This study aimed to evaluate four different models for the genetic evaluation of sixteen conformation traits, milking ease, and milking temperament in Dairy Gir cattle. The models vary based on whether they include only statistically significant fixed effects or all recorded effects, along with contemporary groups (CGs) treated as fixed or random effects. Categorical traits were also analyzed using a threshold model. The adjusted R-squared (Radj2) was used to compare the goodness-of-fit of the linear models. Spearman’s rank correlation and the average accuracy of bull estimated breeding values (EBVs) with at least 20 phenotyped daughters were compared. Models fitting CG as a random effect performed better based on their Radj2 values and had a greater average accuracy of EBVs for most traits. Spearman’s rank correlation coefficients indicated low to medium bull EBV re-ranking between most of the models. The linear models performed better than threshold models for almost all traits. When possible, more parsimonious linear models fitting only significant fixed effects should be used to reduce the standard error of estimation. Additionally, fitting CGs as a random effect seems more beneficial for the genetic evaluation of conformation and milking traits in Dairy Gir cattle in Brazil.
Cunha et al. (Fri,) studied this question.