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首页> 外文期刊>Poultry Science >Bayesian hierarchical model for comparison of different nonlinear function and genetic parameter estimates of meat quails
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Bayesian hierarchical model for comparison of different nonlinear function and genetic parameter estimates of meat quails

机译:贝叶斯分层模型,用于比较肉鹌鹑的不同非线性函数和遗传参数估计

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摘要

This study aimed to compare different nonlinear functions to describe the growth curve of European quails and to estimate growth curve parameters, (co) variance components, and genetic and systematic effects that affected the curve using a hierarchical Bayesian model that allows joint estimation. Three different models were fitted in the first stage (Gompertz, Logistic, and von Bertalanffy). The analyzed data set had 45,965 records of 6,838 meat quails selected for higher body weight at 42 d of age for 15 successive generations, weighed at birth, 7, 14, 21, 28, 35, and 42 d of age. Comparisons of the overall goodness of fit were based on deviance information criterion (DIC) and mean square error. Gelfand's check function compared the models at different points of the growth curve. In the second stage, the systematic (sex and generation) and genetic effects were considered in an animal model. Random samples of the a posteriori distributions were obtained by Metropolis-Hastings and Gibbs sampling algorithms. The Gompertz function presented lower DIC and better adjustment at different ages and was defined as the best fit. The heritabilities of A, b, and k parameters were moderate (0.32, 0.29, and 0.18, respectively). The genetics correlations were A and b (0.25), A and k (-0.50), and b and k (0.03). The samples of the posterior marginal distributions for the differences between the estimates of the parameters of the Gompertz model, for generation, A, b, k, age at inflexion point (APOI), and weight at inflexion point (WPOI) showed differences in relation to sex, the females are heavier, A, WPOI, and APOI for females were also higher. In conclusion, 15 generations of selection and changes in the environmental conditions altered the growth curve, leaving the quails heavier and with greater WPOI and APOI, decreased growth rate, and increased the birth weight. The curve parameters could be used in a selection index, despite the difficulty in selecting quails with higher rate of growth and adult body weight.
机译:本研究旨在比较不同的非线性函数来描述欧洲鹌鹑的生长曲线,并估计利用允许联合估计的分层贝叶斯模型影响曲线的增长曲线参数,(CO)方差分量和遗传和系统效果。在第一阶段(Gompertz,Logistic和Von Bertalanffy)安装了三种不同的型号。分析的数据集具有45,965条记录的6,838次肉鹌鹑,在连续15代的42 d年龄在42岁处被选择,在出生时称重,7,14,21,28,35和42 d。拟合整体良好的比较基于偏差信息标准(DIC)和均方误差。格尔福的检查功能比较了生长曲线的不同点的模型。在第二阶段,在动物模型中考虑了系统(性和一代)和遗传效果。通过Metropolis-Hastings和Gibbs采样算法获得后验分布的随机样本。 Gompertz功能呈现较低的DIC和更好地调整不同年龄,并且被定义为最合适的。 A,B和K参数的遗传性分别适度(分别为0.32,0.29和0.18)。遗传相关性是A和B(0.25),A和K(-0.50)和B和K(0.03)。用于后边缘分布的样品,用于Gompertz模型的参数估计,用于生成,a,b,k,Inflexion点(apoi)的年龄和Inflexion point(wpoi)的权重显示了关系的差异对性而言,女性较重,A,WPOI,女性的Apoi也越来越高。总之,15代选择和环境条件的变化改变了生长曲线,使鹌鹑越重,较大的WPOI和APOI,降低生长速度,并增加出生体重。尽管选择具有较高生长速率和成人体重的鹌鹑难以选择曲线参数。

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