Estimates of genetic parameters for milk yield and persistency of lactation of Gyr cows, applying random regression models

Data consisting of 2,440 first lactations of Gyr cows calving between 1990 and 2005 were used to estimate genetic parameters of monthly test-day milk yield (TDMY). Records were analyzed by random regression models (MRA) that included the additive genetic and permanent environmental random effects and the contemporary group, age of cow at calving (linear and quadratic components) and the average trend of the population as fixed effects. Random trajectories were fitted by Wilmink's (WIL) and Ali & Schaeffer's (AS) parametric functions. Residual variances were fitted by step functions with 1, 4, 6 or 10 classes. The contemporary group was defined by herd-year-season of test-day and included at least three animals. Models were compared by Akaike's and Schwarz's Bayesian (BIC) information criterion. The AS function used for modeling the additive genetic and permanent environmental effects with heterogeneous residual variances adjusted with a step function with four classes was the best fitted model. Heritability estimates ranged from 0.21 to 0.33 for the AS function and from 0.17 to 0.30 for WIL function and were larger in the first half of the lactation period. Genetic correlations between TDMY were high and positive for adjacent test-days and decreased as days between records increased. Predicted breeding values for total 305-day milk yield (MRA305) and specific periods of lactation (obtained by the mean of all breeding values in the periods) using the AS function were compared with that predicted by a standard model using accumulated 305-day milk yield (PTA305) by rank correlation. The magnitude of correlations suggested differences may be observed in ranking animals by using the different criteria which were compared in this study.