Models of random regressions for the estimation of genetic parameters and studies of lactation curves of the Holstein in Cuba
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Abstract
individual records of the weighting at the first lactation from 357 cows of the Holstein breed were analyzed. The animals were from an enterprise of Havana province, Cuba, and the records were from the period 1999-2008. Ten different Models of Random Regressions (MRR)
were compared with the application of the orthogonal polynomials of Legendre. Among the fixed effects, it was included the combined
effect herd-weighting year-weighting month and the fixed curve of order 4. As random, the additive genetic effect and that of the permanent
environment were considered. The calving age was evaluated as covariable. Thirty-one classes of lactation days (with interval of 10 d) were considered for a total of 310 d. The model of Ali and Schaeffer was the one that characterized the best the lactation curve with included effects (with slight peak at 35 d, with 10.66kg/d). The best variance structure was that of order 5. The most adequate model of random regression was that considering the polynomial of Legendre of degree 3 for the additive genetic effect, and of degree 6 for the permanent environment. The highest values of heritability (0.12-0.26) were attained between 20 and 145 d. The genetic correlations ranged from 0.52 to 1, and were stronger at the beginning and middle of the lactation. It is concluded that the MRR are an efficient way of estimating parameters and genetic variations. In this study, the use of heterogeneous residual variances was more adequate to model the milk yield at the control day.
Key words: random regressions, control day, polynomials of Legendre, Holstein.
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