基于随机回归模型估计奶牛产奶量的遗传参数

文章用随机回归模型对奶牛泌乳性状中产奶量的遗传参数进行估计,在Bayesian理论的基础上用Gibbs抽样法估计方差组分。数据来自1988～1999加拿大奶牛育种中心,共计768 205个测定日记录,研究中处理后符合要求的个体为4 686个,测定日记录有43 661个。随机回归模型中加性遗传效应和永久环境效应分镶嵌了5阶和7阶Legendre多项式。5～330 d产奶性状的遗传力在0.2707到0.4291之间变化,0～22 d有明显下降,而在22～125 d迅速上升,在125～190 d有些微的下降而后有缓慢上升。

Estimation of genetic parameters for milk yield of cattle by random regression model

Random regression model was applied into estimation of genetic parameters for milk yield in cattle.Variance components were estimated using Gibbs sampling procedure on Bayesian theory.A total of 768 205 test day(TD) records were extracted for Canadian Jerseys calving between 1988 and 1999.After editing,the calibration sample consisted of 43 661 TD records from 4 686 cows in this study.We nested different order Legendre polynomial within additive genetic effects(5 orders) and permanent environmental effects(7 orders) in the random regression model.Heritabilities of milk yield 0-330 d of test varied between 0.2707 and 0.4291,where heritabilities 0-22 d of test clearly decreased with day of test but ones 22-125 d of test obviously incre-ased with day of teat.In addition,genetic and phenotypic correlations between milk yields at different test day were also obtained using regression model.