# Optimized Animal Models for the Genetic Evaluation of Conformation Traits, Milking Ease, and Milking Temperament in Dairy Gir Cattle

## TL;DR

This study improves genetic evaluation models for conformation and milking traits in Brazilian Dairy Gir cattle to boost productivity and economic returns.

## Contribution

The study identifies optimal statistical models for genetic evaluation of conformation and milking traits in Dairy Gir cattle.

## Key findings

- Models fitting only significant fixed effects and treating contemporary groups as random effects showed better performance.
- Linear models outperformed threshold models for most traits.
- Using parsimonious models reduces estimation error and improves genetic evaluation accuracy.

## Abstract

Enhancing the genetic evaluation of important traits can help increase productivity in dairy animals. This study focused on two groups of traits evaluated in Brazilian Dairy Gir cattle. Conformation traits, which describe the animal’s body and are linked to key production and health traits. Milking traits, which reflect the animals’ capacity to be milked and are especially important for zebu cattle, known for their responsiveness to the milking process. These traits are easy to measure, have moderate heritability, and are assessed early in the first lactation. The first step is to improve the statistical models used to estimate genetic parameters and breeding values. In this study, different models were tested to identify which provided the best goodness-of-fit, leading to the most suitable approach for evaluating conformation and milking traits. As a result, fitting only significant fixed effects in linear models and treating contemporary groups as random effects can be more advantageous for the genetic evaluation of conformation and milking traits in Dairy Gir cattle in Brazil. Implementing these findings in the genetic evaluation of the Dairy Gir breed can enhance genetic gains and ultimately improve farmers’ economic returns.

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.