توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Genetic Properties of Some Economic Traits in Isfahan Native Fowl Using Bayesian and REML Methods
نویسنده(ها): ، ، ،
اطلاعات انتشار: Poultry Science Journal، سوم،شماره۲، ۲۰۱۵، سال
تعداد صفحات: ۷
The objective of the present study was to estimate heritability values for some performance and egg quality traits of native fowl in Isfahan breeding center using REML and Bayesian approaches. The records were about 51521 and 975 for performance and egg quality traits, respectively. At the first step, variance components were estimated for body weight at hatch (BW0), body weight at 8 weeks of age (BW8), weight at sexual maturity (WSM), egg yolk weight (YW), egg Haugh unit (HU) and eggshell thickness (ST), via REML approach using ASREML software. At the second step, the same traits were analyzed via Bayesian approach using Gibbs3f90 software. In both approaches six different animal models were applied and the best model was determined using likelihood ratio test (LRT) and deviance information criterion (DIC) for REML and Bayesian approaches, respectively. Heritability estimates for BW0, WSM and ST were the same in both approaches. For BW0, LRT and DIC indexes confirmed that the model consisting maternal genetic, permanent environmental and direct genetic effects was significantly better than other models. For WSM, a model consisting of maternal permanent environmental effect in addition to direct genetic effect was the best. For ST, the basic model consisting direct genetic effect was the best. The results for BW8, YW and HU, were different between the two approaches. The reason behind this tiny differences was that the convergence could not be achieved for some models in REML approach and thus for these traits the Bayesian approach estimated the variance components more accurately. The results indicated that ignoring maternal effects, overestimates the direct genetic variance and heritability for most of the traits. Also, the Bayesian–based software could take more variance components into account.
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