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作 者:李秀丽 LI Xiuli(Shandong Vocational College of Animal Husbandry and Veterinary,Weifang 261061,China;Shanxi Agricultural University,Taigu 030801,China)
机构地区:[1]山东畜牧兽医职业学院,潍坊261061 [2]山西农业大学,太谷030801
出 处:《中国草食动物科学》2021年第6期33-36,77,共5页China Herbivore Science
基 金:山东省农业产业技术体系羊产业创新团队(SDAIT-10-05)。
摘 要:为了得到考力代羊协方差函数分析的最佳模型和准确的参数估计,以便为考力代羊的选育提供参考依据,利用考力代羊的育种体重记录数据,分为4部分进行:第一,先在固定效应模型中,利用SPSS软件的GLM程序对模型中的固定效应进行筛选;第二,用DFREML软件的DFUNI程序进行单性状分析,利用对数约束似然函数最大值和似然比检验对模型中的随机效应进行筛选;第三,单性状分析的方差组分作为多性状分析的初始值,多性状分析的协方差组分作为协方差函数估计的初始值;第四,用DFREML软件的DXMRR程序进行协方差函数估计时,利用Araike和贝叶斯信息标准(AIC、BIC)对模型中效应的配合阶数进行筛选。结果表明,协方差函数分析模型中固定效应(b)为出生年份、出生月份、出生类型和性别;随机效应为个体加性遗传效应(a)和母体永久环境效应(c),且固定效应和随机效应的配合阶数依次为5、5、4时所得的协方差函数估值最佳。最佳模型为y=Xb+Za+Wc+e(e为误差方差)。In this study,in order to obtain the best model of covariance function analysis of Corriedale sheep and obtain accurate parameter estimation,for providing certain basis on the breeding of Corriedale sheep.The breeding weight records of Corriedale sheep were used.It mainly included four parts:firstly,the GLM program of SPSS software was used to screen the fixed effect in the model in the fixed effect model;secondly,using the DFUNI program of DFREML software to analyze the single trait,the maximum value of log-constrained likelihood function and likelihood ratio test were used to screen the random effect in the model;thirdly,the variance component of single trait analysis was used as the initial value of multi-trait analysis,and the covariance component of multi-trait analysis was used as the initial value of covariance function estimation;fourthly,when using DXMRR program of DFREML software to estimate the covariance function,Araike and bayesian information standard(AIC and BIC)were used to screen the fitted order.Results were the best analysis model was y=Xb+Za+Wc+e,the fixed effects(b)were birth year,birth month,birth type and sex.The random effects were individual additive genetic effect(a)and maternal permanent environmental effect(c),and the matching orders of fixed effect and random effect were 5,5,4(e was the error variance).
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