonidin-rutinoside, anthocyanidin-rutinoside and pelargonidin-rutinoside, apeared in the wild-type spathe, petiole and leaf but did not in the both of mutant spathe, petiole and leaf, indicating that the mutant was anthocyanin-loss (S7 Table). Sequencing and annotation With the devlopment of RNA-seq, transcriptome has become an available and successful alternatvie to in-depth detect difference of gene expression in wild-type and mutant or different cutivars of certain species, such as Enoch et al. [24] characterized a natrual dicromatism of the annual fish Nothobranchius furzeri through RNA-seq. To date, anthocyanin biosynthesis was explored by RNA-seq in many studies, such as Benhong Wu et al. [25] carried out a genomewide transcriptional profiles of berry skins of two cultivars of vitis vinifera in which anthocyanin biosynthesis is sunlight-dependent and independent and Daqiu Zhao et al. [26] revealed coordinated expression of anthocyanin biosynthetic genes mediating yellow formation in Paeonia lactiflora Pall by transcriptome sequencing. Anthurium is one of the most important tropical ornamental plants in the world, but the genomic information available for this species was still limited, although Danqing Tian et al. have characterzied the Anthurium transcriptome of a mixed sample of seedlings of cold treated and control plants [27]. We constructed a transcriptome of four samples from spathes of wilde-type and anthocyanin-loss mutant in flower developmental stage 6 and stage 3, which provided a Comparative Transcriptome Analysis of Anthurium "Albama" more sufficent and detailed transcriptome information of spathes and will faccilitate the subsequent stuties. Interestingly, a different species-based distribution of best matches of BlastX searching again NR database compared to the transcriptome Danqing Tian et al. characterized was presented, the latter showed the closest species was Oryza sativa and followed by A. thaliana, while our results showed that the closest species was Vitis vinifera and followed by Amygdalus pesica, as the number of sequences annoted increased and tissue specificity of gene expression. Structural genes and regulators related with anthocyanin biosynthesis Anthocyanin represents the major red, purple, violet and blue pigments in many flowers and fruits. It is produced by a specific branch of the flavonoid pathway, which is differently regulated in dicot and monocot species. In the dicot, such as Arabidopsis, anthocyanin biosynthesis genes can be divided in two subgroups: early biosynthesis genes (EBGs), i.e. CHS, CHI, F3H, F3'H, FLS, and the late biosynthesis genes (LBGs), i.e. DFR, ANS/LDOX, UFGT, LAR, ANR. A regulatory system based on the cooperation between MYB and bHLH proteins that control floral pigmentation is common in many dicotyledonous species. In petunia and morning glory, an MYB-bHLH-WD40 transcription factors (MBW complex) and a regulatory network similar to that of Arabidopsis has been identified. In monocot maize (Zea mays), two types of transcription factors, a MYB-related protein and a bHLH-containing protein, interact and activated the anthocyanin biosynthetic genes (CHS, CHI, F3H, DFR, ANS/LDOX and UFGT) as a single unit [15]. Although transcription factors from different species are involved in the same biosynthetic process, they are characterized by different target genes. In maize, mutations in the pr1 locus lead to the accumulation of pelargonidin (red) rather than cyaniding (purple) pigments in aleurone cells where the anthocyanin biosynthetic pathway is active [28]. The mutation of anthocyanin-loss may rise from the change of the genes in anthocyanin biosynthesis, glycosylation, acyltransferation and transport. Regulation of anthocyanin biosynthesis in spathe differs from other described species, because dihydroflavonol 4-reductase (DFR) is a key regulatory point and a complex mix of developmental and environmental control signals in described plants [2]. The flavonoid pathway was regulated in a spatial and temporal way during plant development. Regulation of structural genes expression is orchestrated by a ternary complex involving transcription factors from the R2R3-MYB, basic helix-loop-helix (bHLH), and WD40 classes [29]. Repressors of MYB, one special kind of bHLH protein, could form polymer with MYB activator to repress transcriptional activator. They could competitive bind bHLH promoter binding domain with MYB activator to repress bHLH transcription factors. They could competitive bind bHLH transcription factor with MYB activator to inhibit the formation of transcriptional activation complexes. They also could competitive bind promoter binding region of structural genes to stop their transcription [30]. In this study, DFR had no significant difference between the wild-type samples and mutant samples. Meanwhile, CHS, F3H and ANS were also absent in the differential expressed genes list of comparison of wild-type and mutant. Other genes, such as CHI and ANR, were with higher level in the full spread spathe of the mutant than that of the wild-type. It meant that these structural genes and regulators were neither responsible for the anthocyanin-loss mutation, although some regulators changed. Amongst differential expressed regulator genes, PL, MYCA1, C1, MYB1 and UMYB7 expressed with higher level in wild-type than in mutant. Interestingly, AN2, which positively regulates anthocyanin biosynthesis in lily [31], had 0 fragments count in wild-type full spread spathe, but 25 fragments count in that of the mutant. Using the same samples, young full spread spathe, qRT-PCR verified the result. Meanwhile, ANR, C1, CHS, DFR, LAR, F3'H and F3H were both up-regulated in MS3 and WS3 in the comparasion of MS6 vs MS3 and WS6 vs WS3, indicating that the genes or regulators related to anthocyanin synthesis expressed differently in different development of the spathe as reported by Collette [1]. However, AN2, ABC and UFGT showed a differently changing trend. This may be the result of mutation in A. andraeanum. Glycosylation, acyltransferation and transportation play important roles in keeping anthocyanin stable and demonstrating different colors in vacuole [9]. The identified UFGT genes had obvious expressional difference, which may the key genes lead to anthocyanin-loss of mutant. The genes involving in anthocyanin transportion we identified are homologous to GST and MRP. They were both significiantly up-regulatd in mutant than in wild-type with changes from 2 to 4 fold respectively, suggested that anthocyanin may negatively feedback to GST and MRP. So, we hypothesized the anthocyanin-loss mutation were caused by some regulators, such as AN2 and key genes of anthocynin glycosylation UFGT. Conclusions Summarily, this study successfully discovered the differentially expressed genes and regulators between the wild-type and the anthocyanin-loss mutant through comparison of the two transcriptome data. We hypothesized the anthocyanin-loss mutation are caused by expression changes of AN2 and UFGT genes. This hypothesis needs further verification. Plant sample preparation and RNA isolation A. andraeanum "Alabama" wild-type and its anthocyanin-loss mutant plants (New Plant Variety right: ZL201310140892.0, The Office for the Protection of New Varieties of Plant, MOA, P.R. China) were collected from a greenhouse located in the experimental area at the Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences (CATAS). Spathe tissues in stage 3 and stage 6 of the wild-type and the mutant were physically isolated and immediately frozen in liquid nitrogen. Total RNA was extracted from the spathe without spadix dehydrated for 8 min at 65 ℃ using CTAB extraction method. The RNA samples were treated with 10 units of DNaseI (Takara) for 30 min at 37℃ to remove the genomic DNA. The quantity and quality of the isolated total RNA was examined using spectrophotometry and gel electrophoresis. Library preparation for transcriptome analysis and sequencing Poly-A-containing mRNAs were purified from the total RNA samples using the OligoTex mRNA mini kit (Qiagen). The mRNA was then fragmented into small pieces using an RNA fragmentation kit (Ambion). Using these short fragments as the templates, the first cDNA strand was synthesized using random hexamer primers and reverse transcriptase (Invitrogen), and the second-strand cDNA was synthesized using DNA polymerase I and RNase H. The cDNA fragments were purified using the QiaQuick PCR extraction kit (Qiagen) and resolved with EB buffer for end reparation and poly (A) addition. The short fragments were then connected with sequencing adapters, and the products were subsequently purified and amplified via PCR to create the final cDNA libraries. The cDNA library was sequenced using Illumina HiSeq 2000, and the sequencing-derived raw image data were transformed by base calling into sequence data. The raw reads were cleaned by the trimming of adaptor sequences, empty reads and ambiguous nucleotides ('N' in the end of the reads). The reads obtained were then assembled using the Trinty software [16]. In the final step, BLASTX alignments (evalue<1e-5) between unigenes and protein databases, including Nr, Swiss-Prot, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of orthologous group (COG), were performed, and the best alignment results were used to decide the sequence direction of the unigenes. When a unigene happened to be unaligned with none of the above databases, ESTScan software was used to predict its coding regions and to decide its sequence direction [19]. Functional annotation and classification The assembled unigenes were compared with the sequences in the NCBI non-redundant protein (Nr) and Swiss-Prot protein databases using the BlastX algorithm with an evalue cut-off of 1e-5. The functional annotation by gene ontology (GO) terms was performed using the BLAST2GO program [17]. After getting GO annotations, WEGO software was used to undertake GO functional classification for all the unigenes and to investigate the distribution of gene function in the species at the macro level [32]. The COG annotation was performed using the BLASTX algorithm (evalue threshold: 1e-5) against the Cluster of Orthologous Groups database. The KEGG pathways annotation was performed by sequence comparisons against the Kyoto Encyclopedia of Genes and Genomes database using BLASTX with an evalue threshold of 1e-5 [18]. Normalization of genes expression levels and analysis of differential gene expression The gene abundance estimation and DEGs analyssis were carried out by trinity toolkit [16], which required bowtie [33], RSEM [34] and edgeR [35]. Reads of each samples were aligned to the transcriptome assembly by bowtie with a maxium insert size of 800 (default). Then gene abundance was estimated by RSEM, using Fragments Per kb per Million fragments (FPKM) method [36]. The cut-off value for determining gene transcriptional activity was determined based on a 95% confidence interval for all FPKM values of each gene. An FPKM filtering cutoff of 1.0 in at least one of the four samples was used to determine expressed transcripts. DEGs were then analysised by R Bioconductor package edgeR and selected on condition of p-value 0.001 and |log 2 (MS_RPKM/WS_RPKM)| 2. Hypergeometric test with Benjamini & Hochberg false discovery rate (FDR) were performed using the default parameters to adjust the P-value. GO category analysis was carried out using software Blast2GO mentioned above and GO functional enrichment analysis was carried out using GO-TermFinder [20]. KEGG pathway analyses of differentially expressed genes were performed using the KOBAS 2.0 (KEGG Orthology Based Annotation System) [21]. Quantitative real-time PCR (qRT-PCR) Real-time PCR reactions were set up with three biological replications and three technical replicates per experiment. The variance analysis (ANOVA) was performed for statistical analysis after logarithmic transformation of raw data. Total RNA was isolated from the samples and used for cDNA synthesis with the same procedures as detailed above. For qRT-PCR, the transcript levels of genes in the spathe of the wild type and the mutant were using the SYBR Green dye method. Each reaction buffer (10 μl) was composed of 50 ng of cDNA samples, 5 μl of 2× SYBR Green Master Mix Reagent (Applied Biosystems), and 0.2 μM of gene-specific primers (Table 4). Actin was used as an internal control to normalize the relative expression level of the analysed genes in wild type and the mutant anthurium, respectively. The thermal cycles used were as follows: 95 ℃ for 10 min, and 45 cycles of 95 ℃ for 5 s, 60 ℃ for 30 s. Each sample was amplified in four independent replicates. Relative gene expression was calculated according to the delta-delta Ct method of the system. The qPCR products were confirmed by both gel electrophoresis and sequencing. HPLC analysis of anthocyanin The spathe, leaf and petiole of A. andraeanum (1 g for each tissue) were ground in 1.5 mL of 70% methanol containing 2% formic acid, then centrifuged at 14,000 rpm for 10 min at. Then the supernatant was filtered through a 0.45-μm syringe filter before HPLC analysis. Anthocyanins were investigated on an Shimadzu HPLC equipped with a SPD-6VA UV-detector. Plant Transformation and analysis of transgenic plants The full-length cDNA for AN2 was cloned into the vector pMD18-T (Takara) under the control of the CaMV 35S promoter. The orientation of the plasmids was identified by PCR and used for further plant transformation. The plasmids were introduced in the Arabidopsis ecotype 'Columbia' plants using a floral dip method [37]. T1 seeds were screened on MS medium containing 50 mg/L Hyg. Then the positive seedlings were transferred to pots and grown in a growth chamber for futher analysis.

v3-fos

2017-08-02T23:07:27.829Z

2015-01-29T00:00:00.000Z

14928336

s2

Moderately enhancing cytokinin level by down-regulation of GhCKX expression in cotton concurrently increases fiber and seed yield Cotton is the leading natural fiber crop in the world. Cotton seeds are also an important oil and protein source. However, enhancement of fiber abundance usually leads to a smaller seed. Thus, it has become a challenge for cotton breeding to concurrently increase fiber yield and seed yield. To improve cotton yield, we elevated the endogenous cytokinin level in transgenic cotton by constitutive suppression of cytokinin dehydrogenase (CKX), a key negative regulator controlling endogenous cytokinin in plants. The slightly and moderately suppressed transgenic cotton plants showed normal growth and development, while the severely suppressed plants exhibited a typical cytokinin-overproduction alteration. The suppression of CKX led to an enhancement of endogenous cytokinins in transgenic cotton plants. Total cytokinins in moderately suppressed lines, CR-3 and CR-6, increased by 20.4 and 55.5 % respectively, and that in the severely suppressed line (CR-13) increased by 134.2 % compared to the wild type. The moderately suppressed lines showed a delay in leaf senescence, higher photosynthesis, more fruiting branches and bolls, and bigger seed size. Field trials showed that seed yield and lint yield of the moderately suppressed CR-6 line increased by 15.4 and 20.0 %, respectively. Meanwhile, the enhanced cytokinin level in transgenic cottons did not show significant influence on fiber qualities. Our data demonstrated that CKX is a promising gene for crop yield improvement. Electronic supplementary material The online version of this article (doi:10.1007/s11032-015-0232-6) contains supplementary material, which is available to authorized users. Introduction Cotton is one of the most valuable commercial crops in the world. In addition to the fiber used for textile manufacturing, cotton seed is an important source of oil and protein, and the seed hulls are used for cattle feed and mushroom production (Sunilkumar et al. 2006;Wilkins et al. 2000). Cotton fiber is derived from single epidermal cells of seeds. Enhancing the abundance of fiber usually leads to smaller seeds (Miller and Rawlings 1967;Zhang et al. 2005). Thus, it is a challenge for cotton breeding to concurrently increase both fiber yield and seed yield. Cytokinins are a group of phytohormones that regulate cell division and influence numerous developmental and physiological processes of plants (Werner and Schmülling 2009), including leaf senescence (Gan and Amasino 1995), vascular development (Mähönen et al. 2006), cell differentiation at shoot and root apical meristem (Wolters and Jürgens 2009), nutrient uptake and allocation (Séguéla et al. 2008), abiotic (Peleg et al. 2011;Rivero et al. 2007) and biotic stress responses (Choi et al. 2010;Siemens et al. 2006), and regulation of source-sink relationships (Roitsch and Ehneß 2000). Importantly, recent studies have revealed that cytokinin is a key regulator for seed yield (Ashikari et al. 2005; Bartrina et al. 2011). Exogenous application of kinetin (6-furfurylaminopurine), one of the cytokinin compounds, was able to improve the yield of seed cotton and lint fiber (Sawan et al. 2000). However, large-scale commercial applications of cytokinins in crops are unfeasible in practice due to high costs and time consumption (Li et al. 2004). Genetic modification provides a means to manipulate hormone concentrations in plants. Promoting cytokinin biosynthesis is an effective method of overproducing cytokinin in plants. The ipt gene encoding isopentenyl transferase, which catalyses the rate-limiting step in cytokinin biosynthesis, has been widely used for the enhancement of cytokinins in transgenic plants (Klee et al. 1987; Smigocki and Owens 1988;Smigocki 1991;Wang et al.1997;Geng et al. 2001Geng et al. , 2002van der Graaff et al. 2001;Kuppu et al. 2013;Reguera et al. 2013;Rupp et al. 1999;Synková et al. 1999). However, constitutive overexpression of the gene is usually associated with adverse effects on growth and development of the plants (Smart et al. 1991;Medford et al. 1989;McKenzie et al. 1994;van der Graaff et al. 2001;Geng et al. 2001;Guo et al. 2005;Synková et al. 1999). Another approach to elevating endogenous cytokinins is the suppression of cytokinin deactivation. Cytokinin oxidase/dehydrogenase (CKX), which catalyzes the catabolism of cytokinins to inactive products that lack the N 6 -unsaturated side chain (Jones and Schreiber 1997), is a crucial negative regulator controlling endogenous cytokinin contents in the plant kingdom (Mok and Mok 2001;Schmülling et al. 2003;Werner et al. 2001Werner et al. , 2003Kowalska et al. 2010). Decrease of CKX expression level results in more cytokinins in inflorescence meristems, and thus more grains (Ashikari et al. 2005). To increase endogenous cytokinins in cotton, we had tried to generate transgenic cottons using a constitutive promoter, CaMV35S, to control the expression of ipt. However, as happened in cucumber transformed with 35S::ipt reported by Smigocki and Owens (1989), the transformed calli never developed further into plant regenerants (unpublished data). In this paper, by using GhCKXRNAi, we successfully generated cytokinin-overproduction cottons. Our data demonstrated that moderate suppression of GhCKX can significantly improve both seed and fiber yield of cotton. Plant transformation and growth conditions The 35S::GhCKXRNAi construct (Zeng et al. 2012) was introduced into cotton using the method of Agrobacterium-mediated transformation as described previously (Luo et al. 2007). Kanamycin-resistant and GUS-positive plants were screened out for further study. Cotton plants were grown in greenhouse in 30 9 28 cm (diameter 9 height) pots under a 16-h light/8-h dark cycle, at 26-32°C. Pindstrup Substrate (Pindstrup Mosebrug A/S, Denmark) was used as potting mixture. The plants were watered once every 2 days, and fed once every month with compound fertilizer China). Quantification of endogenous cytokinins The concentration of endogenous cytokinins was determined in young leaves (the first main-stem leaf from the apex at 130 days after sowing [DAS]), mature leaves (the fifth main-stem leaf from the apex at 130 DAS), stem shoots (the first internode from the apex at 90 DAS), flower buds (3 days before anthesis) and 35-DPA (days post-anthesis) ovules. Tissues (100 mg) were pooled for each sample. Three independent biological replicates were analyzed for the tissue of each line. Extraction, purification, and quantification of endogenous cytokinins by highperformance liquid chromatography linked to a 4000 Q TRAP LC/MS/MS system (ABsciex, USA) were performed according to the method described by Zeng et al. (2012). The product ion pairs of each cytokinin component and corresponding deuterated internal standards, as well as their acquisition parameters, are summarized in Table S4. Determination of chlorophyll contents Leaves (100 mg fresh weight (FW)] were placed in a 10 mL tube containing 5 mL 80 % acetone and incubated in the dark at room temperature until the tissues became white. Total chlorophyll was determined using absorbance at 645 nm and 663 nm according to the equation: 20.2 A 645 ? 8.02 A 663 (Chory et al. 1994). Photosynthesis measurements Photosynthetic rate was measured by the Li-6400 portable photosynthesis system (LI-COR, Lincoln, NE, USA). The fourth main-stem leaf from the apex (functional leaf) of 10 plants per line at 120 DAS was used for the analysis. The instrument was set at saturating light of 1,200 lmol m -2 s -1 and a CO 2 concentration of 400 ppm. Determination of soluble sugar and soluble protein Ovules and boll shells of 35-DPA bolls at third fruit branch (base to top) were frozen in liquid nitrogen. Samples (100 mg FW of each) were homogenized and extracted in 5 mL 80 % ethanol, and heated for 45 min in boiling water. After cooling to room temperature, the extraction was centrifuged at 3,000 rpm for 10 min. The supernatant was collected to determine the amount of soluble sugars by the colorimetric method with anthrone-sulfuric acid at 620 nm with glucose as a standard. The protein content was determined by the Coomassie Brilliant Blue G-250 method with bovine serum albumin as the standard. Soluble proteins were extracted from 0.2 g of fresh tissue at 4°C with 5 mL of extracting solution containing 93.7 % 0.2 M Na 2 HPO 4 , 5.2 % 0.2 M NaH 2 PO 4 , 2 % PVP, and 0.1 % (v/v) b-mercaptoethanol for 60 min. After centrifugation at 4,000 rpm for 10 min, the supernatant was used for protein determination. Ovule culture Ovules at 0 DPA were harvested and cultured in BT medium according to the method of Beasley and Ting (1974). As well as 0.5 lM gibberellic acid and 5 lM indole-3-acetic acid, trans-Zeatin with concentrations of 0, 0.5, 1.0, 5.0, 8.0, and 15 lM was added to the medium. After 2-week culture in the dark at 32°C, ovules were observed by an MVX-10 microscope (Olympus, Japan). Scanning electron microscopy (SEM) The 0-DPA ovules were imaged by an S-3400 N SEM (Hitachi, Japan). From the similar region of each SEM image, an area of 250 9 250 lm 2 was selected for fiber initial counting. Field experiment Homozygous T 2 generation lines of 35S::CKXRNAi were planted in 2010 in an experimental farm at Southwest University (Chongqing, China) with 15 plants per row. Line CR-6 (T 4 ) was selected as the best line of the moderately down-regulated GhCKX cotton. To assess the agronomic performance of the line, plants were grown in field conditions for randomized comparative trial in 2012 with three replications. Each block was 20 m 2 and contained 60 plants in four rows 1.0 m apart. The space between two neighboring plants in a row was 0.33 m. The plant height (from soil surface to top), fruit branch number, and square number were measured at 105 DAS. The boll number was counted at 130 DAS. After harvest, seed cotton was ginned. Fibers and seeds were weighed separately, and the number of seeds per boll, lint percentage (fiber weight/seed cotton weight), seed index (the weight of 100 seeds), lint index (the lint weight of 100 seeds), fiber yield and seed yield were determined. Fibers (3 9 *15 g) from each line were sampled randomly and sent to the National Center for Evaluation of Fiber Quality (Anyang, China) for measuring their qualities. Down-regulation of GhCKX-enhanced endogenous cytokinins To confirm that regulation of GhCKX changes the level of endogenous cytokinins in transgenic cottons, we determined the content of 13 different cytokinins in the leaves, stem shoots, flower buds, and ovules of two GhCKX moderately suppressed lines (CR-3 and -6) and one severely suppressed line (CR-13) by LC/MS (Tables 1 and S1). Total cytokinins in young leaves of transgenic cotton lines CR-3, -6 and -13 increased 13.6, 28.2, and 79.7 %, respectively, compared to that of the wild type. In mature leaves, the cytokinin level in transgenic lines increased 99.4, 106.7, and 194.5 %, respectively. For stem shoots, flower buds, and ovules, the averaged levels in CR-3 and CR-6 rose 39.8, 59.9, and 36.0 %, respectively, and the content in severely suppressed line CR-13 was rather high, increasing by 61.1, 315.6, and 139.9 %, respectively (Table 1). With the decline in gene expression, the content of cytokinins increased significantly, confirming that down-regulation of GhCKX elevated the level of endogenous cytokinins in cotton. Moderate down-regulation of GhCKX delayed leaf senescence Chlorophyll degradation is a sign of leaf senescence (Kusaba et al. 2007). To investigate whether downregulation of GhCKX in cotton delays the leaf senescence, we compared the chlorophyll content in the leaves of GhCKX moderately suppressed lines (CR-3 and -6), severely suppressed line (CR-13), and wild type at 90, 105, and 120 DAS in field conditions. For upper leaves, there was a steady increase in chlorophyll content in transgenic lines and the wild type from 90 DAS to 105 and 120 DAS (Fig. 2). The content in the three transgenic lines was higher than that in the wild type. For the middle leaves, along with aging, the content in 105-and 120-DAS leaves of transgenic lines and wild-type plants declined. However, the content in transgenic leaves was higher than the wild type. In the aged leaf, i.e. the 120-DAS lower leaves, the content decreased dramatically compared with the upper leaves (Fig. 2). Nevertheless, the content in the transgenic lines was significantly higher than the wild type at 105 and 120 DAS. We further calculated the number of abscised stem leaves per plant at 105, 120, and 140 DAS. During the time, leaf abscission in the cotton increased quickly (Fig. S2), even though the numbers of abscised leaves in the three transgenic lines was much lower than that in the wild type (Fig. S2). The assays of chlorophyll content and leaf abscission demonstrated that leaf senescence was delayed in the transgenic lines. Moderate down-regulation of GhCKX increased leaf photosynthesis and enhanced soluble sugar and protein in the boll We measured photosynthesis of the fourth leaf from the apex at 120 DAS. The photosynthetic rate of CR-3 and CR-6 leaves was higher than the wild type, showing a 10.7 and 12.2 % increase, respectively. However, there was no such enhancement in the leaves of the severely suppressed line CR-13 (Fig. 3a). In addition, the concentrations of soluble sugar and protein in the boll shell and the ovule at 35 DPA (days post-anthesis) of CR-6 and CR-13 were significantly higher than those of the wild type (Fig. 3b, c). Moderate down-regulation of GhCKX increased both seed and lint yield Based on the expression level of GhCKX (Fig. 1), coupled with phenotype observation in transgenic cottons (T 2 generations), one slightly suppressed (the level decreased by less than 30 %) GhCKX line, CR-7, five moderately down-regulated lines, CR-3, -4, -5, -6, and -8 (decreased by 30-70 %), and two severely suppressed (decreased by over 70 %) lines, CR-11 and CR-13, were planted in field conditions to observe their agronomic performance. At the flower stage, the plant height of severely suppressed GhCKX lines CR-11 and -13 was 82.5 ± 13.7 cm and 68.7 ± 6.0 cm respectively, much lower than the control (100.5 ± 3.9 cm; Table S2). At the same time, the height of most of the moderately down-regulated lines showed a slight decreased, and there was not much change in the height between the slightly down-regulated line CR-7 and the wild type. Meanwhile, the moderately downregulated lines bore more fruiting branches than the wild type. In the case of severely suppressed lines CR-11 and -13, the branch number noticeably decreased (Table S2), indicating that moderate down-regulation of GhCKX promoted the development of fruiting branches, but severe suppression of the gene hindered it. The square (flower bud) number at 105 DAS of most of the moderately down-regulated lines was higher, while the square number of the two severely Well-ground samples were extracted in cold 80 % (v/v) methanol. Cytokinins were purified by a Sep-Pak Ò Plus tC18 cartridge (Waters, Ireland) and determined by HPLC-MS/MS systems (ABsciex, USA). The total values were the sum of cytokinin contents in young leaf, mature leaf, stem shoot, flower bud, and ovule, respectively. WT wild type; CR-3, CR-6 and CR-13, 35S::GhCKXRNAi transgenic plants suppressed lines was lower than that of the wild type. After harvest, we counted the boll number per plant and calculated the seed and lint fiber yields. The agronomic behavior of the slightly down-regulated line, CR-7, was very close to the wild type (Table S2). The moderately down-regulated cottons produced more bolls than the wild type. The averaged boll number of the five moderately down-regulated lines was 30.7 ± 1.7, 19.0 % more than the wild type. Moreover, bolls produced by these lines were bigger than the wild type, as indicated by the seed cotton weight per boll and seed index (the weight in grams of 100 seeds, Table S2). Consequently, seed cotton yield per plant of the lines increased significantly. In contrast, the number of bolls and the seed size in the severely suppressed cottons, CR-11 and CR-13, were lower and smaller than the wild type. Interestingly, lint index (the weight in grams of lint in 100 seeds), a measure of the abundance of fiber on the seed, and the lint yield per plant increased in the moderately down-regulated lines, demonstrating that the enhancement of seeds was not at the cost of lint fibers; instead, both seed and lint yield were concurrently improved. However, boll number per plant, seed number and seed cotton per boll, and seed cotton yield and lint yield per plant of the severely suppressed lines CR-11 and CR-13 were dramatically lower than the wild type (Table S2), suggesting that over-dosage of endogenous cytokinins reduced both seed and lint yield. With regard to the quality of the fiber, we did not find notable alterations in fiber length, fiber strength, or micronaire in transgenic cottons (Table S3), suggesting that the increase of endogenous cytokinins in cotton had little influence on the qualities of transgenic fibers. To further assess the performance of the moderately down-regulated GhCKX cotton in yield improvement, we selected CR-6 (T 4 ) as the best line for field trials. As in T 2 generation, yield components, including boll number per plant, seed cotton per boll, lint index and seed index, of the transgenic line were higher than that of the wild type. The seed yield and lint yield increased 15.4 and 20.0 %, respectively, as compared to the wild type ( Table 2). The field trial results confirmed that moderate down-regulation of GhCKX enhanced both fiber and seed yield. Discussion Cotton fibers are derived from single cells of ovule epidermis (Stewart 1975) and fiber cell development is tightly influenced by seed (Ruan 2013). Phytohormones play important roles in the growth and development of seed and fiber cells of cotton (Beasley and Ting 1973;Basra and Saha 1999;Lee et al. 2007). Indole-3-acetic acid and gibberellins were able to promote fiber cell initiation and elongation (Chen et al. 1988(Chen et al. , 1996Zhang et al. 2011;Xiao et al. 2010). Ethylene plays a major role in promoting fiber elongation (Shi et al. 2006), whereas abscisic acid (ABA) inhibits fiber growth (Dhindsa et al. 1976;Gokani et al. 1998;Lee et al. 2007). Brassinosteroids (BRs) participate in both fiber initiation and elongation (Sun et al. 2005;Luo et al. 2007). The inhibitory effect of BRZ on fiber cells could be overcome by (Shi et al. 2006). Cytokinins have an important role in shoot and seed development, but fiber elongation is inhibited by high concentrations of cytokinins in ovule culture (Beasley and Ting 1974). However, the effects of cytokinins on the yield of cotton fiber and seeds remained to be evaluated. To elevate the endogenous level of cytokinins, we successfully generated 35S::GhCKXRNAi cottons. A dose-dependent effect of the gene expression on phenotype alterations was observed. The slightly suppressed cottons did not show distinct morphological and agronomic changes relative to the wild type, while moderate suppression resulted in a delay in leaf senescence, increase in photosynthesis, more fruiting branches and bolls, bigger size of seed, and consequently higher yield of seed and fiber. Along with the decrease in GhCKX expression, the negative impact of cytokinin overproduction on plant growth and development became progressively more severe, and the yield of seed and fiber of the severely suppressed cottons dramatically declined. The cytokinin content assay was well consistent with the dosage change in gene expression. That is to say, along with the decline in gene expression, the endogenous level of cytokinins increased and the enhancement of endogenous cytokinins creates the alterations taking place in the transgenic cottons. The increased cytokinin content caused an enhancement of seed yield in rice (Ashikari et al. 2005) and Arabidopsis (Bartrina et al. 2011). Our ovule culture results demonstrated that application of ZT (trans-Zeatin) at appropriate concentrations (5.0-8.0 lM) in media promoted seed development. However, a high concentration of the cytokinin (15 lM) inhibited seed development (Fig. S3). Results in transgenic 35S::GhCKXRNAi cottons supported this observation. Ovules of the severely suppressed cotton contained high concentration of cytokinins (Tables 1 and S1) and the cotton plants produced less seeds with smaller size, whereas the seed number, seed size, and seed cotton yield were significantly enhanced in the moderately suppressed cottons (Table S2). These results indicated that a moderate enhancement of cytokinins promotes the development of seeds, but overdosage of them inhibits it. In the ovule culture experiment, fiber elongation was inhibited in cytokinin-overproduction transgenic cottons (Yu et al. 2000). In our experiments, no distinct inhibition of fiber initiation was observed in moderately suppressed transgenic cottons (Fig. S4). Meanwhile, there was no distinct difference in fiber length between transgenic lines and the wild type (Table S3), implying that moderate overexpression of GhCKXRNAi has little negative effect on fiber development. Instead, lint index and lint yield of the moderately suppressed GhCKX lines were significantly enhanced. There are two explanations for this enhancement. First, the number of fibers per seed is limited by the surface area of the ovule epidermis. Thus, enhancement of cotton seed development could achieve cotton seed and fiber yield improvement (Ruan 2013). In our experiments, a proper increase of cytokinins promoted seed development and enlarge the seed size (Fig. S3). Bigger seed means larger area of seed coat that bears more fibers. More importantly, early leaf senescence could decrease the assimilation supply for boll and fiber development (Bauer et al. 2000;Peng and Krieg 1991), thus reducing lint yield and fiber properties (Wright 1999;Dong et al. 2006). The delay of leaf senescence in transgenic cottons leads to an increase in chlorophyll concentration and photosynthetic rate of the leaves. Our results are in agreement with previous findings that early-fruit removal significantly increased cytokinins in both main-stem leaves and xylem sap and delayed the main-stem leaf senescence characterized by increases in chlorophyll concentration and photosynthetic activity of leaves (Dong et al. 2009). The enhanced photosynthesis in the leaves of transgenic cotton plants and the increased soluble sugar and protein of the boll (Fig. 3) provide more carbohydrates for the development of seed and fiber. As a result, seed yield and fiber yield concurrently improve. Although seed-specific expression of ipt can alleviate developmental abnormalities resulting from constitutive overexpression of the gene (Ma et al. , 2008Daskalova et al. 2007), the shortcoming of this strategy is that the advantages associated with increase in cytokinins, such as delay in leaf senescence, increase in photosynthesis of leaves, more branches, tolerance to abiotic and biotic stress (Choi et al. 2010;Jeon et al. 2010;Nishiyama et al. 2011;Peleg et al. 2011;Rivero et al., 2007), and resistance to pathogens (Choi et al. 2011), may not benefit the whole plant. In our previous experiments, we failed to generate transgenic 35S::ipt cotton. In contrast, in this paper, using the strategy of suppressing cytokinin deactivation, we successfully obtained transgenic 35S::GhCKXRNAi cottons in which endogenous cytokinin levels were globally and constitutively enhanced (Tables 1 and S1). In terms of manipulation of cytokinin levels in plants, CKX is more likely a softer regulator than ipt. Taken together, our data demonstrated that moderately enhancing endogenous cytokinins by suppressing CKX is a feasible and effective strategy for yield improvement, not only for cotton but also for other seed crops, such as canola, soybean, maize, and rice.

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2015-08-05T00:00:00.000Z

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Review of the 2012 Epizootic Hemorrhagic Disease Outbreak in Domestic Ruminants in the United States An unusually large number of cases of Epizootic hemorrhagic disease (EHD) were observed in United States cattle and white-tailed deer in the summer and fall of 2012. USDA APHIS Veterinary Services area offices were asked to report on foreign animal disease investigations and state diagnostic laboratory submissions which resulted in a diagnosis of EHD based on positive PCR results. EHD was reported in the following species: cattle (129 herds), captive white-tailed deer (65 herds), bison (8 herds), yak (6 herds), elk (1 herd), and sheep (1 flock). A majority of the cases in cattle and bison were found in Nebraska, South Dakota, and Iowa. The majority of cases in captive white-tailed deer were found in Ohio, Iowa, Michigan, and Missouri. The most common clinical sign observed in the cattle and bison herds was oral lesions. The major observation in captive white-tailed deer herds was death. Average within-herd morbidity was 7% in cattle and bison herds, and 46% in captive white-tailed deer herds. The average within-herd mortality in captive white-tailed deer herds was 42%. Introduction Epizootic hemorrhagic disease (EHD) is a noncontagious, vector-borne disease transmitted by biting midges of the genus Culicoides. Epizootic hemorrhagic disease virus (EHDV) is in the family Reoviridae and genus Orbivirus. The normal host range of EHDV is wild and domestic ruminants. The distribution of EHDV in the United States is determined by the distribution of Culicoides sonorenis, the primary vector of EHDV in North America [1]. C. sonorenis populations are found in the western, south central, mid-Atlantic, and southeastern United States [2]. EHDV has also been identified in Australia, Africa, and Asia [3][4][5]. Mertens described 10 serotypes of EHDV: serotypes 1-8, EDHV-318, and Ibaraki virus [6]. However, it has been proposed these 10 serotypes be condensed down to 7 serotypes [7]. The serotypes of EHDV which have been identified in the United States are EHDV-1, EHDV-2, and EHDV-6 [8][9][10][11]. EHD was first described in 1955 in a New Jersey outbreak characterized by high mortality in white-tailed deer [8]. Outbreaks in white-tailed deer are seasonal, occurring from mid-summer to late autumn and appear to occur every 2 to 3 years in endemic areas, and every 8 to 10 years in epidemic areas [12][13]. Three disease syndromes have been described in white-tailed deer: peracute, acute, and chronic. Clinical signs can range from rapid death in the peracute syndrome to sloughing of hooves in the chronic syndrome. Other clinical signs may include fever, anorexia, respiratory distress, edema of the head and neck areas, excessive salivation, oral erosions, and lameness [14]. EHDV infection in cattle does not usually result in clinical disease. When seen, it is a less severe disease than what is observed in deer. Clinical signs observed in cattle may include fever, anorexia, loss in milk production, swollen conjunctiva, nasal and ocular discharge, excessive salivation, stomatitis, oral and nasal erosions, lameness, and dyspnea [15][16]. Laboratory-confirmed cases of EHD have been reported in Oregon in 1969, Tennessee in 1972, and Colorado in 1974 [15]. A study of investigations of cattle with vesicular lesions completed in late summer and early fall in 1996 in 9 Midwestern states reported 32 premises with animals serologically positive for EHDV [16]. A serological study of cattle in Illinois and Indiana detected antibodies to EHDV in 11.8% of 1,110 cattle tested [17]. The clinical signs of EHD in cattle can be similar to those of bluetongue, bovine viral diarrhea, foot-and-mouth disease (FMD), infectious bovine rhinotracheitis, vesicular stomatitis (VS), malignant catarrhal fever (MCF), and bovine ephemeral fever. Because the clinical signs of EHD in cattle are similar to those seen in FMD, VS, and MCF, these cases are often referred to state and federal animal health authorities for investigation as possible foreign animal diseases. An unusually large number of cases of EHD were observed in United States cattle in summer and fall of 2012. The largest numbers of cases were reported in Iowa, Nebraska, and South Dakota. This coincided with a large number of reported cases in captive and free-ranging whitetailed deer in some regions of the United States. The purpose of this paper is to report the findings of foreign animal disease investigations, state veterinary diagnostic laboratory submissions, and other investigations which resulted in a diagnosis of EHD in domestic ruminants. Material and Methods Biological samples for foreign animal disease investigations were collected by veterinarians employed by USDA APHIS Veterinary Services or State Departments of Agriculture who have received specialized training in the diagnosis of foreign animal diseases. Samples submitted to State Veterinary Laboratories were collected for diagnostic purposes by licensed veterinarians or veterinarians employed by State Departments of Agriculture. The types of samples collected included blood samples (serum or whole blood) collected from the jugular or tail (coccygeal) vein, swab or tissue from oral erosions, vesicular fluid from oral lesions, or tissue samples collected from post-mortem examinations of animals. No sacrifice of animals was conducted. No protected species were sampled during the course of this study. All animal care and husbandry was provided by livestock owners. Permission to examine and collect samples from livestock was voluntarily granted by their owners. The USDA does not have an Institutional Animal Care and Use Committee (IACUC) with oversight over diagnostic samples collected from privately owned livestock during a foreign animal disease investigation. Private practitioners or livestock producers who observed vesicular clinical signs in livestock reported these conditions to state or federal animal health officials. A foreign animal disease diagnostician (FADD) was dispatched to examine the livestock and collect diagnostic samples. FADDs are state or federal regulatory veterinarians specifically trained in the diagnosis and sampling methods for diseases foreign to the United States. The findings of the investigation were recorded in the Emergency Management Response System (EMRS), a USDA-APHIS Veterinary Services (APHIS-VS) database used to manage disease investigation and response activities. Diagnostic samples were submitted to the National Veterinary Services Laboratories (NVSL) Foreign Animal Disease Diagnostic Laboratory (FADDL) on Plum Island, New York. After foreign animal diseases were ruled out, samples were tested by the EHD reverse transcription polymerase chain reaction assay (RT-PCR). EHD real-time RT-PCR was performed using a previously published assay which detects the 8 prototype serotypes but was modified to include only 1 primer and probe set as follows [18]. RNA was isolated from whole EDTA blood using QIAampViral RNA extraction kit (QIAGEN, Valencia, CA). EHD RNA (2.5 μL) was mixed with 1 μL of 10 μM forward and reverse primers and 8 μL of water and denatured at 95°C for 5 min followed by a 1-min ice quench. The denatured template (11 μL) was transferred into a master mix with 14 μL of AgPAth-ID one-step RT-PCR reagents (Life Technologies, Carlsbad, CA). The master mix contained 12.5 μL 2X RT-PCR buffer, 1 μL 25X enzyme mix, and 0.5 μL of 10 μM probe labeled with 5'FAM and 3'BHQ-1 (Biosearch Technologies, Inc, Petaluma, CA). Real-time amplification was performed on a SmartCycler II thermal cycler (Cepheid Inc., Sunnyvale, CA) using the following cycling conditions: 1 cycle of 48°C for 1400 sec and 95°C for 900 sec, followed by 40 cycles of 95°C for 15 sec, 48°C for 40 sec, and 70°C for 20 sec. The primers and probe were designed from EHD S10 gene, encoding the nonstructural protein NS3, and targeting EHD serotypes 1, 2, 5, 6, and 7: EHD Probe 192: 5'FAM-TCAAATCAAACGGGCGCAACTATGG-3'BHQ-1 EHD Forward Primer 165: 5'-GCGTTGGATATATTGGACAAAGC-3' EHD Reverse Primer 253: 5'-GCATACGAAGCATAAGCAACCTT-3' All APHIS-VS area offices were asked to submit a set of structured standardized data on FAD investigations resulting in a diagnosis of EHD conducted between June 1 and December 31, 2012. Table 1 summarizes the data elements collected. Collection of data from state laboratories Not all EHD cases were managed as FAD investigations. APHIS-VS offices were also asked to request data from state diagnostic laboratories on submissions with positive EHD results in domestic ruminants with clinical signs suggestive of EHD. Table 1 summarizes the data elements that were requested on submissions to state laboratories. to NVSL for serotyping. Additional cases were identified though they were not submitted as a result of the data request. Accessions were excluded from the data analysis if one or more of the following conditions were true: 1) results did not meet the case definition (PCR positive), 2) results were already reported through a state lab or foreign animal disease investigation, 3) the species was not a domestic ruminant, 4) the samples were collected from animals outside the United States, or 5) the testing was for movement of animals or certification of germplasm. Any possible new cases identified from the STRAND database were confirmed by contacting the APHIS-VS Area Office for the state where the animals were located. Collection of data from clinical cases in Missouri captive white-tailed deer A particularly large number of EHD cases occurred in both Missouri wild and captive whitetail deer populations during the last half of 2012. Reporting of EHD occurrence in captive cervid herds to the Missouri state animal health authorities is not mandatory. In an attempt to capture this information, personal contacts were made with 19 herd veterinarians (or their clinics) working with most of the captive cervid herds in Missouri's Tuberculosis Accredited-Free herd program. There were approximately 105 herds in the program, and the veterinarians contacted represented 90 of those herds. The veterinarians were asked about the occurrence of clinical signs, similar to the information gathered in cattle herds, as well as herd morbidity and mortality. Information was eventually gathered for 49 of Missouri's captive cervid herds. All of the data captured were for white-tailed deer. Because of the prevalence of EHD, the cost of testing, and the peracute nature of the disease, testing had been conducted in only 12 of these 49 herds. The rest of the herds were diagnosed on clinical signs and morbidity/mortality levels without testing any samples. Data analysis A case was defined as a premises which had animals with clinical signs suggestive of EHD and which had EHDV detected by PCR analysis. The case date (week) for use in constructing the epidemic curve was determined using the sample collection date or lab submission date. When this was not available, the reported date of onset was used. Table 2 Clinical signs were reported for 85 of the EHD cases in cattle and bison. The most common sign reported was oral lesions. Overall, 86% of the case-positive premises reported at least 1 animal with oral lesions. Other clinical signs reported in at least 1 animal on case-positive premises were excessive salivation (64%), off feed or difficulty eating (57%), lameness/stiffness (49%), muzzle lesions/crusty muzzle (47%), fever (32%), and teat lesions (7%). Complete information on the number of animals affected and number of susceptible animals was recorded for 82 of the cases (3 bison and 79 cattle). The average within-herd morbidity was 7.12%. The median within-herd morbidity was 3.23%. The reported within-herd morbidity ranged from 0.05% to 100.00%. Overall, 70 of 82 cases reported a within-herd morbidity rate of 10% or less. Of 96 cases which recorded the number of affected animals, 66 cases (69%) reported only 1 animal with clinical signs. Four cases, 2 bison and 2 cattle, had mortality due to EHD. Eleven states reported a total of 65 EHD cases in captive white-tailed deer identified through submissions to state diagnostic laboratories. Ohio (16 cases), Michigan (13 cases), and Iowa (13 cases) reported the most cases resulting from submissions to state laboratories. Missouri reported 9 cases resulting from submissions to state diagnostic laboratories. Missouri also reported 34 cases in white-tailed deer based on clinical signs as described in interviews with private practitioners. EHD cases in captive white-tailed deer by state are summarized in Table 3. The locations of cases in captive white-tailed deer are illustrated in Fig 3. The first case of EHD in captive white-tailed deer was reported on June 1, 2012, in Louisiana, which was the beginning date for this study's data request. The last case was reported during the week of November 13, 2012, based on a clinical diagnosis in Missouri. The majority of Clinical signs were reported for 52 of the EHD cases in captive white-tailed deer. Mortality due to EHD was reported in at least 1 animal on 46 (88%) of the case-positive premises. The most common clinical signs reported in at least 1 animal on the case-positive premises were: being off feed (90%) and fever (81%). Other clinical signs reported in at least 1 animal were: excessive salivation (58%), lameness (38%), oral lesions (17%), muzzle lesions/crusty muzzle (15%), and teat lesions (2%). Complete information on the number of white-tailed deer affected and number of susceptible animals was reported for the 43 clinical and laboratory cases in Missouri. The average within-herd morbidity was 46%. The median within-herd morbidity was 47%. The reported within-herd morbidity ranged from 3% to 94%. The average within-herd mortality was 42%. The median within-herd mortality was 38%. The reported within-herd mortality ranged from 3% to 84%. Events meeting the EHD case definition were also reported in 6 yak herds in Colorado [19], 1 elk herd in Iowa, 1 sheep flock in Iowa, and 1 deer herd in Florida. Discussion An appreciation of the magnitude of the EHD outbreak in 2012 is realized by examining the results of FAD investigations conducted in previous years. During late summer and fall in 2012, there were 83 FAD investigations in cattle and bison resulting in a diagnosis of EHD based on a positive RT-PCR test. During 2010-2011, 3 FAD investigations in the United States resulted in a diagnosis of EHD based on positive PCR results (NVSL STRAND). It is likely that EHD cases were under-reported in areas with high EHDV activity as veterinarians and producers started diagnosing EHD based on clinical signs. This is evident from the data submitted from Missouri on EHD cases in their captive cervid industry. Missouri reported over 3 times the cases based only on clinical symptoms than based on lab results. Other states with captive white-tailed deer operations also remarked that the laboratory cases did not represent the number of cases observed in their respective captive cervid industries. Most of the data on affected animals and clinical signs were compiled from FAD investigations. It should be noted that in most cases not all animals within a herd were examined or tested for EHD. Therefore, the actual morbidity rates within a herd may be higher than the morbidity rate reported here. In addition, there is no standardized format for recording specific clinical signs in EMRS. Therefore, some of the less dramatic clinical signs, such as fever or being off feed, may not always have been recorded by the FADD. Reporting of cases from state diagnostic laboratories was voluntary and reported through the respective area office. Reports were received from 48 of 50 states. Difficulty with interpreting state diagnostic laboratory data may have involved differentiating cases involving captive white-tailed deer versus free-ranging white-tailed deer and differentiating submissions from clinical animals versus animals tested for other purposes. However, these difficulties presented in states with minimal expected EHD activity and did not have a bearing on the findings of this study. We also requested general information on EHD serotypes which were identified during these investigations. While serotyping was not the focus of this study, we feel these results are still worthwhile to include in this report. However, because EHD serotyping was not completed on all laboratory submissions, the serotypes reported below may not be completely representative of what occurred during this outbreak. The EHD serotype was determined for 59 of the 133 cases of EHD in bison and cattle. Serotype 2 was identified in 54 of these cases, which were located in Nebraska, Iowa, South Dakota, Minnesota, and Ohio. Serotype 6 was identified in 3 cases. These cases were located in Illinois and Iowa. Serotype 1 was identified in 1 South Dakota case. One Illinois case in cattle identified serotype 2 and serotype 6 on the same premises. The EHD serotype was determined for 33 of the cases of EHD in captive white-tailed deer. Serotype 2 was identified in 21 of these cases, which were located in Iowa, Missouri, New Jersey, North Carolina, Ohio, and Texas. Serotype 6 was identified in 8 cases in Florida, Illinois, and Iowa. Serotype 1 was identified in 3 cases, located in Florida, Texas, and Louisiana. One Missouri case in captive white-tailed deer identified serotype 2 and serotype 6 on the same premises. It is likely that the high temperatures associated with drought conditions present in many states in 2012 contributed to this EHD outbreak. The National Climatic Data Center reported that 2012 was the warmest year in the 1895-2012 period of record for the contiguous United States [20]. Nineteen states, including Nebraska, South Dakota, and Missouri, had record warm annual temperatures in 2012. High temperatures facilitate the transmission of EHD virus by C. sonorensis midges by decreasing the extrinsic incubation period of the virus [21]. A previous study conducted in Nebraska, South Dakota, and North Dakota indicated that the risk of cattle being seropositive to bluetongue virus (BTV), another orbivirus transmitted by C. sonorensis midges, decreased at more northerly latitudes. This study indicated that BTV was endemic in southern Nebraska [22]. This study also indicated that the eastern limit of C. sonorensis in South Dakota is clearly defined by the location of the Missouri River, and that the eastern limit in Nebraska may also be the Missouri River [23]. In South Dakota and Iowa, a majority of the EHD cases were seen in areas outside the normal range of C. sonorensis. Thirtytwo of the 37 cases in South Dakota were in counties east of the Missouri River. A majority of the cases in Iowa were seen in the western area of the state. Iowa is not considered to be in the normal distribution of C. sonorensis, but western Iowa is adjacent to areas of Nebraska where C. sonorensis is normally found. In Nebraska, all but 1 of the cases was located in the northern half of the state. The regionalization of confirmed clinical cases in these 3 states indicates expansion from the normal distribution of EHDV. The resulting exposure of cattle and whitetailed deer with limited immunity to EHDV resulted in the increase in number of clinical cases of EHD in cattle and captive white-tailed deer. Whether this expansion of EHDV exposure was due to an actual expansion of the range of C. sonorensis or an amplification of EHDV within existing C. sonorensis populations is beyond the scope of this observational study. The clinical signs of EHD can be similar to those seen with foot-and-mouth disease, vesicular stomatitis, and malignant catarrhal fever. Oral lesions and excessive salivation were seen in a majority of the affected herds. Muzzle lesions and lameness were seen in nearly 50% of the herds. The occurrence of EHD during the vector season and low morbidity rates in cattle are especially similar to vesicular stomatitis. If one of these foreign animal diseases is introduced into an area experiencing an outbreak of EHD, detection could be delayed if the clinical signs are attributed to EHD and if the condition is not investigated as a possible foreign animal disease.

v3-fos

2019-04-07T13:08:41.853Z

2015-01-10T00:00:00.000Z

101686076

s2

Biodegradation of Atrazine by Bacteria Isolated from Lotic Water Background: The persistence of toxic herbicides in water and soil has been considered to be potential environmental concern. As atrazine is still used in Nigeria as a major herbicide, a continuous search for atrazine degrading microorganisms is required. Objectives: The effects of incubation period on growth and atrazine degradation by bacteria isolated from a lotic water in the Niger Delta were evaluated and also determined were the effects of temperature and anaerobic incubation on atrazine removal by the most efficient isolate. The bacteria capable of degrading atrazine were isolated from the lotic water using enrichment technique. The optimal incubation period for growth and atrazine degradation by the isolates was assessed by the isolates in Mineral salts medium containing 100 mg/L atrazine for 30 days at 35ºC. The flasks inoculated with the most efficient isolate were also incubated anaerobically and at varying temperatures (25, 30, 35 and 40ºC). were withdrawn every 5 days and growth and atrazine concentration measurements were carried out using standard plate count and HPLC respectively. observed as optimum for growth of the three isolates. Pseudomonas sp. gave the highest atrazine degradation rate of 82.67% followed by Bacillus sp. (75.33%) and Micrococcus sp. (69.33%) at the end of 30 days. Atrazine was degraded at reduced rate under anaerobic condition and temperature of 35ºC was optimum for atrazine degradation by Pseudomonas sp. Conclusion: These atrazine degrading strains may be useful in bioremediation of contaminated wastewater. INTRODUCTION Pesticides, including herbicides, have been used in agriculture with the aim to get greater productivity in crops. However, only small amounts of the released agrochemical reach the specific target while the rest of the application has the potential to move into the soil and may contaminate surface waters [1]. Atrazine (2-Chloro-4-ethylamino-6isopropylamino-s-triazine) is a herbicide widely used to kill weeds globally. Although several countries gave up the use of atrazine because of its toxicity, it is still one of the most popular herbicide in many countries [2]. It is still being used in Nigeria as the herbicide of choice and hence there is a high possibility of soil and water contamination in various parts of the country. The average half-life of atrazine in soil range from 13 to 261 days [3], in river water, it is more than 100 days [4], in seawater it is around 10 days [5] and nearly 660 days in case of anaerobic degradation [6]. However, half-life of atrazine has been previously reported to be 32 days in anaerobic soil and 86 days in the aqueous phase above the soil [7]. As a consequence of its high persistence and mobility atrazine and its metabolites can be detected in surface water, groundwater, drinking water supplies and even in fog [8]. The atrazine molecule consisting of N-alkylated and chlorinated heterocyclic aromatic ring, is a pollutant of environmental concern due to its low biodegradability. Once in aquatic environment atrazine may alter the structure and function of the communities [9]. But microorganisms have demonstrated the ability to metabolize the molecule partially or completely, leading to the formation of NH 3 and CO 2 [10]. Microbial degradation process aids the elimination of atrazine from the environment in a cost effective way [6]. The search of microbial strains capable of degrading atrazine in the environment is fundamental to the development of bioremediation processes [9]. Therefore, the aim of this present study was to isolate bacteria from a lotic water in the Niger Delta that have the ability to degrade atrazine and to evaluate the impact of some parameters on bacterial growth and atrazine degradation. Sample Collection Freshwater sample was collected in sterile plastic bottle from a stream in Akpajo village, Eleme, Rivers State, Nigeria. Source of Atrazine Atrazine used was commercial Multrazine 50 SC (Active ingredient -Atrazine 50%). It was obtained from an agrochemical shop in Port Harcourt, Nigeria. Enrichment and Isolation of Atrazine-Degrading Bacterial Strains The atrazine-degrading bacteria were isolated using enrichment culture technique. The mineral salt medium according to [11] contained (g/L of distilled water): K 2 HPO 4 0.8 g, KH 2 PO 4 0.2 g, NaCl 0.5 g, MgSO 4 0.1 g, CaCl 2 0.4 g, FeSO 4 0.02 g and MnSO 4 0.01 g. The final pH was adjusted to 7.2. The medium was autoclaved at 121ºC for 15 minutes. Ten millilitres of water sample per 100 mL of medium supplemented with 10 mg/L of atrazine as the sole source of carbon and nitrogen in a 250 mL Erlenmeyer flask was incubated at 35ºC for 7 days. The enrichment cultivation was performed with different concentrations (10, 50, 100 and 150 mg/L) of atrazine in the media. The bacteria present in the enrichment culture were isolated on mineral salt agar plates supplemented with 100 mg/L atrazine using spread plate technique. Isolates with distinct colonial morphology were picked and streaked repeatedly on nutrient agar plates until pure. The purified isolates were identified to generic level based on their morphological and physiological characteristics [12]. The Effect of Incubation Period on Atrazine Degradation in Liquid Medium by the Bacterial Isolates The bacterial isolates were tested for their ability to remove atrazine. The isolates were grown in 100 mL of liquid medium containing sterile mineral solution as described in 2.3 and atrazine in the concentration of 100 mg/L as the single source of carbon and nitrogen. The experiment was performed in triplicate and each flask received 0.1 mL of a 24 h culture of each isolate tested. The flasks and the uninoculated control flask were incubated at 35ºC for 30 days. Cultures were withdrawn every 5 days and growth and atrazine concentration measurements were carried out using standard plate count and High-performance liquid chromatography (HPLC) respectively. HPLC Analyses At each sampling time, 1 mL of culture supernatant was extracted with 2 mL of ethyl acetate and further concentrated by air flow to 0.1 mL before analysis. The concentration of atrazine in the extracts were analysed using HPLC under the following conditions: column c-18 (150 x 4.6 mm), mobile phase of methanol: water (50:50, v/v), UV detector at 230nm, continuous flow of 1ml min -1 , oven temperature of 35ºC, runs of 15 min and injection volume of 20 µL. The percentage degradation of atrazine was calculated using the equation [Co -Cx /Co] X 100 where Co is concentration of atrazine (mg/L) in the uninoculated control medium. Cx is the concentration of atrazine (mg/L) in the medium that has atrazine degrading strain. Effect of Incubation Temperature on Atrazine Degradation by Pseudomonas Strain The optimal temperature for atrazine degradation by Pseudomonas strain was assessed by growing the isolate at various temperatures ranging from 25ºC to 40ºC. The isolate was grown in 100 mL of liquid medium containing sterile mineral solution as described in 2.3 and atrazine in the concentration of 100 mg/L as the single source of carbon and nitrogen. The experiment was performed in triplicate and each flask received 0.1 mL of a 24 h culture of Pseudomonas strain. The flasks and the uninoculated control flasks were incubated at varying temperatures (25,30,35, and 40ºC) for 30 days. Cultures were withdrawn every 5 days and growth and atrazine concentration measurements were carried out using standard plate count and HPLC respectively. Effect of Anaerobic Incubation on Atrazine Degradation by Pseudomonas Strain Pseudomonas strain was tested for its ability to degrade atrazine in the absence of oxygen (O 2 ). The isolate was grown in 100 mL of liquid medium containing sterile mineral solution as described in 2.3 and atrazine in the concentration of 100 mg/L as the single source of carbon and nitrogen. The experiment was performed in triplicate and each flask received 0.1 mL of a 24 h culture of Pseudomonas sp. The flasks and the uninoculated control flask were incubated anaerobically at 35ºC for 30 days. Cultures were withdrawn every 5 days and growth and atrazine concentration measurements were carried out using standard plate count and HPLC respectively. RESULTS AND DISCUSSION A total of three atrazine-degrading bacterial strains identified as Pseudomonas sp., Bacillus sp. and Micrococcus sp. were isolated from lotic water using enrichment techniq.ue ( Fig. 1) with Pseudomonas sp. as the most efficient isolate (Fig. 2). Incubation time of 20 days was observed as optimum for the growth of the three isolates (Fig. 1). Atrazine maximum degradation rate of 82.67% for Pseudomonas sp., 75.33% for Fig. 2. Effect of incubation time on atrazine degradation by the bacterial isolates Bacillus sp. and 69.33% for Micrococcus sp. were observed at the end of the 30 days (Fig. 2). The loss of atrazine in uninoculated sterile controls was not evident indicating that the observed growth (Fig. 1) occurred at the expense of atrazine (Fig. 2). The atrazine degradation rates for Microbacterium sp. and Arthrobacter sp. reached 77.7% and 65.6% respectively after 14 days culture in a liquid medium with an atrazine concentration of 100 mg/L [19]. In granular activated carbon column filters inoculated with Rodococcus rhodochrous, atrazine degradation achieved 72.6% after 39 days [16]. Atrazine degradation in media containing atrazine as sole carbon and nitrogen source showed maximum degradation of 80% by Cryptococcus laurentii [20]. These atrazine degrading strains through their metabolism process can reduce or even eliminate the toxicity caused by atrazine as an environmental pollutant so as to decrease the harms to human health and the ecosystem. Total Viable Cells (cfu/ml) sp. sp. sp. The effect of temperature on atrazine degradation by Pseudomonas sp. is presented in Fig. 3. The degradation efficiency was found to be maximum (82.67%) at 35ºC. A decline in the degradation efficiency was observed for temperatures below and above 35ºC. This shows that the isolate is a mesophile and that temperature plays active role in bacterial metabolism and atrazine degradation. Wang and Xie [21] studied atrazine removal from contaminated soil and water by Arthrobacter sp. and the results showed that this strain of bacteria was capable of removing atrazine in a wide range of temperature (25-35ºC). For bacterial strain L-6, maximum biomass and best course of degradation was observed at incubation temperature of 30ºC [22]. The environmental fate of atrazine is largely dependent on various factors such as pH, temperature and atrazine concentration [23]. Pseudomonas sp. slowly degraded atrazine in the absence of oxygen. A 61.33% loss of atrazine was observed after 30 days anaerobic incubation (Fig. 4). There was no loss of atrazine in uninoculated control. Biodegradation of atrazine in absence of oxygen by pure culture has been reported in literature [24,25]. A facultative anaerobic, gramnegative bacterium Ralstonia basilensis (M91-3) capable of using atrazine under anaerobic conditions has been reported [26]. The authors stated that atrazine was degraded by Ralstonia basilensis (M91-3) at reduced rates and the degradation was completely inhibited when the medium was supplemented with NH 4 + . They suggested that the dealkylation and subsequent oxidation of atrazine side chains are coupled with denitrification under anaerobic conditions. CONCLUSION In this study, three atrazine-degrading bacterial strains identified as Pseudomonas sp., Bacillus sp. and Micrococcus sp. were isolated from lotic water using enrichment technique with Pseudomonas sp. as the most efficient isolate. The degradation rates of Pseudomonas sp., Bacillus sp. and Micrococcus sp. at the end of 30 days reached 82.67%, 75.33% and 69.33% respectively. Their optimum growth occurred on the 20 th day. Atrazine degradation efficiency by Pseudomonas sp. was found to be influenced by incubation time, temperature and anaerobic incubation. The degradation of atrazine by these strains may have application in bioremediation of atrazine contaminated environment.

v3-fos

2017-06-19T07:17:03.045Z

2015-07-10T00:00:00.000Z

1448066

s2

Variations in DREB1A and VP1.1 Genes Show Association with Salt Tolerance Traits in Wild Tomato (Solanum pimpinellifolium) Association analysis was conducted in a core collection of 94 genotypes of Solanum pimpinellifolium to identify variations linked to salt tolerance traits (physiological and yield traits under salt stress) in four candidate genes viz., DREB1A, VP1.1, NHX1, and TIP. The candidate gene analysis covered a concatenated length of 4594 bp per individual and identified five SNP/Indels in DREB1A and VP1.1 genes explaining 17.0% to 25.8% phenotypic variation for various salt tolerance traits. Out of these five alleles, one at 297 bp in DREB1A had in-frame deletion of 6 bp (CTGCAT) or 12 bp (CTGCATCTGCAT), resulting in two alleles, viz., SpDREB1A_297_6 and SpDREB1A_297_12. These alleles individually or as haplotypes accounted for maximum phenotypic variance of about 25% for various salt tolerance traits. Design of markers for selection of the favorable alleles/haplotypes will hasten marker-assisted introgression of salt tolerance from S. pimpinellifolium into cultivated tomato. Introduction Soil salinity can be due to high concentration of the ions K + , Na + , Ca 2+ , Mg 2+ and Cl - [1]. When the electrical conductivity (EC) of the saturation extract in the root zone is in the range of 4 dS m -1 , which is equivalent to 40 mM NaCl, soils are considered saline [2]. Cultivated tomato is moderately sensitive to salinity and tolerates up to 2.5 dS m -1 EC. Above this threshold, the crop suffers at least a 10% yield decrease for each unit of increase of soil salinity [3]. Plants react to the presence of increased levels of salt in the soil solution in two phases: a rapid osmotic phase in which increased levels of salt in the soil result in increased osmotic stress to the roots causing a reduction in leaf and shoot growth, and a second ion-specific phase, which starts to affect plant growth when salt accumulates to toxic concentrations in the older leaves [4]. Osmotic stress, ion imbalance and toxicity reduce nutrient uptake and transport capacity leading to nutritional imbalances [5], and finally necrosis and premature death of older leaves. Three mechanisms of salinity tolerance in plants are recognized: The first is osmotic tolerance which is regulated by long distance signals and occurs prior to Na + accumulation in the shoots. The second mechanism is ion exclusion, in which Na + and Clion accumulation in the shoots is minimized. This is a glycophytic response that restricts the entry and accumulation of the potentially toxic ions Na + and/or Clinto the shoots. The third mechanism is tissue tolerance, which is the ability of the plant to compartmentalize the toxic ions Na + and/or Clinto vacuoles, to keep the enzymatic reactions in the cytosol and/or organelles functional [6]. In this context, the maintenance of a high cytosolic K + /Na + ratio and the precise regulation of ion transport are critical for plants to tolerate salinity stress. Plant tolerance to salinity stress involves the functions of many genes that control a range of biochemical and physiological processes. In recent years, substantial research has focused on genetic engineering of candidate genes for abiotic stress tolerance in model plants under controlled conditions, and this has resulted in insights on the role of these genes in key physiological and biochemical processes [7]. Over 18,000 patents have been granted that invoke plant salinity tolerance [1]. Genes that have been used in genetic engineering to improve abiotic stress tolerance include those that facilitate the accumulation of organic compounds with low molecular weight, which serve as osmolytes and contribute to osmotic adjustment. Overexpression of different vacuolar antiports facilitates the exclusion of toxic ions from the cell cytosol [8], while enhanced expression of detoxification enzymes reduces oxidative stress [9]. Other candidate genes that encode regulatory and signaling proteins include, for example, dehydration-responsive element binding (DREB) proteins [10], protein kinases [11], and aquaporins [12]. A comprehensive review of the genes and regulatory networks involved in the improvement of tolerance to drought and salinity stresses has been published [13]. Linkage mapping has been useful to identify major QTLs conferring salt tolerance in plants [ [14][15][16] and to exploit them in breeding programs [17]. However, salt tolerance is genetically complex involving diverse mechanisms and governed by multiple genes and often strongly impacted by the environment resulting in limited progress. In this regard, association or linkage disequilibrium (LD) mapping complements traditional mapping efforts for precision and power of identifying causal variants. This strategy originally established in human and animal genetics has successfully been extended to plants during the last decade [18,19], and recently in tomato [20][21][22]. Association mapping is performed in two ways: genome wide association study (GWAS), which surveys genetic variation in the whole genome to find signals of association for target traits [23] and candidate gene based association study (CGAS), which relates to linking phenotypic variation with the polymorphic sites in candidate genes to identify the causative polymorphisms [24]. Population structure and multiple testing are two issues that need to be addressed while conducting association analysis. The population structure in the genotype panel may lead to false positive associations if the frequency of a certain phenotype varies across sub-populations. The structure issue has been effectively addressed by the development of a statistical model, called unified mixed linear model (MLM) [25], which takes into account both population structure (Q) and relative kinship (k) information while performing association analysis. Multiple testing refers to an instance that involves the simultaneous testing of several hypotheses and if the multiplicity of tests is not taken into account, the probability that some of the true null hypotheses are rejected by chance alone may be unduly large. False discovery rate (FDR) correction of observed P values has been suggested by Storey and Tibshirani [26] to address this issue. While genetic variability for salt tolerance traits is limited in cultivated tomato, sources of tolerance have been reported among wild Solanum species: S. pimpinellifolium, S. peruvianum, S. cheesmaniae, S. habrochaites, S. chmielewskii and S. pennellii [27]. Introgression of salt tolerance traits from distant wild relatives to cultivated S. lycopersicum is difficult due to crossing barriers and linkage drag. Finding sources of salt tolerance in S. pimpinellifolium will be helpful as it is the closest wild relative and readily crossable with S. lycopersicum. S. pimpinellifolium also has been a source of useful genes for many other important horticultural traits of cultivated tomato including yield and disease resistance [2]. It has been suggested that S. pimpinellifolium accessions could be the most promising sources for improvement of salt tolerance in tomato cultivars [28,29]. This species is native to the Andean region of Peru and Ecuador in Western South America [30], where it is found in dense populations located in undisturbed areas and adapted to diverse environmental conditions ranging from the coastal desert climate to humid and foggy conditions of higher altitudes [31]. Considering that the natural range of S. pimpinellifolium encompasses environments as diverse as the Ecuadorian tropical forest and the coastal Peruvian desert, this species is a potential source of beneficial alleles for abiotic stress tolerance. For the present study, we focused on four major genes that have a demonstrated contribution to salinity stress tolerance; NHX1 [32], VP1.1 [33], tonoplast intrinsic proteins (TIP), [12] and dehydration-responsive-element-binding (DREB) protein gene DREB1A [34]. The gene NHX1 is a member of the intracellular NHX antiporter family which catalyzes Na + , K + /H + exchange and is associated with diverse growth and development processes [35]. It is essential for active K + uptake into the vacuole for regulation of turgor and stomatal function [36]. The overexpression of AtNHX1 has conferred improved salt tolerance in Arabidopsis [37] and tomato [32] with salinity tolerance being correlated with increased levels of NHX1 expression. Higher levels of NHX1 expression were reported in S. pimpinellifolium compared to S. lycopersicum, both in the absence of salt stress and after subsequent exposure to salt stress confirming the importance of NHX1 in salt tolerance determination [38]. The NHX1 gene was originally described as a vacuolar Na + /H + antiporter [37], however recent evidence supports a role for NHX1 in the subcellular partitioning of K + rather than Na + [39]. Tomato plants overexpressing AtNHX1 accumulated large K + vacuolar pools but showed no increase in Na + accumulation with salinity stress [39]. Plants overexpressing AtNHX1 exhibited increased tolerance to salinity stress which was postulated to be derived from the role that AtNHX1 plays in K + homeostasis. The AVP1 gene encodes for a vacuolar H + pyrophosphatase located to the tonoplast and plasma membrane [33]. Arabidopsis plants overexpressing AVP1 show increased tolerance to salinity, presumably as a result of increased levels of ion uptake into the vacuole [40]. Salinity tolerance was further increased in transgenic tomato by the co-overexpression of AVP1 and AtNHX1 genes [41]. The TIPs, members of the aquaporin family, targeted to the vacuolar membrane have recently been characterized in tomato [12]. Ectopic expression of tomato SlTIP2;2 in both tomato [42] and Arabidopsis [43] produced plants with salinity stress tolerance which was suggested to be a result of a lower osmotic potential and higher water content under salinity stress. The stress inducible transcription factors DREBs, have been studied extensively in response to environmental stress [44]. They are transcriptionally up regulated in response to abiotic stresses such as drought, salinity and cold, and ectopic expression has been associated with improved salinity stress tolerance in Arabidopsis [44], tobacco [45], and potato [46]. It has not yet, to our knowledge, been investigated in relation to salinity stress tolerance in tomato, however it shows potential as a key single gene that is able to confer tolerance to multiple abiotic stresses when upregulated. The DREB family of transcription factors, of which DREB1A is a member, have been suggested to confer increased salinity tolerance through its involvement in signal transduction pathways for the elevated expression of stress responsive genes such as LEA genes and sugar biosynthesis [45]. Recent work of our group has focused on constructing a core germplasm collection of S. pimpinellifolium [47] and phenotypic expression of salinity tolerance traits in S. pimpinellifolium in comparison with cultivated tomato [48]. In this study, our objectives were to: (a) characterize four candidate genes (DREB1A, VP1.1, NHX1, and TIP), reportedly involved in salt tolerance, for nucleotide diversity and LD in a S. pimpinellifolium core germplasm panel; (b) determine the association between candidate gene polymorphisms and phenotypic traits selected for salt tolerance in the germplasm panel; and (c) identify favorable haplotypes in the candidate genes associated with high salt tolerance in S. pimpinellifolium accessions. Phenotypic evaluation Salt tolerance was assessed both as per se performance under salt stress and relative performance under salt stress compared with control conditions for various yield and survival traits according to the definition of Munns and James [49]. A wide variation with near normal distribution was observed in the germplasm panel for various survival and yield traits under both stress and non-stress conditions (S1 Table). Analysis of variance (ANOVA) revealed significant differences (P = 0.01) among the genotypes for all traits in both stress and non-stress conditions. Most of the traits recorded skewness values less than 1 and kurtosis values less than 3 suggesting near normal distribution except traits like Na content, K/Na ratio under salt stress and most yield related traits under both control conditions and salt stress, which recorded moderate skewness (S1 Table). Interestingly, most of these yield related traits were also correlated with population structure suggesting the effect of genetic background for the observed deviation from normality. Lack of fertilization during the experiment may be another plausible reason for positive skewness in all the yield related traits. Compared to control conditions, significant reduction under salt stress was observed for chlorophyll content (t-value = 24.2), plant height (t-value = 21.8), shoot dry weight (tvalue = 26.7), fruit set percentage (t-value = 4.1), fruit number (t-value = 7.4), and yield per plant (t-value = 10.8) at 1% significance and average fruit fresh weight (t-value = 2.4) at 5% significance. The survival ratings among the 94 accessions were distributed normally ranging from 0 (low) to 4 (high) with an average of 2.0. The control accessions possessed a low survival score of 0.3 for 'Arka Meghali' and 0.9 for 'CA4' (Fig 1). Further details of the phenotyping results including phenotypic correlation coefficients among major agronomic traits and a list of selected genotypes with high survival score, with high fruit number/yield and two genotypes combining high survival score and high fruit number are presented in a previous paper [48]. Population structure and kinship A total of 204 SSR markers were used to understand the population structure in the panel of 94 accessions of S. pimpinellifolium employing a model-based approach as implemented in STRUCTURE. Fifty data sets were obtained by setting the number of possible clusters (K) from 1 to 10 with five replications each. The results were then permuted for each K value using CLUMPP software. Applying the second-order statistics (ΔK) developed by Evanno et al. [50], there was a sharp peak of ΔK at K = 2, suggesting two major populations. Using the kinship matrix, which was developed based on 204 SSR markers, relative kinship estimates revealed that 55.4% of the pairwise kinship estimates were equal to 0 whilst 96.4% were below 0.3, with a continuously decreasing number of pairs falling in higher estimated categories (Fig 2). Sequence diversity and intragenic LD for candidate genes The candidate gene sequence analysis covered a concatenated length of 4594 bp and a total of 33 SNPs and 11 indels with allele frequency greater than 5% were detected in the panel of 94 genotypes (Table 1). This is equal to one SNP/indel per 107 bp. Large differences were found in the number of SNPs/indels and nucleotide diversity parameters across the four candidate genes. The SNP/indel frequency varied from 1/87 bp (NHX1) to 1/131 bp (TIP) and the number of SNPs/indels varied from 18 in the VP1.1 gene to 4 in the TIP gene. The total nucleotide diversity ranged from 0.0031 for NHX1 and VP1.1 to 0.0023 for TIP genes ( Table 1). The LD was calculated for each candidate gene using TASSEL 2.1. Out of 255 locus-pair comparisons in the four candidate genes, 91 pairs (35.68%) had significant R 2 value above the Table 2). Seven pairs were in complete LD. However, TIP, VP1.1 and DREB1A recorded a lower percentage of pairs in LD compared to NHX1 ( Table 2). Marker trait associations STRUCTURE analysis indicated that the germplasm panel had two major populations. Therefore, it was of interest to know if the traits evaluated in this study showed correlation with population structure. It was noted that most of the traits did not correlate with the population structure except chlorophyll content under control, plant height under salt stress, fruit number and average fruit weight under control, and salt stress conditions (Table 3). Mixed linear model based association analysis recorded 28 marker trait associations across the four candidate genes at a significance level of 0.01 (Table 4). A total of seven traits for DREB1A, four traits for VP1.1, three traits for NHX1 and one trait for TIP have been found to be associated in at least one of the environments (control and/or salt stress). DREB1A and NHX1 recorded significant associations especially for yield related traits both under control and salt stress conditions while the physiological traits were associated only under salt stress. VP1.1 did not record any associations under control conditions and all the trait associations were only under salt stress. After the P values were corrected for false discovery rate (FDR), only five alleles showed significant associations (Table 5). Among them, two were in DREB1A (13 bp and 297 bp positions) and three in VP1.1 (470 bp, 983 bp and 1191 bp positions) ( Table 5). None of the variations in NHX1 and TIP showed significant association with salt tolerance traits after FDR correction. Haplotype analysis Intragenic haplotypes for variations possessing significant associations with salt tolerance traits were manually derived for DREB1A and VP1.1 genes. These haplotypes were scored as multiallelic genotypes as suggested by Barendse [51]. The matrix of this genotypic data was used for association analysis to determine the effects of haplotypes on various salt tolerance traits. Three haplotypes with minor allele frequency (MAF) >0.05 were found in DREB1A and two haplotypes were found in VP1. Table 6). Effect of trait associated variations on protein sequence All the five allelic variations were observed in exonic regions. The variant DREB1A_13 had a frame shift mutation because of a 1 bp deletion. The deletion of nucleotide T at 13 bp position led to a change from proline in wild type (allele 0) to leucine (allele 1) and resulted in premature termination of coding sequence. The variant DREB1A_297 had in-frame deletions of 6 bp or 12 bp at 297 bp position. The 6 bp (CATCTG) and 12 bp (CATCTGCATCTG) deletions at this position led to a change in amino acid sequence from SASASA (allele 0) in wild type to SASA (allele 6) and SA (allele 12), respectively (Fig 3). Since these alleles possessed the most significant effect on salt tolerance in S. pimpinellifolium, we name the alleles 6 and 12 as SpDREB1A_297_6 and SpDREB1A_297_12 respectively. Three alleles of VP1.1 had synonymous variations, which did not cause any change in the protein sequence. Discussion A suitable association mapping panel should encompass as much phenotypic and molecular diversity as can be reliably measured in a common environment [52]. Breseghello and Sorrells [53] have reviewed the choice of populations for association analysis in plant breeding programs and suggested that core collections representing the genetic diversity of a species available in genebanks are attractive for association analysis due to the presence of abundant allele diversity. Core collections are useful materials for association analysis of adaptive traits like stress tolerance because of wide allele diversity [54]. The process of selection of a minimum sample with maximum variation while developing a core set has a normalizing effect that is expected to reduce population structure and LD between unlinked loci, thus creating a situation favorable for association analysis [53]. A core set of S. pimpinellifolium was therefore developed [47] for this purpose and is fairly represented in the current experiments. A total of 27 out of the 94 S. pimpinellifolium genotypes (S2 Table) originated from sites close to the sea and might have naturally adapted to high salinity conditions. Population structure and kinship The accuracy of marker-trait association is affected by the relatedness among the members of the germplasm panel in which marker effects are estimated. Gowda et al. [55] demonstrated that close relatedness may lead to a substantial increase in the proportion of total genotypic variance explained by the identified QTL resulting in over-optimistic judgment of the precision of marker-assisted selection. The two subpopulations identified in our analysis of population structure indicated distinct subdivisions based on their center of origin. In this study we used 204 SSR markers to estimate kinship, which is considerably higher than the 100 SSR markers recommended by Yu et al. [56]; hence, a robust kinship estimate can be expected. The kinship analysis indicated that 96% of the pairwise kinship estimates were below 0.25, suggesting that most lines had no or weak relationship with the other lines in this DREB1A Alleles Contributing to Salt Tolerance in S. pimpinellifolium panel-which was to be expected, as the genotypes used in this study belong to a recently established S. pimpinellifolium core collection [47]. Sequence diversity and intragenic LD The Tajima's D test [57] for all four candidate genes showed no significant difference between π and θ, indicating much lower selection pressure, as would be expected for a wild species. Abundant diversity and rapid LD decay in a germplasm panel are ideal for candidate gene association mapping. The genes TIP, VP1.1 and DREB1A recorded a lower percentage of pairs in LD compared to NHX1 ( Table 2). The diverse LD decay rates for different candidate genes indicate a biased and non-uniform evolution of individual genes within the same species as reported by Yu et al. [56]. Marker trait associations The current germplasm panel appeared not to be skewed for salt tolerance in terms of population structure. Yu and Buckler [58] warned that the presence of population structure within association mapping panel may often generate spurious genotype-phenotype associations. The spurious associations cannot be controlled completely by population structure alone as the Q matrix gives only a rough dissection of population differentiation. Therefore, Yu et al. [25] suggested incorporating the pairwise kinship into the mixed model to correct for relatedness in association mapping. Hence, we employed a mixed linear model approach that accounts for both population structure (Q) and relative kinship (k) as implemented in the TASSEL 2.1 software package [59]. The P values were corrected for false discovery rate to address the problem of multiple testing. We considered the five putative allelic variants as major alleles as they explained larger phenotypic variation (17.0% to 25.8%). Edae et al. [60] suggested that a QTL that explains more than 10% of phenotypic variation can be considered a major locus in association mapping. Furthermore, Yu et al. [61] reported that the power and precision of detecting a causal factor in a small panel size of around 100 individuals will be high only for genetic factors accounting for >10% of the phenotypic variation. Among four candidate genes studied in this experiment, DREB1A and VP1.1 showed association with physiological traits; (DREB1A with K/Na ratio and plant height percent reduction under salt stress; VP1.1 with chlorophyll content under salt stress) supporting their role in adaptation to salt stress. However, only DREB1A had association with yield traits (fruit number) under both control and stress conditions. Elevated levels of DREB1 expression have been associated with adaptation to a wide range of abiotic stresses such as heat, drought, cold, and salinity [44]. Several studies have revealed the reduction in chlorophyll content as a response to salt stress. High shoot Clcontent under salt stress was inversely correlated with leaf chlorophyll content [62,63]. This observation strongly supports the association of VP1.1 with chlorophyll content under salt stress found in this study. The results also indicated significant associations with survival traits under stress but not yield traits except in the case of DREB1A_13 which showed association with fruit number irrespective of the stress condition. The possible pleiotropic effect of DREB1A on yield traits needs to be studied in detail. Although survival traits have a low correlation with fruit yield under salt stress [48], a full understanding of the mechanism of these traits would assist breeders in the development of a tomato ideotype for high yield under stress and non-stress conditions. Haplotype analysis In association analysis, every putative marker usually would have multiple alleles in the mapping panel and each of those alleles would contribute differently to the associated trait [64]. Finding a right combination of highly effective alleles at multiple loci within the candidate gene that forms a tolerant haplotype would be more relevant than the individual allele itself at a single locus. It is not sufficient to consider only the effects of an individual SNP when it is possible that another SNP is always modified at the same time. For instance, Jia et al. [64] reported that haplotypes may be advantageous over individual SNPs in the presence of multiple disease susceptibility alleles, particularly when LD between SNPs is weak. The importance of haplotyping is better realized when the actual mutation causing trait variation is not linked with any one SNP but linked with a specific haplotype, and the haplotype effect is stronger than individual SNPs. Therefore, it was in our interest to analyze the association of DREB1A and VP1.1 haplotypes with salt tolerance traits. In the current study, common trait associations of individual SNPs/indels and haplotypes could be detected for K/Na ratio under salt stress, plant height percent reduction and fruit number (DREB1A), and chlorophyll content under salt stress (VP1.1). However, the haplotypes did not improve the phenotypic performance, suggesting that the haplotype effect is only due to LD and not functional synergism among the candidate variations. Hence candidate SNP selection would be as effective as the haplotype selection in the current scenario. Effect of trait associated variations on protein sequence SNPs exist throughout the entire genome, within and outside of coding regions. SNPs residing outside coding regions can occur in intergenic sequences, 5'-or 3'-untranslated regions, intronic regions, and associated non-coding regions such as promoter and transcription factor binding sites. The five alleles exhibiting major associations (R 2 >10%) with salt tolerance traits were of exonic origin, of which DREB1A alleles at 13 bp and 297 bp positions caused amino acid sequence change due to frame shift change and in-frame deletions, respectively. The VP1.1 alleles had synonymous mutations without altering the amino acid sequence. Two hypotheses can explain their significance, the most likely one being that these SNPs do not correspond to the functional mutation but are in LD with it. All markers in strong LD with a functional mutation will appear as significant in association tests. Another possible explanation is that these synonymous SNPs do not lead to amino acid residue changes at protein level; however, they are documented as leading to changes in mRNA structure, stability and splicing or even in delay or acceleration of protein folding that can result in different final protein conformations and functionality [65]. Genes from the DREB family have been isolated and characterized in a number of plants including Arabidopsis [66], wheat [67,68], rice [69,70], and maize [71,72]. Transgenic tomatoes containing a CBF1 (DREB1B) transcription factor from Arabidopsis had enhanced tolerance to water deficit stress, but were also stunted [73]. Growth retardation could be reversed with exogenous application of the growth hormone gibberellic acid. Plant dwarfism and abnormal phenotype are two major aspects that currently limit the practical use of DREB genes of Arabidopsis in crop breeding through a transgenic approach [34]. However, the alleles, SpDREB1A_297_12 (allele 12) and SpDREB1A_297_6 (allele 6) or the haplotypes found in the current experiments can be a good alternative for traditional tomato breeding, without adverse effects like dwarfing and other abnormal phenotypes. The allele SpDREB1A_297_12 which possessed the highest R 2 value in the current experiment recorded a lower reduction in plant height (0.38), more number of fruits (41.08), better survival score (2.10) and a lower K/Na ratio (2.08) compared to the wild type allele (0.41; 13.07; 1.73 and 2.39 respectively). This indicates a favorable effect of this DREB1A allele through tissue tolerance rather than ion exclusion. Further studies are required to validate this mechanism. Generally, once genes that determine the genetic basis of a trait are known, developing functional markers to select for favorable alleles is an important aspect of using genetic information in practical plant breeding [61]. A functional marker is a marker developed from a SNP/indel within a gene that is responsible for variation in the trait [74]. The use of functional markers in molecular plant breeding is more advantageous than linked markers because the latter may lose their diagnostic capacity in breeding populations due to recombination between the marker and the causative SNP region in subsequent generations [74]. Since the functional markers are developed from SNPs within a gene, molecular information can be used confidently across breeding programs to select promising alleles for a trait of interest [75]. The information generated in this experiment can be used to develop functional markers for pyramiding of desirable alleles of multiple genes of interest through marker-assisted backcrossing. However, the benefit of the favorable alleles detected in wild tomato has to be validated in elite lines. The future experiments may also consider the following possibilities: firstly, the small germplasm panel used in this study might be useful for detection and analysis of major QTLs, but a larger panel would be more effective for investigating the role of minor loci in stress tolerance. Secondly, the marker-trait associations that were found in this study could further be demonstrated in linkage mapping using bi-parental populations to rule out the possibility of false positives as the covariance between genotypes and phenotypes can be broken by generating controlled crosses [76]. Combining association analysis with linkage mapping would be helpful, especially for validating rare variants. Thirdly, only three accessions [#26, #46 and #72; S1 Table] recorded the highest survival score of 4.0 [48] in spite of several accessions possessing favorable alleles in the candidate genes studied. This observation indicates that other important genes are likely involved in the expression of salt tolerance. Therefore a genome-wide association study could probably provide information on more key genes implicated with salt tolerance in S. pimpinellifolium. Materials and Methods Plant materials and experimental design for salt stress AVRDC-The World Vegetable Center (AVRDC) maintains a collection of 330 accessions of S. pimpinellifolium [77]. From this collection, a subset of 94 accessions was chosen for the study based on passport data, genetic structure, and a fair representation of the core set developed earlier [47]. Details of the 94 S. pimpinellifolium accessions and their country of origin as well as the collection site, where available, are provided in S2 Table. A total of 27 accessions originated from coastal areas. Two cultivated tomato genotypes-the Indian cultivar 'Arka Meghali' and an inbred line 'CA4', frequently used in AVRDC's tomato breeding program were included as checks. The trials were conducted in net houses at AVRDC headquarters, Taiwan with mean day and night temperatures of 25°/16°C and a photoperiod of 15 hours. We used a split-plot design with two treatments consisting of salt stress (200 mM NaCl) and standard irrigation water (control). Three replications were used per treatment with 3 plants each. The plants were raised in seedling trays with peat moss and were transplanted after 5 weeks into 20 L plastic pots filled with a sterilized mixture of peat, decomposed organic residues, and soil in the ratio of 1:1:1 which possessed an EC of 1 dSm -1 measured by the saturated paste method [78]. A progressive salinization technique was employed for imposition of salt stress. All pots in the salt treatment were irrigated with 500 ml of 200 mM NaCl solution every alternate day, while pots of the control were irrigated with 500 ml of normal irrigation water (0 mM NaCl) at the same frequency. The salinity treatment level was based on prior studies that helped establish a clear distinction between salt tolerance and susceptibility of S. pimpinellifolium, both in terms of survival and yield related traits. No fertilizer was applied in this experiment to avoid interference with the salt treatment. Stress imposition started from the ninth week of sowing, when most of the genotypes started flowering. The duration of the stress treatment was 11 weeks. The average EC of the substrate at the end of the experiment in the salt treatment was 40 dSm -1 , while the substrate of the control measured 1 dSm -1 . Phenotypic evaluation and data analysis During the 11 weeks of stress imposition, various physiological traits as well as yield and yield components were recorded under both treatments. Leaf chlorophyll content was measured at each fourth expanded leaf from the plant top at 15 weeks after sowing using a portable Minolta Chlorophyll Meter SPAD 500. Similarly, leaf sodium and potassium concentrations were measured at each fourth expanded leaf from the plant top at 15 weeks from sowing using Cardy sodium and potassium ion meters (HORIBA, Model C-122 and C-131, Japan). The selected leaves were crushed and homogenized in a sterilized polycover using a metal ball roller. One hundred microliters of homogenized sap was used for estimating the sodium and potassium concentrations. Plant height (cm) was recorded from the base of the plant to the tip of the meristem and shoot dry weight (g) including all above ground parts except fruits was recorded at the end of the experiment. Dry weight was determined after drying at 80°C in an oven until a consistent weight was recorded. A survival score (0-4 scale) was given based on the mode of the performance of a group of plants under stress in each replication for all accessions including check varieties. Percent fruit set was calculated by dividing the total number of fruits by the total number of flowers set on 3-7 th trusses, multiplied by 100. Number of fruits per plant was determined from four harvests at breaker stage. Average fruit weight (g) was obtained by dividing total fruit fresh weight by the total number of fruits collected from a single plant. Yield per plant (g) was determined by measuring total fruit weight. The performance of 94 genotypes and two check varieties for the above traits, except leaf sodium and potassium concentrations (due to negligible concentrations in the control) and survival score under salt stress was compared with their performance under control conditions to obtain percent change in performance due to salt stress. The mean data of the above traits were used to calculate broad-sense heritability (H) based on between and within accession variances. The statistical analysis was carried out using the GENRES statistical program [79]. The experimental details and analysis of phenotypic data was described previously [48]. Population structure, LD and marker trait association analysis Population structure and kinship. A total of 204 simple sequence repeat (SSR) markers (S3 Table) were selected from all 12 chromosomes to determine population structure and kinship. Genotyping followed the methodology described by Geethanjali et al. [80]. An admixture model with correlated allele frequency in STRUCTURE 2.2 software [81] was applied with a burn-in of 30,000 iterations and a total Markov chain Monte Carlo (MCMC; [82]), length of 100,000 to test a number of populations (k) with values from 2-10. Each k was replicated five times and the run that assigned more lines with possibility of > 0.5 in all clusters was used. The likely number of sub-populations was determined using the approach of Evanno et al. [50], in which the change of k (delta k) was maximized. The Pearson correlation coefficients were calculated between Q1 value and each phenotypic trait (R 2 ) to understand the influence of population structure on salt tolerance. Kinship matrix (k) was calculated according to Ritland [83] using the SPAGeDi software package [84]. The SSR markers with allele frequency less than 10% and more than 10% missing data were discarded from the analysis. The distribution of pairwise kinship data points was summarized using Excel's internal function 'frequency'. Diagonal of the matrix was set to 2 and all negative values between individuals were set to zero [25]. Q matrix from STRUCTURE and k matrix from SPAGeDi were formatted to a text file readable by TASSEL for association analysis. Candidate gene specific primer design, amplification, sequencing, and LD analysis. Reference sequences for the selected candidate genes DREB1A (complete cds, AF00011), NHX1 (partial cds, AJ306630), VP1.1 (partial cds, AJ278019) and TIP (partial cds, AY731066) were obtained from the GenBank database of the National Centre for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/genbank/). Primer3 tool was used to design primers based on reference sequences for PCR amplification of the selected candidate genes in order to give maximum sequence coverage [85] (Table 7). DNA extraction followed the methodology described by Geethanjali et al. [80]. The PCR amplicons were purified using a QIAquick PCR Purification Kit (Qiagen) and sequenced using an ABI 3700 DNA analyzer (Applied Biosystems, USA) (genedragon.com.tw). The nucleotide sequences for DREB1A (KM094061-KM094129), VP1.1 (KM244580-KM244651), NHX1 (KM093902-KM093974) and TIP (KM093975-KM244651) have been deposited in the NCBI Genbank database. To identify SNPs, contigs were first generated by aligning forward and reverse sequences of each genotype using the contig assembly program implemented in Bioedit 7.0.0 [86]. The contig sequences of the 94 genotype panel were used to develop multiple sequence alignments using the Clustal W program implemented in Bioedit. These multiple sequence alignment files were used to extract SNPs and indels with minimum allele frequency (MAF) > 5% using SITES command in TASSEL. The SNPs and indels were then used to estimate diversity and intragenic LD in those candidate genes as implemented in TASSEL 2.1 [59]. The reading frame, position of the trait associated SNP/Indels and their effect on the resulting amino acid sequence was studied using ORF finder software (NCBI) and compared with coding sequence (CDS) of the reference accession. Association analysis. Association analysis was conducted to determine the effects of SNPs in each gene on various salt tolerance traits. A mixed linear model [25] was applied for association analysis that evaluated the effects of SNPs/indels/haplotypes with MAF > 5% individually, adjusting for population structure and kinship as implemented in TASSEL 2.1 [59]. To avoid the problem of multiple testing during association analysis, the False Discovery Rate (FDR) corrected significance values were calculated using QVALUE [26]. The q-value is a measure of significance in terms of the false discovery rate similar to the p-value that relates to the false positive rate. Marker-trait associations having a q-value equal or inferior to 0.05 were declared significant. The P and q values determine whether a locus/haplotype is associated with the marker and the marker R 2 evaluates the magnitude of the locus effect [87]. Table. List of 204 SSR markers used for structure and kinship analysis along with their position, repeat motif, and primer sequence. (XLS)

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Goitrogenic and Antithyroid Potential of Green Tea Of Indian Origin Polyphenolic flavonoids, specially catechins are major constituents of tea. Antithyroidal and goitrogenic effect of flavonoids have been reported however such effects of green tea on thyroid physiology has not been explored earlier. Green tea is derived from the tea leaves of Camellia sinensis and widely consumed globally. The green tea extracts(GTE) at different concentrations (1.25g% a” 5 cups of tea/ day; 2.5g% a” 10 cups of tea/ day and 5.0g% a” 20 cups of tea/ day) were orally fed to male rats for 30 days. Similarly, pure catechin was administered orally to male albino rats for 30 days at doses of 25, 50 and 100 mg/kg body weight that are equivalent to above doses of green tea extract in terms of its total catechin content and the morphological and functional changes of the thyroid have been investigated. The overall results reveal that oral administration of green tea extract at 2.5g% and 5.0g% concentrations for 30 days changed the morphology and histology resembling hypertrophy of thyroid follicles with differential colloid sizes as found in hypothyroid due to environment influences associated with significant inhibited activities of thyroid peroxidase(TPO) and 5’ monodeiodinase (5’ DI1) with elevated Na+,K+ ATPase and concomitant decrease in serum thyroxine (T4), triiodothyronine (T3) and increase in serum thyrotropin (TSH) levels developing a state of absolute biochemical hypothyroidism. All these suggest that catechin present in green tea has the antithyroidal as well as goitrogenic potential and its regular consumption at relatively high doses pose a threat to the functioning of thyroid. Introduction gallate), (-) EGC -(Epigallo catechin), (-) EC -(Epicatechin) and (-) ECG -(Epicatechin gallate) with (-) CG -Catechin gallate. Other compounds obtainable in tea are the flavonols (quercetin, kaempferol, myricitin and rutin); caffeine, phenolic acids, theanine and flavour compounds 1 . Green tea is commonly consumed in China, Japan and Eastern Asia, The intake of catechins can be expected to be higher in the Asiatic countries and the health effects of green tea may be more apparent when examined in the Asian communities 2 .Tea is a source of a wide range of phytochemicals that are digested, absorbed and metabolized by the body and tea constituents exert their effects at the cellular level 3 . Epidemiologic evidence provides a convincing argument that polyphenolic antioxidants present in green can reduce several chronic diseases, especially cardiovascular disease and cancer 4 . Despite its enormous usefulness and potential health benefits, flavonoids emerge as phytochemicals of great concern due to their antithyroidal and goitrogenic effect. It has previously been reported that the consumption of flavonoids and some phenolic acids by experimental animals induced enlargement and histological changes in the thyroid gland [5][6][7][8][9] . Studies on effects of tea extracts on thyroid physiology are not available though it is used as whole beverage rather taking any single component of it, so this is very plausible to investigate the effect of total green tea extract on rats. The effects of green tea consumption at different doses on the thyroid physiology have been explored to understand the pathophysiology of its goitrogenic potential in euthyroid rats. For the purpose dose or concentration dependent effects of total GTEs without any specific purification of possible candidate compounds on thyroid gland architecture, thyroid peroxidase (TPO), 5'deiodinase I (5'-DI) and sodium-potassium adenosine triphosphatase (Na + , K + ATPase) activities, and serum levels of thyroid hormones were investigated in vivo and discussed. Background The effects of GTE catechin on the rat thyroid were examined in a 2-, 4-, 8-and 13-week feeding studies. Commercially available polyphenols-60 (P-60) which contains green tea extract catechin at 66.2% was used as a source of catechins. A basic diet containing P-60 at 0 (Control), 0.625, 1.25, 2.5 and 5.0% were fed and goiters were observed in 13-week test. The mean thyroid weight of rats fed a diet containing 5.0% of P-60 (5.0% group) significantly increased to 444% of the control in males and to 304% of the control in females. Histological examinations of the thyroid of the 5.0% group revealed marked hypertrophy and/or hyperplasia of the follicles, some with depletion of colloid and some with rich colloid, and formation of fibrous capsule. Slight hypertrophy of follicular cells was observed in male rats fed a diet containing 2.5% of P-60 (2.5% group). The degree and incidence of thyroid lesions were higher in males than in females. These results indicate that dietary administration of the green tea extract catechin at high doses induced goitre in rats and this may be due to antithyroid effects of catechin 10 . On the contrary, daily oral administration of standardized and defined green tea polyphenols to humans for 28 days was found to be safe 11 . In another dose-response study, dietary exposure of green tea catechin at levels upto 5% in a diet for 90 days to F344 rats resulted in no significant histopathological changes in the thyroid. Therefore, a detailed study on thyroid gland morphological / histological and functional changes in vivo after the exposure of GTE has been investigated. The effects of pure catechin on the thyroid were also studied to delineate whether the anti-thyroidal/goitrogenic effect of green tea extract are modified through catechin, the important flavonoids present in tea 12 . Duration of the treatment The animals were administered the above mentioned 3 doses with GTE for the period of 30 days. Morphological/ Histological Changes The relative weight of thyroid gland increased significantly in a dose-dependant manner in both the GTE and pure catechin treated animals as compared to control group ( Figure 1). The changes in weight are corroborated in the histological changes of the thyroid gland. Normal thyroid gland is made up of thyroid follicles formed by a single layer of low cuboidal epithelium. The nucleus of the follicular cell is round to ovoid, sometimes irregular in shape, centrally placed and uniform in size and inconspicuous. A basal lamina envelops the follicles. Numerous capillaries and lymphatics surround the follicles. The follicular lumen is occupied by colloid, partly composed of thyroglobulin which is evenly applied to the luminal cell borders 15 . Histological sections (E/ H stains) of thyroid of green tea and catechin induced groups are shown in Plates 1 and 2 respectively. The histological features of thyroid glands of pure catechin and green tea extract treated groups of animals along with the control group of rats were shown in Plate 1 and 2. Thyroid gland section from control animals obviously showed no pathologic feature. Thyroid appeared normal both grossly and microscopically in 1.25g % dose of green tea treated group. But diffuse hypertrophy and /or hyperplasia of thyroid follicular epithelial cells without inflammatory reactions was found in the other treated groups. In the 5.0g % group of GTE, the number of thyroid follicles was increased and they were not uniform in shape and colloid content as most of the follicles were colloid rich however, colloid depleted follicles were also observed; while in the 2.5g % group of GTE, the thyroid follicles were diffusely hypertrophic and contain little colloid with increased height of the follicular epithelium from cuboidal to tall columnar. Pure catechins treatment at a doses of 25mg and 50mg/ kg body weight daily for same duration had produced thyroid lesions characterized by the presence of few follicles filled with depleted colloid and irregular shaped follicles having decreased luminal spaces with tall columnar or cuboidal follicular epithelium; while at a dose of 100 mg/kg body weight of pure catechin, the presence of desquamated epithelial cells and mononuclear cell infiltration within the follicles were observed. Goitre is a diffuse or nodular enlargement of the thyroid gland when there is deficiency of circulating thyroid hormone because of inborn errors of metabolism, iodine deficiency, or goitrogenic agents and if the hypothalamic pituitary axis is intact, production of thyroid stimulating hormone (TSH) is increased; consequently, cellular activity and increased glandular activity and glandular mass result in an attempt to restore the euthyroid state. Worldwide the most common cause of thyroid hormone deficiency is an inadequate amount of iodine in the diet, leading to iodine deficiency goitre 16 . Other causes include inborn errors of thyroid metabolism (dishormonogenic goitre), dietary goitrogens and goitrogenic drugs and chemicals. The pathologic changes of simple non-toxic goitre include (a) hyperplasia (b) colloid accumulation and (c) nodularity [16][17][18] . Hyperplasia represents the response of thyroid to TSH, other growth factors or circulating stimulatory antibodies 19 . The hyperplasia may compensate by thyroid hormone deficiency. If the deficiency of thyroid hormone occurs at birth or early in life, cretinism or juvenile myoxedema may result, even though the gland is enlarged and hyperplastic. In hyperplastic gland, the epithelium is tall and columnar; the follicles are collapsed and contain only scanty colloid. Thyroid follicles may not remain in state of continuous hyperplasia but instead undergo involution, with the hyperplastic follicles reaccumulating colloid. The epithelium becomes low cuboidal or flattened and resembles that of the normal gland. Some follicles become much larger than normal, contain extensive colloid and are lined with flat epithelium (overinvolution; exhaustion atrophy). The gland is diffusely enlarged, soft and has glistening cut surface because of the excess of stored colloid. In addition to large follicles filled with colloids, there are foci in the gland where hyperplasia is still evident. This phase of non-toxic goitre is termed as colloid goitre 15 . After oral administration of green tea the weight of thyroid gland increases in a dose-dependant manner i.e. maximum after the consumption of 5gm% (a"20 cups/day) followed by 2.5gm% (a"10 cups/day) and least after 1.25gm% (a"5 cups/ day). Hypertrophy and hyperplasia of the thyroid follicular cells are found after prolonged consumption of both the moderate and high doses of green tea. The findings are almost consistent with the plants foods as found in radish, bamboo shoot, cassava etc. [20][21][22] In 2.5% green tea fed group (a"10cups of tea), thyroid follicles are diffusely hyperplastic, irregularly shaped, lined with enlarged cuboidal or columnar epithelium with depleted colloid, whereas at a dose of 5.0% (a"20 cups of tea), colloid rich follicles with flat epithelial cell and mononuclear cell infiltration. All these observations reveals that consumption of green tea at moderate and high doses (a"10cups or a"20cups/day) develop a morphological state as resembled in goitrous population in environmentally iodine deficient or dietary goitrogen exposed population. Functional Changes of Thyroid Gland Thyroid gland synthesizes thyroid hormones (thyroxine and tri-iodo-thyronine) followed by its storage and release in response to demand of the body. The biosynthesis of thyroid hormone requires highly regulated steps catalyzed by a number of enzymes. In earlier studies it was demonstrated that high consumption of flavonoids diminishes thyroid iodide uptake and thyroid peroxidase (TPO) activity, inducing enlargement and histological changes in the thyroid 5,23,24 . A Brazilian medicinal herb that is known to contain flavonoids 25 , causes inhibition in in vitro TPO activity and scavenges H 2 O 2 , an essential TPO co-factor 26 . Green tea is a rich source of flavonoids and the effects of green tea extracts in the activities of major thyroid hormone synthesizing enzymes in relation to pure catechin are described as following. Thyroidal Na + -K + ATPase It is a membrane-spanning protein complex responsible for extrusion of Na + and absorption of K + by most animal cells, including follicular epithelium of thyroid gland. Iodine required for hormone synthesis accumulates within the gland through the combined actions of Na-K ATPase and Na + , Icontraporter 27 . The activity level of thyroidal Na + -K + ATPase following the method of Esmann 28 at different doses of green and catechin are shown. Thyroidal Na + -K + ATPase activity of both the GTE and catechin treated groups of animals was increased in a dose-dependent manner in comparison to that control group. Na + -K + ATPase activity increased 27.5% and 69.8% at the doses of 2.5g% and 5.0g% GTE group of animals respectively whereas, 17.3%, 34.6% and 87.8% increment were found after the administration of 25mg, 50 mg and 100 mg pure catechin respectively. However, no change in the activity of Na,K+ATPase was observed in 1.25g% green tea treated group (Figure 2). The iodide is concentrated in the follicular cells by an active transport mechanism, the so-called 'Sodium-Iodide Symporter' (NIS) that is energy consuming, connected to a Na + -K + ATPase activity and stimulated by TSH. NIS-mediated iodide transport is inhibited by the Na + -K + ATPase inhibitor ouabain as well as by the competitive inhibitors thiocyanate and perchlorate 29 . Na + -K + ATPase is composed of two subunits in equimolar ratios. These are the á subunit with molecular mass of ~113 kDa and the smaller glycosylated â subunit with a protein portion accounting for 35kDa of the overall molecular mass of 55 kDa. Isoforms exists for á (á 1 , á 2 and á 3 ) and â (â 1 , â 2 and â 3 ) subunits. Hypothyroidism increases the number of Na + -K + ATPase subunits (á 1 and â 1 ) in rat thyroid gland 30 . Increased Na + -K + ATPase activity as observed perhaps for the development of a morphological as well as biochemical hypothyroidism under the influence of flavonoids (catechin) present in tea. Active transport of iodide into the thyroid gland is a crucial and ratelimiting step in the biosynthesis of thyroid hormones which play an important role in the metabolism, growth and maturation of a variety of organ systems 31 . Na + /I " symporter (NIS) is a key plasma membrane protein that catalyzes the active accumulation of iodide (I " ) in the thyroid gland; co transports two sodium ions along with one iodide ion, with the transmembrane sodium gradient serving as the driving force for iodide uptake. The sodium gradient, providing the energy for this transfer, is generated by the ouabain-sensitive Na + -K + ATPase. Na + -K + ATPase activity was increased markedly in the experimental animals treated with in this study TPO is a glycoprotein having a prosthetic heme group located in the apical membrane. The enzyme is also essential for incorporation of iodine into tyrosine residues in thyroglobulin for organification and coupling of the iodotyrosines to form T4 and T3. The human TPO gene is located on chromosome 2 pterp12, spans about 150 kb. The full length human TPO cDNA encodes a protein of 933 amino acids 32 . The amino terminus of TPO is located in the lumen of thyroid follicles, and the extra cellular domains forms a loop created by two intermolecular disulphide bonds which is by a single membrane spanning domain in close proximity to its carboxy terminus 33 . While the prosthetic heme group, a bis-hydroxylated heme that is distinct from the heme b (protoporphyrin IX) found in many other hemoproteins, is covalently bound to glutathione 399 and aspertate 238 of the apoprotein 34 . The activity of TPO is increased by TSH in vivo 35 , and this stimulatory effect is the consequence of increase synthesis of TPO 36 . TSH and other stimulators of cyclic AMP signaling pathway increase TPO mRNA abundance in cultured thyroid cells 37 . The synthesis of thyroid hormones is the major function of the thyroid gland and the main regulatory enzyme for the thyroid hormone biosynthesis is thyroid peroxidase as mentioned. In the present study, thyroid peroxidase (TPO) activity of all the experimental groups except 1.25g% GTE treated group was decreased significantly in comparison to that of the control group. TPO activity was decreased 33.1% and 53.6% respectively at doses of 2.5g% and 5.0g% GTE treated groups whereas, 14.8%, 50.4% and 82.6% inhibition were found at the doses 25mg, 50 mg and 100 mg of pure catechin treated groups ( Figure 3). It is known that a wide variety of environmental substances including foods can induce goiters in rats [20][21][22] . Most of these goitrogenic substances directly interfere with synthesis or secretion of thyroid hormones by various mechanisms, such as blockage of iodine uptake by the thyroid, organification defect due to inhibition of thyroid peroxidase (TPO) and blockage of thyroid hormone release. The reduction in serum levels of thyroid hormones induces an elevation of serum levels of TSH and consequently results in hypertrophy and/or hyperplasia of follicular cells 10 . In consistent with above observations both the GTE and pure catechin exposure decreased the activities of thyroid peroxidase (TPO) in a dose dependent manner. Thyroid peroxidase (TPO), a heme-containing enzyme is found in the apical membrane of thyroid follicular cells, that catalyzes the thyroid hormone biosynthesis i.e. oxidation of inorganic iodide (I -) to reactive iodine (I) for binding iodine to tyrosyl residues in thyroglobulin. Divi and Doerge 38 conducted a structure-activity study of 13 commonly consumed flavonoids and reported that most flavonoids were potent inhibitors of TPO and catechins were also showed the inhibitory effect on TPO activity 39 . Studies by Divi and Doerge 38 showed that genistein, quercetin, kaempferol and naringenin inhibit thyroxine synthesis by acting as alternate substrates for tyrosine iodination, yielding mono, di and tri-iodo-isoflavones. These compounds were also shown to irreversibly inhibit thyroid peroxidase. A probable mechanism of action may relate to the ability of phenolic compounds with a free resorcinol (metahydrophenol) moiety to inhibit TPO. Therefore, the proposed mechanism of action for enzyme inhibition as found involves the conversion of thyroid peroxidase to a free radical that reacts with resorcinol moiety and produces a flavonoid radical. The flavonoid radical could covalently bind to the catalytic amino acid residues on the enzyme, leading to enzyme inactivation. Through their inhibitory activity on thyroid peroxidase, they can cause elevated thyroid stimulating hormone levels, which promote thyroid gland growth and thyroid dysfunction 40 . 5'-Monodeiodinase I The main product of thyroid gland is tetraiodothyroinine (T4) -a pro hormone that must be activated by deiodination to triiodothyronine (T3) in order to initiate thyroid action. The deiodination reaction occurs in the phenolic ring or outer ring of the T4 molecule and is catalyzed by the two tissue specific deiodinase, type 1 (D1) and type 2 (D2). On the other hand, T4 and T3 can be irreversibly inactivated by deiodination of their tyrosil ring (inner ring deiodination), a reaction catalyzed by either D1 or type 3 deiodinase (D3), the third member of the deiodinase group. Therefore, the deiodinase have the capacity to terminate thyroid hormone action 41 . The three deiodinase protein (D1, D2 and D3) are structurally similar (-50% sequence identity). All are the integral membrane proteins of 29 -30 kd and they are similar in the region surrounding the active catalytic centre [42][43][44] . All the three deiodinases have a single transmembrane segment, present near the N -terminus, D1 has small amino terminal extension in the extracellular space, while D2 has in the lumen of the endoplasmic reticulum, and a single transmembrane domain existing the membrane at about position 40 45,46 . As a result the active centre of both D1 and D2 are in the cytosol. D3 has also the integral membrane protein, but its orientation is opposite, so that its active centre is in the extracellular space. GTE and catechin treatment caused a statistically significant inhibition in the activity of 5'-deiodinase I (5'-DI) over the control value. 5'-DI activity was decreased 27.6% and 62.2% at dose of 2.5g% and 5.0g% GTE groups respectively whereas, 20.3%, 40.3% and 70.3% inhibition were found at the doses 25mg, 50 mg and 100 mg of pure catechin treated groups respectively. However, no such significant changes were observed in the animals treated with green tea at the dose of 1.25g% for 30 days (Figure 4). Furthermore, green tea as well as pure catechin exposure had significantly reduced the activity of 5'-monodeiodinase I (5'-DI) in thyroid gland which suggested that green tea catechin decreased the rate of conversion of T4 into T3. 5'-DI is a member of a group of selenoenzymes that metabolize thyroid hormone and thus modulate thyroid hormone action. 5'-DI predominantly found in the liver, kidney and thyroid and responsible for generating most of the circulating T3. 5'-DI can catalyze both activation of T4 by outer-ring deiodination and inactivation of T4 by inner-ring deiodination to produce rT3 47 . Previously, in experimental animals, it has been described that the high consumption of flavonoids including catechin diminished the enzymatic activity of 5'-DI in vivo as well as in vitro study 48 . The result of the present study confirms the earlier findings. Thyroid hormone profiles Serum T4 and T3 levels were significantly decreased in GTE group at 5.0g % dose than the 2.5g % dose as compared to control group of rats. However, the mean serum T3 and T4 levels were significantly lower both in 50 mg and 100 mg /kg catechin treated groups in comparison to control group ( Figure 5) while serum thyrotrophic hormone (TSH) level was significantly increased in both the GTE treated group at high doses over the control values, however, pure catechin significantly enhanced the serum TSH level in 25mg, 50 mg and 100 mg /kg catechin treated groups in comparison to control group ( Figure 6). thyroid function in humans and experimental animals. Changes in the serum concentration of these hormones can reflect disturbances in their glandular synthesis and/or secretion as well as disorders in their extra-thyroidal peripheral metabolism. In the present study, serum T3 and T4 levels were significantly decreased with elevated TSH level in both treated groups of animal. Due to exposure of GTE and catechin, the resulting hypothyroidism causes increased pituitary production of TSH in an attempt to stimulate thyroid to correct the deficiency of thyroid hormones. Conclusion GTE at relatively high doses caused hypothyroidism in rats by altering morphological and functional status of thyroid. Moreover, the commercially available catechins have shown pronounced effect inducing hypothyroidism which validates that the effect of GTE may be due to antithyroidal or goitrogenic effect of catechins present in tea. All these suggest that catechin present in green tea has the antithyroidal as well as goitrogenic potential and its regular consumption at relatively high doses pose a threat to the functioning of thyroid.

v3-fos

2019-04-24T13:12:24.217Z

2015-09-04T00:00:00.000Z

129528366

s2

The fluctuation of the beginning time of flood season in North China during AD1766–1911 This study is based on the Qing government water level gauge records from Wanjingtan of the Sanmenxia Gorge in the middle reaches of the Yellow River, Muluandian in the lower reaches of Qinhe River, and Shijingshan and Lugou Bridge in the lower reaches of Yongding River. The beginning of the flood season has been reconstructed. The anomaly series of the flood season is assessed using pentad scales. The sequence represents the middle reaches of the Yellow River, the lower reaches of the Qinhe River, and the lower reaches of Yongding River. Within the research period, the middle reaches of the Yellow River and the lower reaches of the Qinhe River began the flood season on 6–10 July on average, and Yongding River began 16–20 July. The Yongding River is relatively stable and the start of rainy season of its upstream was basically maintained in early July. The middle reaches of the Yellow River and the lower reaches of the Qinhe River show great fluctuation, with discrepancies up to 3 months. The same anomalous fluctuation in the flood season of the middle reaches of the Yellow River and the Qinhe River is more obvious after the mid-19th century. The delay of flood season by about one pentad in the middle reaches of the Yellow River, Qinhe River, and Yongding River is in accordance with the relative low temperature of the Loess plateau in summer, while the early flood season of the middle reaches of the Yellow River and Qinhe River corresponds with the relative high summer temperature in the Loess Plateau. The beginning time of the flood season in the research area is the time the rainy season begins. The length of summer-monsoon rainy season during 1860s–1940s has been reconstructed, as the Little Ice Age transformed to the Modern Warm Period in China. Rapid warming could change the summer rainy season by 2–3 pentads. Introduction The Asian Monsoon plays an important role in transporting large quantities of heat and moisture to the most-populated regions of the world. Precipitation and the dare of first rain are sensitive to the East Asian Summer Monsoon (EASM) intensity (An, 2000). The rainy season related to EASM has great significance for annual precipitation over northern China (He et al., 2007). The starting date of the rainy season is critical for crop planting and yields (Griffiths, 1994;Tao et al., 1997;Zhu et al., 2011), and changing EASM leads to the changing dates of the river flood season. In this article, three rivers in semi-humid northern China were chosen to study the change of timing of the flood season related to the EASM from 1766 to 1950 (Fig 1). Rain-fed agriculture is the most important part of the economy of China during the past thousands of years. Rainy summers and autumns lead to river floods, and throughout Chinese history government has had to manage flooding to avoid agricultural loss. The Yu-Xue-Fen-Cun (YXFC, Yu/rainfall-Xue/snowfall-Fen/Chinese length unit, approximately 0.32 cm-Cun/10Fen, 3.2 cm) archives of Qing Dynasty (1644e1911) were used to reconstruct the precipitation in the middle-lower reaches of Yellow River, and the rain dates in the semi-arid region of North China (Zheng and Wang, 2005;Ge et al., 2011). In the early 18th century, the Qing government (1644e1912) began to set up water level observation stations on rivers in China. The water level observation station at Wanjintan is on the Yellow river, north of Laoxiancheng, Shanxian county, Sanmenxia city, Henan province. It is an important data source for monitoring the water conditions of the middle reaches of the Yellow River. Similarly, there are observation stations on the Qinhe River and Yongding River, located at Muluandian in Wuzhi County and Shijingshan-Lugouqiao, respectively. According to the rules of Qing Dynasty, when the water level rises 2 Chi (Chi is a Chinese length unit; 1 Chi ¼ 0.32 m) or more, the date and height must be reported to the imperial government. At present, these reports are scattered through the following sources: 'Extracts of the water condition of historical floods in Qing Dynasty at Wanjintan and Xiakou on the Yellow River; Muluandian on the Qinhe River; and Gongxian on the Yiluo River', edited by the Yellow River Conservancy Commission in the 1980s as internal documents. Methods The first date of rising water was converted to pentad-scale, that is to say, July 1 is converted to 7/1, i.e. the first pentad in July. The method of assessing the dates of flood season on the pentad-scale was used in a similar study of the rainy season start date during 1644e1911 (Yang et al., 2007). Use of historical documents is especially suitable for such studies. Pan et al. (2012) studied the annual dates of first rising water at the Wanjintan station on the Yellow River. In light of their conclusion, the average beginning time of flood season in the Sanmenxia Region was July 6e10 during 1766e1911. This date corresponds with the date of the last stage of Meiyü (plum rain) in the middle and lower reaches of the Yangtze River (Ge et al., 2008). When the summer rain-belt moves northward into the Huanghe River valley and North China, the rivers enter flood season in these areas. It agrees with the process of the summer rain-belts, so it should be possible to convert the annual first water rising dates to pentad scale. The Qing Dynasty (AD 1644e1912) was concerned with weather, hydrological events, droughts, and floods. The empire constructed a very efficient recording system using reports from officers and regional intellectuals. Three kinds of archives are very important to this paper. 1) Water level records of the Qing government from the early 18th century; 2) Yu-Fen-Cun (YFC), recording the beginning/ending dates, duration and rainfall infiltration depths into soil for individual precipitation events; and 3) Hydrological records for 1912e1950. Fluctuation of the beginning time of flood season According to the average situation of the reconstruction, the beginning times of flood seasons of both the Yellow River and Qinhe River range from July 6 to July 10. Meanwhile, the flooding season of the Yongding River begins a little later, and ranges from July 16 to July 20. Here, we reconstruct the chronology of the beginning of the flood season of the three rivers on a pentad scale. The standard deviations of Yellow River, Qinhe River and Yongding River are 1.19, 1.01 and 0.64, respectively. There are significant fluctuations in the Yellow River's flood season, and the Qinhe River shows significant instability in its flood season. By comparison, the Yongding River is the most stable one, which shows that the rainy season in the northern Loess Plateau during the Qing Dynasty was relatively stable. Fig. 2 shows the 5-point smoothing average curve of the beginning time of the flood season. Except for an evident fluctuation between 1880 and 1890, the Yongding River's flood season has changed very little. Table 1 shows the extreme value of the date of flood season initiation. All of the extreme events occurred in the period without modern weather and hydrological records. 1842/3-2 is the second pentad in March AD1842 (6e10th March). The extreme value of the flood season dates for the middle reaches of the Yellow River is much larger than for the Qinhe and Yongding Rivers. That was the period when flood disasters along the Yellow River occurred most frequently and severely in eastern Henan Province. At that time, the average flood season initiation date in the Sanmenxia Region was 7 days earlier. In the flood years of 1841, 1842, 1843, 1849, and 1850, the flood appeared in early May or even earlier, except during 1841, 5e10th August. The lengthy flood seasons in 1842 and 1845 even began in early March. From the mid-18th century to the early 20th-century, this phenomenon only happened two times. It might be due to the abnormal high amount of rainfall in the middle reaches of the Yellow River in the spring. The flood season date was generally in the middle of October in the middle reaches of the Yellow and Qinhe River, and in the middle of August in the Yongding River. The middle reaches of Yellow River and Qing River are affected by Bay of Bengal moisture which is carried by southwest monsoon winds in September. Both areas are affected by the autumn rain season, and the flood season in October is the manifestation of strong southwest monsoon winds. The upper reaches of the Yongding River is out of the influence of southwest monsoon wind, so the main reason of stabilization of Yongding River's flood season is that the flood season is concentrated in summer. On the whole, the flood season of the Qinhe River and the middle reaches of the Yellow River was advanced by about 5 days during the 1810e1870s. The flood season of the Qinhe River, the middle reaches of the Yellow River, and Yongding River was delayed for about 5 days in the 1880s. In the 20th century, the flood season of the Qinhe River was delayed, while those of the middle reaches of the Yellow River and the Yongding River advanced. (Fig. 2). The cold period of the 1870e1880s is also apparent, and it did not become warm until the 1920s, which was nearly 20 years later than the average time of the end of the Little Ice Age in the Northern Hemisphere. Fig. 2 shows the comparison of the beginning time of flood season in the middle reaches of the Yellow River and the Qinhe River and the Yongding River with the fluctuation of the summer temperature of the Loess Plateau. The 1880s was the period when the flood season of the rivers was delayed, corresponding to the winter temperature 'cold period' of the monsoon area of eastern China and the sharp cooling process of the loess plateau that began in the 1870s. The summer temperature of the loess plateau was high in the 1820s through 1860s, which corresponds to advanced flood seasons of the Yellow River and the Qinhe River. The 1850e1860s were marked by the rising stage of winter temperature which was opposite to the trend of summer temperature change of the loess plateau (Ge et al., 2003). Along with the 0.5 C decline of the summer temperature of the loess plateau in the 1860s, the flood season of the Qinhe River and the Yellow River was delayed by about a pentad. EASM change and the beginning of flood season The rainy season related to the East Asian Summer Monsoon (EASM) has great significance for annual precipitation in China. In particular, a stronger EASM is accompanied by decreased rainy days and precipitation amount over the region of the Huaihe River and the middle and lower reaches of the Yellow River (Zhang and Liu, 2003;Zhang et al., 2003a,b;Zhu et al., 2005), while such conditions tend to result in more rainy days and precipitation amounts over northern China (Guo et al., 2004). The intensity of the EASM is an important factor influencing the rainfall pattern over eastern China. In the years of strong summer monsoon, the rainbelt rushes quickly over northern China and causes drought in the Yangtze River Valley and wetness along the northern boundary of the EASM (Tao and Chen, 1987). As the intensity of the EASM is significant in determining the northern extension of the summer monsoon, it is reasonable to conclude that the intensity of the monsoon is related to the beginning of the flood season in this area. Different authors have developed several indices to describe the weak/strong fluctuation of EASM(EASMI) (Guo, 1983;Tao et al.,1987;Zhao and Zhang, 1996;Shi andZhu, 1996 Lu andChan, 1999;Sun et al., 2001;Wang, 2001;Zhang and Liu, 2003;Zhang et al., 2003a, b;Guo et al., 2004;Huang, 2004;Lian et al., 2004;Lee et al., 2005;Zhao and Zhou, 2005;Zhu et al., 2005). Guo et al. (2004) reconstructed the index of summer monsoon (Ism) on the basis of the sea level pressure record (SLP) from 1873 to 2000. Fig. 3 shows the relationship between the Ism and the flood season beginning for the Yellow River (Sanmenxia). The weak summer monsoon is the main cause of the delayed flood season of the middle Yellow River and the Qinhe River and Yongding River under the abnormally cold background in the 1880s. The mid-1880s to 1900s was the period when the summer monsoon is weak, which corresponded to the delayed flood season. This phenomenon is also reflected in the monsoon duration in northern Shanxi and Shaanxi Provinces. Summer-monsoon rain-band movement in central China Ge et al. (2003) revealed that the monsoon duration of Taiyuan, Datong and Yulin during 1736e2000 was 10e20 days shorter than that of the 1860s-1900s. According to the above two phenomena, as well as the phenomenon that the flood season advances for about 5 days, it can be deduced that the phenomenon of the weaker summer monsoon of the 19th century caused a delayed rain belt in the entire loess plateau. The earlier flood season in the 1820s À1860s also agrees with the strong summer monsoon. The summer monsoon was strong according to the length variability of meiyu (plum rain) period in the middle and lower reaches of the Yangtze River since 1736. The flood season of the middle reaches of the Yellow River and the Qinhe River is also earlier. This data can be combined with the other series or proxy about rain-band in several areas over China, including the South Rim of Plum Rain in Xiangjiang River (SR), one tributary of Yangtze River, locate in Hunan Province China, the typical Plum Rain Area along the middle reaches of Yangtze River (MRYZR), and the middle reaches of Yellow River (MRYR). Zheng (2010) reconstructed the beginning/end dates of the rainy season over SR since 1861 based on diaries and weather records. The changing of typical Plum Rain and the end dates of the rainy season over MRYR in the last 300 years has already been reconstructed (Ge et al., 2008(Ge et al., , 2011. The average lengths of the Plum rain period and summer rainy season over SR, MRYZR and MRYR is 3.5,5 and 10 pendates in past 150 years, respectively. Compared to the annual length for the three areas during 1860e1890s and 1920e1930s (Fig 4), the length of rainy season over MRYR became shorter, while the SR became longer. The rain belt shifted south to the SR, and North China became drier. The 2 important and serious drought disasters in 1877e1878 and 1928e1929 in MRYR can be found in Fig 4. The summer monsoon rain remained over MRYZR for too long, and the stay over MRYR was very short. The southern shift of the summer rain-band is more clear on an inter-decadal scale ( Table 2). The 1860e1930s was a rapid warming period, as the Little Ice Age finished transformation to the Modern Warm Period in China and the Northern Hemisphere. The rapid warming could lead to the summer rainy season becoming 2-3 pendates shorter. Conclusion The flood season and the fluctuation at Sanmenxia on the Yellow River during 1766e1911, the Qinhe River during 1761e1911, and Yongding River during 1736e1911 were reconstructed based on the water level observation reports of the Qing dynasty. 5-point smoothed chronologies show that flood season was advanced and delayed during 1820e1860s and 1870e1880s, which correlates negatively with the temperature change of the loess plateau. This phenomenon is especially apparent in the 1880s. The cold phase on the loess plateau in 1880s agrees well with the cold phase in the Northern Hemisphere during 1820e1870 (Mann et al., 1998). This shows that the delay of the flood season is a feedback to the colder phase in the Northern Hemisphere. The colder Northern Hemisphere period is not consistent with the warm summer temperature on the loess plateau. It is also inconsistent with the advance of the flood season revealed in this research. The results show that the beginning time of flood season of rivers in this area is related to the temperature fluctuation of the Northern Hemisphere, whereas it should be even more closely correlated with the summer temperature change on the loess plateau. This phenomenon could be a multiyear response to the change of the intensity of the monsoon of East Asia.

v3-fos

2016-05-12T22:15:10.714Z

2015-07-16T00:00:00.000Z

5820026

s2

Effects of Antrodia camphorata extracts on anti-oxidation, anti-mutagenesis and protection of DNA against hydroxyl radical damage Background Antrodia camphorata is a geographically special fungus and is one of the precious traditional medicines of Taiwan. A lot of reports have addressed its antioxidant activities and anticancer activities. In order to understand whether these protection effects were resulted from its ability of preventing DNA against hydroxyl radical damage, the A. camphorata extract was used to examine its antioxidant, antimutagenic and DNA-protective activities. Methods A. camphorata extract was prepared by extracting the lyophilized powder of A. camphorata mycelium with distilled water. The antioxidative activity of this A. camphorata extract was then evaluated by 2,2-diphenyl-1-picrylhydrozyl (DPPH) radical-scavenging assay, and the antimutagenic activities of the extract against direct mutagen 4-nitroquinoline N-oxide (4NQNO) and indirect mutagen benzo[a]pyrene (B[a]P) were evaluated by Ames test. The effects of the A. camphorata extract in terms of DNA protection against hydroxyl radical damage were also investigated. Results It was found that the higher the concentration of A. camphorata extracts, the higher the DPPH radical-scavenging effect. A. camphorata extract at concentrations between 0.625 and 10 mg/ml was found to be neither toxic nor mutagenic. However, the higher A. camphorata concentration (10 mg/ml) used in the test showed higher inhibitory effects on 4NQNO in a dose-dependent manner. The A. camphorata extract also showed reducing and scavenging activities against superoxide anion radical and also exhibited protective effects on DNA against hydroxyl radical-induced damage. Conclusions Results suggested that A. camphorata is a non-toxic and novel material with antioxidant, antimutagenic and DNA-protective activities and could be developed into health foods. Background Antrodia camphorata (also called Chang-Chih or Niu-Chang-Ku) is a member of the Polyporaceae (Aphyllophorales) family and hosts in brown heart rot of the endemic evergreen Cinnamomum kanehirai Hay (Lauraceae) in Taiwan [1]. The fruit body of A. camphorata is a wellknown and expensive medicinal material in Taiwan. Traditionally, it is used as an antidote, anti-cancer, anti-itching and hepato-protective medicine. It has a mild camphor odor like that of its host tree, and the taste of it is very bitter. Currently, there is a shortage of the natural harvested fruit body of A. camphorata because its natural host, C. kanehirai Hay, is one of the endangered species in Taiwan. Due to the rareness and growing slowly in natural environments, the fruit bodies of A. camphorata were expensive and difficult to procure; however, a breakthrough occurred in 1998 when a method of submerged culture for growing A. camphorata was established. Since the mycelium of A. camphorata was easy to obtain by submerged cultivation, many pharmacological effects of crude extracts of A. camphorata in different models of in vivo and in vitro studies were subsequently reported. These pharmacological effects were reviewed by Geethangili and Tzeng in 2009 [2] and classified into nine functional categories, including (1) Anti-cancer activities: Both the fruiting bodies and mycelium of A. camphorata was reported to have potent antiproliferative activities against various cancers both in vitro and in vivo. (2) Anti-inflammatory and immunomodulatory effects. (3) Anti-hepatitis B virus replication: A. camphorata extracts was reported to have antihepatitis B virus activity in vivo in a dose-dependent manner without cytotoxicity. (4) Antioxidant activities: Accumulating data showed that A. camphorata could be a potent direct free radical scavenger. (5) Hepatoprotective activity: A. camphorata was showed to have protective activity against liver hepatitis and fatty liver induced by acute hepatotoxicity of alcohol and also showed to have potential in treating liver diseases. (6) Prevention of liver fibrosis: The filtrate of fermented A. camphorata was found to have preventive and curative properties against rat liver fibrosis induced by CCl 4 -treatment. (7) Neuro-protective effects: Extracts from A. camphorata specimens grown via submerged cultivation were reported to prevent serum-deprived PC-12 cell apoptosis through a PKA-dependent pathway and by suppression of JNK and p38 activities. (8) Anti-hypertensive effects: Methanol extracts of A. camphorata showed potent antihypertensive effects in spontaneously hypertensive rats. (9) Vasorelaxation effects: The extracts of submerged cultural mycelium were reported to have vasorelaxation effects in a concentration-dependent manner. At present, A. camphorata is mainly prepared via the submerged cultivation and used in the formulation of nutraceuticals and functional foods. It is of great interest to examine more functional properties of water extracts of A. camphorata. Few reports thus far, however, have been concerned with studies of the biological and chemical effects of A. camphorata extracts at the level of DNA function. Accordingly, the aim of this study was to elucidate the biological and chemical properties of A. camphorata extracts, including any effects such as mutagenic activity, anti-mutagenic activity against mutagens, and the protective effect of DNA from hydroxyl radical damage. The antioxidant activity and scavenging effects on radicals were also investigated in this study to compare with other reports. Antrodia camphorata and its composition analyses A. camphorata mycelium used in this study was a gift from Prof. Szu-Chuan Shen (National Taiwan Normal University, Taipei), which was produced by Simpson Biotech Co. Ltd. Water content and ash content of A. camphorata were determined according to the standard procedure by using the dried powder of Antrodia camphorata specimens grown by submerged cultivation. The total protein was determined by the Kjeldahl method, as described previously [3]. Preparation of A. camphorata extract (ACE) Dried A. camphorata mycelium from submerged cultivation was grounded into powder. The A. camphorata extract (ACE) was prepared by water extraction. Two hundred milliliter of distilled water was added into 10 g of grounded powder, mixed well and stirred at 4°C for 24 h. After centrifugation, the clear supernatant was collected, concentrated 10 times by rotary vapor machine, and lyophilized into dry powder by a lyophilyzer. The resultant dry powder was ACE and was stored at −20°C for use in the following experiments. Evaluation of total phenolic compounds The total phenoic content was determined by the following procedure and expressed in terms of milligrams of gallic acid equivalent per gram of aqueous extract [4]. The dried powder of ACE was dissolved in distilled water with a proper concentration. One hundred microlitre of ACE solution was added into 2.0 ml of 2 % Na 2 CO 3 , mixed well and held for 2 min. Folin-ciocalteu's reagent (50 %) was then added into samples, mixed well and held for 30 min. The reacted samples were analyzed by spectrophotometer at 750 nm to determine the total phenolic compounds. Scavenging effect on 1,1-Diphenyl-2-picrylhydrazyl radicals Scavenging ability on 1,1-Diphenyl-2-picrylhydrazyl (DPPH) radicals was measured by the method described previously [5]. Each water solution of ACE (0.5-10 mg/ ml) was mixed with 1 ml of a methanolic solution containing DPPH (Sigma) radicals, resulting in a final concentration of 0.2 mM 1,1-diphenyl-2-picrylhydrazyl (DPPH). The mixture was shaken vigorously and left to stand for 30 min in the dark, and the absorbance was then measured at 517 nm. Antioxidant butylated hydroxytoluene (BHT) was used as the positive control. The scavenging activity (%) was defined as the percentage of the reduced absorbance caused by treating DPPH mixture with samples. The absorbance caused by DPPH mixture with water was used as the 100 % control. where A sample is the absorbance caused by treating DPPH mixture with samples and A H2O is the absorbance by treating DPPH mixture with water. Toxicity test Salmonella typhimurium TA98 was obtained from the Bioresource Correction and Research Center (BCRC), FIRDI, Hsinchu, Taiwan. The strain was checked by examining its four genotypes according to the method described by Maron and Ames [6], including the histidine requirement in a biotin control plate and a biotin plate with histidine, rfa mutation test, uvr mutation test and R-factor confirmation. If a sample has toxicity effects on S. typhimurium TA98 in an anti-mutagenic test, it will decrease the number of the testing bacteria and cause a wrong judgment for the data. In order to eliminate such potential error, a toxicity test of ACE was conducted. 0.1 ml of ACE was mixed with 0.5 ml of 0.2 M phosphate buffer (pH7.4) or S9 mixture, then 0.1 ml of activated S. typhimurium TA98 was added and incubated at 37°C for 20 min. A 1 ml sample of the bacteria solution was aliquoted on to a plate, nutrient agar was added and the combination was mixed well. The colony formation units were counted after incubation at 37°C for 48 h. Distilled water was used as control instead of sample. Colony count was monitored to check whether the colony number was reduced obviously; if yes, the concentration of ACE was further reduced until no toxicity was observed. Mutagenesis analysis Mutagenesis analysis needs to be performed in addition of toxicity testing to eliminate possible errors due to a sample's mutagenic effect, because if a sample has the ability to cause mutations, it will influence the number of revertants and result in an error in judgment. 0.1 ml of ACE was mixed with 0.5 ml of 0.2 M phosphate buffer (pH7.4) or S9 mixture, then 0.1 ml of activated S. typhimurium TA98 was added and incubated at 37°C for 20 min. Then 2 ml of molten top agar (about 45°C) was added into the tube, mixed well and then poured into a minimal glucose agar plate. Colonies in the plate were counted for the number of His + revertants after incubation at 37°C for 48 h. Control was designed by using distilled water instead of sample. Each experiment was repeated three times. If the colony count of sampleinduced revertants is higher than that of the spontaneously occurring revertants, it would suggest that the sample possesses the ability to cause mutagenesis. Antimutagenic test Mutagen 4-nitroquinoline N-oxide (4-NQNO) is a direct mutagen, meaning that it has the ability to cause mutation directly and need not be activated by liver enzyme S9. Mutagen benzo[a]pyrene (B[a]P) is an indirect mutagen, meaning that it requires conversion and activation by the liver enzyme mix S9 to generate the ability of mutation. Mutagen 4-NQNO and B[a]P were prepared in DMSO solution with a concentration of 10 and 50 μg/ml, respectively. The test of antimutagenic ability was performed according to the method described by Maron and Ames [4]. ACE solution was mixed with 0.1 ml mutagen (either 4-NQNO or B[a]P), and 0.5 ml of 0.2 M phosphate buffer (pH 7.4) was added with or without S9 mix. One milliliter of the activated S. typhimurium TA98 was then aliquoted into each of the sample tubes. After incubating at 37°C for 20 min, 2 ml of molten top agar (about 45°C) was added into each tube, mixed well and then poured into a minimal glucose agar plate. Colonies in the plate were counted for the number of His + revertants after incubation at 37°C for 48 h. Protection effect analysis of DNA damage Fenton reaction can generate hydroxyl radicals [7]. The radicals would attack the deoxyribose elements of DNA molecules, degrade the molecules by the release of purine and pyrimidine bases, and produce mutagenic sites [8,9]. By assaying the retention of intact DNA molecules, the protection effect of ACE on DNA damage was evaluated. Each 45 μl aliquot of a reaction mixture, which was a blend of ACE (0-200 μg total solids/ml), 5 μl of calf thymus DNA solution (25.0 A 260 unit/ml) (Amersham Biosciences, Piscataway, NJ, USA), 0.9 μl of 3.6 mM FeSO 4 , and 3.6 μl of 24 mM hydrogen peroxide, was incubated at room temperature for 15 min. After incubation, 10 μl of 1 mM EDTA was added to stop the reaction. The blank was the calf thymus DNA solution. The control was the reaction mixture without ACE. Each 10 μl aliquot of the reaction mixture was applied on 1 % agarose gel containing 0.1 % ethidium bromide. The electrophoresis was conducted in TBE buffer (10 mM Tris-boric acid-EDTA, pH 7.4) for 8 min. The gel was then visualized under UV illumination. Composition of submerged cultured A. camphorata The composition analysis showed that the water content of the dry powder of the submerged cultured A. camphorata was 17.55 % (Table 1). In previous studies, the water content was measured to be 68 % in the fresh fruit [10]. The higher water content in the submerged cultured A. camphorata was possibly caused by their higher sugar content, which made it easy to absorb moisture from the humid air. The ash content of the dry powder of submerged cultured A. camphorata was measured to be 8.63 %. This result agreed with the content of general mushrooms supposed to have ash contents between 5 and 16 %, which is mainly composed of phosphorus, potassium and other inorganic salt. The protein content of dry powder of submerged cultured A. camphorata was measured to be 25.39 % ( Table 1). The protein content of the A. camphorata mycelium and fruit body was measured to be 23.84 and 6.6 %, respectively, in previous studies [10]. This higher protein content should be resulted from the thorough utilization of the nitrogen source in the submerged cultivation. Total phenolics content and antioxidant activity of A. camphorata extract It has been reported that phenolic compounds possess antioxidant effects that can be used to clean up the active oxygen and free radicals which can prevent the oxidation of phospholipids in cell membranes and lipids in blood, and that these antioxidant effects can thereby decrease the risk of medical problems due to heart disease or arterial damage, such as strokes. In addition, phenolic compounds have been shown to exhibit anti-mutagenic activity [11,12]. Analysis showed that the total phenolic content of ACE was estimated to be 20.00 mg/g (Table 1). This implied that the antioxidant activity of ACE should be related with the high content of phenolic compounds. Antioxidant agents for inhibiting the lipid oxidation include providing hydrogen to scavenge peroxide radicals, and DPPH is a stable free radical which could accept electrons or hydrogen free radicals to form a stable molecule [13]; therefore, DPPH is a good chemical to generate free radicals and can be used for measuring the antioxidant activity of materials. In the investigation of scavenging ability for DPPH free radicals, results showed that ACE had significant scavenging ability. The scavenging ability was estimated to be 46.53 % when the concentration of ACE was 2.5 mg/ml, and the scavenging ability was proportional to the concentration of ACE. The positive control BHT also showed a scavenging ability of 92.23 % in the concentration of 0.625 mg/ ml (Fig. 1). The antioxidant properties of A. camphorata were first described by Song et al. in 2002 [14]. It was found DMF and water-extracted ACE showed marked activity in free radical scavengeing and showed that the antioxidant ability of A. camphorata is proportional to the total phenolic content [14]; therefore, it is suggested that the scavenging ability of ACE against DPPH radicals should be contributed from the high content of total phenolics. The antioxidant properties of methanolic extracts from A. camphorata were also reported [15,16]. All of studies showed similar results in antioxidant ability, which demonstrated its significant antioxidant activity from the concentration of mg/ml level. Our results Fig. 1 The scavenging effects of Anthrodia camphorata extract against hydroxyl radicals. Data are expressed as mean ± SD (n = 3). The scavenging effect (%) = [1−(the absorbance of samples at wavelength 517 nm/ the absorbance of control (without sample) at wavelength 517 nm)] × 100 % agreed with the study reported by Song et al. since they also prepared ACE by water extraction; however, lower antioxidant activity and total phenolics content were observed, it should caused by preparing extract at 4°C. Toxicity and mutagenic ability of A. camphorata extract Before investigating the antimutagenic ability, ACE was used to perform toxicity and mutagenesis tests against S. typhimurium TA98, because if the ACE has toxicity and mutagenic effects against S. typhimurium TA98, that would result in revertant numbers and an incorrect judgment regarding their antimutagenic effects. According to previous studies, the maintenance of bacteria number after a sample treatment must reach over 80 % of the colony number of the control to prove the sample has no toxic effect [17]. Results of the toxicity test showed that ACE had no significant effect on S. typhimurium TA98. (Table 2) However, the bacteria count was proportional to the addition of ACE, which could be reasonably explained by the fact that ACE provides a good nutritional supplement for bacteria growth. According to the judgment criteria in the method, it would be recognized that the sample possessed mutagenic ability when the number of His + revertants induced by the sample was more than twice the number of spontaneous revertants [18]. The mutagenesis test results indicated that ACE had no effect to cause mutagenesis of S. typhimurium TA98 whether S9 mix was added or not, since the mutagenicity ratio for ACE against S. typhimurium TA98 was between 0.9 and 1.09, indicated that A. camphorata extracts induced His + revertants was much less than twice of spontaneous revertants. (Table 3) According to the criteria proposed by Ames et al. in 1975 [18], ACE of experimental concentrations had no toxicity and mutagenic effect. These results were in accordance with the previous study, which showed that DMSO-extracted ACE had no toxic and mutagenic effect [19]. Antimutagenic ability of A. camphorata extract Two mutagens can be used to evaluate the ability of ACE in the antimutagenic test. One is 4-nitro-quinoline-N-oxide (4-NQNO), which need not the activation by liver's enzyme system. The other one is Benzo[a]pyrene (B[a]P), which requires a liver enzyme to activate its mutagenic ability. The results of the antimutagenic test showed that ACE has significant effects against 4-NQNO to reduce mutagenesis in different dose treatments with inhibition effects of 7.22, 25.52, 31.82, 36.64, and 44.08 %, and also significant effects against B[a]P in different dose treatments with inhibition effects of 1.85, 18.10, 26.16, 27.45, and 30.05 %. The given antimutagenic effect was in proportion to the concentration of the sample whether 4-NQNO or B[a]P was used as the mutagen generator (Fig. 2). A DMSO-extracted ACE was studied for its mutagenicity in the previous study [19]. Our mutagenic data from water-extracted ACE were consistent with that from DMSO-extracted ACE, which showed no mutagenic effect for A. camphorata; however, waterextracted ACE showed better antimutagenic effects on both mutagens than DMSO-extracted ACE. According to the assignment for the inhibition effect of mutagenesis, an inhibitory efficiency higher than 40 % indicates a strong antimutagenic agent; an inhibitory efficiency between 25 and 40 % indicates a moderate antimutagenic agent; and an inhibitory efficiency of lower than 25 % indicates a weak antimutagenic agent [7]. Therefore, ACE was suggested to be a strong antimutagenic agent against mutagen 4-NQNO and a moderate antimutagenic agent against mutagen B[a]P. It is the first report

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Application of life cycle assessment to sheep production systems: investigating co-production of wool and meat using case studies from major global producers Methodology of co-product handling is a critical determinant of calculated resource use and environmental emissions per kilogram (kg) product but has not been examined in detail for different sheep production systems. This paper investigates alternative approaches for handling co-production of wool and live weight (LW, for meat) from dual purpose sheep systems to the farm-gate. Seven methods were applied; three biophysical allocation (BA) methods based on protein requirements and partitioning of digested protein, protein mass allocation (PMA), economic allocation (EA) and two system expansion (SE) methods. Effects on greenhouse gas (GHG) emissions, fossil energy demand and land occupation (classified according to suitability for arable use) were assessed using four contrasting case study (CS) farm systems. A UK upland farm (CS 1) and a New Zealand hill farm (CS 2) were selected to represent systems focused on lamb and coarse-textured wool for interior textiles. Two Australian Merino sheep farms (CS 3, CS 4) were selected to represent systems focused on medium to superfine garment wool, and lamb. Total GHG emissions per kilogram total products (i.e. wool + LW) were similar across CS farms. However, results were highly sensitive to the method of co-product handling. GHG emissions based on BA of wool protein to wool resulted in 10–12 kg CO2-e/kg wool (across all CS farms), whereas it increased to 24–38 kg CO2-e/kg wool when BA included a proportion of sheep maintenance requirements. Results for allocation% generated using EA varied widely from 4 % (CS 1) to 52 % (CS 4). SE using beef as a substitution for sheep meat gave the lowest, and often negative, GHG emissions from wool production. Different methods were found to re-order the impacts across the four case studies in some instances. A similar overall pattern was observed for the effects of co-product handling method on other impact categories for three of the four farms. BA based on protein partitioning between sheep wool and LW is recommended for attributional studies with the PMA method being an easily applied proxy for the more detailed BA methods. Sensitivity analysis using SE is recommended to understand the implications of system change. Sensitivity analysis using SE is recommended to investigate implications of choosing alternative products or systems, and to evaluate system change strategies in which case consequential modelling is appropriate. To avoid risks of burden shifting when allocation methods are applied, results should be presented for both wool and LW. renderable products), as well as for their wider range of cultural and ecological benefits (Zygoyiannis 2006). Sheep also contribute to the substantial environmental impacts of livestock production systems, which occupy over onequarter of the world's land surface area and contribute significant quantities of greenhouse gas (GHG) emissions (Steinfeld et al. 2006). The impacts of the production and consumption of agricultural products are best assessed by accounting for resource use and environmental emissions throughout the full life cycle of a product, and life cycle assessment (LCA) is an important methodology for this (e.g. ISO 2006). However, this is a relatively new area of research and while some LCA studies have been published for livestock products, almost all have been restricted to GHG emissions assessment and carbon footprinting of products. There is a dearth of research on other resource use or environmental impact categories. Additionally, while research on the use of LCA for dairy (Flysjö et al. 2011;Thomassen et al. 2009;van der Werf et al. 2009) and beef production (Lieffering et al. 2010;Nguyen et al. 2012;Peters et al. 2010;Wiedemann et al. 2015a;Williams et al. 2006) has been reported for several major production regions of the world, there are fewer published LCAs on sheep and most of these have focussed on lamb production. Lamb LCA studies cover production in a range of regions, notably the Mediterranean (Ripoll-Bosch et al. 2013), New Zealand (NZ) (Gac et al. 2012;Ledgard et al. 2011), the United Kingdom (UK) (Edwards-Jones et al. 2009;Williams et al. 2006) and Australia (Peters et al. 2010;Wiedemann et al. 2015b). Only two published studies have specifically investigated the LCA of wool, with both examining meat and wool production from single-casestudy farms in Australia (Brock et al. 2013;Eady et al. 2012). A feature common to many sheep farms that adds a degree of complexity to LCA studies is the co-production of meat, wool and milk (FAOSTAT 2014). While for some sheep flocks, particularly in Asia, Africa and parts of Europe, sheep milk is economically and nutritionally important, it is relatively unimportant for most other temperate regions where meat and wool are the main products. Depending on the breed of sheep, the relative proportion and quality of wool and meat may vary, as may the emphasis of the production system towards either product. In some cases, sheep systems exclusively produce meat from shedding sheep such as the Dorper breed, while other meat sheep produce low value wool as a by-product of meat production. In many cases, the system is 'dual purpose' producing both wool and meat for economic returns. In these systems, differences in the breed of sheep and production objectives result in variation in the relative quantity of meat production and in the quality and end-use of wool. Co-production must be addressed in LCA studies, and the results can be sensitive to the assumptions made on apportioning environmental impact between products, and hence can vary significantly depending on the methods used (Ayer et al. 2007;Reap et al. 2008). As interest in the environmental impacts of livestock increases , results for sheep meat and wool production are needed. The aims of this research are to: (1) evaluate several alternative methods for handling the co-production of meat and wool from sheep production systems; (2) quantify the impacts of these allocation methods across multiple impact categories; and (3) discuss the implications of allocation methods for benchmarking studies and scenario modelling for improved practices. A series of case studies were drawn from the major sheepproducing regions of Australia, NZ and UK, which together account for approximately 35 % of global clean wool production (FAOSTAT 2014). The case studies were selected to illustrate the impact of alternative methodologies for handling co-products in systems diverging in relative production emphasis on wool or meat The study did not aim to provide comparative benchmarking results for the countries represented. Goal and scope The case study system boundaries included all supply chain processes associated with the primary production of wool and sheep meat to the farm-gate. Two functional units (FU) were used either independently or together, depending on the main output of the system and the method applied for handling coproduction. Where allocation methods were used, results for meat are presented for live weight (LW) per 'one kilogram of LW at the farm gate' and for wool, results are presented per 'one kilogram of greasy wool at the farm gate'. Case study descriptions Four case studies were used, based on survey data collected over the years 2009 to 2012, from farms representative of major agro-ecological zones, with different sheep production systems and breeds. These systems differed in emphasis on LW and wool production, the level of productivity and regional location as summarised in Table 1. All case studies were pasture grazing systems where the majority of feed inputs are sourced from permanent pastures year-round, with the exception of the UK system where sheep are housed in winter. Case study 1 (CS 1) Sheep production in UK is focused primarily on meat production and wool is generally considered as a by-product of limited value that rarely returns more than 4 % of average farm-gate revenue (Chris Lloyd, pers. comm.). Most wool is coarse-textured and is used for carpets, apparel and household products. A typical case study upland farm (hill country) was selected from the EBLEX 2011 survey farms (EBLEX 2012). This farm is located in an upland region characterised as a less favoured area (LFA) due to its varied topography and relatively high rainfall of at least 1200 mm/year. The LFA is significant for the UK because approximately 50 % of the national flock is found in the uplands LFA. This sheep-only farm system was characterised by high productivity in terms of weaning percentages and growth rates, from large bodied sheep with low wool production (Table 1). Sheep are housed over winter for 1 month when they are fed pasture silage, hay and by-products from horticulture such as surplus potatoes. Concentrates are fed to ewes during the 6 weeks prior to lambing and to lambs to finish them before sale for slaughter at an average of 6 months after birth. Case study 2 (CS 2) NZ sheep production is based on dual-purpose sheep, with most revenue from meat but with wool contributing about 20-25 % of the average farm-gate revenue. The majority (c. 98 %) of the wool is coarse-textured and is primarily used for interior textiles. Most NZ sheep are on hill country and the case study selected is based on the average hill farm from the Beef+ LambNZ Class 4 farms (Beef+LambNZ 2013), which produce 27 % of all NZ lamb and 32 % of total strong wool production (Beef+LambNZ 2013 economic service survey data). Farm data represent the average of 151 farms surveyed by Beef+LambNZ across hill country in the North Island of NZ (average rainfall 1420 mm/year). The farm also contained cattle (representing 48 % of total stocking rate or feed intake) and a combination of system separation (where possible) and biophysical allocation (BA) based on relative feed intake were used to separate out the sheep component of the farm system for this study. Sheep in this system are characterised by moderately high body weights, fecundity and wool production (Table 1). Case studies 3 and 4 (CS 3, CS 4) The majority of Australia's sheep flock is based on the Merino breed, which produces high to very high quality wool for garment manufacture. Modern Australian Merino sheep All datasets were scaled to a standardised flock size of 1000 ewes joined, inclusive of rams, replacements and lambs a DSE dry sheep equivalent, equivalent to an annual feed consumption rate of 400 kg DMI b Equivalents production systems are typically managed to optimise production of both wool and meat, as this is the most profitable production scenario. Case study three was based on farm data from three fine-medium wool Merino production systems from the semi-arid pastoral zone (250-350 mm average annual rainfall) in South Australia (unpublished data). Sheep in this system are characterised by high body weights and high yields of wool and LW (Table 1). Case study four was based on farm data from three superfine wool production systems in the northern tablelands of New South Wales (unpublished data), which is a higher rainfall zone (700-800 mm average annual rainfall) known for producing superfine to ultra-fine Merino wool. This strain of Merino sheep has lower body weights and lower yields of wool and LW than sheep in case study 3 (Table 1). Inventory and impact assessment The total GHG impact assessment applied Global Warming Potentials (GWPs) based on the IPCC Fourth Assessment Report (Solomon et al. 2007). Inventory categories assessed were cumulative fossil energy demand based on the method outlined by Frischknecht et al. (2007) and land occupation. Modelling feed intake and greenhouse gas emissions from livestock systems Feed and animal production data were used as a basis for modelling feed intake and GHG emissions from livestock systems. Feed intake for CS 1 and CS 2 was modelled using equations from the Australian Feeding Standards (Freer et al. 1997) as applied in the NZ national GHG inventory (MfE 2010). Feed intake for CS 3 and CS 4 were modelled based on AFRC (1990) equations as applied by the Australian national GHG inventory (DCCEE 2012). The NZ feed intake model was applied to CS 1 as the UK apply a less detailed tier one method in their national accounts which was of insufficient detail to account for specific aspects of the CS 1 flock such as live weight, wool weight and differences in lamb age and weight at sale. Critical assumptions and references for calculation of livestock GHG emissions are provided in Table 2 and GHG emissions for each supply chain are shown in Table 1. Emissions from other processes and inputs such as from fertiliser and fossil fuel use throughout the cradle-to-farmgate were modelled from inventory data. Land occupation Within LCA, land occupation has commonly been reported as an impact category (de Vries and de Boer 2010), though where land use is simply reported as a unit area of land for a given period of time (i.e. m 2 /year) this more accurately reflects an inventory value than an impact assessment value (Koellner et al. 2013). As noted by Koellner et al. (2013), land use inventories should identify the current use of the land. Globally, sheep production systems utilise a wide variety of land types, and where land occupation is used as a measure of the efficiency of resource use for food or fibre production, it is fundamentally important to classify land in terms of potential alternative uses. In the present study, we classify land occupation in three categories at the inventory level that reflect the quality of the land for use in other agricultural systems and a measure of the disturbance of that land. These three broad land types are: arable land used for cultivation, arable land used for pasture (potentially suitable for cropping) and non-arable land used for grazing (unsuitable for arable crops). Inventory data are presented in Table 1 and results are presented for the land currently used for cultivation only. Fossil fuel energy demand Fossil fuel energy demand was associated with both direct energy use on farm (from fuel, oil and electricity), and energy use in the manufacture and transport of goods and services used by the farms. Modelling of energy demand was based on the inventory of purchased goods, services and transport distances obtained from farm records or surveys (see Table 1). Handling co-production Sheep production systems commonly produce both wool and meat, with different proportions and quality of the wool product. Sheep production systems also commonly produce two meat products (lamb and mutton) of different eating quality. Multiple products present a challenge for assessing the inputs for and impacts of the product in question. The options for handling co-production according to ISO 14044 (ISO 2006) in order of preference are: Methods to avoid allocation: & Clear subdivision of the system; or & System expansion (SE) (expanding the product system to include the additional functions related to the co-products to avoid allocation). Allocation: & Allocation on the basis of physical or biological relationship; or & Allocation on some other basis, most commonly economic (market) value. Sheep are often produced in systems that include other agricultural production either from other livestock species (such as beef cattle) or crops (i.e. cereal grains). This issue is not addressed specifically by this paper, though in the case studies reported here, impacts were divided between subsystems and treated separately. This was done by dividing specific inputs and outputs and attributing these to the subsystem that used or generated them. Inputs and outputs associated with general farm processes were divided using the proportion of land resource used by each sub-system. For mixed sheep and cattle grazing systems, the inputs and emissions were first subdivided where possible and then the remainder were allocated on a biophysical basis according to the relative amount of feed eaten by each animal species. Handling co-production of wool and meat from sheep is more complex, because the system cannot be divided. In the case studies investigated, wool and meat were jointly produced from sheep flocks, though the value and significance of each product varied greatly. While meat was produced from both lambs and cull for age (CFA) breeding animals (mutton), these were not differentiated because both meat products were considered to be functionally comparable (i.e. provision of a high quality protein food source for human consumption). A comparison of seven possible methods for handling co-production of wool and LW was included, these being: BA based on partitioning of digested protein (three methods) or protein mass; economic allocation (EA); and SE (two methods). These are described in the following paragraphs. Methods for conducting biophysical allocation The BA approach was based on the work of Cronje (2012). Wool production is mainly determined by requirements for protein, rather than energy requirements which is the key determinant for milk production (CSIRO 2007). Cronje (2012) suggested using the proportion of Digestible Protein Leaving the Stomach (DPLS) as the biophysical basis for dividing impacts between wool and LW. The DPLS requirements were determined using CSIRO (2007) methods for each flock, and total requirements for maintenance (from endogenous urinary and faecal protein), wool and LW growth, including conceptus growth, were calculated. While this method provides base-level data to inform allocation decisions, subjective decisions are still required to allocate impacts between wool and meat. We investigated three alternative allocation scenarios based on these data: (i) allocation to wool and sheep meat based on the fraction of protein required for wool or meat divided by total utilised digestible protein from the whole flock (BA 1); (ii) allocation based on division of the maintenance requirements for the breeding flock between wool and meat according to the wool to sheep meat ratio (as in (i)) together with all maintenance requirements for slaughter lambs directly attributed to meat and all direct requirements for growth attributed to meat (BA 2); and (iii) allocation of all flock maintenance requirements and requirements for live weight production to the meat product, and allocation of direct wool protein requirements to the wool product (BA 3). Methods for conducting protein mass and economic allocation Allocation was performed using protein mass and economic value, based on farm-gate protein and value for greasy wool and LW (averaged over a minimum of 2 years). The protein content of greasy wool was estimated from the protein content of clean wool on a dry matter basis (i.e. 100 %) adjusted for the dry matter content of clean wool (84 %) and ratio of clean wool to greasy wool. The protein content of live weight was assumed to be 18 % based on Sanson et al. (1993) using a fixed assumption applied to all case studies in the absence of specific data regarding sheep condition scores. The allocation assumptions are provided in Table 3. Methods for conducting system expansion Considering the focus of this paper on wool, the SE methods accounted for avoided meat production via substitution. SE by substitution (the avoided burden method) is more commonly applied in consequential LCA and application for attributional studies has been questioned by some (Brander and Wylie 2011) but supported by others in some situations (Weidema 2000). As the method is a preferred option in the international standards for LCA (ISO 14044), application is justified as a comparison method. This approach has been applied in attributional studies, typically using average data for the substituted product (Finnveden et al. 2009). In this study, two constraints were applied when determining the avoided system: (i) the product must be a suitable replacement in the market; and (ii) the production system must be a suitable replacement taking into account the biophysical (land) resources available to the current sheep system. This latter criterion was included to minimise indirect effects relating to transfers of land resources from one industry to another and possible land use change emissions as a result of the substitution process. Using these two criteria, the avoided product system was assumed to be beef cattle or sheep using different sheep breeds where the focus is strongly oriented towards meat rather than wool. While a number of alternative meat and non-meat products may be possible substitutes for sheep meat in the market, these could not be produced on the majority of land used for the sheep production systems studied, which is non-cultivatable. Alternative grain protein products rely on cultivated land directly, while in the case of pork or poultry cultivated land is required for feed production. Case study 1 For the UK case study, this analysis was based on the avoided product system being beef cattle that were produced on the same farm. Data for the carbon footprint (CF) of beef produced in this farm class category in the UK (based on ten beef farm system analyses by EBLEX 2012) was 13.4 kg CO 2 -e/kg LW. Equivalence factors were applied to adjust for the lower carcase yield from sheep compared to beef cattle. Dressing percentages for sheep were assumed to be 45 %, compared to 51 % for beef cattle (EBLEX 2013). Case study 2 For the NZ case study, it was assumed that the avoided product was beef produced on the same farm class as for sheep. In practice, beef is also produced on these farm systems and this scenario assumed that the farm only carried sheep and not cattle. Data for the resource use and environmental emissions for beef had been calculated as part of this project and in a related NZ beef study (Lieffering et al. 2010). The average CF of beef at the farm-gate was 12.16 kg CO 2 -e/ kg LW for Class 4 farm beef. The corresponding value for fossil fuel energy demand was 7.07 MJ/kg beef LW, and land occupation values were 0.37, 2.92 and 23.0 m 2 /kg LW beef for cultivated land, arable pasture and non-arable land, respectively. Equivalence factors were applied to adjust for the lower carcase yield from sheep compared to beef cattle. Dressing Case studies 3 and 4 Two alternative meat production systems were identified; beef cattle and sheep production based on an alternative sheep breed. Two different alternative sheep systems were proposed, both with a strong emphasis on lamb production and either minor or no emphasis on wool production. In CS 3, the alternative sheep system was a composite crossbreeding system based on Border Leicester crossbred ewes and Poll Dorset rams. This system produced low value wool suitable for interior textiles, requiring a second substitution product, for which nylon was selected. In CS 4, the alternative system was based on Dorper breed sheep which shed their fleece naturally each year, producing no saleable wool. The average CF of the alternative sheep meat was 9.5 kg CO 2 -e/kg LW (CS 3) and 10.7 kg CO 2 -e/kg LW (CS 4). Corresponding values for fossil fuel energy demand were 5.1 and −6.1 MJ/kg LW for CS 3 and CS 4, respectively. Land occupation values were 0.01, 0.0 and 1081.5 m 2 /kg LW for CS 3 and 1.6, 3.1 and 62.4 m 2 /kg LW for CS 4, for cultivated land, arable pasture and non-arable land, respectively. The average CF of beef production was 13.5 kg CO 2 -e/kg LW (CS 3) and 11.9 kg CO 2 -e/kg LW (CS 4) and fossil fuel energy demand was 6. Partitioning of DPLS based on animal function and allocation methods Partitioning of DPLS requirements for the different sheep functions showed that wool constituted only 7 % of the total for CS 1 but was up to 22 % of the total for CS 3 (Table 4), coinciding with relative differences in flock wool production per ewe (Table 2). In contrast, there was little difference in the proportion of DPLS for growth (conceptus + LW gain), at 19-24 % of the total. Total maintenance requirements dominated DPLS at 54-69 % of total requirements. The three methods of calculating BA between wool and meat showed differences according to how the maintenance component of DPLS was allocated. When maintenance was allocated according to the relative requirements for wool and growth (BA 1) it resulted in values for allocation to wool of 22-50 % to wool (for CS 1 to CS 3, respectively). The corresponding range in allocation values for wool where all maintenance was allocated to meat (BA 3) was 7 to 22 %. Allocation by protein mass in wool and LW resulted in 19 to 40 % allocation to wool (for CS 1 and 3, respectively). The largest variation in calculated percentage allocation to wool between farms was in EA, which ranged from 4 to 52 % (for CS 1 and 4, respectively). 3.2 Impact of choice of method for handling co-products on greenhouse gas emissions GHG emissions were 9.7, 8.5, 8.6 and 10.5 kg CO 2 -e for CS 1-4, respectively, when presented on an unallocated, mass basis (i.e. per kilogram total wool and LW product), showing a variation of <25 %. Differences in GHG emissions were due to underlying differences in the production systems and emission sources between the countries, which was not the focus of the study and results should not be interpreted as representative of each country. However, when methods for handling coproduction were applied, GHG results differed substantially between methods (Fig. 1). Emissions per kilogram wool differed by two-to three-fold (depending on case study) by applying BA 1 and BA 3 methods, reflecting the difference in percent allocation in Table 5. The ranking of case study farms was similar across BA 1 to BA 3, although CS 1 and 4 were highest for BA 1 whereas there was little difference for BA 3. The greater mass of LW relative to wool made results more consistent across these different allocation methods for LW (Fig. 2) than for wool (Fig. 1), with the difference between the two most divergent BA methods (BA 1 and BA 3) being 53-69 % for wool but only 17-39 % for sheep meat. Results a Lower value associated with early sale for processing of a proportion of lambs at weaning b Utilised digestible protein is the sum of all protein required directly for production of wool and LW from the PMA method approximated those for the BA 2 method across all case studies. Results produced using EA did not correspond to the underlying biophysical characteristics for wool (Fig. 1). Notably, results from CS 1 were lowest using the EA method and highest using all of the biophysical methods, while results from CS 4 were highest using EA and intermediate using the biophysical methods. Differences in the economic value of products resulted in large differences between EA values across the case studies, ranging from 4 to 52 % of impacts being allocated to wool for the most divergent case studies, CS 1 and CS 4, respectively (Table 5). Differences were less pronounced between the biophysical methods and EA for live weight (Fig. 2). The two SE methods resulted in lower GHG emissions for wool than the allocation methods for three of the four case studies because of the high livestock emissions from the substitution system. Values ranged from negative (CS 1) to moderate (CS 4) in comparison to those for the allocation methods when beef was the substitution product. The range in SE values across the case studies using beef as a substitution product was the result of two main differences: the emissions intensity of the substitution product and the mass of LW produced. The divergent results from CS 1 and CS 4 were related to higher n.a n.a Fig. 1 GHG emissions from greasy wool production across four case studies assessed with seven alternative methods for handling co-production of wool and LW. n.a. not applicable because no meat-specific sheep breeds were identified for the case study emissions intensity of the beef product for CS 1 combined with higher LW productivity for CS 1 compared to CS 4. Fossil fuel energy The same range between the allocation methods shown in the GHG results was also observed in the fossil fuel results (Fig. 3). Results from the SE scenarios followed a broadly similar trend where beef was the alternative product. In the two scenarios where an alternative sheep system was modelled (CS 3 and CS 4), results were similar to beef when substituting with shedding sheep (no allocation to wool-CS 3) but differed when using an alternative sheep system that also produced wool, requiring a second substitution process to account for avoided strong wool production. This product was substituted for nylon, which accounted for the elevated energy use. Land occupation Comparison of methods for handling co-production confirmed the same broad trends for land occupation as observed for GHGs. Estimates of land occupation per kilogram wool using BA1 were two-to four-fold higher than estimates using BA3, with estimates for BA2 being intermediate and similar Fig. 2 GHG emissions from LW production across four case studies assessed with five alternative methods for handling co-production of wool and LW n.a n.a n.d Fig. 3 Fossil fuel energy demand for greasy wool production across four case studies assessed with seven alternative methods for handling co-production of wool and LW. n.a. not applicable because no meat-specific sheep breeds were identified for the case study. n.d. not determined due to non-availability of data to those using PMA. Use of EA resulted in wide variation between CS farms. However, compared to the other impact categories, application of SE resulted in smaller differences in cultivated land attributed to wool compared to the allocation methods. For CS 4, application of SE based on an alternative sheep meat system produced the highest estimate of all methods. The land occupation inventory revealed that sheep systems utilised very little land potentially suitable for cropping, representing 0-12 % of the total land occupation ( Table 1). The inventory of land occupation showed large differences in total land area per kilogram of wool and meat (data not shown) with the highest land occupation associated with CS 3, a farm located in a semi-arid region of Australia where stocking rate was low ( Table 1). The area of cultivated land occupation was low across all case studies, ranging from close to zero for CS 3 to 13.8 m 2 /kg wool in CS 4 (SE) ( Table 6). Using allocation methods only, cultivated land occupation ranged from 0.007 for CS 3 to 1.97 m 2 /kg LW for CS 4 (Table 7). Discussion This paper is the first to examine in detail the effects of a range of methods for co-product handling across diverse sheep systems. In particular, it examines in detail the complexity of BA methods based on protein utilisation, and contrasts this with EA methods and SE. This study was confined to the cradle-to-farm-gate stage of the life cycle of sheep products and further research is needed to handle co-products associated with wool and meat processing. Nevertheless, research in NZ on wool processed into fabrics, garments or carpets used overseas (NZ Merino unpublished, Basset-Mens et al. 2007) and on meat consumed in distant overseas markets (Ledgard et al. 2011) indicated that for GHGs the cradle-to-farm-gate is the dominant contributor to life cycle emissions, constituting about 80 % or more of total emissions, and therefore warrants most research emphasis on methodology. This paper also went beyond examining impacts for GHGs only by including two additional inventory categories of importance to extensive sheep production systems in order to consider any broader implications or trade-offs associated with allocation choice. With the advancement of global benchmarking activities by the Food and Agriculture Organisation of the United Nations (FAO) which include assessment of impacts from sheep ), a robust method for handling coproduction is required. In making these decisions, the requirements for benchmarking and impact assessment for two separate commodity groups (food and textiles) must be taken into account. This would be advanced if studies chose to present and discuss results for both products rather than using allocation as a means of simplifying the system to focus on one product such as meat (e.g. Ledgard et al. 2011;Opio et al. 2013;Peters et al. 2010;Williams et al. 2006) or wool only (Eady et al. 2012). The choice of methods for handling co-production for wool must be done with careful consideration of the goal and scope of the study and the intended end-use of the results. Sheep meat and wool LCA research to date has focussed on quantification of impacts of existing product systems and hot-spot analysis. Many of the published studies represent the first of their type (e.g. Ledgard et al. 2011;Peters et al. 2010;Williams et al. 2006) for their respective countries. In practice, allocation methods are often favoured for attributional studies oriented towards benchmarking and hot-spot analysis. The harmonisation of allocation methods is advantageous to avoid inaccurate comparisons; hence, the development of guidelines that provide more stringent directives regarding allocation (i.e. BSI 2011; LEAP 2014). However, there are several plausible All flocks standardised to 1000 ewes joined, inclusive of rams, replacement breeders and lambs a n.a. not applicable because no meat-specific sheep breeds were identified for the case study (CS) b n.d. not determined due to non-availability of data All flocks standardised to 1000 ewes joined, inclusive of rams, replacement breeders and lambs alternative methods that produce different results for meat and wool. Biophysical allocation The biophysical methods presented here provide a new basis for performing allocation between wool and meat. As both wool and meat are proteinaceous products and wool production is largely determined by protein requirements (CSIRO 2007), this provides a logical basis for determining allocation. However, subjective decisions still remain with respect to the allocation of maintenance requirements for the animal to either meat or wool, and the approach used was found to have a significant influence on the results. Biologically, the maintenance requirements for ruminant animals are the largest component of either protein or energy requirements. Hence, the subjective choice about how to manage this is both inevitable and highly significant. We evaluated this choice by allocating maintenance in three ways but acknowledge other possibilities also exist. Eady et al. (2012) applied a quite different BA method in a sheep system where the primary product was considered to be wool. These authors attributed all impacts associated with maintenance of the sheep flock to the wool product and only attributed direct additional requirements associated with meat production to LW. This bears some similarity to BA approaches developed for dairy cattle (e.g. Dolle et al. 2011) and is similar to the BA 3 method presented here, though the emphasis on wool and LW is reversed. The BA 1 and BA 2 methods are based on apportioning protein requirements for maintenance between wool and meat, with BA 1 being similar to that recommended by IDF (2010) for allocating between milk and meat, i.e. according to the ratio of requirements for each product. BA 2 was similar except that the maintenance requirement for lambs sold for meat was fully allocated to meat. The impact of small differences in allocation methods was highlighted by comparison of results across the case studies with different methods applied. We found that even between similar biophysical methods (BA 1 and BA 2), results could be re-ordered across the CS farm systems if the methods were not harmonised, as evidenced by comparison of CS 1 (using BA 2) with CS 4 (using BA 1), This highlights the importance of harmonisation of BA methods and explicit explanation of methods in research papers to ensure sound conclusions are drawn when comparing studies in the literature. For most sheep systems where lamb is the major product, BA 2 is arguably the most logical set of assumptions to apply since it fully accounts for lamb meat requirements but allocates breeding animal requirements to both wool and meat. Similar results were obtained using the simplified PMA method which is more easily performed and is a reasonable proxy for the more detailed biophysical methods. Economic allocation EA has been the most commonly applied allocation method for sheep systems to date (Brock et al. 2013;Ledgard et al. 2011;Opio et al. 2013;Peters et al. 2010;Williams et al. 2006) and has been argued based on revenue being a price signal that 'drives' production. However, EA will also cause results to vary over time in response to market fluctuations and subsidies or price interventions in addition to changes in environmental impacts, and this could complicate the interpretation of benchmarking results as the knowledge base builds. It is not clear if economic factors should be harmonised by use of the same market values for products from differing time periods or if these economic factors should be an implicit part of an environmental analysis. The common practice of presenting results for only one product in an analysis (i.e. either wool or meat) leaves the possibility of burden shifting between the two products if the economic value changes over time. For benchmarking applications where analysis over time is the objective, such factors may confound results and obscure changes in environmental performance. This could be partly overcome by presenting results for both products and discussing the influence of changed product value on the relative allocation to each product, and by applying fixed economic relationships between products for longitudinal benchmarking studies. However, allocation based on biological processes in the animal are more stable over time and are therefore preferable. Changes in EA factors will impact wool more heavily than meat because the impacts are divided over less product mass and hence this is an issue of greater concern in the wool industry. System expansion Regardless of the allocation method chosen, there are inherent weaknesses in an allocation approach. Where benchmarking results are used in a rating system designed to assist product choice decisions (such as the European Commission's Product Environmental Footprint) they are being designed to influence future supply and demand. Arguably, a partial analysis that fails to account for changes in supply and demand of coproducts will not inform decision makers or consumers of the true impact of their decisions. For products that come from sheep, and particularly for wool, the change in supply and demand for meat may have a large effect on overall environmental outcomes. For example, a choice to avoid wool on the basis of perceived high environmental impact may not reduce environmental impacts if declining wool demand resulted in a substitution at the market level between sheep meat and beef. The implications of such changes are best considered through application of SE using consequential modelling. Similar case studies in the dairy sector showed the importance of considering the impacts of change in co-products. Cederberg and Stadig (2003) found that higher milk production and fewer dairy cows in the Swedish dairy herd resulted in lower emissions intensity for milk, but no change to total emissions when the induced additional production of beef from suckler cows was taken into account. Considering the similarities with respect to co-production between milk-beef and wool-meat systems, it is likely that similar problems would exist if studies focussed on the emissions intensity of wool without accounting for changes in meat production. Zehetmeier et al. (2012) found that mitigation strategies focussing on one product (milk) without taking into account changes in the co-product system (meat) can result in erroneous conclusions because negative changes in the co-product system have the potential to outweigh positive changes in the main product system. Such problems are best addressed by applying consequential LCA, where system expansion is a preferred approach (Weidema 2000). However, within attributional LCA studies SE may be a suitable comparison method to understand the sensitivity of methodological choices and to improve the interpretation by considering the impact if changes in the coproduct system occurred. Considering the sensitivity of results to methods for handling co-production, the choice to apply attributional or consequential modelling during project inception, based on the goals of the study, is highly important for sheep systems. The disadvantage of system expansion is the added complexity, reliance on sensitive assumptions for coproduct substitution and added difficulty in communicating results. In this paper, we applied constraints at both production and product levels on the selection of substitution products. Substitution products were selected to (i) replace the product (meat) in the market, and (ii) replace the production system using equivalent natural resources at the production system level. In most cases, dual-purpose sheep can be replaced at the production level by alternative sheep breeds, beef cattle or goats to maintain meat production. Using chicken meat or pork as a substitution product for sheep meat is valid at the product level, but is not possible if the land used for grazing sheep is unsuitable for grain production to feed chickens or pigs. We note also that substitution at the production system level has other implications. For example, cattle graze in a different manner to sheep and this may result in fewer cattle being grazed per hectare of land than would be suggested by the relative feed requirements of each species. For example, research in NZ on hill country indicates that the equivalent stocking rate for sheep is about 20 % higher than for cattle (Webby 1993), meaning less beef can be produced from the same land area. Similarly, the choice of beef CF value can have a large effect as evidenced by the value for NZ wool changing from −3.4 to +11.5 kg CO 2 -e/kg greasy wool by using the NZ average beef CF value of 9.2 kg CO 2 -e/kg LW (which includes cull dairy cows) rather than the CF value of 12.2 kg CO 2 -e/kg LW relevant specifically to the same class of land as the CS 2 farm. These factors illustrate the importance of careful and detailed analysis when making substitution decisions at the product and production system levels rather than simply using generic alternative meat production systems. Conclusions While meat is the dominant product from global sheep systems, wool is an important co-product that should not be ignored in sheep studies. Decisions regarding the method for handling co-production are more challenging when the implications for both products are given equal consideration, which is particularly important for dual purpose sheep systems. For sheep systems, we provide here a functional BA method based specifically on protein requirements for application in attributional LCA studies. This method generates results that are causally related to production of wool and LW with a higher degree of stability over time than applying an EA method. Specifically, we suggest using the BA 2 method where lambs are a significant product. The PMA method can provide a suitable and simplified BA approach in lieu of more detailed modelling based on DPLS. Application of SE methods showed that results were lower across most impacts compared to the preferred BA approaches, highlighting the sensitivity of studies focused on wool production to methodological choices around co-product handling. Considering the different results achieved when applying SE, careful consideration of attributional and consequential modelling techniques are recommended at the project inception stage for wool studies. We suggest applying SE as a comparison method to highlight sensitivities and to assist in the interpretation of results to avoid erroneous conclusions where a change in supply and demand may occur. Considering that relatively small differences in allocation methodology changed results enough to reorder impacts between case studies, we recommend transparent explanation of allocation methods and reporting of results for both sheep meat and wool products to inform both the food and textile industries. reproduction in any medium, provided the original author(s) and the source are credited.

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2015-02-03T00:00:00.000Z

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Changes in the risk management of Salmonella enterica subspecies diarizonae serovar 61:(k):1, 5, (7) in Swedish sheep herds and sheep meat due to the results of a prevalence study 2012 Background The prevalence of Salmonella in food producing animals is very low in Sweden due to rigorous control programmes. However, no active surveillance is in place in sheep. The authorities decided to perform a prevalence study in sheep herds because findings at slaughter indicated that sheep associated S. diarizonae (S. enterica subspecies diarizonae serovar 61:(k):1, 5, (7)) might be common in sheep. Sampling was stratified by herd size in two groups, small herds with ≤ 30 animals and large herds with > 30 animals. In each stratum, 237 herds were selected at random. Faecal samples received from 244 out of the 474 randomly selected herds were analysed. Results A total of 40 of 100 (40%) of large herds and 17 of 144 (12%) of small herds were positive. The overall adjusted prevalence was 17.6% (95% CI, 12.9-22.2). Sheep associated S. diarizonae was detected in all counties (n = 21). Scientific opinions and an evaluation of on-farm control measures performed concluded that the impact of sheep associated S. diarizonae on human health is very low, and that risk management measures applied in response to findings of sheep associated S. diarizonae in sheep or sheep meat can be expected to have very little impact on reducing risks to human health. As a result, Swedish authorities decided to make an exemption for sheep associated Salmonella diarizonae in sheep and sheep meat in the current Salmonella control measures. Conclusions Sheep associated S. diarizonae is endemic in Swedish sheep herds. It is more common in large herds and not limited to certain parts of the country. The responsible authorities concluded that current risk management actions regarding sheep associated S. diarizonae in sheep and sheep meat are not proportional to the risk. This is the first time in the history of the Swedish Salmonella control programme that an exemption from the legislation has been made for a specific serovar. If there is any future indication of an increasing risk, due to e.g. change in the pathogenicity or development of antimicrobial resistance, the risk assessment will be re-evaluated and control measures reinforced if needed. Background Bacteria of the species Salmonella enterica occur worldwide and are a common cause of gastro-intestinal infections in both humans and animals. Bacteria belonging to S. enterica are divided into six subspecies consisting of more than 2,500 different serovars [1]. Among these, S. enterica subspecies diarizonae serovar 61:(k):1, 5, (7) (sheep associated S. diarizonae (SASd)) is considered as adapted to sheep [2][3][4]. The bacteria have been reported to be commonly found in sheep in the United Kingdom (UK), Norway and Switzerland [5][6][7][8]. The infection in sheep is usually sub-clinical [9] but may cause enteritis, rhinitis, orchitis, and aborted or stillborn foetuses [5,10,11]. SASd is only occasionally isolated from other species [12] and seldom reported in humans. For example, in the UK two human cases were reported during the time period , in the USA, 27 cases were reported between the years 1967-1976 and in Norway, only one case has been reported [4,13,14]. The situation is similar in Sweden, where only one case, which was travel related, has been reported during the last 25 years. S. diarizonae may have atypical growth characteristics, presenting difficulties in identifying this subspecies if laboratory personnel do not have experience with it. The underdiagnosis of this subspecies may therefore be larger compared to S. enterica subspecies enterica. In Sweden, as in Norway and Finland, the prevalence of Salmonella in food producing animals is very low due to a control programme initiated more than 50 years ago [15]. Any finding of Salmonella in feed, animals and food is notifiable and actions are always taken to eliminate the infection/contamination. Infected herds, including sheep herds, are put under restrictions and live animal movements are prohibited. Measures to improve the hygiene, cleaning and disinfection of the stable environment, and if necessary the feeding system and other contaminated areas, and when relevant, elimination of chronically infected animals, are used to eliminate the infection. Two consecutive whole-herd samplings with negative results are required to consider a herd free from infection and lift restrictions [16]. In sheep, 50% of the costs of eradication are funded by the Board of Agriculture. Fresh meat from carcasses of any animal species with demonstrated presence of Salmonella is not considered safe for human consumption and has to be placed on the market for a meat product plant or destroyed. In contrast to cattle, swine and poultry, there is no active surveillance for Salmonella in sheep. Instead, the surveillance relies on passive surveillance including post mortem examinations. However, because infection with SASd is typically subclinical in sheep [9], this surveillance is expected to have a low sensitivity. Clinical disease was only identified in 3 of 11 SASd-infected sheep-herds identified between 1998 and 2010 [17]. In none of these cases was SASd considered to be the cause of the observed disease. This indicates that active surveillance is needed to detect SASd-infected sheep herds. In 1998, a slaughterhouse survey showed that 3 out of 605 (0.5%) faecal samples from ewes and 2 out of 404 (0.5%) faecal samples from lambs were positive for SASd. No other Salmonella types were found [18]. In 2006, swab sampling of sheep carcasses at slaughterhouses according to Commission Regulation (EC) No 2073/2005 commenced. SASd-contaminated sheep carcasses have been detected in this sampling, indicating that the prevalence of Salmonella in sheep might be higher compared to other food producing animals. However, due to lack of denominator data, the prevalence of positive sheep carcasses could not be estimated. No studies have been performed to assess the prevalence of SASd at the herd level. In Norway, SASd is considered to be endemic, with an overall herd prevalence of 12% but with uneven geographical distribution, the regional prevalence varying from 0 to 45% [6]. Norway has a Salmonella control programme as Sweden, but based on a risk assessment that concluded that the impact of SASd on human health in Norway appeared to be marginal [19], control measures taken at the herd-level have been changed in Norway and actions are restricted to herds with clinical illness. It has not yet been decided which risk management actions will be taken when SASd is isolated from fresh meat from sheep carcasses in Norway (Kjell Hauge, personal communication, 2013). There were indications that the prevalence of SASd might also be high in Sweden, indicating that the present control programme was not efficient. Furthermore, there were no indications that this serovar was commonly reported in humans. If this was the case, the benefits of the present control on Salmonella in sheep could be questioned. The relevant authorities jointly decided to perform a prevalence study in sheep herds. Based on the results from the study, the authorities would further assess how to manage this Salmonella type when isolated from sheep. The aim of the present paper is to describe the prevalence study conducted during the winter 2012 and the actions taken by authorities due to the result of the study. Study design The National Veterinary Institute (SVA) obtained data on sheep herds (n = 16,478) from the Board of Agriculture. After exclusion of 1,657 herds where data on herd size was missing, 14,821 herds remained. Altogether these herds contained 409,181 sheep. The herd size distribution was skewed, 79.9% of the herds were considered small with 30 sheep or less and 20.1% had between 31 and 1,425 sheep. The aim was to detect an among-herd prevalence of 1% with 95% confidence. Given a herd sensitivity of 95% (as detailed below), this required that 315 herds were sampled [20]. As it was expected that the number of nonresponders might be high, the sample size was increased by 50% to 474 herds. As the costs for eradication of Salmonella from herds are much higher in large herds we wanted to avoid that most testing would be done in small herds. Sampling was therefore stratified by herd size in 2 groups, small herds with ≤30 sheep and large herds with >30 sheep. In each stratum, 237 herds were selected at random. In each herd enough samples were to be collected to produce a 95% herd sensitivity assuming that in a positive herd, 10% of adult sheep (>1 year) excrete sufficient amount of bacteria to be detected by bacteriological culture [19]. Due to practical and economical reasons it was decided to pool 15 samples in one pool. It was assumed that 50% of the sheep in a herd were adult (Kalle Hammarberg, personal communication, 2011), i.e. small herds were herds assumed to have ≤15 adult sheep and large herds >15 adult sheep. Assuming a test sensitivity of 1, 1 pooled sample was needed to detect a prevalence of 10% with 95% confidence level in herds with up to 19 adult sheep [20] and in larger herds 2 pooled samples were needed. Sampling The sampling was done by the animal owners and the study was conducted anonymously so that fear of control measures would not prevent farmers from participating. Every selected animal owner received a sampling-kit in February 2012 consisting of plastic gloves, 1 or 2 plastic sample collection containers, a padded envelope and a letter with instructions on how to take the sample(s). A referral note to be sent back to the laboratory with the sample(s), where the number of sheep in the herd excluding lambs born in 2012 was to be noted, was included. The county in which the herd was situated was written on the note before it was sent out to the animal owner. The animal owner was instructed to pick a total amount of forty fresh round pieces of faeces (corresponding to at least 25 g faeces) from adult animals from the bedding for 1 pooled sample. Faeces were to be picked from at least 15 different places, in order to represent at least 15 different animals, and from different parts of the herd if the animals were kept in several buildings or pastures. The faeces were collected in the plastic sample collection container(s) and posted to the SVA together with the referral note. The only information about the participating herds that the SVA had access to was the number of animals in the herds and the counties in which the herds were situated. Analysis of faecal samples Analysis of faecal samples was done at the SVA. In case a pooled sample weighted more than 25 g, faeces corresponding to 25 g were picked from different parts of the sample. The 25 g samples were then analysed for presence of Salmonella using the MSRV enrichment method (ISO 6579:2002/Amd 1:2007 Annex D), and each isolate was typed biochemically and sero-typed by agglutination of O-antigen and flagellar antigen according to the White-Kauffman-Le Minor scheme [1], in order to confirm if it was SASd. Statistical analysis The herd-size distribution as well as average herd sizes in small and large herds in source population and study sample were compared. The overall herd prevalence of SASd was calculated by weighting the prevalence in small herds (representing 79.9% of the population), and large herds (representing 20.1% of the population), where p h is the herd prevalence and p sh and p lh are the prevalences in small and large herds respectively. The overall 95% confidence interval was calculated as 1.96 √ σ 2 , using a pooled variance σ 2 , where prop sh and prop lh are the proportions of small and large herds in the population respectively and p sh and p lh are the prevalence of Salmonella in small and large herds respectively. The values n sh and n lh are the number of small and large herds that were tested, respectively. To evaluate the effect of herd size on the probability of being infected, herds were divided into 5 categories that were biologically reasonable (≤15, 16-30, 31-60, 61-100, >100 adult sheep) and the prevalence and 95% confidence interval were calculated. Scientific opinions and evaluation of on-farm control measures Due to the result of the prevalence study, the National Food Agency (NFA) delivered a scientific opinion on the extent of the risk that SASd in sheep may apose to public health. The Board of Agriculture initiated an evaluation of on-farm control measures for SASd. The consequences of on-farm control measures as practiced were compared with the expected consequences of alternative options, such as refraining from control measures or eradication of SASd from the sheep population. The most critical question was how a change of on-farm control measures would be expected to affect public health. In addition, the costs of control measures were investigated. Calculations were made for two scenarios; one representing the current level of detection, and one simulating hypothetical detection of all infected herds. Costs for farmers as well as for the state were taken into account. The potential effects on animal health and antimicrobial resistance were also considered. Prevalence study Samples were received from a total of 262 (55%) out of the 474 randomly selected herds. Eighteen herds were excluded for the following reasons: i) missing herd size (n = 10), ii) 1 pooled sample instead of 2 was collected (n = 7) and iii) 2 samples instead of 1 were collected (n = 1). A total of 244 (51%) herds remained for further analysis. Of these herds, 144 were small herds and 100 were large. The herd size distribution of the source population and the study sample in the 2 groups was similar. The average herd size of small herds was 13.5 in the source population and 9.8 in the study sample. The average herd size of large herds was 75.6 in the source population versus 94.6 in the study sample. A total of 40 of 100 (40%) of the large herds and 17 of 144 (12%) of the small herds were positive for SASd. The overall adjusted prevalence was 17.6% (95% CI, 12.9 -22.2). No other Salmonella type was found. The proportion of positive herds increased with herd size (≤15, 16-30, 31-60, 61-100, >100 adult sheep) from 0.06, 0.22, 0.26, 0.54 to 0.61. The 95% confidence intervals were wide and overlapped between groups. Positive herds were found in all 21 counties in Sweden. Scientific opinion by the NFA The NFA opinion concluded that the present prevalence study indicated that SASd is common in Swedish sheep herds, as is also the case in other countries, e.g. United Kingdom, Norway and Switzerland [5][6][7][8]. Data on swab samples from sheep carcasses from one of the largest sheep slaughterhouses in Sweden showed that 18 (1.8%) of the 990 swab samples taken between 2007 and 2011 were positive for Salmonella (all identified as SASd). This is a significantly higher prevalence of Salmonella than for cattle and swine carcasses. During the same time period (2007 to 2011) only 0.03% of 16,928 carcass swab samples from cattle and 0.02% of 29,583 carcass swab samples from swine were Salmonella spp. positive [21]. Assuming that the prevalence of SASd at this slaughterhouse is representative of all sheep slaughtered in Sweden, about 4,700 sheep carcasses would be expected to be contaminated with SASd each year. The corresponding figures for presence of Salmonella spp. on cattle and swine are 100 and 700 carcasses, respectively. In summary, SASd was considered to have low virulence in humans because the number of reported human cases in Sweden and other countries where this serovar is common in sheep and sheep carcasses is very low, despite the fact that consumers are likely exposed to it in relatively high extent by sheep meat. Consequently, the significance of SASd for public health was assessed to be significantly lower than that of serovars belonging to S. enterica subspecies enterica. It was concluded that risk management measures applied at findings of SASd in sheep or sheep meat can be expected to have very little impact on reducing risks to human health. Scientific opinion by the Swedish Institute for Communicable Disease Control In the scientific opinion of SMI, the impact of SASd on human health was considered when taking the potential underdiagnosis of S. diarizonae into account. Facts taken into consideration included the following: i) there were a low number of reported human cases of SASd in Sweden, ii) there was no invasive human infection with SASd reported in Sweden and iii) the majority of the human clinical laboratories in Sweden had reported S. diarizonae, mostly from faecal samples, i.e. they were able to isolate this subspecies from faeces which is the most complex material to isolate from. Furthermore, a blind test including one typical and one atypical S. diarizone was conducted at a clinical laboratory and the test results were correct. This was a limited test, however, this primary hospital laboratory was used for consultation regarding the possibility of any isolation difficulties regarding SASd. Based on these facts it was concluded that SASd has limited impact on human health. Evaluation of on-farm control measures by the Board of Agriculture The primary consideration for evaluating control measures on-farm were the opinions of the NFA and SMI regarding the effects on public health. In addition, the Norwegian risk assessment [19] was taken into account. The prevalence study indicated that approximately 2,720 SASd-infected sheep herds existed in Sweden, but during the last five years (2008-2012) only 1-2 infected herds were detected per year. Thus, the number of unknown infected herds was substantial. During the years 2008 -2011, the average cost for control measures in a SASd-infected herd was 29,000 € (range 6,800 -55,900 €), divided evenly between the state and the producer. If all infected herds in Sweden could hypothetically be detected, the costs of eradication were estimated to be at least 84 million € shared between producers and the state. Data based on necropsy statistics and healthmonitoring did not indicate that SASd had any considerable impact on animal health in Sweden. Since monitoring of antimicrobial resistance in the Swedish Veterinary Antimicrobial Resistance Monitoring programme started at the SVA in 2000, isolates of S. diarizonae from 9 separate incidents in sheep have been tested and resistance has not been found in any of the isolates [22]. The Board of Agriculture concluded that the sensitivity of the present surveillance is very low and that measures taken in identified infected herds have practically no effect on public health and probably no effect on the prevalence of SASd in the larger sheep population. On the other hand, the impact of risk management actions on the single farmer's economy is significant. To continue on-farm control measures or to try to eradicate SASd from the sheep population would be very expensive and, as shown in the scientific opinions of the NFA and the SMI, would be expected to have little gain to public health. Risk management Based on the abovementioned opinions and the evaluation of on-farm control measures, the Board of Agriculture and NFA decided to change national regulations concerning control measures regarding SASd in sheep. No changes to the existing control measures will be made for SASd in other animal species. Control measures on-farm will no longer be taken if SASd is isolated in a sheep herd. However, despite the change, the Board of Agriculture will still have the possibility to take action on individual cases. Furthermore, if change in the pathogenicity or development of resistance would occur, the exemption for SASd will be reconsidered. All findings of SASd in sheep will still be notifiable and all isolates will be tested for resistance to antibiotics. The NFA has made an exemption in the national legislation for findings of SASd on sheep carcasses, i.e. fresh meat from sheep carcasses contaminated with this serovar is not considered unsafe for human consumption. The exemption applies only to fresh meat from sheep carcasses and not fresh meat from cattle, pigs and poultry. Whether any risk management actions will be taken at findings of this serovar in fresh sheep meat at the retail level will be dependent on the responsible local authorities, who could consider the meat unsafe in accordance with Commission Regulation (EC) No 178/2002. Furthermore, due to EUlegislation (Commission Regulation (EC) No 2073/2005) minced meat, meat preparations or mechanically separated meat from any species contaminated with SASd is considered unsafe for human consumption. Trace back investigations from human cases will continue, i.e. if a sheep herd is a potential source of infection, bacteriological examination of the herd will be done to verify the source of infection. However, the general practices will be that no control measures will be taken in the source herd. Discussion The responsible authorities concluded that current risk management actions regarding SASd in sheep and sheep meat are not proportional to the risk. By making exemptions for SASd in sheep in national legislation regarding on-farm control of Salmonella, the annual costs for control of this serovar in sheep herds can be avoided without any adverse effect on human health. The effect of the change in risk management of fresh meat from sheep carcasses at slaughterhouses is much more limited, since only a few SASd-positive carcasses per year are expected to be found. However, the administrative and actual costs for handling positive findings in terms of contacts with authorities and animal owners, withdrawal when products are placed on the market or destruction of carcasses, and extra hygienic measures at slaughterhouses after positive findings, are expected to decrease. Costs for monitoring of sheep carcasses at slaughterhouses according to the requirements in Commission Regulation (EC) No 2073/ 2005 still remain. Concerning findings of SASd in cattle, pigs and poultry no changes will be made since these species are included in the EU-approved Swedish Salmonella control program, making any immediate changes difficult to carry through. Also, for these species findings of SASd are very rare and thus do not result in great costs. The exemption of SASd from regular control measures in Sweden, including both sheep and sheep meat, will be more extensive than in Norway where exemptions currently only concern live animals. Presently, Norway is also considering to exclude SASd from regular control measures when isolated from sheep meat, both at slaughterhouses, cutting plants and at retail level (Kjell Hauge, personal communication, 2013). The majority of the human clinical laboratories in Sweden use the reference methodology [23] when analysing Salmonella in clinical samples. Some strains of SASd may show atypical growth characteristics, i.e. colony morphologies may differ from what is expected for Salmonella spp. The colonies may be small and may also, due to the lactose fermenting capacity of SASd, exhibit the 'wrong' colour on selective agars [24]. To further evaluate the possibility of underdiagnosis, SASd was included in the annual External Quality Panel (EQA) on feacal diagnostics in the fall of 2012, in which the majority of the clinical laboratories in Sweden are enrolled. The purpose of that specific panel was to investigate the laboratories' ability to identify Salmonella with atypical growth characteristics. All clinical laboratories (n = 24) were able to identify SASd as a Salmonella (data not shown) (information kindly provided by Equalis, personal communication: results from the EQA program in faecal diagnostics, 2012-38).This supports the conclusion from the scientific opinion of SMI that the low occurence of SASd in humans in Sweden is not due to underdiagnosis. The prevalence study showed that the apparent prevalence of SASd in sheep herds in Sweden is 17.6% (95% CI, 12.9 -22.2). As the sensitivity of the test used is not known the true prevalence cannot be calculated but it is assumed to be slightly higher. The among-herd Salmonella prevalence in sheep is much higher than the Salmonella prevalence in other food producing animals. The prevalence of infected sheep herds in Sweden is in the same range as in Norway, however in contrast to Norway [6] no difference in geographical distribution of positive herds could be found in Sweden. The probability of a herd being positive increased with herd size. This is in agreement with previous studies in Norway [6,25], and seems reasonable because in small herds, the probability of becoming infected is expected to be smaller and the probability of spontaneous elimination of the infection may be higher. Therefore, if average herd size continues to increase in Sweden, the proportion of infected herds may also increase. However, even if this does occur, the risk for human infections is still considered to be negligible. Historically the Swedish Salmonella control programme has covered all serovars, thereby preventing introduction and spread of serovars such as S. Enteritidis and multiresistant S. Typhimurium. This is the first time an exemption from the legislation has been made for a specific serovar. At present it cannot be foreseen that requirements of control measures would cease for any other serovar of Salmonella. Furthermore, if there is any future indication of an increasing risk for humans the present risk assessment will be re-evaluated and control measures reinforced if needed. It is therefore important to continuously monitor any changes in the situation such as changes in the number of human cases, as well as in antibiotic susceptibility of the bacteria. Although an increased prevalence in sheep is not considered to be a potential risk for humans, continued monitoring/surveillance of this serovar in sheep and other animals is also essential. Conclusions The results of the study showed that SASd is endemic in Swedish sheep herds. It is more common in large herds and not limited to certain parts of the country. The responsible authorities concluded that current risk management actions regarding SASd in sheep and sheep meat are not proportional to the risk. This is the first time in the history of the Swedish Salmonella control programme that an exemption from the legislation has been made for a specific serovar. If there is any future indication of an increasing risk, due to e.g. change in the pathogenicity or development of antimicrobial resistance, the risk assessment will be re-evaluated and control measures reinforced if needed.

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ARTIGO A perspective for rural development based on the dairy-farming production system in Iporá and surroundings, : the objective of this study was to characterize the dairy-farming production system in Iporá and adjacent municipalities. In the present work 257 interviews were conducted from April to November 2013 in several locations. Mean milk production per farm was 207.9 liters/day and dairy cow yield was 7.8 liters/day. The indicators of pasture degradation was high (n=111/63.8%). Natural breeding was more frequent (n=155/82.4%) than artificial insemination (n=33/17.6%). Milking cows manually was more frequent (n=146/82.9%) than mechanical milking (n=30/17.1%). The most predominant milking construction was the roofless shed with packed earth floor (n=98/63.2%). Milk quality may be reduced due to certain procedures adopted during milking (48 herdsmen dry the saliva of the calf on the teat surface with the cow tail, 63 herdsmen remove the saliva of the calf on the teat surface by hand and dry it on the cow coat, and 67 herdsmen remove the saliva of the calf on the teat surface by hand and dry it on their pants). Vaccination against leptospirosis, bovine viral diarrhea, infectious bovine rhinotracheitis and neosporosis was low (n=26, 24, 20 and 7, respectively). The dairy-farming production system in Iporá and surroundings needs improvements to increase milk production and create opportunities for rural development. INTRODUCTION A dairy production system can be assessed by the zootechnical indexes that are correlated with the dairy farm performance and the profitability of the activity. Dairy farmers should be careful when calculating the zootechnical indexes to identify the ones that present the biggest deviation in regard to a desirable dairy production system (LOPES et al., 2009). Once dairy producers do not have an influence on milk price, there should be better administration and management of the variables that are under the farmer's control and indeed have a great impact on the dairy production system and the profitability of the activity (LOPES et al., 2012). Therefore it is essential to describe and characterize a dairy production system from a particular region, which will help farmers to adopt the adequate existing technologies and consequently increase milk production (CHINELATTO NETO et al., 2005). The economy of Iporá and adjacent municipalities (Amorinópolis, Diorama, Israelândia, Ivolândia e Jaupaci) has been primarily based on dairy farming and, in a lower scale, on beef cattle raising. From a total of 421,000 heads of cattle existing in these six municipalities, 49,800 dairy cows have been milked daily with a production of 154,923 liters of milk (IBGE, 2013). Nevertheless, the data reported by IBGE (2013) are insufficient to accurately characterize the dairyfarming production system in Iporá and surroundings. From this perspective, the survey and the collection of these data are essential to describe more precisely the dairy production system of this region, which requires a structured and detailed methodology that can assess each individual variable aiming to interpret and analyze all information collected as a systemic and holistic model (PORTELA et al., 2002). The objective of the present study was to characterize the dairy-farming production system in Iporá and surroundings, and indicate alternatives that may fit in the dairy production system of this region with potential to increase milk production and create new perspectives for rural development. MATERIALS AND METHODS In the present study 257 interviews with farmers from Iporá and surrounding municipalities (Amorinópolis, Diorama, Israelândia, Ivolândia and Jaupaci) in Goiás State were conducted from April to November 2013. The interviews were carried out by eight students and two faculty members of the Agribusiness Course of the Goiano Federal Institute (IF Goiano, Iporá Campus). The interviews happened in several locations and opportunities, such as in a field day organized by PROCRIA Health and Animal Nutrition, in a joint effort of a family-farming cooperative (COOMAFIR), in meetings of rural communities, in a local association of family-based farmers (APROSANTA), in an agriculture and livestock retailer store from Iporá (PROCRIA), in the office of the Agricultural and Livestock Defense Agency of Goiás State (AGRODEFESA) during the campaign of vaccination against the foot and mouth disease in May and November, and during the 28 th Agricultural Exhibition of Iporá. Farmers were randomly approached for the interviews and the data were collected without identification of the respondents (farmers). Protocols were approved by the Ethics Research Committee of the Goiano Federal Institute (decision # 4/2014). The questionnaire was divided in sections about family composition, socioeconomic and environmental aspects, infrastructure of the farm, main sources of farm income, production system of beef cattle raising and dairy-farming, annual crops cultivation, fruit growing, and vegetable production. The dairy-farming section of the questionnaire contained closed and open questions about milk production, dairy cow performance, indicators of pasture degradation and methods of pasture renovation, breeding methods, milking system, milking routine, and vaccine administration. The data were analyzed using the Statistical Package for Social Sciences (SPSS) version 21.0 (IBM CORP., 2012). Data were entered as quantitative (scale) or qualitative (nominal) variables. Values reported are frequencies, percentages, means and associated standard errors. When appropriate, values are reported in cross tables for a better understanding of the data (Tables 1, 3, and 7). RESULTS AND DISCUSSION The data of farm and dairy cow performance are presented in Table 1. From a total of 177 dairy farms, 112 (63.3%) have a daily milk production of up to 150 liters. The mean number of lactating cows/farm is 26±27 producing 207.9 liters/day, which corresponds to a cow performance of 7.8 liters/day. The data reported in Table 1 are below the mean of Goiás State evaluated from August 2000 to July 2001. At that time, the milk production/farm was 552 liters/day and the dairy cow productivity was 9.86 liters/day (LOPES et al., 2007). Thus, the data reported in Table 1 infer that the dairy-farming production system in Iporá and surroundings indicates low yields and may affect the profitability of the dairy activity. In addition, the high number of dry cows (29±53) compared with the number of lactating cows (26±27) also contributes to reduce dairy-farming performance and has a great impact on the cost of milk produced due to increased feeding costs with cows that are not in lactation (LOPES et al., 2009). The dairy cow performance reported by IBGE (2013) in Iporá and surroundings was 3.1 liters/day (considering 49,800 cows milked daily with a production of 154,923 liters). This productivity is extremely low and in disagreement with the data reported in the present study as well as by Lopes et al. (2007). This discrepancy may happen due to inaccuracy during the collection of data reported by IBGE (2013), although it represents the official data from the Brazilian Government. A high number of dairy farmers (n=111/63.8%) reported indicators of pasture degradation (Table 2), such as reduction of pasture yield, patches of bare soil, weed invasion, and appearance of termite mounds. Accordingly, a high number of dairy farmers have renovated pastures (n=130/75.1%) as an attempt to reverse pasture degradation. The most frequently reported methods of pasture renovation were tilling, fertilization and seed broadcasting (n=33/28.9%); tilling and seed broadcasting (n=33/28.9%); and tilling, soil correction with limestone or phosphate fertilizer or both, and seed broadcasting (n=19/16.7%). However, just five dairy farmers (4.4%) have opted for croplivestock integration as a method of pasture renovation. Crop-livestock integration systems have been reported to reverse pasture degradation with increased crop, pasture, and livestock yields (CARVALHO et al., 2010). The benefits of crop-livestock integration systems include increased soil fertility due to greater accumulation of organic matter, improved nutrient cycling, increased fertilizer efficiency, and better soil aggregation (SALTON et al., 2014). Rotation of crops with livestock can also help to control crop disease and weed invasion, thus reducing production costs and increasing environmental outcomes through less use of agrochemicals (MARTHA JUNIOR et al., 2011). Hence, according to the benefits above-described, dairy farmers in Iporá and surroundings should begin to experience crop-livestock integration as a method of pasture renovation in order to improve the dairy-farming production system. The great majority of farmers (n=155/82.4%) have opted for natural breeding as opposed to artificial insemination (n=33/17.6%) as a breeding method (Table 3). Furthermore, 97 farmers (62.6%) with a daily milk production of up to 150 liters have utilized natural breeding, whereas only 19 farmers (57.6%) with a daily milk production from 201 to 2,000 liters have used artificial insemination. Therefore, the data presented in Table 3 indicate that small dairy farmers have used natural breeding while bigger dairy farmers have opted for the artificial insemination method. In the natural breeding system it is not uncommon that two or more bulls cross with dairy cows and heifers. One of the problems associated with this system is the unknown paternity of the calves if two or more bulls are together with cows or heifers, as well as the reduction in the total number of cows due to the necessity of having bulls on the farm, which will ultimately decrease the potential of milk production. On the other hand, artificial insemination provides for several benefits, such as genetic improvement of the dairy herd due to the introduction of sires with greater milk performance and high heritability for characteristics related with milk production and mammary gland health, reduction on the number of bulls on the farm which will be utilized only in cases when cows and heifers have not been successfully bred by artificial insemination, greater control of the reproductive data of the dairy herd, and early detection of reproductive failures. However, highly-qualified labor for heat detection and artificial insemination procedures, as well as adequate feeding and nutritional management of dairy cows and heifers are necessary to obtain high fertility rates with the artificial insemination method (NEVES et al., 2010). Furthermore, slightly more than half of the farmers (n=42/51.2%; Table 4) have chosen dairy bull breeds (Holstein, Girolando, Dairy Gir, Jersey and Brown Swiss) either in natural breeding or artificial insemination, whereas a little less than half (n=40/48.8%; Table 4) of the farmers have used beef bull breeds (Nelore, Tabapuã, undefined crossbreeding, Simental and Caracu). The choice of a beef bull breed instead of a dairy bull breed can be considered a reproductive strategy that does not contribute to increase milk production and is an indication of a low level of dairyfarming specialization, which has been previously reported to be essential to improve the production system and increase milk production (LEMOS et al., 2003). The destination of dairy bull calves is reported in Table 5. Most of dairy bull calves (n=150/85.2%) have been sold just after they are weaned. Taking into account that a great number of farmers (n=155/82.4%) have chosen natural breeding as a reproductive method (Table 3), the likelihood of either a heifer or a bull calf to be born is 50% each, therefore raising and finishing dairy bull calves for beef may be an attractive alternative to increase farm income and contribute for the improvement of the dairy production system. However, good planning and remodeling of the farm for additional forage production both fresh (during the rainy season) and preserved as either silage or hay during the dry season is necessary in order to raise these animals with satisfactory weight gain. Although overall resources and care with bull calves is much less than with heifer calves on a dairy farm, raising dairy bull calves for veal production has been well consolidated in countries where dairy farming is advanced and developed, such as Holland, France, Italy, the United States and Canada (CARVALHO et al., 2003). In addition, recent studies reported that dairy bull calves grazing on Brachiaria brizantha and fed a high (1% body weight) or medium (0.5% body weight) level of energy supplement (cracked corn plus minerals) gained 0.88 and 0.62 kg/day on a 126-day experiment for the high and medium level of supplementation, respectively (REZENDE et al., 2011). The same animals were further divided in two groups on a feedlot experiment and fed diets with 50:50 or 20:80 forage/concentrate ratio. The expected slaughter weight of 395 kg was obtained after 84, 105, 126 and 126 days on feedlot for the high level of supplementation during raising and 20:80 forage/concentrate ratio during finishing, high level of supplementation during raising and 50:50 forage/concentrate ratio during finishing, medium level of supplementation during raising and 20:80 forage/concentrate ratio during finishing, and medium level of supplementation during raising and 20:80 forage/concentrate ratio during finishing, respectively (REZENDE et al., 2012). Collectively, the data reported by Rezende et al. (2011) and Rezende et al. (2012) suggest that raising and finishing dairy bull calves may be technically and biologically efficient depending upon feeding strategies during the raising and finishing phases. Out of a total of 176 dairy farmers who replied to this variable, 146 (82.9%) have milked cows manually (n=115/ 65.3% once a day and n=31/17.6% twice a day), whereas only 30 dairy farmers (17.1%) have utilized a mechanical milking system (Table 6). Moreover, the roofless shed with packed earth floor was the most predominant (n=98/63.2%) facility ( Table 6). The data presented in Table 6 suggest that the milking system and milking facilities in dairy farms from Iporá and surroundings have not followed the ongoing innovation and technologies of the dairy industry (BOTEGA et al., 2008;MILANI e SOUZA, 2010). In addition, the primary goal of a farming construction is to provide adequate conditions for animal welfare in order to maximize animal performance (COSTA et al., 2013), which may not be the case in roofless sheds with packed earth floor when the excessive accumulation of mud during the rainy season may favor environmental mastitis and a consequent reduction in milk production and milk quality. Smaller farmers with a daily milk production of up to 150 liters have milked cows manually either once (n=87/75.6%) or twice (n=21/67.7%) a day (Table 7), as opposed to bigger dairy farmers with a daily milk production of 201 to 2,000 liters who have milked cows using a bucket milking either once (n=2/50%) or twice (n=12/75%) a day, or a milking parlor twice a day (n=10/100%). Likewise with the data reported in Table 3, the data presented in Table 7 infer that the choice of either a manual or a mechanical milking system is related with the scale of milk production. A great number of dairy farmers have adopted certain procedures during milking which make the entire operation more time consuming and less efficient (Table 8), such as allowing calves to suck from their mothers prior to milking (n=143), tying up cow legs (n=148), tying up calves on the right hand of the cow (n=139), and allowing calves to suck the remaining milk of the cow after milking (n=141). Together, these procedures increase the time spent with milking resulting in less time available for other activities (e.g. feeding, pasture management, silage production, heat detection, fencing, and general maintenance, among others), which could result in improvements of the dairy production system. Still in Table 8, only 24 dairy farmers have adopted milking procedures that prevent mastitis and/or environmental milk contamination (21 farmers start milking with the strip cup test, pre-dipping solution application, teat drying, teat cup attachment, teat cup removal, and post-dipping solution application, while three farmers start milking with the predipping solution application, teat drying, strip cup test, teat cup attachment, teat cup removal, and post-dipping solution application). Contrarily, certain procedures have been adopted which may increase the risk for mastitis incidence and/or environmental milk contamination (48 herdsmen dry the remaining saliva of the calf on the teat surface with the cow tail, 63 herdsmen remove the remaining saliva of the calf on the teat surface by hand and dry it on the cow coat, and 67 herdsmen remove the remaining saliva of the calf on the teat surface by hand and dry it on their pants). After milk has been synthetized in the cow's mammary gland it can be contaminated by microorganisms in two different ways: inside the mammary gland, as a result of mastitis incidence, and shortly after milking by bacteria found on the teat, the udder and the equipment surface (GUERREIRO et al., 2005). Therefore, health of the mammary gland, adequate environmental conditions where cows are housed during milking, and suitable cleaning and sanitization of milking equipment are key factors to minimize bacterial raw milk contamination. The pre-dipping solution application prevents the contamination of milking equipment by environmental microorganisms found on the teat surface and cow-to-cow cross-contamination during milking. The post-dipping solution application avoids the incidence of mastitis shortly after milking while the teat orifice is still open for 20 to 30 minutes (YAMAMURA et al., 2008). Slightly more than half of the dairy farms (n=88/50.6%) have a cooling tank for milk storage (Table 8). Cooling milk temperature to 4ºC within two hours after milking is relevant to the reduction of bacterial growth and maintains the raw milk quality until it reaches the dairy industry (FAGUNDES et al., 2006). Although the data reported in Tables 6 and 8 indicate that the milk quality may not be high owing to poor infrastructure and milking procedures that favor bacterial contamination, farmers should first maximize resources for improving the dairy production system with increasing milk production to create possibilities for investments in new constructions and modern milking equipment. The majority of the farmers have vaccinated their animals against foot and mouth disease (n=176), bovine rabies (n=174) and brucellosis (n=172) ( Table 9). These vaccines are compulsory according to the AGRODEFESA regulations. In addition to the three diseases abovementioned, the number of dairy farmers who have vaccinated animals against blackleg is also high (n=162). Contrarily, the frequency of vaccination against leptospirosis, bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR) and neosporosis was low (n=26, n=24, n=20 and n=7, respectively). Consequently, the animals may be constantly vulnerable to these diseases in cases of possible contact with the pathogenic agent. Leptospirosis is a zoonotic disease that is responsible for economic losses in dairy farms due to abortions, retained placenta, premature births, stillborn calves, cow infertility and reduction in milk production (ELLIS, 1984). Dairy cows nearby the capital of Goiás State (Goiânia) had 81.9% (n=349/426) of prevalence of animals that tested positive for leptospirosis (JULIANO et al., 2000). The same authors reported that nine cows aborted out of 349 positively infected. Losses caused by BVD are a result of infection of pregnant cows causing abortion, stillborn calves, fetal malformation, and calves that are born weak and persistently infected. Studies in non-vaccinated dairy cows detected 65.66% of BVD infection (CHAVES et al., 2012). Similarly to BVD, IBR causes reduction in performance and abortion. Out of 5,511 blood serum samples tested in Minas Gerais State between 1990 and1999, 3,206 (58.2%) contained antibodies against the IBR virus (ROCHA et al., 2001). Neosporosis is also a disease that causes abortion, infertility and stillborn calves. Earlier research reported that the level of infection of neosporosis in culled crossbred dairy cows and fetuses from pregnant culled cows was 97.2% (n=559/575) and 12.7% (n=64/503), respectively, both in blood serum samples collected in a slaughter house in the south of Minas Gerais State (GUEDES et al., 2008). Together, the data reported by Juliano et al. (2000), Rocha et al. (2001), Guedes et al. (2008) and Chaves et al. (2012) indicate that vaccination against leptospirosis, BVD, IBR and neosporosis is essential to prevent economic losses caused by such diseases, especially disruptions in the cow's reproductive system, which will inevitably have an impact on milk production. Pearson correlation coefficients among quantitative characteristics for milk production are presented in Table 10. Milk production (MP) was significantly (P<0.01) correlated with number of lactating cows (LC, r=0.68), number of dry cows (DC, r=0.31), number of culled cows in the last twelve months (CC, r=0.28), number of heifer calves from one day to six months of age (HC1, r=0.42), number of heifer calves from six to twelve months of age (HC2, r=0.25), number of heifers raised on the farm for replacement in the last twelve months (HR, r=0.39), farm size (FS, r=0.27), area of the farm with pasture (AP, r=0.25), amount of concentrate fed daily to lactating cows (CLC, r=0.27), number of calves born in the last twelve months (CB, r=0.37) and number of calves that died in the last twelve months (CD, r=0.26). The variables that were not significantly (P>0.05) correlated with milk production were lactation length (LL, r=0.14), area of the farm designated for silage production (AS, r=0.25), and area of the farm planted with sugar-cane (ASC, r=0.19), Moreover, the coefficient of determination (R²) in the linear regression analysis was high (0.99). The model accounted for the effects of number of lactating cows, area of the farm with pasture, area of the farm designated for silage production, area of the farm planted with sugar-cane, amount of concentrate fed daily to lactating cows, and lactation length as independent variables. When a second linear regression analysis was run considering only the effect of number of lactating cows as an independent variable the R² was lower (0.46). In both linear regression analyses the daily milk production was the dependent variable. The data reported in Table 10 and the R² of the first linear regression analysis suggest that the variables previously mentioned (except lactation length, area of the farm designated for silage production, and area of the farm planted with sugar-cane) are relevant to increase milk production. Therefore dairy farmers should spend the same proportion of resources (knowledge, labor, investments, management, infrastructure, etc.) on these variables in order to improve the dairy-farming production system and increase milk yield. For instance, a good care of a heifer calf since its first day of life means that it will be bred earlier and will become a healthy and productive dairy cow to replace another cow that needs to be voluntarily culled for various reasons (e.g. mastitis, advanced age, laminitis, infertility, etc.). Besides, well-managed pastures will result in a higher high dry matter yield and nutritive value of the forage, and consequently will help to meet the nutrient demand of dairy animals. Thus, farmers should visualize the dairy-production system as different units of the farm that fit together and work as a synchronized model, which will ultimately result in a productive and profitable lactating cow. CB 0.33** MP = milk production (liters/day); LC = number of lactating cows; DC = number of dry cows; CC = number of culled cows in the last twelve months; HC1 = number of heifer calves from one day to six months of age; HC2 = number of heifer calves from six to twelve months of age; HR = number of heifers raised on the farm for replacement in the last twelve months; LL = lactation length; FS = farm size; AP = area with pasture; AS = area for silage production; ASC = area with sugar-cane; CLC = amount of concentrate fed to lactating cows; CB = number of calves born in the last twelve months; CD = number of calves up to three months of age that died in the last twelve months; *P<0.05; **P<0.01.

v3-fos

2019-03-31T13:44:15.852Z

2015-01-10T00:00:00.000Z

88171196

s2

In vitro Microrhizome Formation in Kaempferia parviflora Plantlets produced in vitro from rhizomes of Kaempferia parviflora were used as the source of explants for microrhizome development. Sixty percent of the plantlets formed microrhizomes in liquid medium supplemented with1 mg/L BAP+1 mg/L NAA, with 60 g/L sucrose. The treatment gave the highest fresh weight of microrhizomes, at 265 mg/plantlet. This optimized protocol is suitable for the commercial production of disease-free Kaempferia microrhizomes that can be stored and transported easily. INTRODUCTION The increasing demand for many plant species for food and medicine poses a threat to their rapid depletion from their natural habitats. In this regard, the capability to regenerate and propagate plants from cultures of cells and tissues is one of the most exciting and useful aspects of in-vitro cell and tissue culture. In many instances, in vitro culture can provide a sustainable alternative supply that alleviates the pressure of harvesting from the wild. Original Research Article Kaempferia parviflora is an herbaceous species belonging to the Zingiberaceae family. Since ancient times, it has traditionally been used as a health-promoting tonic that is both a stimulant and a vitalizing agent. The plant is very popular for its purported ability to enhance sexual performance mostly in males, and for which various presentations of this product are available especially in the Thai market for traditional medicines. This medicinal herb is propagated vegetatively through rhizomes, but mass propagation by this means is very slow. Tissue culture can be an important tool for rapid multiplication of slow propagating species such as this. Propagation through axillary bud multiplication is a relatively easy method to obtain uniform planting material. In vitro rhizome formation in ginger has been reported [1,2,3]. In vitro ginger rhizome formation in cultures supplemented with high sucrose concentrations (9 to 12%) has been reported [4] and the multiplication of microrhizomes has helped in the conservation of Zingiber [5]. Microrhizome formation is affected by many factors such as the concentrations of auxins, cytokinins and sucrose in the culture medium, as well as the temperature and photoperiod [6,7,8]. In recent times, storage organs such as bulbs, corms, tuber sand rhizomes have become a focus of attention in vegetative propagation because such propagules can be directly transferred to the soil with minimal acclimatization or hardening. Microrhizomes are easy to acclimatize and store; they are also less vulnerable to transportation conditions. There are a few reports on propagation success with microrhizomes of turmeric [9,10,11,12,13]. However, there being no publication on in vitro microrhizome culture of Kaempferia parviflora, we present this report on our study. Establishment of Initial Cultures Cultivated plant of Kaempferia parviflora ( Fig. 1ab) were cultivated in the glasshouse at the Malaysian Agricultural Research and Development Institute (MARDI) Serdang, Selangor, Malaysia. After one month in the green house when the rhizomes had sprouted, buds from the shoots were collected and used as the source of explants. The shoots were cleaned under running tap water for an hour, then washed with a commercial laboratory detergent and rinsed thoroughly with water. The explants were then immersed in 1% (v/v) fungicide (Benomyl 50%, Benlate ®) for one hour and again rinsed thoroughly under running tap water. Subsequently, the explants were surface sterilized with Clorox®, followed by several rounds of rinsing with sterile distilled water. The outer layers of the leaf sheaths of the buds were removed with a sterile surgical blade under aseptic conditions. The sterilized explants were then inoculated onto basal Murashige and Skoog's (1962) medium supplemented with 3.0 mg/L benzyl aminopurine (BAP) for the in vitro production of plantlets. The pH of the medium was adjusted to 5.8prior to autoclaving (121°C) under 1.05kg/cm 2 pressure for 15 minutes. The cultures were grown under white fluorescent light (3,000 lux) adjusted to a photoperiod of 16 hrs light/8 hrs darkness at 25±2ºC. The plantlets obtained in vitro were used for the microrhizome experiments described below. Induction of Microrhizomes Aseptic shoots approximately 4.5 cm long from plantlets of in vitro cultured Kaempferia parviflora were used as explants for the induction of microrhizome. The explants were sub-cultured in 150 ml flasks on basal solid medium (3 g/L phytogel) consisting of MS medium supplemented with 3% sucrose and varying concentrations of benzyl aminopurine (BAP) (0, 0.5, 1.0, 3.0 and 5.0 mg/L) and napthyleneacetic acid (NAA) (0, 0.5, 1.0, 3.0 and 5.0 mg/L), or in combinations of both the growth regulators. The cultures were then incubated under 16 hrs light/8 hrs darkness. After six months of culture, the percentage and fresh weight of microrhizomes that developed were recorded. In a separate experiment, the effects of the sucrose and agar concentration were examined to test their effects on rhizome formation over three months. Explants were cultured on medium containing 1 mg/L BAP+1 mg/L NAA and different concentrations of agar. The treatments of agar were solid 3g/L, semi-solid 1.5 g/L and liquid no agar that cultured on orbital shaker, with supplementation of sucrose in varying concentrations (0, 10, 30, 45, 60, 90 and 120 g/L). After three months of culture, the percentage and fresh weight of microrhizomes that developed were recorded. For cultures on the solid medium, all the explants were subcultured onto fresh medium at one month intervals. In the case of the liquid medium, the medium was replaced with fresh medium at monthly intervals. Ten explants were transferred into each jar containing 40 ml of the above media, with three replicates for each treatment. Statistical Analysis The data (10x 3 replicates per treatment) were subjected to one way analysis of variance (ANOVA) to assess treatment differences and interaction using SPSS version 11.0 software. Significance of differences between means was tested by Duncan's Multiple Range Test (p ≤ 0.05). RESULTS AND DISCUSSION Microrhizome formation induced directly on cultured explants is influenced by factors such as growth regulators [14] and sucrose [15,16]. These factors are commonly studied in combination with one another. In the present study, Kaempferia parviflora plantlets regenerated in vitro were cultured in the presence of different concentrations of sucrose and the growth regulators BAP and NAA. After five month of culture in solid media (Fig. 1c), microrhizomes were produced in five treatments, with the highest success rate of 15% obtained using the culture medium containing 1mg/L BAP+ 1mg/L (Table 1). This treatment gave 79 mg fresh weight of microtubers/flask. In comparison, the culture medium that contained 3mg/L BAP+ 3mg/L NAA, and another medium that contained 3 mg/L BAP+1mg/L NAA registered only 10% and 5% respectively in successful microrhizome production, producing 46 mg and 21 mg fresh weight of microrhizomes/flask respectively ( Table 1). The number of microrhizomes produced after five months of culture varied according to the growth regulators employed. It was evident that microrhizome production was more efficient when cultured in the presence of both plant growth regulator, BAP and NAA than single application. The results of the present investigation supported the report that obtained a positive response on microtuberization of yams when BAP was incorporated into the culture medium together with NAA [17]. In that report, the combination of NAA and BAP (0.2-0.2 mg/L) stimulated the formation of microrhizomes in Dioscorea cayennins-rotundata and D. alata. This finding was further supported by a scientist who made similar observations when they combined BAP (3 mg/L) and NAA (2 mg/L) to achieve 98% formation of microtubers that subsequently differentiated into shoots [18]. In the present study, the percentage of plantlets producing microrhizome varied according to the concentration of BAP and NAA used in combination, as noted [17]. Nevertheless, the concentration that gave the optimum response would depend on the plant genotype and growth regulators used. According to a report [19], an understanding of the relationship between the aerial parts of the plantlet and microrhizome initiation is important in appreciating the transport mechanisms that allow assimilates to be transferred to the rhizome. The factors controlling microrhizome initiation are different from those that control microrhizome induction [20]. A genetic component comes into play, and increasing BAP concentration could result in a decrease in the number of genotypes responding positively. In their study on Solanum tuberosum, [21] found that that 0.75 mg/L BAP gave the highest microtuber weight. It is relevant also to note the observation of [22] who found relatively high concentrations of BAP (0.75 and 1 mg/L) increased microtuber weight. The role of cytokinin and auxins, individually or in combination, in raising the frequency of in vitro tuberization potato has been observed [6,23]. The effects of sucrose and agar to improve microrhizome production were next evaluated. Different concentrations of sucrose (10-120 g/L) were tested using solid, semi-solid or liquid media containing 1 mg/L BAP and 1 mg/L NAA (Fig. 1d). Microrhizomes were produced after 3 months when the explants were cultured in a liquid medium supplemented with 30-60 g/L of sucrose ( Fig. 1e-h). Even more microrhizomes were produced after 90 days, with the basal medium supplemented with 45 to 60 g/L sucrose. The best result (with 60% of the plants producing microrhizomes) was obtained with 60 g/L sucrose added to the liquid culture medium. Good results were also obtained using 45 g/L sucrose in the liquid medium (35% success), or with 60 g/L sucrose in the semi-solid medium (25% success) ( Table 2). In the solid and semisolid media, treatment with 10-30 g/L of sucrose did not produce any mizrorhizomes. The medium with sucrose concentrations of 90 -120 g/L also produced rhizome however, the plant become more rapidly retarded and died. Results are mean values ± standard errors after 5 months of culture The fresh weight of the microrhizomes produced was reflected in its percent success in production. Thus, 60 g/L sucrose in the liquid culture medium resulted in the highest fresh weight of microrhizomes (256 mg/flask). This was followed by the liquid medium containing 45 g/L sucrose which produced 145 mg of microrhizomes per flask. The results from the present investigation showing the best result with 60 g/L (i.e. 6%) sucrose are consistent with the reports [9,10,11] who found that optimum microrhizome formation in Curcuma were obtained in culture media containing 6 -9% sucrose.Similar results have been reported [24] in their study on Curcuma longa. They observed that media containing 60 g/L sucrose and 3 mg/L BAP resulted in the most successful rhizome formation. Their study also found that further increase in sucrose concentration from 60g/L to 90 g/L decreased the percentage response in rhizome formation. In the present study, increasing sucrose concentration to 90-120 g/L resulted in death of the plantlets, or their plant becoming retarded. Previous work has emphasized the importance of sucrose being present in the culture medium for microrhizome formation. The turmeric plantlets cultured in a medium containing 80 g/L sucrose, and supplemented with low concentrations of growth regulators produced rhizomes under an 8 h illumination period [11]. Areported in agreement, stating that the induction of microrhizomes in media containing either 80g/L or 90g/L sucrose elicited the best response in Zingiber officinale after three months of culture [25]. On the other hand, microrhizomes obtained from the treatment with 100g/L sucrose were retarded and they exhibited symptoms of vitrification together with the decaying of buds. In a separate study on ginger, however, [4] found that microrhizomes of plantlets developed in vitro in MS medium enriched with sucrose at 90 g/L or 120 g/L. A recent investigation [26] showed that microhizomes of Costus pictus were successfully initiated on ½ strength MS medium supplemented with 0.44 mg/L NAA+ 7.2 mg/L BAP, together with 50-130 g/L sucrose. It was observed that the media containing 90 g/L sucrose produced the largest microrhizomes, in terms of size and average fresh weight. A report of the effect of sucrose on microtuber induction in potato. They concluded that tuberization could be induced by an addition of 8% sucrose when kept under short (8 h) photoperiods [27]. Where ginger (Zingiber officinale) is concerned, [4] found that temperature and photoperiod had no effect on rhizome induction, but sucrose -as an energy source -was the major determinant of rhizome formation. CONCLUSION The in vitro microrhizome formation system for Kaempferia parviflora was optimized in the present study. Liquid MS medium supplemented with 1mg/LBAP+1mg/L NAA and 60g/L sucrose was the most effective for microrhizome formation. Production of in vitro microrhizomes would provide a suitable source of disease-free seed rhizomes that could be stored and transported easily. In addition, in vitro microrhizomes do not require acclimatization in the field. The present protocol contributes towards an improved commercial propagation system for Kaempferia parviflora, rendering its cultivationmore efficient and productive. The protocol also can be utilized by commercial growers for large-scale production of diseasefree ginger and thus provide a sustainable supply for the pharmaceutical sector.

v3-fos

2019-03-20T13:04:33.586Z

2015-07-01T00:00:00.000Z

83858326

s2

Causes and Breaking of Seed Dormancy in Flowering Dogwood ( Cornus florida L.) . Cornus florida seeds show strong dormancy. In this study, we investigated the causes of the dormancy by assessing the permeability of the stony endocarp, the germination of seeds after mechanical dissection, and the effect of endogenous inhibitors. Water uptake by intact and cracked seeds during imbibition showed that the endocarp formed a strong barrier for water absorption. Meanwhile, extracts from endocarp decreased the germination frequency of chinese cabbage seeds from 99.3% (control) to 2.7%. Therefore, the endocarp was the mechanical barrier and contained endogenous inhibitors for seed germination. However, the germination percentage of decoated seeds and dissected seeds with the exposed radicle were only 13.3% and 28.7%, respectively. It was found that the endosperm also played a role in seed dormancy. Extracts from endosperm decreased the germination frequency of chinese cabbage seeds from 99.3% (control) to 53.0%. By contrast, extracts from embryo did not affect the germination of chinese cabbage seeds. When tested with the excised embryos, germination percentage was up to 85.3% at the 16th day of incubation. Taking these results together, we concluded that the endocarp and endosperm were responsible for seed dormancy in C. florida . To break the seed dormancy of C. florida , stratification and soaking in sulfuric acid are the effective means. The highest germination frequency was achieved by immersing seeds in 98% sulfuricacid for 10 minutes,thensoaking the seeds in500 mg · L L 1 gibberellic acid (GA 3 ) for 72 Flowering dogwood (C. florida L.), a member of the subgenus Benthamidia in Cornus, is a small-to medium-sized deciduous tree native to eastern North America (Borer et al., 2013;McLemore, 1990;Rushforth, 1999). The species is prized for the ornamental value of the pink, red, or white petal like, enlarged bracts in early spring, and brilliant red foliage and bright red berries in autumn. As noted by the U.S. Department of Agriculture Census of Horticultural Specialties (USDA-NASS, 2010) from retail and wholesale sales, in the United States, and especially in states such as Tennessee, C. florida is an economically important ornamental tree and may also be used as an important food source for wildlife in forests when its fruits ripen in autumn (Paul and David, 2008;Stiles, 1980). In addition, C. florida is widely considered as a calcium pump, increasing the rates of mineralization of the forest litter and soil because of the high calcium concentrations in its foliage (Holzmueller et al., 2007;Thomas, 1969). Typically, C. florida is propagated from seeds, but the seeds usually develop strong dormancy (Coartney et al., 1989), which may be a great challenge for seed reproduction (Dirr and Heuser, 1987). Studied with C. kousa var. Chinensis, Fu et al. (2013) indicated that the dormancy of chinese dogwood could be classified as physiological dormancy due to the existence of inhibitory substances in the endosperm. However, the causes of C. florida seed dormancy remains largely unknown thus far, except that Laufmann and Wiesner (1998) reported rapid germination of eastern dogwood (C. florida cv. Small) by embryo extraction, cut cotyledons, and GA 3 . Normal seed germination of C. florida requires a moist prechill treatment at 3-5°C for 3-4 months. In this study, we aimed to identify the multifaceted causes and to establish a practical and powerful method to successfully break the seed dormancy of C. florida that can be applied in seed reproduction practice. Materials and Methods Source of seeds. The seed of C. florida is encased within a stony endocarpic pit (hereafter seeds with endocarp are referred to as the seed). In this study, the seeds of C. florida were imported via Lovelace Seed Company (Elsberry, MO) in Spring 2013 and stored at 4°C. The seeds were collected from Knoxville, TN. Water permeability of the endocarp. To test whether the hard stony endocarp may restrict water imbibition for germination, two experiments were performed to test the water absorption capability of the seed. In Expt. I, 30 intact seeds enclosed within the endocarp were weighed on an electronic balance accurate to 0.001 g, then were immersed in 200 mL distilled water at room temperature for 168 h. At 12-hour intervals, the seeds were removed from the water, surface dried using filter paper, and weighed. The seeds were then reimmersed. The final weight measurement was recorded after soaking for 14 cycles for 168 h. In Expt. II, the same procedure was repeated except for the fact that the endocarp was cracked in the micropylar region of pliers, otherwise, the procedures were identical to those used in Expt. I. The two experiments were conducted using three replicates of 30 seeds each. In each experiment, the water uptake ratio was calculated and expressed as a percentage of the seed fresh weight. Germination after mechanical manipulation. Three experiments were performed to identify whether different tissues restrict the germination of C. florida seeds. Before the experiments, seeds were treated as follows: a) the stony endocarp was completely removed following breakage using a pair of pliers (''decoated seeds'') ( Fig. 1A); b) the decoated seeds were carefully dissected using a singleside blade to expose the radicle (''radicleexposed seeds'') ( Fig. 1B); and c) the embryo was excised from the seed (Fig. 1C). After these preliminary treatments, the materials were incubated on moist absorbent cotton at 25°C and an 8-h photoperiod. During incubation, the seeds were watered every 2 d. Germination was monitored every second d for 16 d. The germination percentage was determined in accordance with the International Seed Testing Association (ISTA) (2011) guidelines. Three replicates of 50 seeds were used in each of the three experiments. Extraction of inhibitors of seeds. Inhibitors of C. florida seed germination were extracted from the endocarpic pit, the endosperm, and the embryo using methanol as the extract solvent. The extraction procedure was conducted as that described by Hou et al. (2014). First, the endocarps, the endosperms, and the embryos were excised separately. Then, the endocarps were ground into powder in a mill grinder, and the endosperms and the embryos were separately ground into powder in liquid nitrogen. The powdered samples were extracted with methanol in a soxhlet apparatus. The extracts were obtained by the following procedures: the powdered samples (2.5 g) were suspended separately in 40 mL of 80% (v/v) methanol at 5°C for 24 h three times. Subsequently, the combined supernatants from the extractions for each tissue were evaporated under vacuum at 37°C to remove the solvent completely. Finally, 2 mL of each extract was diluted to 100 mL with distilled water. The activity of inhibitors in the extracts was determined by incubating nondormant chinese cabbage seeds in petri dishes moistened with the extracts. Three replicates of 100 cabbage seeds were used for each extract. Seeds in each replicate petri dish were soaked in 5 mL of the extract solution for 3 h, whereas control seeds were soaked in distilled water for the same period. The seeds were incubated in a growth chamber at 25°C with an 8-h/16-h (light/dark) photoperiod. Seedling emergence was counted daily for 6 d. A seedling was classified as emergent in accordance with the ISTA (2011) rules. Germination percentage was calculated based on the number of normal seedlings that emerged as a proportion of the total number of seeds sown. Evaluation of methods to break seed dormancy. We applied the following treatments to evaluate their capability to break the dormancy of C. florida seeds. In treatment 1, seeds were immersed in 500 mg · L 1 GA 3 for 48, 60, 72, and 84 h at room temperature. A parallel control was conducted using seeds imbibed in water for 84 h without GA 3 . The water or GA 3 solution was changed twice daily (Hartmann et al., 1989). After soaking, the seeds were stratified at 5°C (cold stratification) for 90 d. In treatment 2, seeds were soaked as in treatment 1, but were stratified during the d at 15°C and during the night at 5°C (alternative stratification) for 90 d. During stratification, water was added to keep the sand with water-holding capacity of 50% to 60%. In treatment 3, seeds were soaked in concentrated sulfuric acid (98%) with seeds: acid of 1:2 (v/v) for 0, 5, 10, or 20 min (chemical scarification). During treatment, the solutions were stirred continuously with a glass rod. After chemical scarification, the seeds were washed in running water for 24 h. Next, the seeds were soaked in 500 mg · L -1 GA 3 for 72 h and stratified at 5°C for 60 d. After completion of the stratification treatment, the germinability of four replicates of 50 seeds each was tested in moistened sand at 25°C with an 8-h/16-h (light/dark) photoperiod. The number of germinated seeds was counted every other day for 30 d. During the germination test, water was added to keep the seeds moist. A seedling was classified as emergent in accordance with the ISTA (2011) rules. The germination percentage was calculated as described above. Statistical analysis. A completely randomized design was used in all experiments. The effect of the treatments was assessed by the final germination percentage for each trial. The significance of differences between the means was assessed using the least significant difference (LSD) test with SPSS v19.0 (http:// support.spss.com/). Results Water absorption by C. florida seeds. The cracked seeds absorb water more rapidly than the intact seeds. The water uptake by cracked seeds increased to a saturation level of 16.9% in 24 h, and then leveled off. In contrast, the water uptake by intact seeds only increased to 7.3% in 24 h, and it would take at least 168 h for the intact seeds to achieve a nearly saturation level of water uptake (Fig. 2). Germination after mechanical manipulation of seeds. The excised embryos showed no dormancy. After incubation for 7 d, the embryonic axis elongated and the cotyledons of excised embryos started to expand and turned green (Fig. 1D). The germination percentage was 85.3% after 16 d of incubation. In contrast, the germination percentage of decoated and radicle-exposed seeds were only 13.3% and 28.8%, respectively, after 16 d of incubation. Inhibitor activity of extracts from C. florida seeds. Extracts from the excised embryos of C. florida showed no significant effect on cabbage seed germination (P = 0.217) comparing to the control, whereas extracts from the endosperm significantly (P < 0.001) reduced the percentage germination of cabbage seeds from 99.3% (control) to 53.0%. Soaking cabbage seeds in the same concentration of extracts from the endocarp had an even more significant (P < 0.001) negative effect on cabbage seed germination (reduced to 2.7%). It indicates that both the endosperm and the endocarp contain endogenous inhibitors, which play an important role in the dormancy of C. florida seeds. Effects of cold and chemical scarification on C. florida seed germination. Germination responses under different GA 3 soaking periods combined with stratification treatments showed significant differences. Generally, with increasing duration of soaking in GA 3 up to 72 h, seed germination increased significantly (P < 0.05) in both treatment 1 and treatment 2. Compared with the control (soaking in GA 3 for 0 h combined with 90 d of cold stratification), for which 22.3% germination was recorded, seed germination increased to 79.0% when seeds were soaked in GA 3 for 72 h followed by 90 d of cold stratification (Table 1). For the same duration of soaking in GA 3 , germination in treatment 1 (cold stratification) was slightly higher than that in treatment 2 (alternative stratification), except for soaking in GA 3 for 0 and 60 h (Table 1). Statistical analysis showed that the effect on seed germination of cold stratification was not significantly different from that of alternative stratification (P > 0.05). However, we observed that the germination speed was more erratic when seeds were treated with alternative stratification. Therefore, seeds were only cold stratified at 5°C (cold stratification) in treatment 3. It is also notable that soaking seeds in GA 3 for 72 h had the best effect on seeds germination in both treatment 1 and treatment 2 (Table 1), thus only 72 h-GA 3 soaking was performed in treatment 3. To shorten the duration of cold stratification, seeds were scarified in sulfuric acid before GA 3 soaking (72 h) in treatment 3. With chemical scarification, most seeds germinated at cold stratification of 60 d, and we achieved seed germination percentage of 81.8% at cold stratification of 60 d when seeds were first scarified in sulfuric acid for 10 min (Table 1). Thus, chemical scarification shorten the duration of cold stratification from 90 to 60 d. However, if we increased the scarification duration to 20 min, seed germination percentage would be greatly reduced (lowered to 5.5%). This indicated that excessive chemical scarification would cause damage to the seeds. Discussion Causes of C. florida seed dormancy. Water uptake is a fundamental requirement for the completion of seed germination (Manz et al., 2005). In this study, water absorption by intact seeds increased slowly to 15.8% after imbibition for 168 h (Fig. 2). This finding indicated that the endocarp of C. florida could restrict water uptake and that might be one cause of seed dormancy. However, water uptake by seeds with a cracked endocarp was 16.9%, only marginally higher than that of intact seeds, which was even lower than that of intact seeds from C. kousa var. chinensis (Fu et al., 2013). Thus the water content was likely to be inadequate for the metabolic processes required for germination. Therefore, in addition to the endocarp, the endosperm may also retard water absorption. The identity of factors that influence water uptake and the water absorption mechanism in C. florida requires further exploration. Laufmann and Wiesner (1998) reported that the cotyledons of eastern dogwood (C. florida L. cv. Small) significantly inhibited germination of excised embryos. In this study, the germination percentage of excised embryos with cotyledons was 85.3%, and extracts from excised embryos did not inhibit the germination of cabbage seeds. Thus, the cotyledons did not inhibit the germination of excised embryos of C. florida seeds. Fu et al. (2013) also found that there was no dormancy in the excised embryos with cotyledons of C. kousa var. chinensis. We proposed that the effect of cotyledon on seed dormancy might vary among different Cornus species. Germination of decoated and radicle-exposed seeds was significantly lower than that of excised embryos, which indicated that the endosperm was a barrier to seed germination. Extracts from the endosperm and endocarp significantly decreased cabbage seed germination, which suggested that an endogenous inhibitor might contribute to C. florida seed dormancy. Our findings indicate that seeds of C. florida show both physical and physiological dormancy as the restriction of water absorption and the inhibition of extracts, which belongs to the combinational dormancy category according to the seed dormancy classification of Baskin and Baskin (2004). Methods of breaking C. florida seed dormancy. Many procedures, such as stratification with low or alternate temperatures (Ertekin, 2010;Li et al., 2013;Murat et al., 2010), plant hormones, and other chemical treatments (Li et al., 2012;Mark, 1994) are effective in overcoming seed dormancy in a wide variety of species (Bewley and Black, 1982;Cohn, 1987Cohn, , 1990Laufmann and Wiesner, 1998). To break the physical dormancy, sulfuric acid is the effective scarifying agent (Bhatt et al., 2000). The data reported herein showed that soaking seeds with 500 mg · L -1 GA 3 for 72 h combined with cold stratification was effective to break seed dormancy of C. florida (Table 1), while it required a long period of cold stratification (90 d). Soaking seed in sulfuric acid (98%) for 10 min before GA 3 treatment would reduce cold stratification requirement to 60 d. Immersion of C. florida seeds in sulfuric acid scarified the hard endocarp, which would accelerate water absorption and gas exchange, and ultimately results in rapid and uniform germination (Everitt, 1983;Hartmann et al., 1989). However, soaking the seeds in sulfuric acid for longer time would drastically decrease the germination percentage (Table 1), indicating excessive scarification would damage the seeds. Based on our study, rapid promotion of C. florida seed germination was achieved by immersing seeds in sulfuric acid for 10 min before soaking in 500 mg · L -1 GA 3 for 72 h followed by cold stratification at 5°C for 60 d. As a conclusion, we have established an appropriate method to break C. florida seed dormancy that can be applied in practical seed reproduction practice. ---5.5 ± 1.3 d -Values of germination percentage are displayed with the mean ± SE (n = 50). In treatment 1 and treatment 2, germination percentages followed by the same letters in the same row indicated no significant difference at P # 0.05 by the LSD test, whereas those followed by different letters in the same row indicated significant difference at P # 0.05 by the LSD test. Both treatment 1 and treatment 2 indicated that soaking seeds in GA 3 for 72 h had the best effect on seed germination, thus only 72 h-GA 3 soaking was performed in treatment 3 (''-'' indicates germination is not carried out at the corresponding period of GA 3 treatments). In treatment 3, significance test was made for germination percentages of seeds soaking in sulfuric acid for different duration.

v3-fos

2016-05-14T04:31:47.022Z

2015-06-10T00:00:00.000Z

1717006

s2

Anaplasma infection of Bactrian camels (Camelus bactrianus) and ticks in Xinjiang, China Background To date, anaplasmosis has been reported to be a subclinical disease in Indian and Arabian one-humped camels (Camelus dromedarius) and llamas (Lama glama). However, no information on Anaplasma infection in two-humped Bactrian camels (Camelus bactrianus) in China has been published to date. The aim of this study was to investigate the prevalence of Anaplasma spp. in domestic Bactrian camels and ticks in Xinjiang, China. Findings A total of 382 ticks were collected from the Bactrian camels and from environmental sources. Of these, 84 were morphologically identified as belonging to the Rhipicephalus sanguineus group and genetically identified (12S rDNA, 16S rDNA and the cytochrome c oxidase 1 genes) as R. sanguineus group ticks (temporally designated as Rhipicephalus sp. Xinjiang). PCR testing showed that 7.2 % (20/279) of the camels harbored Anaplasma platys DNA. However, microscopic examination revealed no A. platys inclusions in blood smears from the camels. The PCR prevalence of A. platys DNA was 9.5 % (6/63) in Rhipicephalus sp. Xinjiang from the Bactrian camels and 14.3 % (3/21) in Rhipicephalus sp. Xinjiang from the vegetation. A. platys DNA was not detected by PCR in other tick species (Hyalomma asiaticum, Dermacentor niveus and Hyalomma dromedarii), and no other Anaplasma species were detected in these samples. Conclusions This is the first report of A. platys in Bactrian camels in Xinjiang, China. The moderate positivity observed indicates that these animals might be a natural host for this pathogen in China. Background Anaplasmosis is an infectious disease caused by a Gramnegative obligate intracellular bacterium of the Anaplasmataceae family (order Rickettsiales). The order was reclassified in 2001 and includes several genera, including Anaplasma, Ehrlichia, Neorickettsia, and Wolbachia [1]. These arthropod-transmitted bacteria are important emerging pathogens of both animals and humans [2]. Of the known Anaplasma spp., Anaplasma marginale is the most virulent, and is responsible for extensive economic losses to farmers in tropical and subtropical areas [3][4][5]. A. marginale is considered capable of infecting dromedaries, cervids, domestic buffalos and cattle [6][7][8][9]. A. phagocytophilum is the causative agent of human granulocytic anaplasmosis [10,11], a life-threatening disease associated with high mortality rates in humans; A. phagocytophilum can also infect dromedaries, llamas, and cervids [7,12]. A. platys, the causative agent of canine infectious cyclic thrombocytopenia, is usually a mild disease with a worldwide distribution, although its virulence may vary from region to region [13,14]. A. platys is supposed to be transmitted by R. sanguineus sensu lato [15,16]. Nonetheless, a definitive proof of the vector competence of this tick for A. platys is currently lacking [17]. Sample collection The region investigated in Xinjiang, China is located at latitudes 39°30′ to 41°27′ north and longitudes 79°39′ to 82°01′ east. The study was performed in May 2014. In total, 279 blood samples were randomly collected from free-choice grazing camels in desert regions. Blood smears were prepared from blood samples obtained by ear venipuncture of individual Bactrian camels. All of camels were clinically examined before blood sample collection. Ticks on camels were collected directly and transferred to labeled vials, whereas dragging was used to collect ticks from the vegetation [29]. This method is considered inefficient for sampling Hyalomma spp. ticks because they are concealed in favorable micro-habitats and display an active host-seeking behavior [30]. Thus, Hyalomma spp. were collected from the walls and crevices of camel sheds. Three hundred and eighty-two ticks were collected from camels, environment vegetation, and animal sheds. All ticks were labeled according to their sources (i.e., camel, vegetation or animal shed), and were morphologically identified according to the methods of Teng and Jiang [31]. Ticks belonging to the R. sanguineus group (n = 84) were subject to further identification using the methods of Dantas-Torres et al. [32]; these methods are based on PCR amplification and sequence analysis of the 12S rDNA, 16S rDNA, and cytochrome c oxidase (cox1) genes. PCR products of three genes were purified and ligated into pGEM T easy vector. The recombinant plasmids were transformed into Escherichia coli DH5α competent cells. As for each PCR samples, at least three positive clones identified by their own relative specific primers were sequenced by the Gen-Script Corporation (NJ, China). Basic Local Alignment Search Tool software (http://blast.ncbi.nlm.nih.gov/ Blast.cgi?CMD=Web&PAGE_TYPE=BlastHome) was used for sequence analysis. Representative 12S and 16S rDNA genes and cox1 gene nucleotide sequences have been deposited in GenBank. Microscopy Blood smears were air-dried, fixed in methanol, stained with a 10 % solution of Giemsa (Sigma-Aidrich, Santa Clara, CA, USA) in phosphate-buffered saline (pH 7.2), and then subjected to microscopic examination. DNA extraction After species identification, all the ticks were washed in 70 % ethanol, rinsed three times in sterile phosphatebuffered saline, and dried on filter papers. They were separated individually and stored at −80°C until the DNA extraction. Genomic DNA from 279 whole blood samples and 382 of the tick samples was extracted individually using DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. DNA yields were determined using a NanoDrop ND-2000 Spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA). Molecular detection of Anaplasma spp. using speciesspecific primer sets PCR was used to detect and identify Anaplasma spp. from Bactrian camels and ticks using the genera-specific and species-specific primers listed in Table 1 [16,[33][34][35]. PCR reactions were performed in a DNA thermocycler (Bio-Rad, Hercules, CA, USA) and the PCR conditions were the same as those reported previously [16,[33][34][35]. DNA from ovine whole blood without Anaplasma and Ehrlichia DNA and DNA from each bacterial species were included in each PCR reaction as negative and positive controls; of positive control, A. platys DNA originated from dog, A. ovis DNA from goat, A. marginale DNA from cattle, A. bovis DNA and A. phagocytophilum DNA from red deer. To assess the presence of specific bands for Anaplasma spp., PCR products were separated by 1.5 % agarose gel electrophoresis and the purified DNA products were sequenced. Only when the PCR and sequencing results were consistent were the samples identified as positive for Anaplasma spp. Representative sequences of the newly identified pathogens have been deposited in GenBank. Ethical approval This study was approved by the Animal Ethics Committee of the Lanzhou Veterinary Research Institute, CAAS (No. LVRIAEC2013-010). Use of the field samples was approved by the Committee on Animal Research and Ethics of China. Tick identification The 382 ticks identified herein included the following four species: Hyalomma asiaticum (n = 186, 154 adults from camels and 32 adults from animal sheds), R. sanguineus group (n = 84, 63 adults from camels and 21 adults from vegetation), Dermacentor niveus (n = 60, 42 adults from camels and 18 adults from vegetation), and Hyalomma dromedarii (n = 52, 39 adults and 2 nymphs from camels, and 11 adults from animal sheds) ( Table 2). Ticks morphologically identified as belonging to the R. sanguineus group were also genetically characterized as R. sanguineus group ticks and temporally designated as Rhipicephalus sp. Xinjiang. The nucleotide sequences reported in this article have been deposited in GenBank (12S rDNA: KR809575-KR809580; 16S rDNA: KR809581-KR809588; cox1: KR809589-KR809595). All R. sanguineus group ticks isolates in the present study shared 99.8 %-100 % identity in their 12S rDNA gene sequences, 100 % identity in 16S rDNA and cox1 gene sequences. As compared with sequences available in Genbank, the highest sequence identities were found with sequences labeled as R. turanicus from USA. However, compared with a reference sequences of R. turanicus from Turkmenistan they showed identity of 96.2-96.5 % for 12S gene (GenBank accession number: KF145151), 95.3 % for 16S gene (Gen-Bank accession number: KF145150) and 90.5 % for cox1 gene (GenBank accession number: KF145153). Microscopic examination of blood smears No obvious suspected cases of anaplasmosis were observed based on the signs of fever, anemia, emaciation, slight ataxia, and anorexia in the geographical region we investigated. No microscopic evidence of Anaplasma infections in the blood smears from the Bactrian camels was observed. Discussion To the best of our knowledge, this study is the first to report on the prevalence of Anaplasma infection Bactrian camel in China. The three species-specific primer sets for A. platys (based on the 16S rDNA gene, the groEL gene and the gltA gene) gave consistent PCR results, confirming the occurrence of A. platys in Bactrian camels and ticks. The highest prevalence of A. platys occurred in Rhipicephalus sp. Xinjiang ticks collected from the environment and in Rhipicephalus sp. Xinjiang from Bactrian camels; these camels had the lowest prevalence of A. platys infection. As far as we know, this is the first report of A. platys infection of Bactrian camels worldwide. To date, two other Anaplasma spp., A. marginale and A. phagocytophilum, have been associated with anaplasmosis in dromedaries and llamas [7,[19][20][21][22]. However, A. marginale and A. phagocytophilum were not detected in the Bactrian camels and four species of ticks that we studied in Xinjiang, China. Other Anaplasma spp., such as A. ovis and A. bovis, were also not detected in our samples. Anaplasmosis is reported to be a subclinical disease in Tunisian, Indian, and Arabian onehumped camels [20][21][22][23][24]. In the present study, A. platys infections were detected by PCR but there were no obvious signs of anaplasmosis (fever, progressive anemia, generalized lymph node enlargement, emaciation, slight ataxia and anorexia) in the Bactrian camels. One possible explanation for this finding is that A. platys infections in camels show only minimal or no subclinical signs. Dromedary camels are wildlife in Xinjiang, but samples from these animals were not collected in this study; hence, information on anaplasmosis in dromedary camels is not available. A. platys infects mainly dogs, and cases of canine anaplasmosis have been reported in many countries [13-17, 25, 35]. A. platys infections have been reported in dogs in southern China [25], but the tick species that transmit it have not been determined as yet. Recently, an infection with A. platys was detected in a cat in Brazil [36], and infections with this bacterium have also been detected in goats [26] and red deer in China [28]. DNA from A. platys was also detected in red foxes [37], in a veterinarian with clinical anaplasmosis [38], and in two women from Venezuela [39]. These data indicate that A. platys bacteria have a broad host range. However, the ability of A. platys to act as a zoonotic pathogen has not been established; hence, further studies are necessary to determine its zoonotic potential. Detection of A. platys in the moderate number of the Bactrian camels sampled herein indicates that these animals are exposed to the bacterium and that a desert life cycle for this pathogen is possible for camel populations in Xinjiang, China. Therefore, Bactrian camels might play a role in the transmission of this pathogen, possibly by serving as natural hosts. Additionally, because A. platys infections have been reported previously in dogs, we speculate that, in Xinjiang, A. platys infections in Bactrian camels might be transmitted from ticks fed on naturally infected dogs. In the desert region of Xinjiang, the animals that cohabitate with Bactrian camels include dogs, wolves, foxes and rabbits. Dogs are a natural host of A. platys. However, additional studies will be needed to determine whether wolves, foxes and rabbits can be infected by A. platys. Furthermore, PCR detected DNA from A. platys in Rhipicephalus sp. Xinjiang ticks collected from Bactrian camels and in local vegetation. Several studies have reported the presence of A. platys DNA in R. sanguineus group ticks; hence, this pathogen is supposed to be transmitted by R. sanguineus group ticks [15,16,40]. The finding of A. platys DNA in Rhipicephalus sp. Xinjiang ticks raises important questions regarding their role as vectors of A. platys for camels in Xinjiang, China. Conclusion This is the first report to demonstrate the occurrence of A. platys in Bactrian camels in Xinjiang, China. The moderate prevalence of A. platys we observed in Bactrian camels indicates that they might be a host for this pathogen in desert regions.

v3-fos

2018-04-03T04:57:48.693Z

2015-10-17T00:00:00.000Z

25660526

s2

Delimitation of the Earliness per se D1 (Eps-D1) flowering gene to a subtelomeric chromosomal deletion in bread wheat (Triticum aestivum) Highlight The major flowering time genes cloned to date regulate photoperiod and vernalization response. We identified a deletion containing genes regulating earliness per se, which fine tune flowering in hexaploid wheat. KASP name and primers Sequence TaMOT1-D1 TaMOT1-D1_KASP1_F TaMOT1 Wheat orthologues were assigned to chromosome arms by homology to chromosome arm sorted survey sequence as described in Materials and Methods. Of the forty genes, eleven genes, TaBradi2g14730, TaBradi2g14460, Bradi2g14440, Bradi2g14400, Bradi2g14380, Bradi2g14370, Bradi2g14340, Bradi2g14310, Bradi2g14290 and Bradi2g14210, and TaBradi2g14190 were all shown to be part of the segment that has several genes deleted from Spark, and Cadenza and they are shown in red colour (Table S2). Twelve of the forty genes had no matches with wheat group one chromosomes and these are shown in blue ( Table 1). Out of the twelve genes that do not match group 1 wheat chromosomes, five matched the wheat group three chromosomes and these are Bradi2g14070, Bradi2g13870, Bradi2g13820, Bradi2g13810, and Bradi2g13800 (Table S2). The gene Bradi2g14770 matched group 3 genes but the match on group 1 was on 1DS. The genes Bradi2g14740, Bradi2g14120 and Bradi2g14110, matched homologues on both group 1 and group3 wheat chromosomes (Table S2) and these were not used to define the deletion because amplification from group 3 would not be distinguishable from group1 in the absence of polymorphism that can be used to differentiate the locations. The genes Bradi2g14780, Bradi2g14750, and Bradi2g14440 (Table S2), matched genes on both group1 and group3 chromosomes but none of the three had sequence match with the group 3 D genome chromosome of "Chinese Spring" and hence Bradi2g14440 was used to define the deletion. The gene Bradi2g14730 matched both group1 and group 3 but when the genes were aligned, the group 1 genes were sufficiently different from the group 3 genes hence primers were designed to be specific to 1DL and this gene was also found to be among the deleted genes ( Fig. 2). Eleven genes outside the 1DL deletion matched group 1 chromosomes only and all these were used to define the deletion (bold black Table S2). 60 1AL_TaELF3 CCGGGTGGTCCCGCACACAGCGCGCACCGCGTCAGAGTCGGCGGCGCGCATCTTCCGGTC 60 TuELF3 CCGGGTGGTCCCGCACACAGCGCGCACCGCGTCAGAGTCGGCGGCGCGCATCTTCCGGTC 60 AtELF3 CCGGGTGGTACCGCACACGGCGCGCACCGCGTCGGAGTCGGCAGCGCGCATCTTCCGGTC 60 1DL_TaELF3 CCGGGTGGTACCGCACACGGCGCGCACCGCGTCGGAGTCGGCAGCGCGCATCTTCCGGTC 60 XBarc62 - GATCCAGATGGAGAGGCAGCAGAACGGCCCGTGAccgagcgaccgcatgcggtgcttggc 120 1AL_TaELF3 GATCCAGATGGAGAGGCAGCAGAACGGCCCGTGAccgagcgaccgcatgcagtggttggc 120 TuELF3 GATCCAGATGGAGAGGCAGCAGAACGGCCCGTGAccgagcgaccgcatgcggtggttggc 120 AtELF3 GATCCAGATGGAGAGGCAGCAGAACGGCCCGTGAcagagcgaccgcatgcggtggttggc 120 1DL_TaELF3 GATCCAGATGGAGAGGCAGCAGAACGGCCCGTGAcagagcgaccgcatgcggtggttggc 120 XBarc62 - codon (TGA). The sequence labelled Xbarc62 is the expressed sequence tag (EST) accession BV211449 used to design the XBarc 62 SSR marker (Song et al., 2005). The PCR primers are underlined and labelled primer 1, Primer 2 (designed to be specific to 1DL) while primer 3 and 4 were designed by Song et al., (2005) and amplify from both 1DL and 1AL (Fig. 1). The difference between primer 2 and 3 is that primer 3 is shown by the single underline while primer 2 includes the whole of primer 3 and four additional bases (gaag) shown by double underlining which make primer 2 1DL specific (fig1). The D homeologue is 11bp longer than the A and B homeologues in the region between the two black downward arrows (Fig. 1). The start and end of the 'ATCT' SSR that is scored by the XBac62 marker is shown by the upward arrows and also by the dotted underline and the black horizontal bar flanked by the two upward facing arrows.

v3-fos

2019-03-20T13:09:22.448Z

2015-01-01T00:00:00.000Z

84019048

s2

Characteristics of the Relationship between Natural 15N Abundances in Organic Rice and Soil Abstract The characteristics of the relationship of natural 15N abundances (δ15N values) between rice and soil in organic farming and conventional farming were examined, and the possibility of discriminating organically grown rice from conventionally (non-organically) grown rice using this relationship was explored. Organically grown rice, conventionally grown rice and soil samples were collected from farmers’ fields in Daisen city and Yokote city, Akita prefecture, Japan as well as from the experimental fields of NARO Tohoku Agricultural Research Center located in Daisen from 2007 to 2009. Organic fertilizers and synthetic fertilizers available on the market in Akita prefecture were also collected. The δ15N values of those samples were measured. Regardless of the farming method, the δ15N values of rice reflected those of the soil. The δ15N values of the organic fertilizers available on the market were likely to be higher than those of the soil. Meanwhile the δ15N values of the synthetic fertilizers were negative and lower than those of the soil. The δ15N values of organically grown rice tended to be higher than the regression line obtained from the δ15N values of rice and soil without N source application. The δ15N values of conventionally grown rice tended to be lower than the regression line. These results indicated that the relationship of the δ15N values of rice and soil without an applied N source could aid in discriminating between organic rice and conventional rice. Demand for organic food, including rice (Oryza sativa L.), is growing. Certified organic rice production in Japan increased from 7,777 Mg in 2001 to 10,342 Mg in 2012 (Ministry of Agriculture, Forestry and Fisheries, 2014a). Meanwhile, mislabeled organic rice, which was grown conventionally using synthetic fertilizer, has been traded as organic rice in the marketplace (Ministry of Agriculture, Forestry and Fisheries, 2008). Recently, food frauds appear in various types of food including mislabeled organic rice and have become a major social problem (Ministry of Agriculture, Forestry and Fisheries, 2014b). Because the food frauds endanger the safety and security of food, the development of preventive measures against the food frauds is an important issue. An objective and scientific method to discriminate between organic and conventional (nonorganic) rice needs to be developed to prevent cases of misrepresentation. Methods for residue analysis of pesticides have been developed (Tanizawa et al., 2005;Kobayashi, 2009). Regarding nutrient management regime, natural 15 N abundance (δ 15 N value) has received attention as an indicator to discriminate organically grown crops from conventionally grown crops. The δ 15 N values of organically grown crops without synthetic fertilizer tend to be higher than those of conventionally grown crops with synthetic fertilizer, as observed in some vegetables (Nakano et al., 2002(Nakano et al., , 2003b(Nakano et al., , 2010Bateman et al., 2005Uehara, 2005, 2006a;Yun et al., 2006;Camin et al., 2007Camin et al., , 2011Amor et al., 2008;Rogers, 2008;, fruits (Camin et al., 2011), and tea (Morita et al., 1999;Hayashi et al., 2011). δ 15 N values have also been reported to be higher in organic rice than in conventional rice (Fujita et al., 2003;Suzuki et al., 2009), and a threshold value of 3‰ has been proposed (Fujita et al., 2003). However, the validity of this threshold value has not been fully assessed. Furthermore, the relationship of δ 15 N values between rice grown organically or conventionally and their respective soils has not been investigated. Soil is the major nitrogen (N) source for rice plants which accounts for 60 to 70% of total N taken up by the rice plant (Shoji and Mae, 1984). Then the soil may be one of the influential factors for the δ 15 N value of rice, suggesting the importance of the relationship of the δ 15 N values between rice and soil. Other N sources, such as organic materials and synthetic fertilizer, may also affect the δ 15 N value of rice. Organic farming might leave a distinctive signature in the relationship of δ 15 N values between rice and soil. This study was performed to investigate characteristics of the relationship of δ 15 N values between rice and soil in organic and conventional farming, and to explore the possibility of discriminating organic rice from conventional rice using the relationship. Sample collection Rice and soil samples were collected from the experimental fields in NARO Tohoku Agricultural Research Center (NARO/TARC, 39º29΄ N, 140º30΄ E) located in Daisen city, Akita prefecture, Japan in 2007. In the same years, rice and soil samples were also collected from farmers' fields where organic or conventional farming was conducted in Daisen city (39º27΄ N, 140º29΄ E at the city office) and Yokote city (39º19΄ N, 140º34΄ E at the city office), Akita prefecture, northeast Japan. In organic farming, rice plants were grown with application of only organic fertilizers without synthetic fertilizer. In conventional farming, rice plants were grown with application of synthetic fertilizer. The soil type of the paddy fields in the study area is alluvial soil [Fluvisol and Greysol (FAO, 2006)]. In the fields of NARO/TARC, experiments on the application of rice straw compost, livestock manure compost, organic fertilizer and synthetic fertilizer were performed for multiple studies as listed in Table 1. The rice straw compost was produced at NARO/TARC by piling with occasional turnover in a composting house. Rice straw for composting was gathered from the experimental fields in NARO/TARC. The livestock manure compost was produced by Akita Prefectural Livestock Experiment Station, Daisen, Akita, Japan. Three types of manure were used, cattle manure, swine manure and chicken manure, at a ratio of 6:3:1, respectively. The manure was stirred with a rotary mixer under forced aeration at a composting facility followed by piling in a composting house. The organic fertilizer was commercial pelletized organic fertilizer made from wastes from fish processing, livestock processing and plant processing, namely, fish lees, feather meal, soymeal, rapeseed oil cake and others. The synthetic fertilizer was ammonium sulfate. In the plot where only organic materials, namely rice straw compost, livestock manure compost or pelletized organic fertilizer, was applied, rice plants were organically grown in terms of fertilizer management. Then in the present study, rice from these plots was regarded as organically grown rice. In each plot, rice plants were harvested from the area of approximately 3.3 m 2 at the maturity stage. Topsoil was collected by an auger consisting of a stainless steel tube 3 cm in diameter around the harvesting location. The topsoil thickness was approximately 15 cm. The varieties of rice used were Akitakomachi. In some plots, samples were collected every year (three times), and in other plots, sample collection was performed only once or twice. In the farmers' fields in Daisen and Yokote, four hills of rice plants (about 0.2 m 2 ) were harvested from two RSC, only rice straw compost was applied; LMC, only livestock manure compost was applied; OF, only pelletized organic fertilizer was applied; RSC + SF, both rice straw compost and synthetic fertilizer were applied; LMC + SF, both livestock manure compost and synthetic fertilizer were applied; SF, only synthetic fertilizer was applied; -N, no nitrogen source was applied. Table 2). The rice variety was Akitakomachi. In some fields, sample collection was conducted every year (three times), and in other fields, sample collection was performed only once or twice. Nineteen types of commercial organic fertilizer were collected in 2008. Two types were made from wastes from plant processing, 12 types from wastes from fish, livestock and plant processing, four types from chicken manure, and one made from cattle manure. These organic fertilizers could cover most types of organic fertilizer available on the market in the study area. Four types of synthetic fertilizer, namely, ammonium sulfate and three compound fertilizers were also collected. Two compound fertilizers contained 13% of N, phosphorus (in phosphorus pentoxide equivalent, P 2 O 5 ) and potassium (in potassium oxide equivalent, K 2 O), respectively. Another compound fertilizer contained 15% of N, P 2 O 5 and K 2 O, respectively. These synthetic fertilizers were common types in rice farming. Sample preparation and analysis Rice plants were threshed and hulled. The brown rice (hulled rice) was finely ground with a vibrating mill (TI-100, C.M.T., Saitama, Japan). The soil was air-dried at room temperature, passed through a 2-mm sieve and finely ground with the vibrating mill. Organic fertilizers were oven-dried at 70ºC, then finely ground with the vibrating mill. These samples were put into tin capsules and analyzed for natural 15 N abundance using an isotope-ratio mass spectrometer (IRMS) coupled with an elemental analyzer (DeltaXP, Thermo Fisher Scientific Inc., Waltham, MA, USA). The synthetic fertilizers were dissolved in distilled water. The solution was put into a tin capsule and freeze-dried. They were then analyzed for natural 15 N abundance using the IRMS coupled with an elemental analyzer. Nitrogen isotope data are reported in conventional δ notation in units of per mil (‰) with respect to atmospheric N according to the following equation: δ 15 N sample (‰) = (R sample /R air -1) × 1000, where R sample and R air are 15 N/ 14 N ratios of the measurement sample and the air, respectively. Statistical analysis Regression analysis was conducted between δ 15 N values of rice and soil in the plots where no N source (neither organic material nor synthetic fertilizer) was applied in NARO/TARC using JMP 9.0 (SAS Institute, 2010). Results The δ 15 N values of rice and soil at NARO/TARC are shown in Fig. 1 . RSC, only rice straw compost was applied; LMC, only livestock manure compost was applied; OF, only pelletized organic fertilizer was applied; RSC+SF, both rice straw compost and synthetic fertilizer were applied; LMC + SF, both livestock manure compost and synthetic fertilizer were applied; SF, only synthetic fertilizer was applied; -N, no nitrogen source (neither organic material nor synthetic fertilizer) was applied. **P < 0.01, ***P < 0.001. Discussion The results of the present study suggest that the relationship of the δ 15 N values of rice and soil without an applied N source can aid in discriminating between of organic fertilizers are likely to be higher than those of the Japanese paddy soil; and the δ 15 N values of the synthetic fertilizers would be lower than those of the Japanese paddy soil. A previous study showed that the mean δ 15 N value of the alluvial soil in Japan was 3.2‰ (Yoneyama et al., 1990), which was the dominant type of Japanese paddy soil (Wada, 1984). δ 15 N values of synthetic fertilizers have been reported to be as low as atmospheric N (Shearer et al., 1973;Freyer and Ali, 1974;Black and Waring, 1977;Yoneyama, 1996;. On the other hand, the reported δ 15 N values for organic fertilizers in Japan were high, ranging from 4.2‰ to 20.8‰ (Morita et al., 1999;Tokunaga et al., 2000;Nakano et al., 2003aNakano et al., , 2003bNakano et al., , 2010Nakano and Uehara, 2005, 2006b, 2009Nishida et al., 2007;Hayashi et al., 2011). The regression lines of the δ 15 N values of rice and soil without an applied N source were similar for 3 years (Fig. 1). However, these lines were not fully identical and this implied that the relationship between the δ 15 N values of rice and soil could vary somewhat with cropping year. The results of the present study suggest difficulty in using a particular δ 15 N value for rice as an indicator of organic growth conditions. Fujita et al. (2003) proposed a threshold value of 3‰, which meant rice with a δ 15 N value lower than 3‰ is most likely conventionally grown rice. The results of the present study indicated that this threshold value was incomplete, because there were many conventionally grown rice samples with δ 15 N values higher than 3‰. Further study is needed to assess the validity of this discriminant approach in other areas and to clarify the organic rice and conventional rice. The δ 15 N values of organic fertilizers used at NARO/TARC were higher than the δ 15 N values of plot soils where these organic fertilizers were applied (Figs. 1 and 3). The δ 15 N values of most organic fertilizers available on the market were higher than the δ 15 N values of soils in farmers' fields in Daisen and Yokote (Figs. 2 and 3). Hence, the δ 15 N values of rice grown with these organic fertilizers could be higher than those of rice without an N source application. In contrast, the δ 15 N values of the synthetic fertilizers were negative. These low δ 15 N values of the synthetic fertilizers corresponded to well-known facts that δ 15 N values of the synthetic fertilizers were as low as around atmospheric N, i.e., 0‰ (Shearer et al., 1973;Freyer and Ali, 1974;Black and Waring, 1977;Yoneyama, 1996;. Rice grown with the synthetic fertilizer would be affected by the low δ 15 N value, resulting in lower δ 15 N values than those of the rice grown without an N source application. In the plots where both organic fertilizers and synthetic fertilizers were applied, the δ 15 N values of rice might vary with the application rates of organic fertilizers and synthetic fertilizers, their δ 15 N values, and their N efficiencies for rice plants. The N efficiency of synthetic fertilizers is generally higher than those of organic fertilizers (Nishida et al., 2004;Chalk et al., 2013). Consequently, the influence of the synthetic fertilizer N with a low δ 15 N value was likely to be more apparent than those of organic fertilizers. This discriminant approach is effective when the relative descending order of the δ 15 N values are organic fertilizer, soil and synthetic fertilizer. In many cases, the δ 15 N values cause for annual variation of the relationship between the δ 15 N values of rice and soil. Additionally, other methods to help discriminate organic rice from conventional rice are expected to be developed. A combination of multiple methods will enable a more sensitive discrimination between organic and conventional rice.

v3-fos

2016-05-04T20:20:58.661Z

2015-10-01T00:00:00.000Z

17110608

s2

Prevalence of intestinal and haemoprotozoan parasites of small ruminants in Tamil Nadu, India Aim: The aim of the present study is to assess the prevalence of intestinal and haemoprotozoan parasites of small ruminants (Sheep and Goats) in North Western part of Tamil Nadu, India. Materials and Methods: A total of 630 faecal samples (251-sheep, 379-goats) and 554 blood smears (242-sheep, 312-goats) were examined, for the presence of eggs of intestinal and haemoprotozoan parasites, respectively. The samples were received from the Veterinary college hospital and Veterinary dispensaries in North Western part of Tamil Nadu. Faecal samples were processed by sedimentation technique and examined under low power objective (×10), and blood smears were stained using Giemsa’s technique and examined under oil immersion (×100). Result: The analysis of data on the prevalence of intestinal and haemoprotozoan parasites of sheep and goats in North Western part of Tamil Nadu for the period from 2004 to 2013, showed an overall prevalence of intestinal parasites was found to be 67% and 35% in sheep and goats, respectively, whereas only 11% of sheep and 3% of goats had the haemoprotozoan parasitic infection. Highly, significant difference (p<0.01) in the prevalence of intestinal (χ2=65), and hemoprotozoan (χ2=15.4) parasitism was observed between sheep and goats. Intestinal parasites such as strongyles, Trichuris, Moniezia, amphistome, and coccidia were identified in which the highest prevalence was observed with coccidia, followed by strongyles, Monezia, Trichuris, and least with amphistome in both the sheep and goats. The haemoprotozoan parasites recorded were Theileria and Anaplasma species, of which, Anaplasma spp. being the highest and Theileria spp. the least prevalent in both the sheep and goats. The seasonal prevalence of intestinal parasites showed highest in rainy season, followed by moderate in winter and least with summer in both the sheep and goats, whereas the haemoprotozoan parasites recorded were the highest in summer followed by winter and least with rainy season. Conclusion: The present study suggests that North Western part of Tamil Nadu is highly endemic for intestinal parasites such as coccidia and strongyles and haemoprotozoans such as Anaplasma and Theileria species in small ruminants. Introduction Gastrointestinal (GI) parasitism is one of the major health problems affecting productivity of small ruminants worldwide [1]. GI parasitic infection in sheep and goats are of much economic importance because, small ruminants rearing has become a major source of income especially for the poor marginal farmers in rural areas of India [2,3]. Recurring losses in productivity due to widely prevalent parasitic infection is important and common recurrent problem for small ruminant's production in most parts of the world [4]. Vast studies on the prevalence of GI parasites have been documented from different parts of India [5][6][7][8][9][10] and a few numbers in Tamil Nadu [11]. In addition to GI parasitic infection, small ruminants are also highly susceptible to haemoprotozoan parasites [12]. The tropical environment is the major reason for the development of these parasitic diseases [13]. A proper understanding of the epidemiology of parasitic diseases is a prerequisite for the rational design for the effective preventive and control measures against the dreadful parasitic diseases. Although most of the studies have been carried out with respect to epidemiology of blood and gastrointestinal parasitism in large animals, there is no much study on small ruminants in North Western part of Tamil Nadu, hence, the present study was undertaken to assess the parasitic infection in small ruminants. Ethical approval Samples were collected from clinical cases coming to Veterinary hospital at Veterinary College and Research Institute, Namakkal. So, this particular study does not require ethical approval. Study area Faecal samples and blood smears were received from the Veterinary college hospital and Veterinary dispensaries in and around Namakkal area, which is located in North Western part of Tamil Nadu. The geographical location of the study lies between 11.00 and 11.360 North latitude and 77.280 and 78.300 East longitude and witnessed a temperature range of 35-38°C with maximum of 42°C, relative humidity of 57-55% and rainfall about 1-4. The season in this area can be broadly classified into hot and dry summer from March to June, rainy (monsoon) season from July to October and the winter (mild) season from November to February. Study period The data recorded in the specimen register of Department of Veterinary Parasitology were compiled and analyzed for a period of 10 years from January 2004 to December 2013. Sample size A total of 630 faecal samples (251-sheep, 379-goats) and 554 blood smears (242-sheep, 312goats) were examined, for the presence of eggs of intestinal parasites and haemoprotozoan parasites, respectively. Faecal sample examination Faecal samples submitted to Department of Veterinary Parasitology were processed by sedimentation technique and examined under low power objective (×10). The ova of intestinal parasites were identified based on their morphological features [14]. Blood smear examination Thin blood smears received from the Veterinary College Hospital and Veterinary dispensaries were fixed in methanol (5 min) and stained with Giemsa's stain (30 min) [15] and examined under oil immersion (100 X magnifications), for the presence of blood parasites. The parasites were identified based on their characteristic morphology [16]. Statistical analysis Data were statistically analyzed using Pearson Chi-squared test at p<0.01 regarded as statistically significant [17], and Microsoft Excel was used for presentation of the results. Results The analysis of data on the prevalence of intestinal and haemoprotozoan parasites of sheep and goats in North Western part of Tamil Nadu for the period from 2004 to 2013, showed an overall prevalence of intestinal parasites was found to be 67% and 35% in sheep and goats, respectively, whereas only 11% of sheep and 3% of goats had the haemoprotozoan parasitic infection (Table-1). Highly, significant difference (p<0.01) in the prevalence of intestinal (χ 2 =65) and haemoprotozoan (χ 2 =15.4) parasitism was observed between sheep and goats. Intestinal parasites such as strongyles, Trichuris, Moniezia, amphistome, and coccidia were identified in which the highest prevalence was observed with coccidia, followed by strongyles, Monezia, Trichuris and least with amphistome in both the sheep and goats ( Figures-1 and 2). The haemoprotozoan parasites recorded were Theileria and Anaplasma species, of which, Anaplasma spp. being the highest and Theileria spp. the least prevalent in both the sheep and goats. The seasonal prevalence of intestinal parasites showed highest in rainy season, followed by moderate in winter and least with summer in both the sheep and goats whereas the haemoprotozoan parasites recorded were highest in summer, followed by winter and least with rainy season (Table-2). Highly, significant difference (p<0.01) in the prevalence of intestinal and haemoprotozoan parasitism was also observed among different seasons in sheep and goats. Discussion Among the intestinal parasites observed in this study, coccidian infections were predominant in both the sheep and goats. This result is in conformity with the findings from Namakkal reported the higher incidence of Eimeria spp. in 34.61% of sheep [18] and 26.57% of goats in Greater Kamrup district of Assam [19] and similar findings are also reported from Nigeria, the high prevalence of coccidia was observed in both the lambs and kids [20]. The high prevalence of coccidiosis in small ruminants obtained in this study could be as a result of the management system operated by most small ruminants' owners especially during the rainy season when animals are confined to avoid damage to crops. Consequently, such animals are overcrowded in the pens, which are not properly cleaned regularly. These factors with the high humidity of the rainy season predispose them to high parasitic infections. Next to coccidia, strongyle infection was observed high in both the sheep and goats in this study. The observed high prevalence rate of intestinal nematodes agrees with the findings of earlier investigators [20][21][22]. It was reported that the prevailing climatic conditions especially rainfall and temperature favor the development and survival of parasitic nematode eggs of infective stages [23]. The least infection of amphistome in sheep and goats may be due to the presence of fewer water bodies in the study, which limited the accessibility of infection through snails. An effort that was made to know the influence of seasonal variation on the prevalence of helminths infection was found to be significantly high during monsoon, followed by moderate in winter and least in summer in both the sheep and goats. The present investigation is in conformity with the report from Maiduguri, Nigeria [24] a high prevalence of Haemonchus and Trichostrongylus species were encountered during rainy season and attained peak counts at the same time in both goats (June) and sheep (August). In other study from Tamil Nadu recorded a significantly higher helminthic infection during Northeast monsoon followed by Southwest monsoon, then winter and least infection during the summer season [25]. There was a definite seasonal influence in faecal egg counts of the sheep and goats and this corresponded with the pattern of rainfall. Environmental conditions are usually favorable for the development, survival and translocation of pre-parasitic stages during the rainy season. Therefore, there is a gradual build-up of adult worm populations in grazing animals so that higher prevalence of helminths recorded during the rainy season. Thereafter, sustained during winter and declined during dry season. In contrary to the present finding, higher percentage of parasitic infection was also observed in goats of the subtropical area of J and K during summer followed by winter, spring and lowest in autumn [26]. The difference could be due to the seasonal dynamics influencing ecological and environmental conditions of the study area. The haemoprotozoan parasites recorded in this study showed highest in summer, followed by winter and least with rainy season. This study is in agreement with our previous studies in cattle [27] reported that prevalence of theileriosis was significantly higher during summer, followed by moderate in monsoon and less in winter season. The species of haemoprotozoan parasites reported in this study were similarly observed by Takeet et al. [28] in sheep that Anaplasma ovis is the most prevalent haemoprotozoan parasite in both sheep and goats [29]. A relatively high incidence of the haemoprotozoan parasite could be attributed to the favorable environmental conditions for the survival and transmission dynamics of the arthropod vectors. Considerable seasonal variation with respect to the occurrence of the haemoprotozoan disease may be due to changes in macroclimate that is essential for breeding of ticks. Conclusion The present study suggests that North Western part of Tamil Nadu is highly endemic for coccidia and strongyles and Anaplasma in small ruminants. The result of this study clearly shows that most of the small ruminants kept in the area of study are infected with blood and intestinal parasites. Recommendation The outcome of the present study would help to forecast disease outbreak not only in this region but also applicable to other parts of the country where similar type of climatic condition prevails. Prevention and control programs against these parasites of sheep and goats in endemic areas will improve the production potentials of these animals and the economic well-being of the marginal farmers. There is a need for further investigations using molecular techniques for the accurate identification of the carrier status of haemoprtozoan parasites in small ruminants. Authors' Contributions RV, NR, GP, and PA: Blood smear examination and identification of parasites. RV and GP:Preparation of manuscript and analysis of data. All authors read and approved the final manuscript.

v3-fos

2018-06-02T17:32:46.562Z

2015-01-01T00:00:00.000Z

44188128

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The Effects of Increasing Organic or Inorganic Zinc on Growth Performance and Carcass Characteristics of Finishing Pigs A total of 3,390 pigs (PIC 337 × 1050; initially 63.2 lb), housed in three replicate barns, were used in this study to determine the influence of increasing organic or inorganic Zn sources on growth performance and carcass characteristics of finishing pigs. A total of 126 pens of pigs were allotted to 1 of 7 dietary treatments, with 24 to 27 pigs per pen and 14 to 17 replications per treatment. All diets contained a trace mineral premix that provided 55 ppm of Zn from ZnSO4. The seven experimental treatments were a control diet with no additional zinc included in the diet; the control diet with an additional 25, 50, or 75 ppm of Zn from a zinc AA complex (ZnAA; Availa®-Zn; Zinpro Corporation, Eden Prairie, MN); or the control diet with an additional 25, 50, or 75 ppm of zinc from ZnO. Diets were fed in meal form, for five dietary phases, and formulated to maintain a constant standardized ileal digestible Lys:NE ratio within phase. Overall, a Zn × level interaction (quadratic; P < 0.05) was observed for ADG as pigs fed increasing ZnO had similar ADG, while pigs fed added levels of 25 and 50 ppm ZnAA had decreased performance compared to those fed the highest level of ZnAA. A Zn source × level interaction (quadratic; P < 0.05) was also observed for overall F/G. This was due to pigs fed diets with 25 or 50 ppm Zn from ZnAA having poorer F/G compared to pigs fed similar levels of ZnO. The interaction in ADG also led to a tendency (quadratic; P < 0.10) for a Zn source × level interaction for final BW. No differences were observed for ADFI. For carcass characteristics, a Zn source × level interaction (P < 0.05) was observed for HCW, as pigs fed diets with 25 or 50 ppm Zn from ZnAA had decreased HCW compared with those fed 75 ppm Zn from ZnAA, while increasing ZnO did not influence HCW. Loin depth and percentage lean tended to increase and then decrease (quadratic; P < 0.10) as added ZnAA increased; however, a similar response was not observed for increasing added ZnO. These data suggest that in finishing pigs, supplemental ZnO did not impact growth performance, but low inclusion levels of ZnAA increased F/G and reduced final BW. The Effects of Increasing Organic or Inorganic Zinc on Growth Performance and Carcass Characteristics of Finishing Pigs 1,2 E. W. Stephenson,J. C. Woodworth,M. D. Tokach,J. M. DeRouchey,R. D. Goodband,and S. S. Dritz 3 Summary A total of 3,390 pigs (PIC 337 × 1050; initially 63.2 lb), housed in three replicate barns, were used in this study to determine the influence of increasing organic or inorganic Zn sources on growth performance and carcass characteristics of finishing pigs. A total of 126 pens of pigs were allotted to 1 of 7 dietary treatments, with 24 to 27 pigs per pen and 14 to 17 replications per treatment. All diets contained a trace mineral premix that provided 55 ppm of Zn from ZnSO 4 . The seven experimental treatments were a control diet with no additional zinc included in the diet; the control diet with an additional 25, 50, or 75 ppm of Zn from a zinc AA complex (ZnAA; Availa®-Zn; Zinpro Corporation, Eden Prairie, MN); or the control diet with an additional 25, 50, or 75 ppm of zinc from ZnO. Diets were fed in meal form, for five dietary phases, and formulated to maintain a constant standardized ileal digestible Lys:NE ratio within phase. Overall, a Zn × level interaction (quadratic; P < 0.05) was observed for ADG as pigs fed increasing ZnO had similar ADG, while pigs fed added levels of 25 and 50 ppm ZnAA had decreased performance compared to those fed the highest level of ZnAA. A Zn source × level interaction (quadratic; P < 0.05) was also observed for overall F/G. This was due to pigs fed diets with 25 or 50 ppm Zn from ZnAA having poorer F/G compared to pigs fed similar levels of ZnO. The interaction in ADG also led to a tendency (quadratic; P < 0.10) for a Zn source × level interaction for final BW. No differences were observed for ADFI. For carcass characteristics, a Zn source × level interaction (P < 0.05) was observed for HCW, as pigs fed diets with 25 or 50 ppm Zn from ZnAA had decreased HCW compared with those fed 75 ppm Zn from ZnAA, while increasing ZnO did not influence HCW. Loin depth and percentage lean tended to increase and then decrease (quadratic; P < 0.10) as added ZnAA increased; however, a similar response was not observed for increasing added ZnO. These data suggest that in fin- Introduction The NRC (2012) 4 estimates the dietary Zn requirement for a growing pig weighing from 50 to 270 lb ranges from 50 to 60 ppm. Historically, the trace mineral premix is considered to be the sole source of supplemental Zn for meeting and/or exceeding the NRC requirement estimate, of growing and finishing pigs. Recently, research has reported growth performance benefits from greater concentrations of supplemental Zn when included in diets containing ractopamine (Fry et al., 2013 5 ;Rambo, 2013 6 ). However, Paulk et al. (2015) 7 added either ZnO or an organic Zn source at 75, 150, or 225 ppm of the diet starting at 35 or 41 d before slaughter, in diets containing ractopamine, and observed no benefit from the supplemental Zn nor a difference between Zn sources. It is not clear if supplementing Zn at levels greater than that supplied by the trace mineral premix, and for the entire finishing period, will lead to growth or carcass performance benefits. Previous studies with Zn additions to grow-finish diets were performed in university research settings. However, under a commercial environment, pigs have lower feed intakes and growth rates, due to higher stocking density and other detrimental environmental factors. Therefore, the objective of this study was to determine the influence of increasing Zn, from either an organic or inorganic source, on growth performance and carcass characteristics of grow-finish pigs housed in a commercial facility. Procedures The Kansas State University Institutional Animal Care and Use Committee approved the protocol used in this experiment. The study was conducted in three barns at a commercial research-finishing facility in southwest Minnesota. The three barns were similar in design with completely slatted concrete floors, natural ventilation, and double-curtain sides. Each pen was equipped with a 4-hole stainless steel feeder and bowl waterer for ad libitum access to feed and water. Feed additions to each individual pen were made and recorded by a robotic feeding system (FeedPro; Feedlogic Corp., Wilmar, MN). Animals and Diets A total of 3,390 mixed sex pigs (PIC 337 × 1050; initially 63.2 lb) were used in this study, and housed in three replicate barns. Barn 1 utilized 1,122 pigs for 112 d; barn 2 used 1,159 pigs for 114 d; while barn 3 included 1,109 pigs fed for 120 d. On d 0 within each barn, pens of pigs (24 to 27 pigs per pen) were ranked by average pig weight and randomly assigned within weight blocks to 1 of 7 dietary treatments, resulting in six replicates per barn in a randomized complete block design. All diets contained a trace mineral premix that provided 55 ppm of Zn from ZnSO 4 . The treatments were arranged as a 2 × 3 + 1 factorial with two Zn sources and three levels of Zn added at the expense of corn. The seven experimental treatments were a control diet with no additional Zn included in the diet; the control diet with an additional 25, 50, or 75 ppm of Zn from ZnAA (Availa®-Zn; Zinpro Corporation; Eden Prairie, MN); or the control diet with an additional 25, 50, or 75 ppm of Zn from ZnO. Diets were fed in meal form for five dietary phases (60 to 100, 100 to 135, 135 to 170, 170 to 230, and 230 to 280 lb; Table 1). Ractopamine HCl (Paylean; Elanco Animal Health, Greenfield, IN) was included at 5 ppm in all diets, in the final phase. Diets were formulated to maintain a constant standardized ileal digestible Lys:NE ratio within phase, based on previous research conducted in the same research facility. Due to a malfunction of the robotic feeding system that resulted in interrupted feed delivery, six pens from replicate barn 1 and eight pens from barn 2 were removed from the study. Additionally, two pens were removed from the dataset in barn 3 due to a broken gate, which allowed pigs from two pens to comingle. For pens removed from the data set, data for all phases were eliminated. This resulted in 14 replicates for pigs fed the control diet; 17 replicates per treatment for pigs fed either 25, 50, or 75 ppm Zn from ZnAA; and 17, 14, and 14 replicates for pens of pigs fed either 25, 50, or 75 ppm Zn from ZnO, respectively. Sample Collection Samples from each diet and group were collected for each phase. Samples were then combined for a composite and analyzed for DM, CP, crude fiber, ether extract, ash, ADF, NDF, and Zn (Ward Laboratories, Inc., Kearney, NE; Tables 2, 3, and 4). An additional Zn analysis was also conducted at Cumberland Valley Analytical Services (Hagerstown, MD). Results of Zn analyses from both labs were combined, and the mean analytical values are reported. Pens of pigs were weighed, and feeder measurements recorded approximately every 2 to 3 wk to calculate ADG, ADFI, and F/G. On d 99, 97, and 103, the 4, 3, or 4 heaviest pigs in barns 1, 2 and 3, respectively, were marketed according to standard farm procedures. Prior to marketing, pigs were individually tattooed with a pen ID number to allow for recording of carcass measurements on a pen basis. On d 112, 114, and 120 for barns 1, 2, and 3, respectively, final pen weights were taken, and pigs were transported approximately 58 miles to a commercial packing plant (JBS Swift and Company, Worthington, MN) for processing and carcass data collection. Carcass measurements taken at the plant included HCW, 10 th rib loin depth, backfat, and percentage lean. Percentage carcass yield was also calculated by dividing individual HCW at the plant, by average final live weight of pen at the farm. Fat depth and loin depth were measured with an optical probe inserted between the third and fourth last rib (counting from the ham end of the carcass), at a distance approximately 2.75 in from the dorsal midline. Statistical Analysis The experimental data were analyzed as a randomized incomplete block design using the GLIMMIX procedure of SAS (SAS Institute, Cary, NC) with pen as the experimental unit. Data from barns 1, 2, and 3 were analyzed as a combined data set, and the statistical model included the fixed effect of dietary treatment, and the random effects of barn and block within barn. Studentized residuals were evaluated, and no evidence of departure from normality was observed. Also, data were evaluated for heterogeneity of variance, and no evidence for heterogeneity of variation was found across replicate barn, blocks, or treatments. Orthogonal contrasts were constructed to test the linear and quadratic effects of Zn, Zn source, and Zn source × dose interactions. Backfat, loin depth, and lean percentage were adjusted to a common carcass weight for analysis. Significant differences were recognized at P < 0.05 while a tendency was recorded between P > 0.05 and P ≤ 0.10. Results and Discussion A calculated concentration for Zn in diets was determined by using book values provided by NRC (2012) 4 for ingredients used in this study. The control diets for phase 1, 2, 3, 4, and 5 were calculated to contain 85, 84, 82, 81, and 81 ppm, respectively. Analyzed Zn concentrations for the control diets were slightly greater than the estimated concentrations. Although some variation in analyzed levels of Zn existed, analyzed Zn content still increased with increasing Zn treatments. For the grower period (phases 1 to 3), there were no Zn source × level interactions. A Zn source effect was observed as pigs fed added ZnO had better F/G (P = 0.046), compared to pigs fed ZnAA (Table 5). A Zn level effect was also observed (quadratic; P = 0.020) as pigs fed 25 and 50 ppm added Zn had poorer F/G than pigs fed 75 ppm added Zn. This was driven by a F/G response (quadratic; P = 0.006) that was observed for pigs fed supplemental ZnAA, with pigs being fed 25 and 50 ppm Zn from ZnAA having poorer F/G, compared with pigs fed a diet containing 75 ppm Zn from ZnAA. No treatment differences were observed for ADG, ADFI, or BW during the grower period. Within the finishing period (phases 4 to 5), a Zn source × level interaction was observed (quadratic; P < 0.05) for ADG, as pigs fed increasing ZnO had similar performance; however, pigs fed 25 and 50 ppm Zn from ZnAA had poorer ADG than pigs fed 75 ppm Zn from ZnAA, which had ADG similar to pigs fed the control diet. A tendency (quadratic; P < 0.10) for a Zn source × level interaction was also observed for final BW, as pigs fed increasing ZnO had similar BW; however, pigs fed 25 or 50 ppm Zn from ZnAA weighed less than pigs fed 75 ppm Zn from ZnAA. A tendency for a Zn source × level interaction (quadratic; P < 0.10) was also observed for F/G, as pigs fed increasing levels of ZnAA were observed to have poorer F/G at lower inclusion levels of Zn, in comparison to pigs fed increasing ZnO. A Zn level effect was observed (P = 0.017) for ADFI, as pigs fed diets with 25 or 50 ppm added Zn had decreased feed intake, compared to pigs fed diets with 75 ppm added Zn. An ADFI effect was also observed (quadratic; P = 0.014) for pigs fed ZnAA. Similar to the Zn level effect, a reduction in ADFI was observed for pigs fed diets with 25 and 50 ppm Zn from ZnAA. Swine Day 2015 Overall, Zn source × level interactions (quadratic; P < 0.05) were observed for ADG and F/G. The ADG response was due to pigs fed increasing ZnO having consistent ADG across treatments, while pigs fed 25 or 50 ppm of added Zn from ZnAA had reduced ADG compared to pigs fed 75 ppm Zn from ZnAA. The interaction for F/G was due to pigs fed 25 or 50 ppm Zn from ZnAA having poorer F/G than those fed 75 ppm Zn from ZnAA, while pigs fed supplemental ZnO had similar feed efficiency as Zn concentration increased. No differences were observed for overall ADFI. Similar to overall ADG and final BW, a Zn source × level interaction (quadratic; P < 0.05) was observed for HCW. The response was observed because there were no differences in HCW among ZnO treatments; however, pigs fed 25 or 50 ppm Zn from ZnAA had lower HCW than pigs fed the diet with 75 ppm Zn from ZnAA. Tendencies (quadratic; P < 0.10) for increases in loin depth and percentage lean were also observed for pigs fed increasing ZnAA, with values peaking at 25 and 50 ppm supplemental Zn from ZnAA, respectively. No differences (P > 0.10) were observed for carcass yield and backfat. In conclusion, these data suggest that increasing Zn beyond the level recommended by NRC (2012) 4 did not improve growth performance or carcass composition. Unexpectedly, our study indicates that adding lower concentrations of an organic Zn source could worsen performance compared to a higher level of organic Zn, or similar levels of inorganic Zn. This response does not agree with previously published research, and it is unclear why such a response was observed. More research should be conducted to better understand how low levels of added organic Zn impact performance of pigs housed in a commercial environment.

v3-fos

2016-05-04T20:20:58.661Z

2015-03-14T00:00:00.000Z

2757668

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Highly cadmium tolerant fungi: their tolerance and removal potential Background Soil and effluent of lead and zinc industries contain high concentration of cadmium. The present study was conducted to isolate tolerant fungal strains from cadmium -polluted sites in Zanjan province, Iran. Methods Cadmium tolerance and bioremediation capacity of seven isolates including Aspergilus versicolor, Aspergillus fumigatus, Paecilomyces sp.9, Paecilomyces sp.G, Terichoderma sp, Microsporum sp,Cladosporium sp were determined. Results Minimum inhibitory concentration values among 1,000-4,000 mg lˉ1proved great ability of isolated strains to survive in cadmium polluted environments. The most tolerant fungi, Aspergilus versicolor, showed tolerance index of 0.8 in 100 mg lˉ1 cadmium agar media. Fungal resistance against cadmium is depended directly on strain’s biological function. A. versicolor was found to bioaccumulate over7 mg of cadmium per 1 g of mycelium, followed by 5.878, 5.243, and 5.075, 4.557 by Paecilomyces sp, Aspergilus fumigatus, Microsporum sp and Terichoderma sp, respectively. Conclusion It can be noted that tolerance of the strains appears to be independent from bioaccumulation capacity. Finally, the results indicated that A. versicolor could be a prospective candidate for bioremediation processes. Background Human jump toward industrialization and comfort life is a leap into environmental pollution and consequently deterioration of human health. The environment is polluted by heavy metals from industrial wastewaters during metal processing as well as other pollutant routes. Virtually, any industrial activity using metals has a metal disposal problem [1]. Nature of heavy metals is non-biodegradable and persistent; therefore, environmental compartments (soil and water body) are not able to purify themselves from these toxic pollutants. Heavy metals can be divided into essential metals such as copper, manganese, zinc, and iron, and nonessential metals such as cadmium, lead, mercury, and nickel [2]. Cadmium and lead are included among the major pollutants because of their high toxicity [3][4][5][6]. Cadmium is released to ecosystem by mine tailing, effluents from textile, leather, tannery, electroplating and galvanizing industries, as well as cadmium batteries. Biomagnification of cadmium in nature and migration through drinking water, food and air to human body cause severe health effects like kidney damage, bronchitis and cancer [3]. As industrial development train is not stoppable, struggle with heavy metal pollution requires novel remediation methods. Conventional treatment systems have failures which include insufficient metal sequestration, high costs, high reagents and/or energy requirements, and generation of toxic sludge or other waste products that require disposal. Restoring metals in an efficient and economical procedure has necessitated the use of different options in metal-separating methods. Research shows that bioaccumulation of metals by organisms has been successful to some extent [3]. Bioremediation of heavy metals from aqueous solutions is a relatively new process that has been confirmed as a promising process in the removal of heavy metal pollution. The major advantages of biosorption are its high effectiveness in reducing the heavy metal ions, and the use of inexpensive biosorbents. Biosorption processes are particularly suitable to treat dilute heavy metal wastewater [7]. Biomass obtained from different sources is used in biotreatment and its key feature and potential controlled for the process. Rather than searching thousands of microbial species for particular metal sequestering features, it is beneficial to look for biomasses that are readily available in large quantities to support potential demand. While choosing of the biomaterial for metal sorption, its origin is a major factor to be taken into account [8]. Among biological sources, fungi possess a number of advantages including producing great biomass, rapid growth, availability, and flexibility to rough circumstances. The uptake of metals by fungal biomass appears to involve a combination of two processes: bioaccumulation (i.e. active metabolism-dependent processes, which may include both transport into the cell and partitioning into intracellular components) and biosorption (i.e. the binding of metals to the biomass by processes that do not require metabolic energy) [9]. Fungi are ubiquitous members of subaerial and subsoil environments, and often become a dominant grouping metal-rich or metal-polluted habitats [10]. Recent studies have shown that the strains isolated from contaminated areas have remarkable potential to tolerate such toxic conditions. Microorganisms have been shown to possess ability to survive by adapting or mutating at high concentrations of heavy metals [11,12]. This could play a key role to explore newcomer resistant isolates from pool of biomasses. Exhibiting high tolerances to heavy metals, these isolates were selected for bioremediation studies. Generally, fungi have often been proposed as bioagents for metal recovery processes [13]. This study was carried out to isolate fungi from cadmium-contaminated sites from Zanjan province of Iran for the first time and evaluate their resistance level toward cadmium as well as assessing their bioaccumulation capacity in order to expand knowledge about bioremediation science. Materials The aqueous solutions of cadmium were prepared by diluting Cd (II) standard stock solution (concentration 1000 mg L -1 ) obtained by dissolving Cd (NO 3 ) 2 .4H 2 O in deionized water . Fresh dilutions were prepared for each experiment. Cd (NO 3 ) 2 .4H 2 O was purchased from Merck, Germany. Potato dextrose agar (PDA), malt extract agar (MEA) and potato dextrose broth (PDB) were used as solid and liquid medium, respectively. PDA and MEA medium were purchased from Merck, Germany. PDB medium was purchased from Scharlau, European Union. Deionized water was used in all experiments (TKA Smsrt2Pure, Germany). All laboratory glassware and plastic were soaked in 2 M HNO 3 technical grade, rinsed with distilled water and heat dried 2 h, at 180°C before use. Sampling and experimental sites The research areas characterized in this study were lead and zinc refinery industries as contaminated sites and municipal wastewater treatment plant as control site located in Zanjan province, Iran. These locations were selected based on their cadmium pollution densities. Soil samples were taken from six different spots to a depth of 20 cm from waste dumping areas. Effluent samples of industries were collected from wastewater discharge of plants. Control sample was obtained from aeration tank of municipal wastewater treatment plant. Samples were placed in sterilized glass bottles, transported on ice (4°C), taken to the laboratory and analyzed within 8 h. The wastewater and soil samples were analyzed for total content of Cd. The soil samples were dried at 105°C manually ground and sieved (500 μm pore size). One g of soil samples were digested with 70% HNO 3 (1 M) and 30% H 2 O 2 using microwave digestion (Sineo MDS-10, China). Cadmium concentrations were analyzed by a Varian Atomic Absorption Spectrophotometer (AA 240, Australia) [14]. Isolation of strains Fungal strains were isolated on PDA and MEA by serial dilution method in order to avoid overlapping colonies. Streptomycin (15 mg lˉ1) and chloramphenicol (50 mg lˉ1) were added to mediums after autoclaving at 15 psi for 15 min and 121°C to arrest bacterial growth. The soil samples (1 g) were suspended in 100 ml of sterilized water. The mixture was shaken (200 rpm) for 30 min at room temperature. All samples were diluted up to (10ˉ3). 0.1 ml of different dilutions were spread on Petri plates (diameter 10 cm) containing 20 ml media. Plates were incubated at 28°C in dark condition and monitored every day up to 10 days and each developed colonies were sub-cultured and isolated into fresh PDA plates. Purified isolates were kept on slants at 4°C and recultured every 4 weeks [15]. Screening for Cd-tolerant fungi In order to select Cd-tolerant strains, 100 mg lˉ1Cd stress was added to PDA medium. The pH of the solid growth medium was adjusted to 6 with 1 M sodium hydroxide solutions before autoclaving in all experiments in this study. The small agar plugs with young mycelium from the edge of the stock cultures were cut and transferred to surface of solid medium. Plates were incubated at 28°C for at least 10 days and visually inspected for microbial growth every day. Cadmium-tolerant strains were subjected to resistance studies. Cadmium tolerance index of fungi Five mm disks from 10 day old pure cultures of each fungal isolates were inoculated into PDA (three replicates) supplemented with 200 mg lˉ1 Cd [4]. The inoculated plates were incubated at 28°C for 10 days. In parallel, cultures without cadmium were performed as a control. The radial growth was evaluated from four measurements (in millimeters) that passed through the center of the inoculated portion. The initial diameter of the portion was subtracted from the growth diameter [5]. The mean of perpendicular diameter measurements was recorded for each plate on the day10th. The tolerance index (TI), an indication of the organism response to metal stress was calculated from the growth of strain exposed to the metals divided by the growth in the control plate [16]. The higher the TI, the greater the resistance. Determination of minimum inhibitory concentration Minimum inhibitory concentration (MIC) was defined as the minimum inhibitory concentration of the heavy metal that inhibited visible growth of test fungi [17]. PDA medium was enriched with increasing concentration of Cd (200, 400, 600, 800, 1,000, 2,000, 3,000, and 4,000 mg lˉ1Cd). Plates were inoculated with agar plugs from the edge of the 10 day old growing cultures. If no apparent growth of fungi was observed after ten days on the plates, the metal concentration was considered as the highest metal concentration tolerated by the tested fungus. Identification of selected fungus All the resistant fungal isolates were initially identified by colony characteristics on PDA characterized to the genus level on the basis of macroscopic characteristics (colonial morphology, color and appearance of colony, and shape), microscopic characteristics (septation of mycelium, shape, diameter and texture of conidia) and the help of the Principles and practice of clinical parasitology [18]. Molecular identification of cultures was carried out with some modifications by extracting chromosomal DNA of potential fungus according to previous study [19]. Briefly, a pure culture of the isolated fungal strain was grown in liquid shaking PDB medium at 28°C and 120 rpm for 72 h. The biomass was then harvested and washed with sterile distilled water. Cells were broken up by liquid nitrogen, re-suspended in Hoffman Winston extraction buffer; then, proteins were removed with phenolchloroform and DNA was precipitated by adding pure ethanol. DNA concentrations and A260/A280 ratio were determined with biophotometer (Biophotometer plus, Eppendorf Germany). An A260/A280 ratio of 1.8-2.1 was considered acceptable for PCR (polymerase chain reaction)-based procedures. Part of the 18 s rDNA fragments was amplified using primers 817 F and 1536R [20]. The PCR mixture consisted of 25 μl of 2x PCR Master Mix (Fermentase, USA), 10 pM of each primer, 21 μl water and approximately 2 μg genomic DNA as template in a total volume of 50 μL. The PCR was performed in a Thermo cycler (icycler, USA) using a thermal cyclic condition at 94°C (7 min) followed by 8 cycles at 94°C (1 min), 59.5°C (45 s) and 72°C (1:30 min), then 30 cycles with 94°C (1 min), 56°C (45 s), 72°C (1:30 min) with a final extension at 72°C for 10 min. A sample (5 μL) of the PCR product was analyzed by electrophoresis in 2% agarose gel with 1xTBE buffer. Electrophoresis was performed at 80 V for 40 min. The purified amplicons were sequenced by using an automated sequencer (Bioneer, Korea). The sequences were compared using the BLAST program (http://www. ncbi.nlm.nih.gov/BLAST/) for identification of the isolates [21]. Cadmium bioaccumulation by active fungus To determine the bioaccumulation ability of the 7 fungal isolates, inoculums (six 5 mm disks of mycelia strain) were prepared from 10-day-old pure fungal culture and inoculated into 250 ml Erlenmeyer flask containing 100 ml potato dextrose broth (PDB) plus 100 mg lˉ1 cadmium. Initial concentrations of Cd (II) in each conical flask were checked by AAS before fungal inoculation. pH was adjusted to 6 [22]. Un-inoculated controls (PDB medium with 100 mg lˉ1 of Cd and without any fungal inoculums) were served to detect any possible abiotic Cd (II) reduction brought about by media components. All flasks were incubated at 28°C on a rotary shaker at 120 rpm in dark conditions. After 10 days of incubation (logphase ( [23], flasks containing fungal biomass were harvested and filtered through Whatman No.42 filter paper. Filtered PDB medium was used for determining total Cd concentration. Biomass samples were rinsed three times with distilled water and dried in hot air oven at 80°C until a constant weight (24 h) was achieved. The dried fungal biomass was weighed and defined as dry biomass (g) [24]. The amount of heavy metal uptake (q, mg/g) was calculated by using the following equation [25]: In above equation, q (mg/g) is mg of metal ions uptake per gram biomass; Ci (mgLˉ1) is the initial metal concentration of liquid phase; C f (mgLˉ1) is the final metal concentration; m (g) is the amount of dry biomass; and V (L) is the volume of the medium. Data analysis All experiments were carried out by triplicate sample. Values reported in this paper are the means ± S.D. The difference in TI and uptake capacity of each isolate was studied by one-way ANOVA followed by post-Hoc multiple comparisons by Duncan's method using SPSS16 (USA, I1, Chicago, SPSS Inc.). The difference was considered as significant when P < 0.05. Sites characteristic The range of Cd in earth soils lie between 0.2 and1.1 mg kgˉ1. The highest Cd concentrations (in mg kgˉ1) are reported for soils in the vicinity of metal-processing industries, for example, in Belgium, 1781; in Poland, 270; and in the United States, 1500 [26]. Table 1 demonstrates Cd content of environmental samples. Cd concentrations of soil samples used in this study were 56.90and 488.25 (mg kgˉ1soil) for lead refinery industry and zinc refinery industry respectively. Since dumping waste areas were selected for soil samples, it is not surprising that Cd content was too high. The Cd concentration in effluent of mentioned industries were 50.23and 70.65 (mg lˉ1) respectively, whereas Cd in aeration tank of municipal wastewater treatment plant was 0.23 (mg lˉ1). Clearly these values are 500 times higher than Industry Effluent Guidelines regulated by EPA [27]. These results could be due to the fact that Zanjan province is located close to two major heavy metal processing plants in Iran, as well as neighboring to Mahneshan heavy metal mine. Number of cadmium-resistant isolates and their origin As shown in Table 1, sixteen strains could tolerate 100 mg lˉ1 Cd toxicity. These strains were from different sampling sites. It is known that microorganisms isolated from natural environments contaminated with heavy metals often exhibit tolerance to heavy metal pollutants [28]. Cadmium stress exerted in this study to isolated fungus from municipal wastewater treatment site, made nonfavorable lethal growth medium. Discrepancy in conditions the fungi were adapted to resulted in extinction of isolated fungal population from municipal wastewater. Only one resistant isolate was obtained from low-polluted area. In contrast, the number of resistant isolates from heavy metal industrial sites was significant. It is well known that a longtime exposure of water and sediment to heavy metals can produce considerable modification of their microbial populations, reducing their activity and their number. Generally, pollution of soil and water by heavy metals may lead to a decrease in microbial diversity. This is due to the extinction of species sensitive to the stress imposed, and enhanced growth of other resistant species [29]. Table 2. Results from Table 2 show that soil natural sources trigger microorganisms with higher tolerance ability than aquatic sources. Except Terichoderma sp, there was no strain from industrial effluent which could survive in over 1000 (mg lˉ1) Cd. Evolutionary adaptation to metal-contaminated soils is a well-documented phenomenon, particularly because it is one of the most striking examples of microevolution driven by edaphic factors [30]. Cadmium-resistant assays minimum inhibitory concentration Cadmium concentration in sites and the levels of survival against Cd toxicity were not related to each other, as Terichoderma sp was able to survive up to 2000 (mg lˉ1) Cd toxicity which is 10000 orders of magnitude than Cd concentration in urban wastewater. Other examples are about Paecilomyces sp.9 and Paecilomyces sp.G from lead refinery industry which were able to grow up to 4000 (mg lˉ1) Cd stress, whereas strains from zinc refinery industry with Cd concentration over eight order of magnitude in soil than lead refinery industry only could tolerate up to 2000 and 1000 (mg lˉ1) Cd. It implies that some microorganisms There are some studies supporting the idea that there is a very little difference in metal tolerance between strains from polluted and unpolluted sites [32]. Indeed, presence of metal may act as a fatal toxicity on microorganism population, but does not have any influence on microbial tolerance ability. MIC values of 0.328 mM for filamentous fungi and 1 (mg lˉ1) for Aspergillus, Penicillium and Fusarium were reported [29,33]. In another study no determinations were made for cadmium since the majority of the tested fungi were unable to grow in the presence of this metal [34]. In a study conducted in 2007, MIC values of 5,000, 3,000 and 4,000 (mg lˉ1) Cd were reported for Rhizopus sp., Terichoderma and Aspergillus,respectively. These reported MIC values are relatively similar to the values we observed [31]. Considering previous studies, Paecilomyces sp.G and Paecilomyces sp.9 are newly introduced fungus with remarkable tolerance potential. Tolerance index The reduced tolerance index reflects the inhibitory growth function of heavy metal [35]. To select the most tolerant fungi, the actual resistant potential of fungi must be tested. Tolerance level of fungi can be revealed through both TI and MIC assays. Although it is crucial for scientists to discover a fungus with great ability to survive in extremely high heavy metal concentration, from an environmental engineer view, that fungus is salient and applicable for purification systems which in response to metal toxicity could grow and multiply faster. It implies that the more rapidly the fungi can adapt to polluted environment and develop its colonies, the more beneficial it is for treatment process. The term adaptation speed is an important armor that prompts one fungus more powerful than other fungi with higher MIC property. TI of each fungus in this study (Figure 1) demonstrated different orders of tolerance, as follows: Aspergilus versicolor and Terichoderma sp have shifted up to first level of tolerance with TI of 0.85 and 0.69 respectively, followed by Paecilomyces sp.G, Paecilomyces sp.9 and Aspergillus fumigatus with TI of 0.56, 0.52 and 0.5 respectively which were fairly tolerant fungi and finally at end of the list were Cladosporium sp (0.36) and Microsporum sp (0.35). Aspergilus versicolor from highly polluted zinc industrial site posed minimal reduction in growth (%15). It might be due to the high concentration of cadmium in soil of strain's original environment that induced resistance strategy on fungal metabolism; therefore Aspergilus versicolor was able to adjust rapidly to polluted culture media. Based on the result, Aspergilus versicolor was a highly adaptable fungus in response to cadmium stress. Excessive Cd in soil could trigger the evolution for higher Cd tolerance in Suillus luteus [36]. An exceptional fungus was Terichoderma sp again. Despite the fact that this fungus was from least polluted area with % 31 reductions in growth, it adapted better than five remaining fungi. Trying to find rigid general regulation between the microorganism's origin and fungal resistance to heavy metal is cumbersome effort. The trustworthy theory is: fungal resistance to heavy metal is depended directly on biological function of the strain. The Cd-resistance was found to be independent from the pollution level at the site of origin [29,32,37]. TI results in this study illustrated that Aspergilus versicolor was the most tolerant and Microsporum sp and Cladosporium sp with 65% suppression of mycelia growth were the most sensitive fungus. Results from relative study showed that Cadmium at concentration of 1 mM posed the strongest inhibition toward isolates from the genera Aspergillus, Fusarium, Alternaria and Geotrichum. Only Penicillium isolates expressed tolerance index of 0.8 [34]. In another study, growth of Aspergillus flavus was inhibited by 40% at 1 mM Cd concentration [38]. Copious heterogeneity in TI of the isolates, especially in strains of the same genus (Aspergilus versicolor, Aspergillus fumigatus) and (Paecilomyces sp.9, Paecilomyces sp.G) proved the theory that various genera and also isolates of the same genus do not necessarily have the same heavy metal tolerance [25,31,34,39]. It comes into mind that tolerance skill is not inherited among microorganisms, in other word it is acquired from ecosystem. Various tolerance strategies related to different morphological alteration On exposure to cadmium, morphological changes were observed in all isolated fungi. Several authors have reported the formation of colorful mycelia in the presence of heavy metals on agar media [28]. Other than Aspergilus versicolor and Cladosporium sp genera, decoloration of fungus occurred by increasing the cadmium concentration in medial growth. Pink color changed to white in Paecilomyces sp. and Paecilomyces sp.9 genera (Figure 2). In Terichoderma sp and Aspergillus fumigatus, green color changed to white. Red color appeared in cracked mycelium of Aspergilus versicolor and sides of its colonies in media were polluted with Cd ( Figure 3). Red pigmentation in Aspergilus versicolor was probably due to the binding of Cd to the protein in the cell wall of mycelium. It has been previously suggested that production of pigments in fungal cell and cell free media is accompanied with precipitation of metal ions on the call wall [23]. Consistent with this study, Sills hirsutum produced a yellow-orange pigment both extracellular and in the mycelium, when cultivated in the presence of 0.25 mM or more Cd [40]. Jarosz-Wilkołazka et al. reported that the presence of Cd induced formation of orange-brown pigment which colored the fragile mycelium of Abortiporus biennis, as well as the cell-free culture medium [41]. The appearance of condensed, frizzy mycelium was clearly visible in Aspergillus fumigatus, Cladosporium sp, Microsporom sp, Paecilomyces sp.G, and Paecilomyces sp.9 generas. In the case of a toxic metal-containing domain, aggregated mycelia could produce high local concentrations of extracellular products such as complexing agents, precipitating agents, polysaccharides and pigments with metal-binding abilities [42]. In Terichoderma sp, isolated in this study, aerial mycelium vanished ( Figure 4). On Cd-containing agar most of the mycelium of Paxillus involutes grew submerged rather than on the surface as occurs on Cd-free agar [40]. Possible explanation for these different morphological changes among isolates may be due to the vast detoxification/tolerance mechanisms that each strain applies. The variation in the metal tolerance might be due to the presence of one or more types of tolerance strategies or resistance mechanisms exhibited by different fungi [31]. Bioremoval of cadmium by fungal isolates There has been steady progress in studying the biosorption of heavy metals, resulting in the identification of some biomass types that show very promising uptake of metallic ions [43]. The biosorbents used in heavy metal biosorption are usually obtained after screening the heavy metal resistant/tolerant microorganisms from polluted environments [14]. Adaptation of fungal isolates to heavy metal successfully created organisms with greater efficiency in bioaccumulation [35]. Because the putative specific resistance mechanism(s) could have a potential for biomitigation of contaminated sites, the metal sequestration capacity of the fungus was evaluated [44]. Cadmium bioaccumulation (mg of cadmium uptake per g of dry biomass) of all the tested fungal isolates from liquid media containing 100 mg lˉ1 of Cd is presented in Figure 5. The genera, Aspergilus versicolor, Paecilomyces sp.G, Aspergillus fumigatus, Microsporum sp, Terichoderma sp, Paecilomyces sp.9 and Cladosporium sp showed the bioaccumulation capacities of 7.313, 5.878, 5.243, 5.075, 4.557, 2.849 and 2.631 mg gˉ1 in sequence of decreasing the potential. Surprisingly the best accumulator fungus was the most tolerant strain too. However, for the rest of the fungus this trend was not continued. Except Paecilomyces sp.G that appeared semi accumulator and semi tolerant, Aspergillus fumigatus and Microsporum sp were among the sensitive isolates; however, they were moderately accumulator fungi. These results suggest that removal capacity is not proportional to level of tolerance. Similar observations regarding the lack of correlation between metal tolerance and removal capacity have been reported earlier [25,31,32]. Indeed; uptake capacity was related to the type of tolerance mechanism of fungi. In biotreatment criteria, the resistant mechanism and remediation strategies of microorganism should be distinguished and the parts that these topics have in common be selected. Going through mechanisms of tolerance that finally leads to discovering new biouptake activities (bioaccumulation and biosorption) is essential in this field. A diversity of specific metal accumulation strategies has been known. The physicochemical properties of metals and the physiology of the organism both influence metal uptake [45]. It can be hypothesized that diminished uptake in Cladosporium and Paecilomyces sp.9 generas contributed to cadmium rejection mechanism of tolerance utilized by this fungus. Fungi are able to restrict entry of toxic metal species into cells by reduced metal uptake and/or increased metal efflux [42]. These microorganisms are known as metal excluders [46]. In contrast, higher Cd removal in Aspergilus versicolor may relate to accumulation of cadmium in cell structures. Fungal biomass can act as a metal sink, either by: (1) metal biosorption to biomass (cell walls, pigments and extracellular polysaccharides); or (2) intracellular accumulation and sequestration; or (3) precipitation of metal compounds onto and/or around hyphae [42,47]. Fungi were known to accumulate significant amount of cadmium, for example uptake concentrations of 6.46 mggˉ1by Aspergillus nijer and 16.25 mg gˉ1 by Trichoderma viride have been reported earlier [48]. Pisolithus tinctorius presented maximal uptake of 600 mg kgˉ1 dry weight at 10 mg lˉ1 cadmium concentration [5]. Conclusion The present study declared seven highly tolerant fungi . These fungi exhibited various resistance strategies towards cadmium and they had an ability to sequester cadmium from liquid media. Aspergilus versicolor remarkably differed in detoxification behavior from other isolated fungi in this study. The fungus showed a remarkable potential to actively grow in presence of Cd and reduce cadmium concentration to less toxic levels. Introducing Aspergilus versicolor as scavenger biota is the first step of emerging this fungus in bioremediation science. Efforts are being made to make bioremediation technically/economically feasible; therefore, we should direct our attention to exploit whole potential of microorganism. Understanding metal uptake process genetically, manipulation of cell structure such as autoclaving or drying biomass, and using combo strains are innovative technologies in biotreatment studies.

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Genetically Modified Foods and the Probable Risks on Human Health Changing existing features of living beings or giving new features to them by changing the natural gene sequence through biotechnological methods is called “genetically modified organisms”, in short “GMO”. Nowadays, lots of food consumed is either totally genetically modified food or a type of food including food components produced by gene modification technology. Improving nutritive quality, extracting aminoacids as food additives and enzymes in microorganisms, increasing retention period and organeolepticquality, new planting methods, precocity, resistance against disease, stres, herbicide and viruses, better waste utilization, saving of soil, water and energy, creating new bioprocesses are the probable advantages of genetically modified organisms, whereas changes in food quality, genetic diversity threats, unfair competition between organic suppliers and traditional suppliers, noncompulsory awarness raising in some countries, food industry dominated only by a few big companies, biopiracy and consuming of natural resources by foreigners are among the probable disadvantages of genetically modified foods. Among the hesitations about GMO widely used and consumed all over the world, the most topical issue is the probable health risks caused by GMOs which are consumed as food. Through gene transfer, some features causing allergy and disease can be carried from other organism and as a consequence of this, there may be the risk of finding unexpected biochemical products in transgenic products. As uncertainities about GM foods continue, studies conducted in many countries have revealed that there are many differences among people’s information, attitude and behaviour toward this issue in various countries. Modified food is affected by factors such as education and knowledge level, risk perception, socioeconomic status, media, etc. Besides, level of income and occupation follow them. In the present compilation based on literature, it is aimed to summarize the facts related to GMO. For this reason, the probable risk factors for human health, consumer reaction, the pros and cons of GMOs stated by defining GM generally are explained in the study. With the present study aiming to reveal GM foods and their probable health risks for human, it is concluded that consumers accept the existence of biotechnologic applications but they are not familiar with these products and also consumers have great considerations about GMO produced by genetic modification and they display a negative attitude toward GM products.Consumer should be informed due to all these reasons. Media organs, therefore, have a significant role as the source of information and they will also contribute to raise awareness in society. Introductıon Biotechnology proceeding with an incomprehensive pace is not only a research area but also it enters our life in many fields ranging from health to nutrition and from our goods to pets. Gene-modified organism (GMO) which is the most publisized product of biotechnology and one of the most popular debates in recent years, continues to be the topical issue of today's world [1]. Any organism that is produced by altering its genetic, material features or by adding some new features via biotechnological techniques is called genetically modified organism (GMO). Today, both pros and cons or health risks of GMOs have started to be argued [2,3]. As there is no certain information about the results of using these products, this situation leads to some questions and disscussions focusing on human being, animal, environment and biological diversity. Undoubtedly that the most significant issue about GMOs is the effects of these foods on human health [4]. Food which is closely connected with human health and the most significant factor in terms of adequate and balanced nutrition of world population should be of good quality, abundant, cheap and healthy [5]. Genetically Modified Foods The history of selective breeding, the oldest form of genetic engeneering, dates back to ten thousand years, the times when people were organized as agricultural societies. Naturally, selective breeding intervention was performed among the individuals that are relatives, congener or suitable for gene exchange. Today's technology indicates that we can change genetic material directly with deliberate intervention and that between different kinds we can get hybrids not found in nature [6]. It allows gene transfer amongdifferents kinds of creatures from different worlds which cannot be mixed in nature. A fish gene to a tomato and human genes to a sheep, a pig or to Escherichia coli bacteria which lives in the intestines of all mammals can be transferred [7]. Nowadays, most of the foods consumed is either a genemodified food or a kind of food that includes food components produced by gene modification technology [8]. Genetically modified products are totally identical to their natural samples as of their superior fundamental features such as colour, smell, appearance. All over the world, lots of various products have been regenerated by genetic modification and have obtained patent to be used as humanedible and animal feed from health institutes in many countries. Corn, soya, tomato, potato, rice, wheat are the leading agricultural products derived from GM species. The most popular products are soya, cotton, corn and canola and among these the process is applied mostly to soya. In a study conducted in Turkey, as a consequence of the screening, foodstuffs and local seeds did not contained genetically modified organisms, whereas all imported soy and maize seeds were transgenic [9]. Besides these foods, rice, pumpkin, sunflower, peanut, cassava and papaya are also grown as GM. Studies have still been continuing on banana, raspberry, strawberry, cherry, pineapple, pepper, melon and watermelon. Among grains, only for paddy a gene providing resistance to herbicide is transferred. There hasn't been a transgenic product for crops like wheat or barley which have high economic cost [10]. Another application related to GMOs is improving the nutritional value of crops. In the most known example of this, 4 genes encoding the enzymes for ProvitaminA (β-caroten) are isolated from Narcissus pseudonarcissus plant and Erwiniauredovora bacteria and transferred to rice [11]. As the grains of this transgenic rice are bright yellow-green, it is called as "golden rice" [12]. Ingredients obtained from genetically modified plants; oil, flour, pulp, syrup, flavour, pigments etc. are used in many branches of industry. Soyabean is given resistance to herbicide by transferring SPSPS gene which is not affected by glyphosate. This gene is isolated from 'Agrobacterium', common bacteria found in soil. Hence, GM soyabean produce EPSPS in bacterial form [13]. Mice was fed orally on EPSPS protein with an amount thousand times greater than the amount of acute dose given to human beings and no toxicity was observed and also there were no functional disorders caused by protein allergy [14,15,16]. The gene, isolated from gram-negative Bacillus thuringiensis (Bt) bacteria and encoding Bt endotoxin which provides a natural resistance against some pesticides like bioinsectiside, is transferred to corn in order to give resistance to an insect called corn stem borer. When planted, this transgenic corn produces toxin and prevents the insect living on itself [12,16,17]. Genetic modification studies are also conducted on animals. For animals, studies aim especially to give resistance against diseases, to control their growth or to change wool quality and milk component. As a result of these studies, fish is the only animal economically produced [18]. Studies of the genes transfer which increase growth and give resistance against cold weather conditions are stil being conducted on 20 kinds of fish particularly on carp, catfish, salmon, and tilefish [19]. In 1993, milk production is increased in milkcows which are given rBGH (recombinant bovine growth hormone) approved by US FDA. GM animals can be used for the production of lactose-free milk, low-fat milk, low-fat meat, meat with special protein, special-quality meat and milk [20,21]. Besides herbal and animal products, GMO technology is also used for microorganisms. Genetically modified microorganisms (bacteria, fungi and mold) are used as enzyme and food additives in various productions such as bread, beer, cheese, grapery products etc. in order to obtain aminoacid [12]. In fermented meat, milk and other food industries, lactic acid bacteria is commonly used as starter culture for fermentation of foods such as cheese, yoghurt, kephir, sausage and alike. These cultures give the food typespesific flavour and smell by enabling maturation of the fermented food [22,23]. Probable pros and cons of genetically modified organisms are summarized in Table 1 [24]. Effects of the Genetically Modified Foods on Human Health In a report published in 2005, World Health Organization (WHO) stated that GMOs have potential risks for human health and growth and have no history of being consumed as a secure food and also that replacing a new gene to the genome of the food modified can cause undesirable developmental and physiological effects [25]. Despite all their benefits, transgenic products have some risks. As these products have some genes that aren't found in the ones grow in nature, they bring some significant hesitation with them. Foreign genes can create unpredictable changes by both increasing nutritional value of some foods and decreasing the value of some other foods [20]. Antibiotic Resistance Through gene transfer, some features causing allergy and disease can be carried from other organism and as a consequence, there may be the risk of finding unexpected biochemical products in transgenic products. Antibiotic resistant genes are used as markers during gene transfer. Antibiotic resistance emerges due to the transmission of antibiotic resistant genes to the animal or human systems [26]. If antibiotic resistant genes are transmitted to pathogen microorganisms, this makes it difficult to control any bacterial infections [27,28]. The lateral transfer of antibiotic resistance to the bacteria in animal or human systems can cause many health risks [29]. Bovine spongiform encephalopathy (known as mad-cow disease), a topical issue in the USA and many European countries, was occurred in cattle in 1985 and people who consumed the meat contaminated by the brain and spinal cord of infected carcasses got sick after a 10-year incubation period and died in about two months. It is known that the infectious agent is transmitted to cattle by giving them Scrapie-infected sheep carcass meal rendered in concentrate cattle fattening feed as a cheap protein resource [30]. The water consumed by the animal, the meat and milk of which we benefit from, is medicated regularly by antibiotics [31]. In a report published by World Health Organisation (WHO), it is stated that germs develop immunity to antibiotics as a result of wrong antibiotic use and antibiotics used for humans don't have any effect on health. Moreover, studies have indicated that the antibiotics transmitted to humans kill non-resistant bacteria but cause strong and harmful bacteria to multiply in human body and they also decrease the effect of antibiotics given during an infection [31,32]. Allergy Allergy parts of donor genes can be transmitted to recepient plant or animal by genetic modification of genetic modification plants. Besides, in lots of genetically modified foods, donor microorganisms which have unknown allergenic potential can be used. Genes and new gene combinations transferred from non-food resources can cause allegic reaction or make the existing allergic reaction worse [33]. Sometimes genetically modified products which can cause health problems canbe mixed into natural products during production period. One of the significiant examples of this is "StarLink" incident in USA.StarLink is the trading name of a genetically modified corn developed by Aventis Crop Science Company. This corn includes Cry9C protein and it is defined as "a potential alergenic" by US Environmental Protection Agency (EPA) so in 1998 EPA stated that StarLink can only be used as animal feed or in industry but it cannot be used as human food [34,35]. According to Ozdogan and Ekmen (2002) soyabean given Brazi-nut gene to enhance nutritional value caused severe allergic reaction and was prohibited in 1994 [36]. Products which have "2S" gene transferred to soyabean from Brazilnut were recalled from the market as they caused allergy [37]. In their study, Gupta et al. have reported that in cotton farm and factory workers who pick and load cotton producing Bt toxin, some upper respiratory tract, eye and skin related allergies was observed [38]. Toxicity Herbal products by genetic modification can form some unexpected mutations and these mutations can develop new and high level toxins in foods [36]. There have also been many research results indicating that toxic materials in transgenic plant residue penetrate into soil and water.It is observed that endotoxins produced by some genes can stay in soil for 33 weeks. Therefore toxins are likely to join in the food chain of other organisms [39].GMOs have insect killer genes with genes transmitted because of terminator technology. As the toxic material is produced continously in the plants with these genes, they are called "pesticideproducing plants" [40]. Cumulating of these toxins in the tissue causes significant risks. The type of a well-known substance named L-tryptophan which was undergone genetic engineering process caused the death of 37 Americans and a blood disease (Eosinophilia Myalgia Syndrome "EMS")in 5000 people in 1989 [41]. Studies have shown that fermentation process carried out by Bacillus spp. microorganism modified by recombinant DNA technology [20]. In 1967, a potato defined as Lenapo potato designed with a high level dry-matter rate and used in chips production was released to the market in the US. Two years later this potato was recalled by US Agriculture Ministry as it forms solanine toxin [42]. In laboratory tests, it was determined that the potatoes genetically modified by using a viral promoter Cauliflower Mosaic Virus (CaMv) known with snowdrop flower DNA, are poisonous for mammals. These potatoes whose chemical composition is quite different from natural potatoes damaged the vital organs and immunity system of the mice. The most dangerous part is a gastric viral infection occurred in the mice and there is strong evidence that the reason of the disorder is a viral promoter named CaMy. This promoter is widely used in GMOs [41]. According to Ince et al., (2013), toxicity, allergenicity and antibiotic resistance genes of Cry protein in Bt corn can be laterally transferredto the microflora of human digestive system, which threatens human health [43]. Cancer It is stated by some researchers that GMOs can directly or indirectly have carcinogenic effects. Especially, herbicide resistant chemicals like bromoxynil and glufonsinate used for cotton, soya, corn and rape are known to directly cause cancer [44].Hormone and hormone-like substances affect human health in a negative way. Stilbene group among synthetic anabolic used for cattle fattening has some carcinogenic effects [45]. Genetically modified bovine growth hormone (rBGH) is injected to cattle in order to enchance milk production. rBGH causes an increase of insulin-like growth factor (IGF-I) in milk. IGF-I causes both normal and cancer cells to grow. The increase of IGF-I level in blood leads to lymphoma, breast, ovarian and uterine, prostate, colon, lung and pancreatic cancer [46]. When animals consume feed including high levels of Dioxin (naturally found and a side product produced by various industrial process like rendering), dioxin cumulates into fatstoring tissues of animals. Consuming the animal products contaminated by high level dioxin have long term toxic and carcinogenic effects on human [47]. Consumer Attitude toward GM Products and Effective Factors Altough uncertanities about GM foods continue, studies have shown that there are many differences among people's information, attitude and behaviour toward this issue in various countries [48,49]. When the studies conducted are examined, it can be concluded that the attitude toward genetically modified food is affected by factors such as education and knowledge level, risk perception, socioeconomic status, media, etc. Besides, level of income and occupation follow them. In present compilation, literature related to high-level factors will be emphasized. Education and knowledge level is observed to be highly effective in thoughts about GM products. In a study by Christopher et al., (2008) 40% of consumers nation-wide stated that they wouldn't consume GMOs even if they are beneficial to health and environment. Also consumers in England, French, Spain and Italy told that they wouldn't consume any GMO product [50]. In a study conducted abroad, it is observed that consumer attitude twowards GMO is "positive" in US and "negative" in other countries. Contrary to findings in Turkey and other countries, nearly half of the US people support agricultural biotechnologies, regard genetically modified foods as "improved" and also taking the advantages of these products into consideration, they think that widespread use of these products can reduce pesticide use and improve nutrition quality [51,52,53]. In their study conducted in European countries, Pardo et al., (2002) reported that 20% of the study group stated that they have enough knowledge about GMO and among the countries, Greeks was the lowest knowledgable country with a rate of 5% while Holland was the highest with a rate of 36% [54]. Magnusson et al., (2002) in their study conducted among consumers in Switzerland, observed that well-educated, young male participants have a more positive attitude toward GM foods [55]. In a study to determine university students' knowledge level and thoughts about transgenic products (GMO), Temelli and Kurt (2011) have concluded that students don't have enough knowledge about transgenic products and they approach GMO products with caution and they also need to be enlightened about these products [56]. Tekedere et al., (2011) reported that 40(36%) of the students think that they have enough knowledge about GMO whereas 71(64%) of them think that their knowledge about GMO is inadequate. This finding is students' own perception and indicates thay they believe they have knowledge about GMO but it doesn't academically mean that their knowledge is adequate [57]. Lan's (2006) studies have shown that Chinese people don't have enough knowledge about GM foods. 73.2% of the participants stated that GM foods are hormone-injected foods and 72.1% said that people who eat GM products would have cancer [48]. In their study, Adana et al., (2014) (research the knowledge and opinions of nursing and midwifery students about genetically modified organisms. 74.3% of the students think GM products are harmful for human health, 74.9% think GM products are potential carcinogenic. It is observed that nursing and midwifery students don't have enough knowledge about this issue [59]. Cankaya and Iscen (2015) have examined the knowledge level and opinions of prospective science and technology teachers about GMOs. According to the findings of the study, nearly all of the prospective teachers think GMOs are harmful and they have a negative attitude toward using GM products [60]. In a study to determine the knowledge, attitude and behaviour of medicine students toward genetically modified organisms, 71.9% of participants (n=308) stated that they weren't informed enough about genetically modified foods [61]. In a study conducted to determine mothers' attitude toward genetically modified organisms, it is observed that mothers have a high risk perception against GMOs but a low level of knowledge about them. Most of the mothers (96%) stated that GM products have harmful effects on human health and 82.6% of them told that they don't want to use them for child nutrition and they won't buy these products [62]. Risk perception toward GMO technology changes among people. The result of a study by Bilen and Ozel (2012) indicated that most of the students (87%) had an awareness regarding genetically modified (GM) products. The results also revealed that students think that GM products have risks. Overall, the students thought that GM products should be used for the benefit of technology and people. Based on the findings from this study, some implications for biotechnology education are made [63]. In Kocak et al.,(2010) studies 56.9% of the participants stated that genetically modified food production is risky for all living beings in nature. It ıs observed that risk perception of research group is high [61]. Ergin et al., (2008) found this value as 65.3% in their study [64]. In Italy and America, consumers' risk perceptions toward genetically modified foods are quite similar, yet Italian customers are found to be more sensitive against probable risks than Americans are. As they care more about the effects of genetically modified foods on human health, they display a tendency to consume them less [65]. It is found in a study by Lan that risk approach and negative attitude toward GM foods increase by the increase of socioeconomic level of the country. They stated that underdeveloped countries support GMO technology more [48]. Contrary to this, Magnusson et al. reported in their study that Americans or Canadians are more positive toward GMO than European people are (55). In a study with university students, Ozdemir and Duman(2010) have found that for nearly more than half of the participants (about 54%) GMO use is unfavourable for human health, for 24% GMOs are damaging for human and environment and for 73% GMOs are insecure [53]. According to the results of the study by Ozmert and Yaman et al., (2011), consumers don't have enough knowledge about GMO products and their knowledge level increases as their level of education increases. Consumers have a negative attitude toward products of this technology in general [66]. Algan Ozkok's study (2015) about consumer opinions on GM foods has revealed that most of the women have a negative attitude toward GMOs. 73.2% (n=957) of participants think that GM products are hormonal foods, 72.1% (n=969) think that consumers of GM foods can develop cancer, 71.5% (n=962) think that GM foods have allergenic effcts on human body and 66.1% (n=967) think that GM products are toxic for human body [67]. Accordind to the result of the study by Kaya et al., (2010) university students regard genetically modified products as potential risk and they have a negative opinion on production, cunsumption, ecological effects and the use of these roducts but they have a positive opinion on genetic applications [68]. According to their study named Urban Consumer's Attitude toward Genetically Modified Organisms and Food in Turkey, Kaya et al., (2014) stated that the negative perception is due to the considerations related to consumers' health, environment and biological diversity and natural resources. In Turkey, urban consumers think that GM foods which are thought to be unhealthy, carcinogenic and allergenic can cause biological pollution, intoxication, infertility, organ damage and antibiotic resistance when consumed or produced [69]. Another effective factor related to thoughts about GM products is media. Tekedere et al., (2011) reported that 70(63.1%) of the students stated that they heard GMO term first through Radio/Television. 19(17.1%) of them stated that they heard about it in classes at school. Acquaintances (10.8%), newspapers and magazines (6.3%), family (1.8%) and internet (0.9%) follow them respectively. When radio, television, newspaper, magazine and internet are considered as media, it is revealed that 78(70.3%) of the participants heard about GMO by means of media [57]. Maekawa and Macer (2004) found by their research that the rate of those who state that they heard genetically modified organism first on TV/radio was 67.8% and of those who heard it from this survey was 8.4%. In a study on students, Maekawa and Macer observed that concerns and debates about GMO started in 1990s in Japon and that the people heard genetically modified organisms from daily newspapers, television or articles [70]. Huang et al., (2006) in their study, stated that the rate of hearing about GM food is 67% in China, 77% in the USA, 77-92% in European countries. In the study, it is also stated that the reason of the low rate in China can be due to fewer debates on GMO in local media [71]. In a study conducted to determine the knowledge, attitude and behaviour of women living in housing estate toward genetically modified organism, it is observed that most of the participants (91.9%) gained their knowledge from TV, newspaper, magazine etc. This situation can be caused by the fact that GMO have become more popular lately and participants follow the media closely [67]. Kocak et al., (2010) reported in their study that the rate of participants who heard about genetically modified organism first through Radio/TV is 67.8% and of those who heard it from this survey was 8.4% [61]. In a study conducted with pre-school staff, it is detected that the knoeledge about hormone, additives and genetically modified foods is limited and gathered from TV. The reason why the knowledge levels are different is that the source of information is mostly media, internet or environment. In the study by Lu (2006), Chinese people's lack of information about GM foods is found to be the result of limited broadcasting or publishing in media [72]. In the study, it is also stated that the students heard GMO term first from media although they don't prefer media as a source of education. Therefore useful strategies should be developed to use effectively the power of media providing informal knowledge. Among them, distance education, video conference, education with TV are some options. This power of media can be benefited for GMO issue to develop social consciousness. Conclusion Among the hesitations about GMO widely used and consumed all over the world, the most topical issue is the probable health risks caused by GMOs which are consumed as food. While genetically modified foods continue to emerge, debates about the effects of them on environment and health become a growing problem. Generally, experts of the issue support studies to continue but consumers react against them as they don't have enough knowledge. In this respect, GM products should be released to the market after enough scientific studies are conducted and should be checked in legal framework and also consumers should be informed about the issue. By this study aiming to reveal the probable risks of genetically modified foods for human health, it is observed that consumers accept the existence of biotechnologic applications but they are not familiar enough with these products. Also the study indicated that consumers have great considerations about GMO produced by genetic modification and they display a negative attitude toward GM products. GMO technologies have the danger of causing harmful and unpredictable adverse effects that cannot be reversed or rectified. Consumer should be informed due to all these reasons. Media organs, therefore, have a significant role as the source of information and they will also contribute to raise awareness in society.

v3-fos

2019-04-24T13:07:23.986Z

2015-01-01T00:00:00.000Z

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s2

Reconstruction Support for the Farmland Struck by Tsunami Reconstruction support of the disaster-stricken areas in the city of Soma, Fukushima Prefecture, was started in May 2011. Sediment transported from the sea by the tsunami was from 5 to 10 cm thick on surface of the paddy fields. The tsunami sediment was mixed with the original soil of the paddy fields, and mole drains were formed to improve water drainage toward the lower layer. Subsequently, rainwater alone was used for salt removal. However, the pyrite in the soil had gradually oxidized until the pH dropped to 3.8, so converter slag was applied to neutralize the sulfuric acid. In May 2012, rice was transplanted into paddies from which the salt had been removed. On September, 10.7 t brown rice was harvested. The yield of brown rice harvested per hectare was 6.3 t, about 20 % higher than the amount before the disasters. Fig. 4.1 Map of Soma City affected by the tsunami .2 Paddy fi elds struck by tsunami adjacent to Matsukawaura Lagoon among these trees were cars, tractors, and washed-up fi shing boats. The local farmers were devastated, bemoaning the fact that it would take years before the paddy fi elds could be restored to their original state. Under the huge amount of debris was a thick layer of accumulated tsunami sediment containing vast quantities of salt transported from the sea by the massive tsunami. Classifi cation of Post-tsunami Farmlands Based on the First Field Survey Based on a fi eld survey undertaken in May, we classifi ed the farmlands into the following three types. 1. Paddy fi elds adjacent to the coast that were still fl ooded because of land subsidence and that contained a large amount of debris 2. Paddy fi elds that had been affected by the tsunami, but had started to dry up by the survey in May, were located several kilometers from the coastline and contained little debris 3. Sites such as greenhouses and upland fi elds that were affected by the tsunami but contained no debris Properties of Tsunami Sediment Accumulated on the Surface of Tsunami-Hit Farmlands (a) Soil chemical properties of tsunami sediment The soil chemical properties of the tsunami sediment collected during the fi eld survey from May 1 to 3, 2011, are shown in Table 4.1 . The sodium chloride content estimated from the exchangeable sodium content reached 2.9-5.7 %, with a high electrical conductivity (EC) of 12-24 mS/cm serving as an indication of the salt concentration. The sodium chloride content in seawater is approximately 3 %, but tsunami sediment with almost twice this amount of salt was observed (Table 4.1 ). However, high levels of salt content were limited to the clay layer on the surface of the tsunami sediment, with the salt content in the sand layer underneath showing a sharp progressive decline. The cation-exchange capacity (CEC) in the clay layer of the tsunami sediment was about 30 mEq/100 g, which tended to be higher than in the soil of either paddy fi elds or greenhouses. In addition, the soils contained a large amount of exchangeable magnesium and potassium. Because the tsunami sediment contains substances transported from the seabed, we were concerned about the possibility of acidifi cation similar to that found in soil on reclaimed land from the sea. We therefore measured the total sulfur content and Table 4.2 , the total sulfur contents of the tsunami sediments were about 1 % and pH (H 2 O 2 ) was 2.2-2.6. As soil with a pH (H 2 O 2 ) of 3 or less is defi ned as an acid sulfate soil, the sediment transported by the tsunami was assessed to be a potential source of acid sulfate soil. (b) Harmful elements contained in the tsunami sediment We analyzed the levels of harmful elements such as cadmium and arsenic in the tsunami sediment and the soil layers underneath collected from the survey sites already mentioned (Table 4.3 ). The cadmium content in the tsunami sediment ranged from 0.32 to 0.65 mg/kg, with an average value of 0.39 mg/kg. The content in the soil layers underneath ranged from 0.28 to 0.39 mg/kg, with an average value of 0.29 mg/kg. Although the cadmium level in the sediment was higher than that of the underlying soil, it was equivalent to the median value of 0.39 mg/kg in farmland soil across the country. The amount of arsenic in the tsunami sediment and soil was less than 10 mg/kg for both, which was the same as or lower than the background value in the soil. The amounts of zinc, copper, lead, nickel, and chrome in the tsunami sediment were almost the same as those in the soil. Mix Soil Layers Without Removing Tsunami Sediment The tsunami sediment contained as much as 10-20 mS/cm of salt and a large amount of water-soluble boron (B) at 20 mg/kg, both of which substantially hinder the growth of vegetation. Meanwhile, the cation-exchange capacity (CEC) was higher than that of the plow layer, with large amounts of exchangeable magnesium and potassium serving as soil nutrients. Harmful elements such as cadmium and arsenic were a particular concern, but their levels were not found to be higher than those of the plow layer. We knew that the salt and boron in the soil could be leached out with water, while soil acidifi cation caused by the oxidation of pyrite could be corrected by applying lime material. We therefore decided to remove salt by mixing the sediment with the original soil and without removing the soil introduced by the tsunami. Use Converter Slag as Lime Material to Remove Salt The chloride ions in the salt are anions that exist as water-soluble ions not adsorbed by the soil colloids, but the sodium ions exist as water-soluble sodium in the form of counterions to chloride and exchangeable sodium adsorbed by the soil colloids. Therefore, when lime material is applied and mixed thoroughly with the soil, a cation-exchange reaction occurs between the calcium ions in the slag and the exchangeable sodium, allowing the exchangeable sodium to be converted to watersoluble sodium. For this reason, converter slag generated as a by-product during the steel manufacturing process in steelworks is used as lime material. The raw materials of converter slag such as iron ore, coal, and limestone contain no harmful components; the main component is calcium silicate, whereas the secondary components include micronutrients such as iron, manganese, and boron, in addition to free lime (quicklime) and magnesium. As a result, even if the pH (H 2 O) is raised to about 7.5 or higher by using converter slag in the soil, it is unlikely to cause a defi ciency of micronutrients in the crops. In addition, converter slag acts more slowly than calcite or dolomite in mitigating soil acidifi cation, and can therefore also be used to counter soil acidifi cation caused by the oxidation of pyrite in the tsunami sediment. Just in Time In the disaster zone affected by the tsunami, local farmers naturally assumed that they would have to remove the tsunami sediment, known as hedoro or "sludge," that had accumulated on the surface of the soil in strawberry greenhouses ( Fig. 4.3 ). In fact, sludge removal work was scheduled to take place a few days after we fi rst visited a strawberry farm that we were assisting. However, we managed to persuade the farmer that there was no need to remove the tsunami sediment. Instead, the fi rst thing we did was to expose the soil to the rain by ripping off the plastic rooftops of the greenhouses and the mulching on ridges, which had been untouched since March 11. After we had fi nished analyzing the soil to confi rm that there were no problems associated with harmful elements, the farmers themselves mixed the tsunami sediment with the original soil in June (Fig. 4.4 ). There Is No Better Salt-Remover than Rain Instead of removing the tsunami sediment at the strawberry farm, we mixed it with the original soil on June 16. At that time, 10 t/ha of converter slag was applied as a lime material to accelerate salt removal ( Fig. 4.5 ). The electric conductivity (EC) in the fi rst 10 cm of the surface layer decreased from 0.64 mS/cm in July to 0.35 mS/ cm in August, but the EC in the next 40-cm layer from 10 to 50 cm decreased only to the 1.5 mS/cm level. In addition, the amount of exchangeable sodium remained at 139 mg/100 g, with a high sodium percentage of 16.6 %. We therefore decided that strawberry planting should be delayed until the following year, with sorgo (a kind of green manure) planted in the meantime as a means of preparing the soil for the replanting of strawberries in September 2012. The sorgo planted on September 6, 2011 grew to almost the height of a human, reaching 1.5 m after a month (Fig. 4.6 ), and the yield of sorgo reached approximately 40 t/ha. After crushing with a hammer knife mower, the sorgo was plowed into the soil with a rotary plow. As shown in Fig. 4.7 , the monthly rainfall in Soma is generally highest from June to October, and 844 mm of rain fell during this period in 2011. As a consequence, the amount of salt removed using rainwater alone was greater than expected. There is no better salt remover than rain. A Discriminating Approach to Restart of Strawberry Cultivation by Soil Although we managed to suffi ciently remove salt and adjust pH in the plow layer by September 2011, a high concentration of salt still remained in the lower layer, at a depth of about 40 cm, as shown in Fig. 4.8 . If the roofs of the greenhouses were replaced and strawberries planted at this stage, it was possible that the salt in the lower layer might rise into the plow layer. As strawberries are highly susceptible to the effects of salt, we pushed the strawberry planting back by a year to fall 2012. In the meantime, we planted cash crops such as spinach, turnips, and sugar snap peas instead (Fig. 4.9 ). By September 2012, the salt concentration in the lower layer had also dropped, allowing strawberry seedlings to be replanted. These subsequently grew well and harvesting started in January 2013, making these the fi rst soil-cultivated strawberries to be harvested in this strawberry-producing area, which had been severely damaged by the tsunami (Fig. 4.10 ). Rejuvenating Green Manure: Also Used in Hachinohe, Aomori Prefecture After the disasters, we were contacted by Koutaro Kimura, whom we had met at an agricultural seminar in the city of Hachinohe, Aomori Prefecture. He told us that his strawberry farm had been damaged by the tsunami (Fig. 4.11 ). As the Kimura farm was near the coast, the tsunami sediment was mainly sand in a layer 30 cm thick. We therefore advised him to mix this tsunami sand with the original soil using a power shovel and to apply converter slag. The basic salt removal method was the same as that employed in the strawberry farm in Soma. After salt removal by the rain, Aoba millet was planted as green manure instead of sorgo, as millet is more resistant to the yamase , or cold Pacifi c winds descending from the mountains into Hachinohe, which is situated further north than Soma. The millet planted on June 20 grew well and reached a height of 80 cm by July 20 (Fig. 4.12 ). However, as shown in Fig. 4.13 , growth was observed to be lacking in certain sections of the millet. We analyzed soil samples taken from these spots, and found residual salt in them; this residue resulted from inconsistencies in mixing the layers of soil using a power shovel, in contrast to Soma where the soil was mixed with a rotary plow. Consequently, this discovery demonstrates the effi cacy of planting green manure to confi rm the removal of salt. To a farmer, such variations in growth are easier to understand than chemical analysis of the soil, and by concentrating on mixing the soil in areas that do not grow well, more uniform salt removal can be achieved. Thus, in salt-damaged farmlands, green manure serves a secondary purpose of confi rming salt removal. Taking on the Challenge of Planting "Soma Revival Rice" Figure 4.2 shows the scene we came upon when we fi rst visited Soma on May 1, 2011. The devastation was beyond our imagination and we thought it would probably take years to restore the land to its original state. Nonetheless, all the debris in the paddy fi elds had in fact been removed by September, and weeds such as barnyard grass could be seen growing here and there, even though much of the paddy surface had dried up like a tortoise shell and been reduced to a barren desert (Fig. 4.14 ). The tortoise shell effect was caused by sediment transported from the sea by the tsunami that had dried and cracked in a layer about 10 cm thick ( Fig. 4.14 , top right). Although no vegetation could be seen at all in the areas where tsunami sediment had accumulated, we noticed that weeds were fl ourishing in a line around the paddies (Fig. 4.15 ). Upon close examination, these lines were found to be caterpillar tracks made by machines as they entered the paddies to remove debris such as pine trees. Comparison of the soil between the caterpillar tracks and the areas without vegetation revealed that the EC and available boron level were signifi cantly lower in the caterpillar tracks areas (Table 4.4 ). This discovery served to validate the Soil Acidifi cation Within the Expected Range As shown in Fig. 4.16 , tsunami sediment was mixed with the original soil in 60 ares of paddy fi elds on September 27, 2011, and mole drains were formed to improve water drainage toward the lower layer. Subsequently, rainwater alone was used for salt removal. As a result, the EC, which serves as a guide for rice planting, dropped to 0.7 mS/cm by April 3, 2012 (232 days after soil mixing). However, the pyrite in the soil had gradually oxidized until the pH (H 2 O) dropped to 3.8, so converter slag was applied on April 23 (Fig. 4.17 ) to neutralize the sulfuric acid. Fields of Golden Rice Plants After a 2-Year Hiatus In May 2012, rice of the variety known as Hitomebore was transplanted in three plots of 1.7 ha of paddies whose salt had been removed by the aforementioned method. No fertilizer was applied as we believed that the alkaline effect resulting from the rise in pH value caused by the application of converter slag would cause an increase in mineralization of organic nitrogen. The rice seedlings grew extremely well after transplanting, with no inconsistencies in their growth. On September 26, a total of 10.7 t brown rice was harvested from the 1.7 ha of paddies ( Fig. 4.18 ). The yield of brown rice harvested per hectare was 6.3 t, about 20 % higher than the amount before the disasters. Thus, we had managed to return the rice paddies to fi elds of gold after a 2-year hiatus. The Highest Safety Standards for "Soma Revival Rice" The city of Soma is located about 40 km from the Fukushima Daiichi nuclear power station. A radioactive cesium level of about 750 Bq/kg was detected in soil taken from paddies that produced this fi rst crop of the rice that we were to call "Soma Revival Rice." However, not only was there no trace of radiation detected in the brown rice, but even the stems and leaves, which absorb radiocesium more easily than the grains, showed no trace of radiation at all. As cesium and potassium belong to the homologous elements, when a large quantity of potassium (exchangeable potassium of 25 mg/100 g or more) exists in the soil, it has been known to suppress the absorption of cesium by the rice. As the paddy soil mixed with tsunami sediment contained about 60 mg/100 g of exchangeable potassium, the process of mixing in the tsunami sediment had ended up suppressing radioactive cesium absorption by the rice. The levels of harmful elements such as cadmium and arsenic measured in the rice itself were 0.01 mg/kg for cadmium and 0.04 mg/kg for arsenic (Table 4.5 ). In the case of cadmium, this was signifi cantly lower than the 0.4 mg/kg that is the nationally stipulated limit in Japan. Although there is no limit set for arsenic, the level measured was only one-quarter of the 0.16 mg/kg average for rice produced in Japan. On the other hand, when levels of "healthy" minerals were compared with levels in the Standard Tables of Food Composition in Japan, the rice was found to contain higher levels of magnesium, phosphorous, and potassium (Table 4.6 ). The Project Launches In total, 1,100 ha of farmland were affected by the tsunami in Soma, and only 140 ha were being farmed again by March 2013, the bulk of this being areas that suffered relatively minor damage. Of the farmland that was devastated by large volumes of debris and accumulated tsunami sediment, only a fraction had been restored and just 1.7 ha were the paddies we had rehabilitated using the Soma Method. We aimed, therefore, to restart farming on a larger scale by expanding the use of the Soma Method from an isolated 1.7-ha point on the map to a larger 50-ha area in 2013. We therefore submitted a proposal and obtained the consent of the Soma City authority and JA Soma (the local agricultural cooperative) to launch the Soma Project. Subsequently, a representative of all three parties involved in the project requested the CEO of Japan's largest steelmaker, Nippon Steel & Sumitomo Metal Corporation, to help by supplying 450 t of converter slag at no cost, which the CEO promptly granted. The Project Gets Under Way On March 8, 2013, press conferences to announce the converter slag donation by Nippon Steel & Sumitomo Metal Corporation were held in Tokyo (Tekko Kaikan) and Soma's City Hall (Fig. 4.19 ). Open Access This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. In April, the Soma City Hall prepared a warehouse in Soma Port to accept a large amount of converter slag transported by 10-t trailers. At around the same time, the farmers started cultivating rice seedlings. Beginning April 19, a large tractor fi tted with three lime sowers was used by the farmers to start scattering converter slag and mixing it into the soil (Fig. 4.20 ). Subsequently, the farmers fl ooded the paddy fi elds and wet tilled the land. Rice planting was then started in all the paddy fi elds from May onward (Fig. 4.21 ). In some paddies where the EC had been high, the farmers passed irrigation water through after the rice was planted. Thanks to these measures, the rice fl ourished without any problems, and as of August 30, gold-tinged ears of rice have started to droop down, ready to be harvested from mid-September onward (Fig. 4.22 ).

v3-fos

2019-04-07T13:03:43.397Z

2015-12-15T00:00:00.000Z

56244428

s2

Effect of Salinity and Temperature on Seed Germination and Seed Vigor Index of Chicory (chichoriumintynus L.), Cumin (CuminiumCyminium L.) and Fennel (Foeniculum Vulgare) To evaluate the effect of different levels of salinity and temperature on germination and seed vigor of three medicinal plants of Chicory (Cichoriumintybus L.), Cumin (Cuminumcyminum L.) and Fennel (Foeniculumvulgare) three separated experiments were carried out by factorial experiment based on complete randomized block design with three replications in 1393 at the laboratory of Agricultural University of Payam Noor, Meshkinshahr center for each plant. Factors were salinity with six levels (0. 2, 4, 6, 8 and 10 ds/m for all plants) and temperature with three levels (22, 25 and 28 oC for Chicory; 27, 29 and 31 oC for Cumin; 17, 19 and 21 oC for Fennel). Seedling tissue water content was affected by salinity levels in Cumin and Fennel. Salinity reduced seedling length, shoot length, root length, germination percentage, germination rate, seedling dry and fresh weight and seed vigorindex. In all traits that affected by salinity, the highest rate was observed in the control. Seed vigor index, germination percentage, dry weight of seedling, fresh weight of seedling in Chicory, seedling length and root length in Cumin and seed vigor in Fennel were significantly affected by temperature regime. In general it can be stated that Fennel, Cumin and Chicory, are the most sensitive to salinity respectively by 74, 72 and 47% reduction in seed vigor index at the highest levels of salinity in compared to the control level. Effect of Salinity and Temperature on Seed Germination and Seed Vigor Index of Chicory (chichoriumintynus L.), Cumin (CuminiumCyminium L.) and Fennel (Foeniculum Vulgare) Introduction Soil salinity is one of the major factors of soil degradation that limit crop production. Many social and economic problems are caused by salinity that affects the growth, productivity and distribution of plants (Bojovic et al. 2010). Salinity inhibition of plant growth is the result of osmotic and ionic effects and the different plant species have developed different mechanisms to cope with these effects (Munns, 2002). High rate of seedling mortality, delayed germination, stunted growth and reduced yield are some of the most common effects of salted soils. Research in relation to the effect of salinity has mostly been carried out on agricultural, forage and fuel wood species. However, little work has been done for exploring the possibility of using salted soil for the cultivation of medicinal plants (Zahir and Hussainn, 2010, Asimi andSahu, 2013, Jahanshir, 2015). Reduction in osmotic potential in salt stressed plant can be a result of inorganic ion (Na + , Cland K + ) and complete organic solute (soluble carbohydrates, amino acids, proline, betaines, etc.) accumulations (Hasegawa et al. 2000). Some plants will tolerate high levels of salinity while others can tolerate little or no salinity. Salinity acts like drought on plants, preventing roots from performing their osmotic activity where water and nutrients move from an area of high concentration. Therefore, because of the salt levels in the soil, water and nutrients cannot move into the plant roots. Germination is a critical part of plant life histories. The ability of their seeds to germinate at high salt concentration in the soil is therefore of crucial importance for the survival and perpetuation of these species. Recently, medicinal plants have received much attention in several fields such as agro alimentary, perfumes, pharmaceutical industries and natural cosmetic products. Although, secondary metabolites in the medicinal and aromatic plants were fundamentally produced by genetic processing but, their biosynthesis is strongly influenced by environmental factors. A biotic environmental stresses, especially salinity has the most effect on medicinal plants. The different results were dedicated from the effect of salinity stress on the quantitative and qualitative parameters. For instance, it was found that, increasing of salinity stress decreased almost all of growth parameters. Liopa-Tsakalidi (2010) reported that enhancing salinity treatments lead to growth reduction. It also reduces germination amounts and seedling weight. Overall, salinity through enhancement of osmotic pressure leads reduction of water absorbance and metabolically and physiological processes will be under its effect. So it causes more delay in germination beginning following by enhancing seed germination duration. Therefore seedling growth can be limited by decreased mobilization of seed reserve and/ or the conversion efficiency of mobilized seed reserves. Salinity is one of the environmental factors having a critical influence on seed germination, seed physiology and plant establishment (Hashemi and Akhavan Armaki, 2015). Salinity affects imbibitions, germination and radical elongation. It reduces substrate water potential, thereby restricting water and nutrient uptake by plants (Safarnezhad and Hamidi, 2008). Salinity may also cause ionic imbalance and toxicity. Because substrate salinity fluctuates through the growing season, a plant may be exposed to different salinity levels, at various stages of development, with potentially significant consequences on population dynamics (Hosseini and Rezvani Moghadam, 2006). Present study was conducted to see the possible effects of NaCl salinity and different temperature on the germination and seedling growth of three species of medicinal plants. The findings might help enhancing the medicinal wealth of Iran by utilizing the otherwise non-productive saline habitats. Material and Methods In order to evaluate of the effect of different levels of salinity and temperature on germination and seed vigor of three medicinal plants of Chicory (Cichoriumintybus L.), Cumin (Cuminumcyminum L.) and Fennel (Foeniculumvulgare) three separated experiments were carried out by factorial experiment based on complete randomized block design with three replications in 1393 at the laboratory of Agricultural University of Payam Noor, Meshkinshahr center for each plant. Factors were salinity with six levels (0. 2, 4, 6, 8 and 10 ds/m for all plants) and temperature with three levels (22, 25 and 28 o C for Chicory; 27, 29 and 31 o C for Cumin; 17, 19 and 21 o C for Fennel). Distilled water was used for the control (zero) and sodium chloride salt solutions for specific electrical conductivity. Salinity levels were created by solving the amount of salt (NaCl) (Manufactured by Merck Company with a purity of 95%) in distilled water. Each experimental unit consists of one sterile Petridish containing 100 seeds. Seed sterilization was performed by using 70% alcohol (10 seconds), 10% sodium hypochlorite (60 seconds) and fungicides (60 seconds). After treatment, the Petri dishes were placed in Germinator with relative humidity of 80%, temperature 25°C (16 hours) and 15°C (8 hours). The duration of the test was 12 days. On the last day of test 10 seedlings randomly selected from each Petridish and the average length of root and shoot were determined. Then the 10 seedlings were placed to measure root dry weight and shot dry weight for 24 hours at 70°C in electric oven. The total number of germinated seeds in a Petridish was recorded until the twelfth day of germination. Germination Rate (GR), Germination vigor index and water content of seedling tissue were determined by Equation 1, 2 and 3 respectively (Segatoleslami, 2010). Data were subjected to analysis by the SAS software and graphs were drawn using Excel program. Mean comparison of traits showed that in the case of Chicory with increasing salinity, seedling length, shoot length and root length were significantly decrease ( Table 2). Results showed that in Chicory, maximum of seedling length, shoot length and root length (33.09, 20.54 and 13.13 mm, respectively) was observed at control level of salinity and minimum of them (21.86, 13.50 and 8.7 mm) were obtained at highest level of salinity ( Table 2). In case of Cumin, mean comparison of traits showed that with increasing salinity, seedling length, shoot length and root length, were significantly decrease ( Table 2). Also results showed that maximum of seedling length (229.2 mm), shoot length (149.2) and root length (77.1 mm) were obtained at control level of salinity ( Table 2). In case of Fennel, maximum of seedling length (97.98 mm), shoot length (57.05 mm) and root length (40.92 mm) and minimum of them (53.68, 57.05 and 22.32 mm respectively), were obtained at control Seedling Length, Shoot Length and Root Length In case of Chicory analysis of variance showed a significant effect of salinity on seedling length, shoot length and root length. Temperature levels were not significantly effected on these treats (Table 1). Salinity and temperature were significantly effect on seedling length, shoot length and root length in Cumin (Table 1). Also seedling length and root length were significantly affected by salinity and temperature levels in Fennel (Table 1). who also reported significant decline in growth at 10 ds/m and higher salinity levels. Our results are in agreement with Fallahi et al. (2008) in which they showed that with increasing in salinity levels, the seedling length had decreased and minimum and maximum length of seedling were observed for control and 300 Mm NaCl treatments, respectively. Fresh and Dry Weight of Seedling Results showed that salinity and temperature were significantly effect on fresh and dry weight of seedling in Chicory (Table 1). In case of Cumin and Fennel, fresh and dry weight of seedling was significantly affected by salinity. However temperature levels were no significantly effect on those traits in Cumin and Fennel (Table 1). With increasing salinity in the Chicory, fresh and dry weights were decreased. Maximum of fresh and dry weight (1.69 and 0.87 mg, respectively) and minimum of them (1.26 and 21.86 mg, respectively) was obtained at control levels and highest level of salinity (10 ds/m), respectively (Table 3). In other hand at the highest levels of salinity fresh and dry weights were reduced by 25 percent compared to control (Table 3). In the case of effect of temperature on fresh and dry weight of seedling in Chicory, result indicated that maximum of fresh and dry weight of seedling was obtained jointly at 25 and 29 O C condition. Minimum of those traits were observed at 22 O C condition (Table 3). In case of Cumin and Fennel maximum of fresh weight (0.14 and 3.7 mg, respectively) and minimum of them (0.083 and 3.78 mg, respectively) were obtained at control levels and highest level of salinity (10 ds/m), respectively. Similar results were observed for dry weight of seedling ( Table 2) Water Content of SeedlingTissue Water content of seedling tissue, play important role in various physiological processes. In the present study analysis of variance showed a significant effect of salinity on water content of seedling tissue of Cumin and Fennel (Table 1). Water content of seedling tissue of Chicory was not significantly affected by salinity. Also temperature levels were not effect this trait in all three studied plants (Table 1). Maximum water content of seedling tissue in Cumin (52.71%) and Fennel (52.54%) was obtained in the control and the lowest level of this trait (44.84 and 46.01%, respectively) was obtained at highest level of salinity (Tables 2 and 4). Shadded and Zaidan (1989) Germination Percentage and Germination Rate Results showed that salinity were significantly effect on germination percentage and germination rate in Chicory, Cumin and Fennel (Table 1). Germination percentage was affected by temperature regimes in Chicory and Fennel. However temperature levels were no significantly effect on germination rate in all three studied plants (Table 1). Germination percentage and germination rate in all three plants was significantly decreased with increasing salinity levels (Figures 1 and 2). The highest decrease in germination percentage was observed in Cumin with about 70 percent. The lowest decrease in germination percentage (38%) was found in Chicory. 53% reduction in germination percentage was found in Fennel. Chicory, Cumin and Fennel germination rate significantly decreased with increasing salinity levels ( Figure 2). Increasing salinity Seed Vigor Index In all three studied plant analysis of variance showed a significant effect of salinity on seed vigor index. Temperature levels were not significantly effect on this treat (Table 1). Results indicated that with increasing salinity seed vigor was significantly decreased (Figure 3). With increasing salinity to 10 ds/m, seed vigor was decrease to 47.4, 72.26 and 74.4 percent in Chicory, Cumin and Fennel, respectively. Since the seed vigor index is obtained by multiplying of seedling length and germination percent, reduction in seed vigor was expected. Seed vigor decrease with increasing salinity also been reported by Segatoleslami (2010 (Tables 3 and 4). Conclusions According to the results, all germination characteristics except the shoot length in Fennel, root shoot ratio in all three studied plant and water content of seedling tissue in Chicory significantly declined with increasing salinity. Seed vigor index, germination percentage, dry weight of seedling, fresh weight of seedling in Chicory, seedling length and root length in Cumin and seed vigor in Fennel were significantly affected by temperature regime. Finally it can be stated that Fennel, Cumin and Chicory, respectively by 74, 72 and 47% reduction in seed vigor index at the highest levels of salinity in compared to the control level are the most sensitive to salinity. Consequently, based on the results, the published studies and regarding high medicinal values of this genus and their sensitivity to salinity stress, we recommend that the genus is cultivated in environments that plants are not in expose to salinity. (Segatoleslami, 2010). References In case of effect of temperature levels on germination percentage in Chicory and Fennel results showed that maximum of this trait (46.59 and 52.80, respectively) was obtained at 25 C in Chicory and 19 C in Fennel (Tables 3 and 4).

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2015-07-10T00:00:00.000Z

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Microbiological and Chemical Quality of Packaged Sachet Water and Household Stored Drinking Water in Freetown, Sierra Leone Packaged drinking water (PW) sold in bottles and plastic bags/sachets is widely consumed in low- and middle-income countries (LMICs), and many urban users in sub-Saharan Africa (SSA) rely on packaged sachet water (PSW) as their primary source of water for consumption. However, few rigorous studies have investigated PSW quality in SSA, and none have compared PSW to stored household water for consumption (HWC). A clearer understanding of PSW quality in the context of alternative sources is needed to inform policy and regulation. As elsewhere in SSA, PSW is widely consumed in Sierra Leone, but government oversight is nearly nonexistent. This study examined the microbiological and chemical quality of a representative sample of PSW products in Freetown, Sierra Leone at packaged water manufacturing facilities (PWMFs) and at points of sale (POSs). Samples of HWC were also analyzed for comparison. The study did not find evidence of serious chemical contamination among the parameters studied. However, 19% of 45 PSW products sampled at the PWMF contained detectable Escherichia coli (EC), although only two samples exceeded 10 CFU/100 mL. Concentrations of total coliforms (TC) in PSW (but not EC) increased along the supply chain. Samples of HWC from 60 households in Freetown were significantly more likely to contain EC and TC than PSW at the point of production (p<0.01), and had significantly higher concentrations of both bacterial indicators (p<0.01). These results highlight the need for additional PSW regulation and surveillance, while demonstrating the need to prioritize the safety of HWC. At present, PSW may be the least unsafe option for many households. Introduction UV disinfection being the three most commonly employed treatment methods, and with many systems incorporating multiple treatment steps (Table A in S1 File, [9]). Sierra Leone's Ministry of Health and Sanitation (MoHS), as well as non-governmental organizations (NGOs) working in the country, are concerned about potential health risks from PSW products of unknown quality [9]. Sierra Leone has legislation regulating packaged water, and the Sierra Leone Standards Bureau (SLSB) established national standards for packaged water quality in 2010; however, the regulatory framework is uncoordinated, with unclear roles among government agencies, and standards are not effectively enforced (idem). Implementing and enforcing regulations is complicated by the transient nature of small PSW producers, who can easily relocate and rebrand to avoid regulatory sanctions. Basic data on PSW quality in SL could inform government efforts to refine and enforce packaged water regulations, and to implement monitoring and surveillance efforts (idem). However, government agencies in SL lack such data, nor have prior studies systematically examined PSW in that country. In this work, we assessed the quality of PSW manufactured and sold in Freetown, SL, (where most of SL's PSW producers are concentrated). To place these findings in context, we simultaneously assessed the quality of household water used for consumption (HWC) in a representative sample of households. To our knowledge, this is one of the first studies to assess and compare the chemical and microbiological quality of PSW products and HWC in a sub-Saharan African context, and the first such study to incorporate random sampling, appropriate analytical methods, and quality assurance/quality control (QA/ QC) procedures [21]. This work provides insights into the safety of an increasingly important source of water for consumption in SL and West Africa, and will inform policymakers seeking to regulate and monitor PSW in SL and elsewhere, while ensuring progressive realization of access to safe water. Sampling procedure Packaged water manufacturing facilities (PWMFs) within SL were enumerated using records from Sierra Leone's Packaged Water Taskforce-an inter-ministerial body working to coordinate the regulation of the industry. Local markets and retail shops were also visited to identify additional PW brands not included in the database, and the contact information printed on the packaging of these brands was used to update the PWMF database. The majority of identified PWMFs (83/117) were located in Freetown (Table B in S1 File). Further sampling activities focused on producers in the capital, as this provided a convenient sample that included the majority of the country's PW industry. A random sample of 49 Freetown PWMFs was selected; Since the PW industry in Freetown (and this sample) are dominated by PSW producers, PWMFs primarily producing bottled water (n = 5) were excluded from the analysis, leaving 44 PWMFs that primarily or exclusively produced sachets. Retail shops and street vendors in Freetown (25 each) were also selected for point-of-sale (POS) sample collection: Freetown was divided into quadrants, and a main thoroughfare with a high density of PW shops and vendors was identified in each. Enumerators walked down each thoroughfare from one end to the other, sampling each third store on alternating sides of the street. A total of 25 stores were sampled in this manner. The same approach was then used to sample 25 street vendors on thoroughfares with a high density of such vendors. At each selected POS, enumerators recorded GPS coordinates, identified all brands of packaged water for sale, and sampled one brand at random (by drawing numbers out of a bag). POS samples comprising BW (n = 4) were excluded, leaving 46 PSW samples. A random sample of 60 households was also enumerated. Briefly, Freetown was divided into 10 sections of approximately equal area, and a main street was identified within each. Enumerators walked down the street, sampling each third house on alternating sides of the street until six households were surveyed in each section, for a total of 60. At each household, respondents were asked to provide a glass of the water that they used for drinking. A brief questionnaire was also administered, and self-reported data were collected on drinking water collection and storage practices, the source of the collected water sample (e.g. piped supply, dug well, or protected spring), as well as the storage conditions (e.g. stored vs. continuous in-house supply, method of serving if stored), and the type of household water treatment method used, if any (S2 File). Oral informed consent was obtained from all household survey participants and documented by enumerator's written certification that consent was obtained. The decision to use oral consent was based on the rationale that because literacy rates in Sierra Leone are low [22], asking respondents to sign a written consent form would be unethical, since many potential respondents would be unable to understand it. Furthermore, it was anticipated that restricting the study to the small minority of respondents able to read and understand a written consent form would bias the sample towards those with higher levels of education and wealth, and would consequently invalidate any comparison of the health risks associated with packaged water and water from other sources, particularly for Freetown's more vulnerable populations. This work was reviewed and received a formal waiver from the Institutional Review Board at The University of North Carolina at Chapel Hill (Study # 13-2165). The IRB found the full study exempt, including the use of oral consent; no additional separate waiver was given for the use of oral consent or any other specific aspect of the study. No identifiable personal information was collected from any participants. Sample collection PSW samples were collected at three stages in the manufacturing and distribution chain (Table C in S1 File): 1) Raw influent water (Raw samples); and 2) Finished PSW products (PWMF samples) were sampled at each PWMF; 3) PSW products were sampled at the POS (POS samples). Each raw water sample comprised three 300-mL sample aliquots collected in either sterile 500-mL glass bottles or sterile 710-mL Whirl-pak bags (Nasco, Fort Atkinson, WI). These aliquots included one unamended aliquot for all chemical analyses except nitrate and arsenic, one acidified aliquot (3 mL x 1 M HCl per 300-mL aliquot) for nitrate and arsenic analyses, and one unamended aliquot for microbiological analysis. Finished PW samples were placed in secondary plastic bags, except for aliquots to be sampled for arsenic and nitrate, which were preserved by acidification, as above. All POS samples were purchased prior to collection and analysis. The exterior surfaces of sachets were sampled at the POS ("exterior sample") as follows: one enumerator held the PSW product with sterile gloves while a second enumerator rinsed the exterior with 300 mL of sterile buffer. The rinsate was collected in sterile Whirl-pak bags. A glass of household drinking water was received from each respondent by an enumerator and poured into sterile Whirl-Pak bag. QA/QC Quality assurance/quality control procedures included the daily collection of field blanks and duplicate samples (at least 10% of all samples, each). All field and lab blanks were free from detectable E. coli and TC; 62% and 62% of E. coli and TC duplicates had relative deviations of <25%, respectively; 94% and 69% of E. coli and TC duplicates had absolute deviations of < = 5 colony-forming units (CFUs)/100mL, respectively. Upon collection, all samples were immediately placed on ice and transported to the laboratory in coolers at 1-4°C (verified using WarmMark temperature indicators, Shockwatch, Dallas, TX). Samples were refrigerated at 4°C upon arrival at the laboratory, and analyzed within 12 hours of collection (longer holding times were due to logistical constraints, although most samples were analyzed within 6 hours). Previous research shows that such holding times have little effect on measured E. coli concentrations at holding temperatures below 10°C, although analysis should always be conducted as rapidly as possible [23]. The SLSB laboratory in Freetown, Sierra Leone carried out all chemical and microbiological analyses. Laboratory analyses Physico-chemical parameters measured were: pH, conductivity, and free chlorine (measured on-site during sample collection); turbidity, total hardness, fluoride, iron, manganese, nitrate, and arsenic (measured at SLSB). Nitrate and arsenic analyses were performed using acidified aliquots (3 mL x 1 N HCl per 300-mL aliquot), while all other analyses were performed using non-acidified aliquots. These methods are summarized in Table D (in S1 File). Sachets for microbiological analysis were aseptically opened in the SLSB laboratory using ethanol-cleaned scissors. Samples were analyzed for E. coli and total coliforms (TC) via membrane filtration [24]. A 100-mL sample was filtered through a 0.45 μm membrane (Millipore, Billerica, MA). The filters were then placed on RAPID' E. coli 2 Agar (Bio-Rad, Hercules, CA) plates and incubated at 35°C for 24 hours. Data analysis Results were analyzed using Stata/IC 13 (Statacorp, College Station, TX). Wilcoxon signedrank tests were used to compare log concentrations of E. coli and TC between raw water and finished PSW samples from PWMFs and to compare PSW from the POS and exterior samples. Wilcoxon rank-sum (Mann-Whitney) tests were used to compare log concentrations of E. coli and TC between samples from various sampling points. McNemar's test (for paired data) and Fisher's exact test (for unpaired data) were used to compare the proportion of positive samples from various sampling points and conditions. Samples producing colonies that were too numerous to count (TNTC) were reported as the highest countable concentration of E. coli or TC (250 CFU/100 mL). For the purpose of calculating log EC and TC concentrations, values of 0.5 CFU/100 ml were substituted for those samples in which no CFUs were detected. Adjusted geometric mean concentrations were calculated using these adjustments. While PSW samples at the POS were collected in duplicate, the results of the first replicate POS sample were always used for hypothesis-testing and quantitative comparisons (sensitivity analysis found no significant differences in the results between the two replicates). Statistical significance for all hypothesis tests was assessed at the 5% and 1% levels. 3.1.2 Manufacturing facility. Most finished PSW samples at the PWMF were free from detectable E. coli and TC (81% and 62%, respectively; Table 1, Fig 1), and few samples contained >10 E. coli (4%) or TC (19%) CFU/100 mL, while fewer contained > 100 CFU/100 mL (0% and 2%, respectively). Finished PSW products at the PWMF had significantly lower log concentrations of E. coli and TC than raw water samples (p<0.01) and were significantly less likely to contain detectable E. coli and TC than raw water samples (p<0.01, Table 2). When PWMF samples were disaggregated by producer characteristics, a non-significant trend was observed towards lower frequency and concentrations of E. coli and TC for the largest and smallest 20% of producers (by total production volume) vs. producers with production volumes in the middle three quintiles, as well as for producers using a disinfection method (chlorine, ozone, ultraviolet [UV], or reverse osmosis) vs. those not using disinfection, and for those with a license to produce PSW vs. those without a license (Table E in S1 File). 3.1.3 Point of Sale. 46 PSW samples representing 32 brands were randomly obtained at the POS. Of these samples, 25 were collected from street vendors and 21 from retail shops. The majority of finished PSW samples at the POS (63%) had E. coli concentrations <1 CFU/100 mL, while 33% were free from detectable TC ( Table 1, Fig 1). There was no significant difference in the proportion of samples containing detectable E. coli or TC, or in the log concentrations of E. coli or TC, between samples from street vendors vs. retail shops (Table F in S1 File). However, exterior samples collected from street vendors were significantly more likely to contain detectable E. coli and TC than exterior samples from retail shops, and had significantly higher concentrations of both types of indicators (Table F in S1 File). The microbiological quality of drinking water improved significantly with treatment, and TC concentrations increased significantly along the finished PSW supply chain (i.e., from PWMF to POS), while there was a nonsignificant trend towards increasing E. coli concentrations along the supply chain (p<0.001 and p = 0.07, respectively). Finished PSW products at the POS were not significantly more or less likely to contain detectable E. coli or TC than finished PW samples or raw (influent) water samples obtained from PWMFs, nor did POS samples contain significantly different log concentrations of E. coli from PWMF or raw water samples; however, TC concentrations in POS samples were significantly higher than those of finished PW samples at the PWMF, although they were not significantly different from raw water TC concentrations ( Table 2, Fig 2). 100 mL, respectively. The presence of E. coli in household samples was not correlated with the original source of the sample, household water treatment, or the method of extracting water from the storage container (Table H in S1 File). No comparisons were made for TC, since all samples were positive. The log concentration values for E. coli and TC in HWC were significantly higher than in finished PSW samples from the PWMF, and significantly higher than TC values for PW samples from the POS; there was a nonsignificant trend towards higher E. coli concentrations in HWC than in PW at the POS (p = 0.08; Table 2, Fig 2). The proportion of samples with detectable E. coli was not significantly different between household water for Consumption (HWC) samples and POS samples, although HWC samples were significantly more likely to contain detectable TC than POS samples. By contrast, HWC samples were significantly more likely to contain detectable E. coli and TC than PSW samples collected at the PWMF ( Table 2, Fig 2). The proportion of samples with E. coli and TC concentrations >10 CFU/100 mL were both greater for HWC samples than PSW samples collected at the PWMF and POS (p<0.01, P<0.001, respectively)). HWC samples had significantly higher log concentrations of TC, but not E. coli, than raw water samples at the PWMF (Table 2, Fig 2). HWC samples were also significantly more likely to contain detectable TC, but not E. coli, than raw water samples collected at the PWMF. A significantly higher proportion of HWC samples also contained TC (but not E. coli) concentrations >10 CFU/100 mL relative to raw water samples collected at the PWMF (Fisher exact test, p = 0.000, p = 0.49, respectively). 3.1.5 Bottled water samples. Due to the small number of BW samples obtained at the PWMF and POS, these samples were excluded from the current study. However, it is interesting to note that all BW samples were free from E. coli and TC at the PWMF (n = 5), all BW samples were free from E. coli at the POS (n = 4), and all but one sample was free from TC at the POS (Table I in S1 File). BW samples were not significantly less likely to contain E. coli or TC (p>0.05), nor did they have significantly lower concentrations of either indicator than PSW samples (p>0.05), presumably owing to the small number of BW samples obtained in our random sampling. Physico-chemical water quality The majority of raw water samples and PSW samples collected at both the PWMF and POS were in compliance with national and WHO guidelines for eight of the physico-chemical parameters measured, but not for pH and manganese (Table 3). A minority of raw and PSW samples at the PWMF fell outside the specified pH range of 6.5-8.5, as did over half of POS samples, while the majority of all samples exceeded manganese limits of 0.4 mg/L (Table 3). However, deviations from standards were not large, with all samples containing <0.7 mg/L Mn and falling within the pH range 4.5-8.0. No significant changes in physico-chemical water quality were observed along the supply chain; PW samples at the POS and PWMF resembled raw water for all physic-chemical parameters except for turbidity, which was lower for PSW than for raw water. The majority of HWC samples were in compliance with national standards and WHO guidelines for all physico-chemical parameters measured except pH and manganese (Table 3). Most household water samples (97%) fell outside the national standards for pH and manganese, with values ranging from pH 4.0-6.9 and 0.3-0.6 mg/L, respectively (Table 3). Water quality of packaged water products The results suggest that the majority of PSW products manufactured in Freetown conformed with national and international guidelines for E. coli at the time that they were produced, and did not contain chemical contaminants at concentrations posing a substantive risk to human health. Physico-chemical quality. Other PW studies have also reported pH values below the WHO recommended range in Sri Lanka, [25] and above the recommended range in Nigeria Table 3. Results of chemical analysis for raw water and finished packaged sachet water (PSW) samples. Mean (range), % compliant with WHO guidelines, (n). Parameter National Standard (SLSB, 2010) WHO Guideline [26] Raw water [15]. The WHO guidelines for pH (6.5-8.5) are aimed at reducing corrosion in metal pipes [26], and thus may not be relevant to PSW; however, use of acidic municipal piped water for manufacturing PSW products may correspond to heightened risk of contamination from lead, copper, and other metals that can leach from distribution pipes, and these should be periodically monitored by local water utilities and by PWMFs using municipal water supplies. Other studies have also reported high manganese concentrations in PW; A recent Nigerian study found 42.5% of bottled and sachet samples exceeded 0.4 mg/L, with concentrations as high as 12.9 mg/L [27]. While chronic exposure to high manganese concentrations has been associated with neurological and cognitive impairment, the concentrations reported in this study (< = 0.6 mg/L) probably do not represent a substantial increase in risk relative to the Tolerable Daily Intake of 0.06 mg/kg of body weight established by the WHO [28]. 4.1.2 Microbiological quality. The finding that a minority of PSW products sold in Freetown, SL do not meet applicable standards of microbiological water safety is consistent with reports of contamination in PSW products from other West African countries. Addo et al. [29] detected E. coli and TC in 6.7% and 83.3% of samples obtained from a Nigerian PWMF, respectively (n = 30), although another Nigerian study found no detectable E. coli in 30 samples analyzed [11], and a recent study in Accra, Ghana, found similar results [30]. Variable results across studies are to be expected: reported concentrations of fecal indicator bacteria (FIB) in PSW may vary with raw water quality, treatment methods and efficacy, sampling locations and methods, as well as with the analytical media and methods used. Furthermore, few previous PSW studies in SSA have reported using QA/QC protocols or cold chain management. Thus, while microbiological results should be compared across PSW studies with great caution, it is useful to review the current findings in the context of other studies of PSW in SSA, many of which report detecting E. coli and/or TC in PSW samples. The observed reduction in log concentration of E. coli and TC between raw water and finished PSW products in this study is consistent with the finding that all PSW producers reported treating their influent water prior to packaging. However, the presence of detectable E. coli and TC, as well as turbidity levels as high as 3 NTU, in some finished PSW samples suggests that some producers may not be adhering to best practices and/or that their treatment processes may be insufficient. Furthermore, other contaminants beyond those tested in this study, including additional microorganisms (e.g. bacteria, human enteric viruses, and parasites), chemical contaminants, and/or radionuclides, could be present in finished PSW products sold in Freetown. Studies of PW in other settings have detected a variety of bacteria [15,31], protozoan cysts [31], and other parasites, fungi, and molds [32][33][34][35]. These findings suggest that many organisms, particularly more recalcitrant contaminants such as protozoan cysts, helminth eggs, and fungi, may be common in raw water used for PW production, and may pass intact through some treatment processes used in PW manufacturing. The current study obtained only a small number of BW samples, and the prevalence and concentrations of EC and TC in these samples were not significantly different from those in PSW samples; however, the data are suggestive of a trend towards better microbiological quality in BW vs PSW in Freetown. This trend merits further study with a larger sample size to determine what manufacturing and/or distribution process variables may account for any differences in safety. Since the cost per liter of BW may be substantially higher than that of PSW, substitution of BW for PSW may not be an option for many LMIC residents, but improving the safety of PSW through improvements in policy and practice may be feasible. Changes in water quality along PSW supply chains The greater TC (but not E. coli) concentrations found in samples at the POS vs. the PWMF may be due to growth of microorganisms already present within PSW products and/or to recovery of damaged microorganisms rendered viable but non-culturable (VBNC) by treatment processes (exogenous contamination seems unlikely, as sachets are hermetically sealed and are transported in secondary packaging). Dada et al. [11] also found significantly greater prevalence of detectable TC in PSW samples from shops (40%) and street vendors (45%) vs PWMFs (6.7%) in Nigeria. However, as in our current study, Dada et al. did not find a significant difference in TC contamination between sachets from retail stores and those from street vendors. In contrast, a study from Rio de Janeiro, Brazil found greater concentrations of TC, fecal coliforms, and Pseudomonas aeruginosa in bottled water samples obtained from street vendors vs. commercial establishments [36]. Ejechi and Ejechi [37] found higher prevalence of detectable TCs and fecal coliforms on the exteriors of sachets from street vendors (100% and 47%, respectively) vs. retail stores (45% and 6%, respectively), consistent with our findings for E. coli and TC. Egwari et al. [38] detected E. coli on the exteriors of 29% of sachet samples (n = 96) obtained from POSs in Lagos, Nigeria, but did not detect E. coli in the contents of any samples. They also found greater TC contamination in PW products obtained from pails and wheelbarrows compared to samples obtained from refrigerators. While we found no difference in TC concentrations between PW from street vendors and retail shops, perhaps due to the small sample size, our finding that TC increased along the supply chain are consistent with the implication of El-Salam et al. (2008) that TC concentrations increase in PW stored at ambient temperatures [31]. The study team observed that PSW products were frequently transported, stored, and/or sold at ambient temperature conditions, and this may be a factor in the observed increase of TC concentrations along the supply chain. Further work investigating the effects of storage and transport conditions, time between production and sale, organic carbon content of PSW, and other factors on TC concentrations at the POS may be of interest. However, it is useful to recall that growth of TC does not necessarily indicate an increase in the concentrations of infectious human pathogens in PSW. Comparison of PW to alternative sources HWC was not significantly different from PSW with respect to the physico-chemical parameters studied. However, HWC samples had significantly higher prevalence and concentrations of E. coli and TC than PSW samples collected at the PWMF, and significantly higher TC concentrations than PSW collected at the POS, with a strong (nonsignificant) trend towards higher E. coli concentrations in HWC vs PSW at the POS as well. Thus, while improvements are needed in the microbiological safety of PSW in Freetown, PSW may be safer than the drinking water stored in many homes. With only 60% of Sierra Leone's population having access to improved sources of drinking water [39], and with many improved sources also providing contaminated water [21], many consumers may resort to alternative sources, including PSW, surface water, and open wells; among these options, PSW may be the safest. Table J (in S1 File) summarizes selected prior studies comparing the microbiological quality of drinking water sources and PW products; many of these studies support our conclusion that, while improvements in the microbiological safety of PW products is needed, PSW may be a safer alternative to stored water from municipal and private water supplies in some LMIC settings. Policy implications The results of this work have important policy implications for PSW regulation in SL and other LMICs where PSW consumption is substantial. The prevalence of microbiological contamination in PSW products and the deterioration of water quality along the supply chain suggest the need to improve PSW manufacturing, transportation, and storage practices. Increased regulatory oversight may support these improvements [40], and should emphasize microbiological safety relative to the physico-chemical parameters included in this study. Such oversight should include monitoring, surveillance, training and education of producers, distributors, and retailers, and provisions for identification and removal of problematic PSW products from the market. Despite the potential risks associated with PSW products in SL, regulators should to avoid dissuading consumers from drinking PSW, as it may often be safer than alternative sources of HWC. While PSW may be an important source of water for consumption, it cannot replace other sources for the majority of domestic needs such as cooking, bathing, etc., as this would be impractical from logistical and economic perspectives. While the sample size in this study did not provide conclusive results for BW, BW may prove safer than PSW, and its use should not be discouraged; however, BW consumption volumes may be insignificant compared to PSW consumption in Freetown, and regulatory efforts should thus focus on improving the safety of PSW, while not discouraging its use, to maximize health gains. Despite the large and growing importance of PSW [9], monitoring programs have been slow to collect data on this drinking water source. For example, sachet water was only introduced in the most recent MICS for Ghana [4], despite the importance of PSW in this country over the last decade. Monitoring of PSW use and safety by governments and development agencies will be an important step in regulating its production and distribution. However, as policymakers work to regulate PSW, they should also improve the safety and reliability of HWC by improving municipal drinking water supplies and expanding continuous access to these supplies. Additionally, they should assess the potential of safe household water storage and/or treatment for those households that currently lack such access in their home. Limitations of this study While useful indicators of microbiological water quality, FIB they have important limitations: FIB are more sensitive to chemical and UV disinfection than some recalcitrant pathogens [41]; TC can multiply in water at ambient temperatures [42]; and FIB rendered VBNC by treatment processes may recover under some conditions [43]. Finally, TC have many non-fecal environmental sources [34], and E. coli has non-fecal sources as well [25,27]. Nevertheless, most plausible pathways for contamination of PSW by FIB imply increased risk of fecal contamination, suggesting that differences in the prevalence and concentration of E. coli among water types in this study indicate differences in microbiological safety, while differences in TC prevalence and concentration in PSW samples at the PWMF indicate differences in treatment efficiency. While FIB are imperfect indicators, their regular use in PSW monitoring and quality control would represent a substantial improvement over current practice. The current work comprised a moderate-sized cross-sectional study; a larger longitudinal study would facilitate robust comparison of PSW safety across subgroups (shops vs. street vendors, producer size, treatment methods, BW vs. PSW, etc.), and across batches and seasons. Furthermore, the use of more robust sampling techniques (i.e. enumerating and randomizing all vendors and households in Freetown; a method that was cost-prohibitive for the current study) could better prevent bias towards shops and households readily accessible from the main street. Next steps Further work should assess the concentrations of more recalcitrant microorganisms (viruses, protozoan cysts, etc.) as well as additional chemical contaminants (heavy metals, radioisotopes) in PSW products, piped water, and HWC in Freetown and other LMIC settings to more thoroughly assessing the potential health risks to PSW consumers. Further exploration of the mechanisms by which water quality deteriorates along the supply chain may also be of interest, with potential implications for regulatory policy and monitoring. More broadly, Policy research is needed on best practices for safe manufacturing and distribution of PSW products in LMIC settings. Such work could emphasize cost-effective approaches to regulating and monitoring an industry in which manufacturers materialize and disappear or re-brand overnight [5]. Efforts to improve physico-chemical water may focus on collaboration with municipal utilities to ensure proper monitoring, treatment, and distribution of water throughout service areas. Such policies should be developed and implemented in a manner that takes into account the safety of both PSW and other sources of water for consumption, as addressing either in isolation may lead to unintended adverse consequences. Conclusions While many sachet water products sampled in Freetown, Sierra Leone were free from E. coli and TC, some PSW products contained levels of E. coli corresponding to intermediate human health risk levels. There is a clear need for improved manufacturing process controls, as well as enhanced monitoring and regulation of PSW products manufactured and sold in SL to improve their safety. Nevertheless, comparisons with HWC samples suggest that sachet water may be safer than many alternative sources of water for consumption currently used by Freetown residents. Water and health sector stakeholders should not dissuade consumers from consuming PSW until the safety of alternate sources can be ensured, and increasing in-home access to safe and reliable municipal drinking water in Freetown should remain a top priority. Until such infrastructure improvements are realized, PSW may remain the least unsafe option for many households. Supporting Information S1 File. Supporting Information Tables. Table A. Percentage of producers reporting the use of various water treatment methods. Table B. Geographic distribution of all producers in Freetown compared to distribution of all surveyed producers nationwide. S2 File. Supporting Information Survey Instruments. This file contains the survey instruments used for data collection in this study. The file contains a packaged water manufacturing facility (PWMF) questionnaire as well as a household questionnaire. (DOCX) S3 File. Supporting Information Raw Data. This file contains all raw data related to the work presented in this study. The file contains all data used in the analyses presented in this study, as well as additional data, collected through the administration of the questionnaires in S2 File, that were not included in the scope of this study. All identifiable information has been anonymized to prevent disclosing the identities of household survey respondents and PWMF survey respondents. (XLSX) S4 File. Supporting Information POS List. This file contains a list of points of sale (POSs) visited in this study. POSs are listed by POS ID, and GPS coordinates for each POS are included. POS IDs beginning with "store" correspond to retail shops, while POS IDs beginning with "street" correspond to street vendors and hawkers. (XLSX)

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Impacts of feeding less food-competing feedstuffs to livestock on global food system sustainability Increasing efficiency in livestock production and reducing the share of animal products in human consumption are two strategies to curb the adverse environmental impacts of the livestock sector. Here, we explore the room for sustainable livestock production by modelling the impacts and constraints of a third strategy in which livestock feed components that compete with direct human food crop production are reduced. Thus, in the outmost scenario, animals are fed only from grassland and by-products from food production. We show that this strategy could provide sufficient food (equal amounts of human-digestible energy and a similar protein/calorie ratio as in the reference scenario for 2050) and reduce environmental impacts compared with the reference scenario (in the most extreme case of zero human-edible concentrate feed: greenhouse gas emissions −18%; arable land occupation −26%, N-surplus −46%; P-surplus −40%; non-renewable energy use −36%, pesticide use intensity −22%, freshwater use −21%, soil erosion potential −12%). These results occur despite the fact that environmental efficiency of livestock production is reduced compared with the reference scenario, which is the consequence of the grassland-based feed for ruminants and the less optimal feeding rations based on by-products for non-ruminants. This apparent contradiction results from considerable reductions of animal products in human diets (protein intake per capita from livestock products reduced by 71%). We show that such a strategy focusing on feed components which do not compete with direct human food consumption offers a viable complement to strategies focusing on increased efficiency in production or reduced shares of animal products in consumption. Increasing efficiency in livestock production and reducing the share of animal products in human consumption are two strategies to curb the adverse environmental impacts of the livestock sector. Here, we explore the room for sustainable livestock production by modelling the impacts and constraints of a third strategy in which livestock feed components that compete with direct human food crop production are reduced. Thus, in the outmost scenario, animals are fed only from grassland and by-products from food production. We show that this strategy could provide sufficient food (equal amounts of human-digestible energy and a similar protein/calorie ratio as in the reference scenario for 2050) and reduce environmental impacts compared with the reference scenario (in the most extreme case of zero human-edible concentrate feed: greenhouse gas emissions 218%; arable land occupation 226%, N-surplus 246%; P-surplus 240%; non-renewable energy use 236%, pesticide use intensity 222%, freshwater use 221%, soil erosion potential 212%). These results occur despite the fact that environmental efficiency of livestock production is reduced compared with the reference scenario, which is the consequence of the grassland-based feed for ruminants and the less optimal feeding rations based on by-products for non-ruminants. This apparent contradiction results from considerable reductions of animal products in human diets (protein intake per capita from livestock products reduced by 71%). We show that such a strategy focusing on feed components which do not compete with direct human food consumption offers a viable complement to strategies focusing on increased efficiency in production or reduced shares of animal products in consumption. However, the livestock sector as a whole has considerably grown in absolute terms and contributes substantially to global warming, water and air pollution and biodiversity loss [1,3,4]. This overall growth of livestock production parallels population growth and increasing per capita incomes that are associated with increasing shares of animal products in human diets [5]. About one-third of arable land is currently used for feed production [1,6,7] and about a third of global cereal production is fed to animals [8]. This leads to considerable trade-offs with producing food for direct human consumption as food provision via animals entails large conversion losses [9][10][11][12]. The proportion of arable land used for livestock feed production is expected to increase further, thus increasing the pressure on arable land areas [8]. Several strategies to increase sustainability in livestock production have been suggested. They largely fall into three categories. (1) Productivity increases, aiming at meeting expected demand while curbing environmental impacts ('efficiency strategies' [13]): they include improved feeding and feed use efficiency, improved digestibility, protein and mineral contents, optimally matching the animals' requirements, breeding and herd management [2]. They contribute to the sustainable intensification of agriculture [14,15] and provide many benefits for society. For example, if applied globally, GHG emissions from the livestock sector could be reduced by 30% when compared with a reference without such intensification [16]. (2) Reduced demand for animal products ('sufficiency strategies'): they include changes in human diets and demand patterns, but also measures such as the replacement of ruminants' products with monogastrics' products [9,17,18]. Changes in dietary patterns can have considerable mitigation potential, as demonstrated by several modelling studies [19][20][21]. A comprehensive overview of the literature, distinguishing between supply and demand-side measures, can be found in [21]. (3) Reduction of the use of food-competing feed components in livestock rations, which also affects the availability of livestock products (a 'consistency strategy' [22] or 'transformation of the food system' [15]): this consistency strategy shifts the focus from livestock's role in the food system as a source for high-quality protein, to another role, which is to use resources that cannot otherwise be used for food production. These resources are (a) grasslands, which cover two-third of global agricultural area and can be used for food production by ruminants, whereas a large proportion of these grasslands is not or less suitable for arable crop production [23][24][25] and (b) food waste and by-products of food production-consumption chains, such as brans, whey and oil-cakes [26,27]. The rationale is that environmental pressures from livestock production could be reduced by focusing on grassland-based ruminant production and by reducing the amount of primary feedstuffs derived from cropland in both ruminant and monogastric feeding rations [3,7,20,28]. This affects production and consumption at the same time as it would also lead to a reduction in animal product supply. While the impacts of the efficiency and sufficiency strategies have been modelled in detail in previous works [9,16,18,29,30], the consistency strategy of reducing foodcompeting feedstuffs (FCF) in livestock rations has not previously been assessed to this extent. In this paper, we explore the potential for sustainable livestock production by modelling the impacts of such a consistency strategy on food provision as well as on natural processes. We scrutinize the potential and challenges of reductions in FCF and investigate the implications of such a consistency strategy as one option for sustainable livestock production. It has to be pointed out that the consistency strategy that we analyse in this paper is a complement and not a substitute of the sufficiency and efficiency strategies. It restricts the feeding rations for livestock and thus limits the availability of livestock products for human consumption. Corresponding changes in consumption patterns are thus one important implication of this strategy. We use a mass-flow model of the food system to investigate the effects of the consistency strategy of reducing FCF on crop and livestock production patterns, human dietary patterns and key environmental indicators. This study examines the implications of such a strategy from a physical and biological perspective, aiming at maximal coverage regarding countrywise production and availability of final and intermediate commodities and related nutrient requirements and availability, as well as environmental impacts. It explicitly does not aim at assessing price changes and market effects and the decision behaviour of farmers and consumers. The purpose of this study is, instead, to examine the system-level food and environmental implications of pursuing this consistency strategy and to identify whether it could be a complement to efficiency and sufficiency strategies. Methods This analysis employs a bottom-up mass-flow model of the agricultural and food sector, described in the following and the electronic supplementary material. The model uses FAOSTAT [6] as the central data source and covers 180 plant production activities (e.g. cultivating 1 ha of wheat for a year) and 22 livestock production activities (e.g. keeping a dairy cow for a year). The base year refers to mean values for the years 2005 -2009. These are the most recent data available that are compatible with the other datasets used, with 192 single countries and territories as geographical reference units. Country-specific herd structures for cattle, pigs and chickens were estimated to improve calculations of feed requirements and GHG emissions. Herd structures were calculated for each country with an optimization model using a cross-entropy estimator. These models predict the most likely average herd structure in a country based on the relation between producing and living animals according to FAOSTAT as well as a number of normative data (see electronic supplementary material, §1.3.2). For each activity, we defined inputs and outputs, i.e. all physical flows related to individual activities. Inputs for livestock activities include four categories of livestock feeds: (i) fodder crops grown on arable land, i.e. according to FAO, land being cropped or fallow, (ii) concentrate feed derived from humanedible food (e.g. grains, pulses) grown on arable land, (iii) grassland-based fodder, and (iv) fodder from agricultural/agriindustrial by-products. While (i) and (ii) are in competition with production of human-edible food, (iii) and (iv) are not. The term grasslands is used synonymously with the term grazing land. Further inputs for livestock activities are energy input for buildings, in-stall processes and fences. Outputs of animal production activities include human-edible and human-inedible products, manure excretion, nutrient losses and GHG emissions owing to enteric fermentation and manure management (CH 4 , N 2 O, NO 3 and NH 3 ). Country-specific data for amounts of concentrate feed and by-products used are derived from FAOSTAT food balance sheets (see electronic supplementary material, §1.3.7). Inputs for plant production activities included arable or grassland areas, mineral fertilizers, manure, crop residues, symbiotic nitrogen fixation, herbicides, fungicides, insecticides and management practices. Outputs from plant production activities include crop yield quantities, crop residues and nitrogen losses during fertilizer application. Based on these data, we calculated livestock feed and fertilizer supply/demand balances at national, regional and global level. The main model outputs are food availability (equation (2.1)) and environmental impacts (equation (2.2)). where i is the index of geographical units, j is the index of activities, k is the index of farming systems, l is the index of inputs and outputs, m is the index of nutrients for human consumption, n is the index of utilization types (food, feed, seed, waste, other) and s is the index of units of inputs and outputs. FA is the food availability expressed in kcal or g protein, AL is the activity level (ha per year for land-use activities, number of animals per year for livestock activities), OUT is the output (kg per ha or kg per animal), NCHC is the nutrient contents for human consumption [%] and UF is the utilization factor [%]. In the electronic supplementary material, we describe how food availability per person, activity levels, inputs and outputs, nutrient contents and utilization factors are determined in our model. Modelling environmental impacts Environmental impacts are aggregated across all geographical units, activities and farming systems (equation (2.2)). Activity levels (AL i,j,k ) are multiplied by inputs (IN i,j,k,s,o ) and the impact factors of the inputs (IF i,j,k,l,s,o ). N-surplus NO 3 losses to soil, and NH 3 and N 2 O losses to the atmosphere occur as a result of N use in agricultural systems. Consequently, sensitive terrestrial and aquatic ecosystems are adversely affected. N-surplus is defined as the difference between the N content of outputs (e.g. yields) and inputs (e.g. fertilizer quantities) for each country and activity. Changes in cropping areas, animal numbers (manure), production quantities, mineral fertilizer use and N-fixation thus potentially lead to changes in N-surplus. Based on equation (2.2), the amount of N is calculated by multiplying the mass of an input (IN) or output (OUT) by its N content. Relevant inputs for calculating the N-surplus are mineral N fertilizers, N-fixation, organic fertilizer, crop residues and seeds. Relevant outputs are yields and crop residues. IF is defined as the N-content of the inputs, whereas all outputs are defined as negative values. As a basis for calculating GHG emissions, N-losses during fertilizer application are separated according to the type of fertilizer (mineral, manure, crop residues) and the substance emitted (NH 3 , NO 3 , N 2 O). Model factors are specified according to IPCC 2006 Guidelines (Tier 1). Model calculations for the total N-balance in the base year are in line with literature values reported for different sources and the overall balance [1,31,32]. We did not include estimates of atmospheric nitrogen deposition in the N-surplus calculations. Greenhouse gas emissions GHG emissions of the agricultural sector have been estimated by several projects at regional [28] or global level [33 -36]. Estimations of global GHG emissions of the agricultural sector are between 4.2 and 5.2 Gt CO 2 -eq [21] and this constitutes approximately 10 -12% of total global emissions. GHG emissions were modelled according to the Global Warming Potential (GWP) 'IPCC 2006 100a' tier 1 methodology [37]. For enteric fermentation modelling, we used the tier 2 methodology in order to capture the impacts of different feeding regimes on GHG emissions. Additionally, the GWP owing to the production of inputs from non-agricultural sectors (mineral fertilizers and pesticides) was included in calculations according to LCA studies [38,39], the ecoinvent 2.0 database and [40]. To calculate the GHG emissions from processes and buildings, the cumulative energy demand (CED) values for different processes were taken from ecoinvent 2.0 and transformed into GWP values with process-specific conversion factors derived from ecoinvent 2.0. Emissions from deforestation and from organic soils under agricultural use were taken directly from [41]. According to equation (2.2), all relevant inputs (e.g. fertilizers) and processes (e.g. enteric fermentation) were specified in physical quantities. The respective CO 2 -eq values of CO 2 , CH 4 (25) and N 2 O (298) were used as IF, as suggested in the IPCC 2006 guidelines. Restricting the analysis to the common emission categories, total GHG emissions calculated for the base year in our model are similar to [16,41]. These references only differ substantially in terms of enteric fermentation calculations; the results of our model are similar to [41]. Annual deforestation potential Because agricultural land is scarce and natural grasslands are generally not well suited for cultivation (water or temperature limited), increasing the amount of land needed for agricultural production increases pressure on grasslands and forests [42]. Conversion of grassland to cropland may also indirectly lead to increased deforestation, owing to displacement effects that result in the conversion of forests to meadows and pastures [43,44]. With limited data available, we have assumed that additional cropland generally increases pressure on forests and may lead to increased deforestation. Following Kissinger et al. [45], we have attributed 80% of deforestation to agriculture. Following Alexandratos & Bruinsma [8], we have forecast constant grassland areas. The deforestation potential of agricultural land expansion was estimated from the average annual growth in agricultural area and the average annual deforestation rates in each country from 2005 to 2009 (taken from FAOSTAT). Deforestation rates in the scenarios were calculated by multiplying the change in land areas in each scenario by the ratio of deforestation areas over agricultural land area expansion, scaled by a factor of 0.8 to account for the 80% of deforestation attributed to agriculture. In cases where no change in agricultural land area was reported for the years 2005 -2009, deforestation values were calculated using the total agricultural area (instead of the change in agricultural area) as a proxy for the pressure of agriculture on forests. In these cases, deforestation rates were calculated by multiplying the total agricultural land area in each scenario by the ratio of deforestation areas from [41] over total agricultural land area in the base years, scaled by the factor 0.8. The indicators for deforestation were applied only in the cases of positive deforestation rates. Deforestation was set to zero in countries where total forest area increased. Other indicators Here, we provide short descriptions only, further details can be found in the electronic supplementary material, §1.3.9. P-surplus is calculated analogously to the N-surplus. All P-flows are expressed as P 2 O 5 . No differentiation between types of P-losses is made. Therefore, the balance (inputs -outputs) calculated expresses a 'loss potential', acknowledging that large quantities of P are fixed in soils. The total P-balance in the base year as calculated in our model is in line with literature values reported in [31]. Non-renewable energy use is calculated according to the life cycle impact assessment methodology, 'CED' [40]. Only the non-renewable energy categories (fossil and nuclear energy) are used, and renewable energy components are disregarded. Inventory data for each activity were taken from the ecoinvent 2.0 database and [41 -44]. Water use was derived based on AQUASTAT [46] data for irrigation use per tonne of irrigated production and data on irrigated areas for various crops and crop categories covered in [13]. As there is no consistent dataset on pesticide use covering different countries, we developed an impact assessment model for assessing pesticide use incorporating three factors: pesticide use intensity per crop and farming system, pesticide legislation in a country, and access to pesticides by farmers in a country (for details, see electronic supplementary material, §1.3.9.4). Soil erosion potentials were derived based on an assessment of soil erosion susceptibility per crop and soil erosion rates per country (literature review and expert judgements, details in electronic supplementary material, §1.3.9.5). Scenarios We calculated a reference scenario based on the most recent FAO projections for agricultural production patterns and food production and demand in 2050 [8], and a range of scenarios with a gradual reduction of FCF ranging from the reference scenario (referred to as 100% FCF) to 0% FCF. Each scenario presented provides the same amount of per capita energy as the reference scenario as the main measure of food availability. Additional scenarios, for constant per capita protein supply and for constant land use are given in the electronic supplementary material, §2. By-products from food production (brans, oilseed cake, whey, etc.) are assumed to be fed to animals in each scenario (electronic supplementary material, §1.3.5). Livestock numbers were derived from per-animal feed requirements and the available feed supply in each scenario. Land no longer required to supply animal feed was allocated to plant food production, according to the mix of crops in the reference scenario until the global levels of energy or protein for human consumption match the requirements of the reference scenario. For making the scenarios more comparable, grassland areas were kept at the level of the reference scenario [8]. Yields per animal were assumed to drop with reduced FCF. To account for the uncertainties regarding this effect, we computed the uncertainty range of 0 -40% yield decrease with such feed pattern changes (electronic supplementary material, §1.4.3). The values presented in the paper refer to the mid-value of 20% yield reduction. Values for the boundary cases (0% and 40%) are presented in the electronic supplementary material, §2. Fish and seafood also decreased with a reduction of FCF, as such feed is used in aquaculture (assuming fed aquaculture to comprise about 20% of fish and seafood in the current situation, about 45% in the reference scenario [47,48], electronic supplementary material, §1.4.1.6). For the scenario with 0% food-competing feedstuffs (0%FCF), the induced reductions in animal protein supply were compensated by adjusting the share of legumes in cropping patterns to at least 20%, by allocating larger shares of the areas freed from feed production to legumes (electronic supplementary material, §2). This allows keeping the share of energy delivered through protein at recommended levels of at least 10% also without animal products. Average crop rotations were thus assumed to include a legume crop once every 5 years. This is also feasible agronomically, e.g. regarding breaking disease cycles in legumes. The effect of climate change on yields was assessed by means of sensitivity analysis based on the references and details given in electronic supplementary material, §1.4.3, covering a range rsif.royalsocietypublishing.org J. R. Soc. Interface 12: 20150891 from zero yield increases under strong climate change impacts to yield increases as reported in [8], signifying no climate change impact. Changes in agricultural production patterns In the reference scenario for 2050 [8], grassland area is assumed to stay constant compared with the current situation (base year), whereas arable land is projected to increase from 1.54 to 1.63 Mha, i.e. by 6% (figures 1 and 2), resulting in a 2% increase in total agricultural land area. In the reference scenario, animal numbers are projected to increase from 1.39 to 1.85 billion animals for cattle (33% increase), from 0.9 to 1.2 billion animals for pigs (27% increase) and from 17.6 to 33.9 billion animals for chickens (by 93%) if compared with the base year (figures 1 and 3). Compared with the base year, the scenario with 100% reduction of FCF resulted in a 335 Mha decrease in arable land area, which corresponds to a decrease of 22% in arable and 7% in the total agricultural area. For cattle, in the scenario with 0%FCF, the number would increase by 60 million, i.e. 4% compared with the base year, and goat, sheep and buffalo numbers would increase by 320, 240 and 80 million, respectively (i.e. 37%, 22% and 44%), as these animals are mainly fed on grasslands and are thus less dependent on feed sources that compete with direct food production. In the 0%FCF scenario, the number of monogastrics is substantially reduced by 12.37 billion (i.e. 70%) for chickens and 810 million (88%) for pigs ( Changes in food consumption patterns Food consumption patterns are represented via projected provision in quantities, calories and proteins per capita and day (table 2), differentiated by commodity group (see electronic supplementary material, §1.3.8). We report food supply before subtraction of food waste at retail and consumption level. For the production level, the quantities of food loss reported in FAOSTAT have been used in order to be consistent with Alexandratos & Bruinsma [8]. To allow for optimal comparison with the reference scenario, per capita calorie supply from both plants and animals in the scenarios was kept constant at the level of the reference Figure 1. Impacts of feeding less food-competing feedstuffs to livestock ('food -not feed') on land use, livestock numbers, human diets and the environment in 2050. rsif.royalsocietypublishing.org J. R. Soc. Interface 12: 20150891 scenario (3028 kcal cap 21 d 21 ). This slightly differs from the 3070 kcal cap 21 d 21 reported in [8] owing to some differences in assumptions for cases where we had access to newer information, or where underlying information from [8] has not been available. This high number of calorie availability includes food wastage of about 30-40% on global average, which when deducted leads to a level in the range of human maintenance requirements. In the scenario with 0%FCF and at the same time keeping energy levels in human diet constant, the share of energy delivered through protein would change from 10.8% to 10.3% owing to the higher share of crops in the human diet, and crops generally having lower protein relative to energy contents (figures 1 and 4). Owing to the decreasing animal numbers and livestock yields, the share of livestock products in the total protein supply would drop from 38% to 11% and the share of livestock products in the total energy supply would drop from 17% to 5% (with 20% livestock yield reduction; figures 1 and 4). This is also reflected in the per capita daily consumption quantities of different commodity groups. Meat, eggs and milk drop from 136, 26 and 274 g cap 21 day 21 to 26, 2 and 138 g cap 21 day 21 , respectively. Climate change (i.e. lower yield increases) leads to further small changes in dietary composition with less livestock products and more grains, legumes and fish. Environmental impacts We focus on the presentation of the results on N-surplus, GHG emissions and deforestation. Results on land occupation have been covered already above. Results for the other impacts (P-surplus, non-renewable energy use, water use, pesticide use and soil erosion) are included in figures 1 and 5 and discussed shortly; more details can be found in the electronic supplementary material, §2.1. Details for the calculations are provided in the Methods section and in particular in the electronic supplementary material, §1.3. In the reference scenario, all environmental impacts are exacerbated compared with the base year, except for deforestation rates (figures 1 and 5). The N-surplus (i.e. total input minus total extraction by crops per ha; global average, including grasslands) increases by 34%, which means an increase from 18.6 to 25.0 kg ha 21 yr 21 . This is driven by the increase in output from the whole food system, which leads to correspondingly increased input use, i.e. mineral fertilizer inputs and N-fixation (as legume areas and production increase as well), whereas the increases in agricultural area are much lower. GHG emissions increase by 27%. This again reflects the increase in production volume; increased emissions from higher ruminant numbers and manure quantities as well as increased fertilizer inputs to the fields are the main drivers of these emission increases. With deforestation and organic soils included, the increase in GHG emissions in comparison with the base year is 16%, which reflects the lower changes in those two additional categories in comparison with the agricultural production. Deforestation pressure decreases by 13% compared with the base year. The decrease in deforestation rates is due to the reduced expansion rates in agricultural area between now and 2050 compared with the expansion rate in the base years 2005-2009. The lower expansion rates of agricultural land are due to assumptions about yield increase and cropping intensity increase in the reference scenario [8]. Those effects, and not the utilization of additional land, are the main mechanisms through which increased food demand would be met. For the other environmental impacts, most notably, freshwater use increases by about 60%, owing to an increase in irrigated areas and irrigation intensity. Pesticide use and erosion potential increase by about 10% each, driven by the increase in arable land areas, and P-surplus and non-renewable energy demand increase by 30% and 20%, driven by the general increase in production volumes and corresponding input use. For the 0%FCF scenario, the environmental impacts are lower than in the reference scenario just described (figures 1 and 5). Compared with the current situation, the N-surplus per ha would drop by 22%, as the whole production volume and corresponding demand for inputs is decreased. GHG emissions would increase by 1%, or would drop by 5% by including deforestation and organic soils. This is due to a drastic reduction in animal numbers and manure quantities, as well as in total N-fertilizer quantities needed. It is important to point out that owing to the focus on grassland feed, the number of ruminants is reduced much less than the number of monogastrics (figures 1 and 3), and that the effect of reduced emissions from enteric fermentation is thus less prominent than it would be in a strategy that would predominantly aim at reducing ruminants to reduce emissions from enteric fermentation. We also note that we did not include atmospheric N-deposition in the calculations. Given that animal husbandry and mineral fertilizers account for a large share of NH 3 emissions as the key source for N-deposition [49], we thus rather underestimate how the reduction of FCF affects the N-surplus, as these sources are also correspondingly lower. Deforestation pressure is reduced by 21% compared with the base year, which reflects the reduced land demand already reported above. The other environmental impacts besides water use are lower than in the base year, driven by the reduced production volumes, animal numbers and cropland areas. Freshwater use still increases by 25% owing to the increase in the share of irrigated areas (figures 1 and 5). How environmental impacts change as a result of climate change effects on yields is also displayed in figure 5. Generally, the environmental impacts in the 0%FCF scenario are still smaller than in the reference scenario, but the relative advantages decrease if climate change impacts are included (electronic supplementary material, §1.4). Creating synergies between enhanced food availability and reduced environmental impact A continuation of current food consumption and production trends, as forecast in Alexandratos & Bruinsma [8], increases per capita food availability until 2050. However, food availability in that scenario hinges on large yield increases over the next 40 years, with environmental impacts projected to increase substantially. If projections of climate change effects and natural limitations on yields are considered, then agricultural land areas would have to increase drastically to meet the forecast demand for 2050 (figure 2). Livestock production with lower shares of FCF would generate synergies between increased food availability and reduced environmental impacts. Our exploration of the impacts of a consistency strategy with 0%FCF shows that reduction in land use and emissions can be realized, albeit with significant changes in people's diets, as well as changes of the role of livestock. It would avoid drastic increases in the demand for agricultural land area, in particular if more pessimistic yield forecasts under climate change transpire. The results of our study are not to be understood as forecasts but as explorations of possible long-term futures. It is important to note that the results of this study are subject to uncertainties, stemming from known data flaws or lacking data, particularly for smaller countries and developing countries. Therefore, extrapolation of some datasets is unavoidable, and uncertainties of future trends that are not included in the model, for instance the share of renewable energies in country-specific energy mixes, demand for biofuels or potential new technologies such as cultured meat, evolve. However, because we use the model at global level and model only fundamental changes in food systems, the general trends of our results are meaningful, as shown in the uncertainty analysis (see electronic supplementary material). Such an exploration of possible long-term futures is required, as fundamental changes in the food system will not be feasible within the timeframe of only one decade. Implications of the strategy with reduced foodcompeting feedstuffs for livestock production Advocating reduced grass-based production of ruminants and enhanced use of concentrates, which contain humanedible feedstuffs, for both ruminants and monogastrics is not the only strategy to achieve sustainable intensification. Here, we show that a consistency strategy which reduces FCF is a viable alternative. Such a strategy could combine the advantages of breeding, veterinary health measures and feed management, with a strategy that aims at reducing the amount of cropland-derived feedstuffs, to thus alleviate land-use competition [50]. Ruminants have been the focus of sustainability discussions because of the large CH 4 emissions from enteric fermentation [1,3]. Roughage-fed ruminants could, however, play an important role for food security, as they allow the use of resources that are otherwise not, or only barely, usable for food production, as is the case with most global grasslands [23]. Therefore, in the scenarios with 0%FCF, the number of monogastrics is reduced much more than the number of ruminants, and roughage-fed ruminants still provide an important source of protein. We show that a food system with ruminant-and grassland-based animal products can provide enough food while reducing environmental impacts. Furthermore, grasslands can contain large carbon stocks and can provide many ecosystem functions [24]: much of which would be lost if grassland were converted to arable land [51][52][53]. An important challenge to the livestock feed industry will be to further improve the use of agricultural residues, agro-industrial by-products and waste material to produce high-quality feedstuffs [54,55], where reuse is a far better option than landfilling, incineration, composting or anaerobic digestion. From modelling production systems to modelling food systems While most studies concentrate either on production issues [16] or consumption patterns [15,30], this assessment emphasizes the importance of considering the nexus between agricultural production patterns and systems with food consumption. Thus, it links the discussion of sustainable food production and sustainable food consumption and can be used to assess integrative strategies that have an impact on both resource efficiency of production and the availability of certain foodstuffs. We show that despite roughagefed beef or milk having a higher carbon footprint than products from intensive, concentrate-fed cattle systems, or even pig and poultry, the scenario with 0%FCF results in a more sustainable food system than the reference scenario based on business-as-usual projections, as losses in resource efficiency are more than offset by the beneficial effects of reducing feed production on arable land. This perspective rsif.royalsocietypublishing.org J. R. Soc. Interface 12: 20150891 of connecting efficiency and consumption strategies can complement existing life cycle assessments and economic modelling approaches [56]. The scenarios we have investigated would necessitate dietary change; namely reduced consumption of animal products, with particular reductions in pig and poultry meat, and eggs. This is viable from a physical and food availability point of view and would also yield other benefits, primarily related to human health [57]. High consumption of livestock products has been linked to non-communicable and chronic diseases, and obesity [29]. The societal acceptability of such dietary change is not well understood, but is clearly key to any successful implementation of such a strategy [19], and likely remains challenging [58]. While other studies examining the impacts of changing food consumption patterns concentrated on the reduction of ruminant production or on livestock products in general, this study provides insights into the relative benefits of roughage-fed meat and milk over other livestock products from the perspective of sustainable consumption. We have shown that in such a scenario, the reduction in consumption of monogastric livestock products would be much more drastic than for ruminant meat. Thus, there are alternatives to the frequently suggested replacement of ruminant with monogastric meat, which is based on carbon footprints or attributional life cycle assessments of single products that do not consider the limited availability of arable land and the utilization of grasslands. Our scenarios are based on nutrient balances and assessments of the physical and technical viability of different food production scenarios and global food system scenarios that have not previously been captured in global land-use models. This provides important insights concerning the physical viability and environmental effects of these food system scenarios. However, to assure food security, access to food, stability and utilization also need to be addressed in addition to food availability [14]. Reducing the amount of human-edible crops that are fed to livestock represents a reversal of the current trend of steep increases in livestock production, and especially of monogastrics, so would require drastic changes in production and consumption. Achieving such drastic changes is a huge challenge for society. Policy measures on both the supply and demand sides would be required to assist such structural change necessary to prevent potential future crises for food availability, the environment and human health [15,50]. Long-term and global ex ante impact assessments, such as that presented here, are essential to inform the scientific debate and to provide a basis for informed decision-making. Clearly, to decide on specific policy measures and implementation options for these strategies, physical models that assess the principal viability and impacts need to be complemented with economic models to take market effects on demand and supply into account [59]. Such economic assessment is, however, beyond the scope of this study. Ideally, elements of all proposed strategies may best be combined to achieve sustainable food systems, complementing increased efficiency with reduced meat consumption and changed livestock feeding patterns towards less human-edible crops and feed from arable land. Such a combination would avoid the need to pursue one strategy to very high levels of implementation, that are likely expensive and unrealistic, but a combination of strategies, each implemented at intermediate levels may be promising. The contribution of this paper is to show that a consistency strategy with 0% FCF can play a significant role in such a combination of complementary strategies, on par with the other previous suggestions.

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Effect of seed maturation stages on physical properties and antioxidant activity in flaxseed (Linum usitatissimum L.) Flaxseed is the seed from the flax plant (Linum usitatissimum L.), which is a member of the Linaceae family. As the source of linen fibre, flaxseed has been cultivated since at least 5000 BC; today it is mainly grown for its oil (Liu et al., 2016). The spherical fruit capsules contain two seeds in each of five compartments. The seed itself is flat and oval with a pointed tip. Seed colour is determined by the amount of pigment in the outer seed coat the more pigment, the darker the seed (Coskuner & Karababa, 2007). Its’ seeds containing about 36 to 40% of oil, have long been used in human and animal diets and in industry as a source of oil and as the basic component or additive of various paints or polymers (El-Beltagi et al., 2007). Flaxseed oil is the richest plant source of linoleic (omega-6) and linolenic (omega-3) polyunsaturated fatty acids (PUFA), which are essential for humans since they cannot be synthesized in the organism and must be ingested in food (El Beltagi et al., 2007). Flaxseed oil is qualitatively different from the more common vegetable oils with high PUFA proportions, such as soya oil, sunflower oil, rape oil, olive oil, etc and it has a relatively low glucosinolate content (El-Beltagi et al., 2007). The protein and fibre content in the seed are also important nutritional parameters: the crude protein content in the seed ranges from 25% to 35%, while the crude fibre content is about 28% (Bilek & Turhan 2009). Introduction Flaxseed is the seed from the flax plant (Linum usitatissimum L.), which is a member of the Linaceae family. As the source of linen fibre, flaxseed has been cultivated since at least 5000 BC; today it is mainly grown for its oil (Liu et al., 2016). The spherical fruit capsules contain two seeds in each of five compartments. The seed itself is flat and oval with a pointed tip. Seed colour is determined by the amount of pigment in the outer seed coat the more pigment, the darker the seed (Coskuner & Karababa, 2007). Its' seeds containing about 36 to 40% of oil, have long been used in human and animal diets and in industry as a source of oil and as the basic component or additive of various paints or polymers (El-Beltagi et al., 2007). Flaxseed oil is the richest plant source of linoleic (omega-6) and linolenic (omega-3) polyunsaturated fatty acids (PUFA), which are essential for humans since they cannot be synthesized in the organism and must be ingested in food (El Beltagi et al., 2007). Flaxseed oil is qualitatively different from the more common vegetable oils with high PUFA proportions, such as soya oil, sunflower oil, rape oil, olive oil, etc and it has a relatively low glucosinolate content (El-Beltagi et al., 2007). The protein and fibre content in the seed are also important nutritional parameters: the crude protein content in the seed ranges from 25% to 35%, while the crude fibre content is about 28% (Bilek & Turhan 2009). The effectiveness of lipid unsaponifiable matters in retarding oil deterioration has been demonstrated by many investigators (Herchi et al., 2014a). In flaxseed, lipids are protected against oxidation by various mechanisms, for example, the presence of antioxidants such as lignans, phenols, tocopherols and flavanoids (Herchi et al., 2015). In addition to preventing fat rancidity, these antioxidants could increase commercial value of food products and have beneficial effects on human health. The antioxidant ability of lignans, tocopherols and flavanoids is related to the presence of OH groups which may directly bind to free radicals and chelate metals (Pengkumsri et al., 2015). Flaxseed oil is cited as potentially useful by the American Heart Association in the prevention of cardiovascular diseases, including reduction of serum cholesterol, platelet aggregation, and inflammatory markers, improving glucose tolerance and acting as an antioxidant (Santos et al., 2014). To the best of our knowledge, the chemical composition and oxidative stability during flaxseed hull development have been investigated (Herchi et al., 2014b) but no work have been reported on the physicochemical properties and antioxidant activity of whole flaxseed from different stages of maturity. The objective of this research was to analyze physical properties, phospholipids contents and antioxidant activity during flaxseed development. Chemicals and reagents All solvents and standards used in the experiments were purchased from Fisher Scientific Company (Ottawa, Ontario, Canada). Plant materials The variety of flaxseed "P129" was obtained from Institut National Recherche Agronomie Tunis (INRAT), Tunisia. This variety of flaxseed (L. usitatissimum L.) was grown in restricted zones (15 m × 3 m) on the Agronomy farm of the INRAT from the middle of November 2006 until the end of June 2007. Each sample was collected at intervals after a number of days of flowering (DAF) ranging from 7 th DAF to 56 th DAF. Moisture and seeds weights were determined by weighing 100 seeds before and after drying to constant weight in a vacuum oven at 80 °C for 72 h. Capsule diameter was measured, using a digital caliper, at approximately weekly intervals for all 10 capsules between 7 and 56 DAF. Lipid extraction The total lipids were extracted by the method of Folch et al. (1957) modified by Bligh & Dyer (1959). Flaxseeds (40 g) were washed with boiling water for 5 min to denature the phospholipases (Douce, 1964) and then crushed in a mortar with a mixture of CHCl 3 -MeOH (2:1, v/v). Fixing water was added and the homogenate was centrifuged at 3000 rpm for 15 min. The lower chloroformic phase containing the total lipids was dried in a rotary evaporator at 40 °C. Lipid class separation by Thin-Layer Chromatography Lipid classes were separated by TLC using glass plates (20 × 20 cm) covered with silica gel (G60, Merck) at a thickness of 0.25 mm. For this, the plates were activated at 120 °C for 2 h immediately before use, and approximately 30 mg of total lipids per gram of adsorbent was fractioned. Phospholipids (PLs) were separated using a mixture of chloroform-acetone -methanol-acetic acid -water (50:20:10:10:5, v/v/v/v/v) as described by (Lepage, 1967). Lipid spots were detected after a brief exposure of the plates to iodine vapors saturating a tightly closed vat. The identification of lipid classes was made by comparing their Retention Factor (RF) values with those of authentic standards chromatographed under the same conditions. After the detection of the lipid classes, the plates were submitted to a nitrogen stream in order to eliminate iodine, and individual bands were scraped from the plates and corresponding phospholipids were recovered from the silica gel by elution with 5 mL of hexane. Phospholipids (PL) extraction (Diol SPE) The SPE cartridge was preconditioned with 20 mL chloroform, 20 mL chloroform/methanol (9:1, v/v), and 20 mL chloroform. Lipid extracts dissolved in 2 mL chloroform were loaded onto the cartridge and eluted with the following solvents: 30 mL chloroform to remove neutral lipids, 25 mL acetone to remove glycolipids, and 30 mL methanol plus 10 mL of chloroform/methanol (1:1 v/v) to recover phospholipids. Lipid fractionation using this solvent system has been previously described (Herchi et al., 2011b). The recovered fraction was dried in a rotary evaporator and weighted in order to determine the PL amount in the oil. The PL fraction was re-dissolved in 1 mL of methanol for LC-MS analysis. Determination of PL molecular species by HPLC-MS LC-MS experiments were performed using a method described in detail by Herchi et al. (2011b). The method employed an Agilent1200 LC system (Agilent Technologies, Palo Alto, CA) coupled to an Applied Biosystem /MDS Sciex 3200 QTRAP LC/MS/MS with a Turbo Ion Spray source. The phospholipid fractions from flaxseeds were separated using an Ascentis Express HILIC column (15 cm × 2.1 mm, 2.7 mm). The mobile phase consisted of 92/8 acetonitrile/125 mM ammonium formate pH3.0 (A) and 10 mM ammonium formate in water with 0.2% formic acid pH3.0 (B). The solvent gradient initiated at 0% B, increased to 16% B in 12 min, to 70% B in 0.1 min and maintained at 70% B for 5 min, and returned to initial solvent composition in 0.1 min and reequilibrated for 20 min prior to next injection. The injection volume was 2 µL and flow rate was 200 µL/min. MS analysis of phospholipids was performed using ESI in the negative ion mode. Nitrogen was used as curtain gas, nebulising gas, and turbo gas. The instrumental settings were as follows: spray voltage 4000 V; curtain gas (CUR) 25; nebulizer gas (GS1) 40; turbo gas (GS2) 30; and ion source temperature 400 °C. Analyst 1.4.2 software was used for data acquisition and analysis. Relative concentrations of each phospholipid class and species were estimated using uncorrected peak areas of extracted ion chromatograms (EIC). The MS/MS data was obtained during HILIC-LC separations using information dependent acquisition (IDA) enhanced product ion (EPI) scan modes which automatically trigger MS/MS acquisition as molecular species are detected. The total ion chromatogram (TIC) together with the extracted ion chromatograms (EICs) of PL classes from flaxseed oil is presented by Herchi et al. (2011b). Total polyphenol content The content of total polyphenol was determined by using the Folin-Ciocalteu colorimetric method, based on the reaction of the reagent with the functional hydroxyl groups of phenols. A one-gram oil sample was weighed, dissolved in 10 mL hexane and transferred to a separatory funnel. Then, 20 mL of a methanol-water mixture (80:10 v/v) was added. After 3 min of shaking the lower methanol-water layer was removed. The extraction was repeated twice and the methanol-water phases were combined. The methanol-water extract was driven to dryness in a rotary evaporator under a vacuum at 40 °C. The dry residue was then dissolved in 1 mL of methanol. The extraction procedure described above was performed three times (Parry et al., 2005). An aliquot (0.2 mL) of the methanolic extract was placed in a volumetric flask (10 mL). Diluted Folin-Ciocalteu reagent (0.5 mL) was added. After 3 min, saturated sodium carbonate (1 mL) was added. The flask was filled with water up to 10 mL. After 1 h, the absorbance at 765 nm was measured using a UV-vis spectrophotometer (LKB-pectronic 20 D+) with a 1-cm cell. Total phenolic compounds were determined after preparation of a standard curve. Gallic acid was used as a standard. Results are expressed as mg of gallic acid equivalent per kg of oil. Determination of antioxidant activity The oil obtained was subjected to screening for its possible antioxidant activity. The oil was assessed using 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging assay. All the data were the averages of triplicate determinations of three tests. The DPPH free radical-scavenging activity of oil was measured using the method described by Gorinstein et al. (2004). A 0.1 mM solution of DPPH in methanol was prepared. An aliquot of 0.2 mL of sample was added to 2.8 mL of this solution and kept in the dark for 30 min. The absorbance was immediately measured at 517 nm. The ability to scavenge the DPPH radical was calculated with the following Equation 1: Where A 0 is the absorbance of the control, A 1 is the absorbance in the presence of sample. Statistical Analysis Statistical analysis was performed by using the Proc ANOVA in SAS (software version 8). All analyses were replicated three times for each sample. Morphology and physical properties during flaxseed development A summary of the physical properties of flaxseed during development is shown in Table 1. We did not find any study in the literature on the effect of maturation on the physical properties of flaxseed. All the properties except from sphericity increased slightly with maturity. Capsule diameter increased rapidly from 7.2 mm to 12.8 mm at 28 DAF, and then increased more slowly with maturation to around 13.4 mm at approximately 42 DAF (Table 1). Thereafter, capsule diameter decreased slightly to 12.4 mm at maturity. Table 1 indicates that the seeds expand in length, width, thickness, arithmetic and geometric mean diameter within maturity. Similar results have been reported by some researchers (Coskuner & Karababa, 2007). The geometric mean diameter of flaxseed is lower than for okra seeds (Calisir et al., 2005) and higher than that of sesame seeds (Tunde-Akintunde & Akintunde 2004). Oblate spheroid and Ellipsoid shapes showed an increase during flaxseed development. The data obtained from the work may be of interest to people seeking information on physical properties of flaxseed to aid in design and fabrication of processing equipment for the product. Table 2 shows comparative analysis of the individual phospholipids contents in total phospholipids using TLC (Thin layer chromatography) and HPLC-MS. TLC revealed the presence of six phospholipids at different stages of maturity, phosphatidylglycerol (PG), phosphatidic acid (PA), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylcholine (PC) and lysophosphatidylcholine (LPC). Similar phospholipids classes were detected by HPLC-MS (Herchi et al., 2011b). Using TLC, The total phospholipid content was high (46%). Both methods shows continuous decrease in the total phospholipid content from about (46%-35%) at 7 DAF to (4%-2%) at 56 DAF. All the results showed significant differences between HPLC-MS and TLC for quantitative determination of phospholipids classes. Herchi et al. (2012) have studied the change of fatty acids (FAs) composition of the total phospholipid mixture, but information on the changes of fatty acids composition in each class of phospholipids in flaxseed at different stages of seed development, using HPLC-MS, is still insufficient or limited. Practically no literature data are available on the modifications of each molecular species of each PL during development, which play a pivotal role for the study of the change of the nutritional quality of flaxseed oil. Table 3 gives the evolution of fatty acids composition in each individual phospholipid. The major fatty acids in all the six phospholipids were found to be linolenic, linoleic, oleic and palmitic acids. The highest amount of linolenic acid (31%) was observed in PG. Linoleic acid content in PE was found to be the maximum (51%) compared to other phospholipids. It was found that PG contained a higher amount of palmitic acid and a lower amount of oleic acid, whereas PC contains a lower amount of palmitic acid and a higher amount of oleic acid. It was observed that the unsaturated fatty acids were mostly located in PC, whereas the saturated fatty acids predominantly occupied PG compared to other phospholipids. Rao et al. (2009) reported that the phospholipids fraction of jatropha seeds oil was further characterized and quantified and found to contain phosphatidyl choline (PC) 60.5%, phosphatidyl inositol (PI) 24% and phosphatidyl ethanolamine (PE) 15.5%. They mentioned that linoleic acid content in PE was found to be the maximum (41%) compared to other phospholipids. The highest amount of phosphatidylcholine was observed at 49 DAF. Phosphatidylcholine as well as its essential fatty acid (omega-6 fatty acid) (12%) and choline components is required for many vital functions in the cardiovascular, reproductive, immune, and nervous systems. This characterization can be proposed as an application for the study of specific technology markers in the flaxseed processing industry. Changes in total polyphenol content and antioxidant activity during flaxseed development The change in total polyphenol content during flaxseed development is presented in Figure 1. Total polyphenol content decreased steadily from early to late development stage. A similar kind of decrease in Total phenolic compounds was reported by Herchi et al. (2011a). The decrease in Total polyphenol content has been attributed to the oxidation of polyphenols by polyphenoloxidase during fruit maturity (Eiberger & Matthes, 2011). The total polyphenol content of flaxseed oil, as reported by Zhang et al. (2007) ranges from about 77 to 115 mg / kg oil, as gallic acid equivalents. The antioxidant capacity of flaxseed oil at different stages of maturity was assessed with the DPPH radical-scavenging assay. The change in antioxidant activity during flaxseed development is presented in Figure 2. To our knowledge, no data are available on the changes in antioxidant This result showed more ripened of flaxseed had a higher of DPPH. Flaxseed oil exhibited higher antioxidant activity. The highest value of antioxidant activity was found in ripe flaxseed (42 DAF). In fact, it appears that there is no important correlation between antioxidant activity and total polyphenol amounts. At 7 DAF where a high content of total polyphenol was detected (140 mg / kg oil), the antioxidant activity was weak (30.82%) in comparison to other stages such as at the 42 DAF (96 mg / kg oil) and the antioxidant activity was 55.37%. Although the constituents of flaxseed oil, which show free radical scavenging action is still unclear, it is possible that the antioxidative activity of flaxseed oil are caused, at least in part, by the presence of polyphenols (Herchi et al., 2014a(Herchi et al., , 2015 and other yet to be discovered antioxidant compounds. The trend of a decreasing antioxidant capacity during ripening was also observed in durian fruits by (Haruenkit et al., 2010). Conclusion Physical characteristics changes during flaxseed development. The results of this study have shown that each phospholipids class has a specific fatty acids composition at different maturity stages. Linoleic acid content in PE was found to be the maximum (51%) compared to other phospholipids. It was observed that the unsaturated fatty acids were mostly located in PC, whereas the saturated fatty acids predominantly occupied PG compared to other phospholipids. Total polyphenol content were highly accumulated on the 7 th DAF and mature stages of flaxseed resulted high antioxidant activity. The result of this study will provide valuable information for flaxseed breeders and growers in developing and producing functional food resources and products.

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