遗传力
统计
阿卡克信息准则
特质
方差分量
拟合优度
动物模型
数学
马
遗传相关
兽医学
人口学
医学
遗传变异
生物
内科学
人口
计算机科学
遗传学
社会学
古生物学
程序设计语言
作者
Jennifer Doyle,Alan G. Fahey
标识
DOI:10.1093/jas/skac247.011
摘要
Abstract The current genetic evaluations of the Irish Sport Horse are undertaken on a single trait called the Lifetime Performance Rating (LPR). The LPR represents the highest level a horse has achieved two double clear rounds in show jumping in both national and international performances. The objective of this study was to compare the method currently used in these evaluations (Model 1, Table 1) to a modified methodology to determine the most accurate method for estimating breeding values (EBV) for the LPR. Genetic parameters and EBVs were generated based on the LPR of 30,355 horses using eight different animal models. Each of the eight models considered the additive genetic variance as the random effect and a combination of following fixed effects: sex, year the highest level was first achieved, age the highest level was achieved, maximum age of the animal in the competition data, Thoroughbred percentage (TB%), and TB% divided into eights. (Table 1). The goodness-of-fit of each model was evaluated using the Akaike’s information criteria and the genetic parameters produced by each model. Heritability estimates for LPR ranged from 0.26 to 0.32 depending on the model used (Table 1). The inclusion of age or maximum age in the model decreased the residual variances, and thus, increased the heritability estimates of LPR; these models also performed better than those that did not consider age in any form. The models that considered the effect of TB% were not a significantly better fit than those that did not consider this effect. In conclusion, future genetic evaluations of LPR in the Irish Sport Horse would benefit from using a model that considers either the age or maximum age of performance of each horse, alongside the year the highest level was achieved, and the sex of the horse.
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