Variance components and genetic parameters for milk production of Holstein cattle in Antioquia (Colombia) using random regression models¤

Background: genetic parameters of lactation curve in dairy cattle can be analyzed as longitudinal data using random regression models (RRM). Objective: the goal of the present study was to estimate variance components and genetic parameters for milk production in Holstein cattle located in Antioquia province using RRM. Methods: a total of 3,158 monthly controls corresponding to 741 first lactations of Holstein cows were evaluated. The RRM included several Legendre polynomials to estimate the population fixed-curve coefficients and to predict the direct additive genetic and the permanent environment effects. Additionally, heterogeneous residual variances were considered by grouping the days in milk into 5 and 10 classes. Eleven models with first to fourth order polynomials were used to describe the direct additive genetic and the permanent environment effects. The residue was modeled by considering five variance classes. Models were compared using Schwartz Bayesian and Akaike’s information criteria. Results: the best model was obtained by fourth order Legendre polynomials to estimate the fixed curve of the population, genetic and permanent environment effects. In addition, 5 kinds of days were used to model the residual variances. The variance for the animal genetic, phenotypic, permanent environment, and residual effects decreased as days increased. Milk production heritability in early lactation was 0.36, increasing until 95 days (0.41), with subsequent decrease, reaching 0.10 at 245 days. The permanent environment variance values decreased to 125 days (0.13) and then increased to 215 days (0.21), to finish at the last stage of lactation with values of 0.05. The genetic and phenotypic correlations between milk yields at different days of lactation decreased as days intervals