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The comparison of standard and fully recursive multivariate models for genetic evaluation of growth traits in Markhoz goat: predictive ability of models and ranking of animals
The Journal of Agricultural Science ( IF 1.7 ) Pub Date : 2020-10-23 , DOI: 10.1017/s0021859620000830
Mohammad Razmkabir , Morteza Mokhtari , Peyman Mahmoudi , Amir Rashidi

Data of 2780 Markhoz kids originated from 1216 dams and 211 sires during 1993–2016 in Markhoz Goat Breeding Station, located in Sanandaj, Iran, were used. Traits investigated were body weights at birth, weaning, six-month age [six months weight (6MW)], nine-month age and yearling age [yearling weight (YW)]. Two considered multivariate models including standard multivariate model (SMM) and fully recursive multivariate model (FRM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values $(r(y,\hat{y}))$ of records. Spearman's rank correlation coefficients between posterior means of direct genetic effects of the studied traits of kids under SMM and FRM were also calculated across all, 50, 10 and 1% top-ranked animals. In general, FRM performed better than SMM in terms of lower DIC and MSE and also higher $r\lpar y\comma \;\hat{y}\rpar$. For all traits, the lowest MSE and the highest $r\lpar y\comma \;\hat{y}\rpar$ were obtained under FRM. All structural coefficients estimated under FRM were statistically significant except for that of 6MW on YW. Comparisons of Spearman's rank correlations between posterior means of direct genetic effects of kids for growth traits under SMM and FRM revealed that taking the causal relationships among the studied growth traits of Markhoz goat into account may cause considerable re-ranking for the animals in terms of estimated breeding values, especially for the top-ranked animals. It may be concluded that FRM had more plausibility over SMM for genetic evaluation of the studied growth traits in Markhoz goat.

中文翻译:

Markhoz山羊生长性状遗传评价的标准和完全递归多变量模型的比较:模型的预测能力和动物的排名

使用了 1993 年至 2016 年期间来自伊朗萨南达杰的 Markhoz 山羊繁育站的 1216 头母羊和 211 头公牛的 2780 名 Markhoz 孩子的数据。调查的性状是出生体重、断奶体重、六个月大[六个月体重(6MW)]、九个月大和一岁年龄[一岁体重(YW)]。使用偏差信息准则 (DIC) 和预测能力测量值(包括误差均方 (MSE) 和 Pearson 观察值与预测值之间的相关系数)比较了两个考虑的多变量模型,包括标准多变量模型 (SMM) 和完全递归多变量模型 (FRM)$(r(y,\hat{y}))$的记录。还计算了所有 50、10 和 1% 排名靠前的动物在 SMM 和 FRM 下研究的儿童性状的直接遗传效应的后验平均值之间的 Spearman 等级相关系数。一般而言,FRM 在 DIC 和 MSE 较低以及更高的方面表现优于 SMM$r\lpar y\逗号\;\hat{y}\rpar$. 对于所有性状,最低 MSE 和最高$r\lpar y\逗号\;\hat{y}\rpar$是在 FRM 下获得的。除了 YW 上的 6MW 之外,在 FRM 下估计的所有结构系数都具有统计学意义。比较 SMM 和 FRM 下儿童直接遗传效应后验均值对生长性状的 Spearman 等级相关性表明,考虑到所研究的 Markhoz 山羊生长性状之间的因果关系可能会导致动物在估计值方面进行相当大的重新排名育种价值,特别是对于排名靠前的动物。可以得出结论,对于 Markhoz 山羊所研究的生长性状的遗传评估,FRM 比 SMM 更合理。
更新日期:2020-10-23
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