Data comprising 68,523 test day milk yield of 8,536 cows of the Holstein breed, calving from 1996 to 2001, were used to compare random regression models, for estimating variance components. Test day records (TD) were analyzed as multiple traits, considering each TD as a different trait. The test day records were analyzed as longitudinal traits by different random regression models regarding the function used to describe the trajectory of the lactation curve of the animals. The Wilmink's exponential function, the Ali and Schaeffer logarithmic function and the Legendre orthogonal polynomials of second and fourth order were used. The comparisons among the models were based on the following criteria: estimates of variance components of the multiple-trait model and random regressions models, values of residual variance and values of the logarithms of the likelihood functions. The heritability estimates obtained using the multiple-trait model varied from 0.110 to 0.244, for the random regression models the values ranged from 0.127 to 0.301, being the largest estimates observed in the models with larger number of parameters. The random regression models which used the Legendre polynomials was the model which better described the genetic variation of the milk yield.
genetic evaluation; milk yield; random regression
