Inferência bayesiana sobre parâmetros genéticos de bovinos da raça Girolando

Abstract

This study aimed to estimate genetic parameters associated with milk production in Girolando cattle, using a Bayesian model with the Hamiltonian Monte Carlo (HMC) sampler, implemented through the rstan package in the R software. The dataset used comprises 295 unique animals, totaling 485 observations. The results showed that the estimated heritability was 0.235, with a HPD interval (Highest Posterior Density) from 0.09 to 0.38, suggesting that approximately 23.5% of the variability in milk production is explained by genetic factors, although environmental and management factors also play an important role. The analysis of fixed effects indicated that the blood compositions 5/8H, 3/4H, and 1/2H had the greatest impactson production, suggesting that these genetic compositions have greater potential for improving milk yield. The fractions above indicate the Holstein (H) blood percentage in crosses with the Gir breed. The objectives of the study were successfully achieved, as it was possible to estimate the heritability of milk production and identify the blood compositions with the greatest productive impact, providing support for genetic selection strategies in the herd. As a future perspective, it is recommended to include other fixed-effect variables and more detailed pedigree information to improve the analysis of productive performance, considering both genetic and non-genetic effects.