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使用线性、门限和生存贝叶斯模型对古泽拉肉牛首次产犊年龄进行遗传评估。

Genetic evaluation of age at first calving for Guzerá beef cattle using linear, threshold, and survival Bayesian models.

机构信息

Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.

Department of Animal Science, Universidade Federal Rural da Amazonia, Capanema, Para, Brazil.

出版信息

J Anim Sci. 2018 Jun 29;96(7):2517-2524. doi: 10.1093/jas/sky112.

Abstract

Age at first calving (AFC) is characterized as a censored trait due to missing values provided by recording mistakes and nonoccurrence or delay in calving communication. In this context, we aimed to compare several statistical methods for genetic evaluation of AFC in Guzerá beef cattle under a Bayesian approach. Seven different methods were used for this purpose. The traditional linear mixed model (LM), which considers only uncensored records; the LM with simulated records (SM), which is based on data augmentation framework; the penalty method, in which a constant of 21 d was added to censored records; the bivariate threshold-linear method considering (TLcens) or not (TLmiss) censored information; and the piecewise Weibull proportional hazards model considering (PWPHcens) or not (PWPH) censored records. Heritability estimates ranged from 0.19 (TLcens) to 0.28 (SM) in nonsurvival approaches; and 0.40 and 0.46 to PWPH and PWPHcens methods, respectively. In general, breeding values correlations between different methods and the percentage of selected bulls in common indicated reranking, with these correlation ranging from -0.28 (between SM and PWPH) to 0.99 (between TLmiss and LM). The traditional LM, which considers only uncensored records, should be preferred due to its robustness and simplicity. Based on cross-validation analyses, we conclude that the TLmiss could be also a suitable alternative for breeding value prediction, and censored methods did not improve the analysis.

摘要

初配年龄(AFC)被视为一种删失性状,这是由于记录错误以及配种信息缺失或延迟导致的。在此背景下,我们旨在贝叶斯框架下比较几种用于评估 Guzerá 肉牛 AFC 的统计方法。为此目的,我们使用了七种不同的方法。传统的线性混合模型(LM)仅考虑非删失记录;基于数据扩充框架的模拟记录线性混合模型(SM);对删失记录添加 21 天常数的惩罚方法;考虑或不考虑删失信息的双变量门限线性方法(TLcens 和 TLmiss);以及考虑或不考虑删失记录的分段 Weibull 比例风险模型(PWPHcens 和 PWPH)。非生存方法的遗传力估计值范围为 0.19(TLcens)至 0.28(SM);生存方法的遗传力估计值范围为 0.40 和 0.46 至 PWPH 和 PWPHcens 方法。一般来说,不同方法之间的育种值相关性和共同选择的公牛百分比表明了重新排序,这些相关性范围从 -0.28(SM 和 PWPH 之间)到 0.99(TLmiss 和 LM 之间)。仅考虑非删失记录的传统 LM 因其稳健性和简单性而应优先考虑。基于交叉验证分析,我们得出结论,TLmiss 也可以作为一种用于预测育种值的合适替代方法,并且删失方法并没有改进分析。

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