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Genetic modelling of daily milk yield using orthogonal polynomials in random regression

Data comprising 68,523 test day milk yield of 8,536 cows of the Holstein breed, daughters of 537 sires, distributed in 266 herds, calving from 1996 to 2001, were used to compare random regression models, for estimating variance. Test day records (TD) were analyzed by different random regression models regarding the function used to describe the trajectory of the lactation curve of the animals. Legendre orthogonal polynomials function of second, third and fourth order were used. The random regression models included the effects of herd-month-year of the control, genetic group of the animals; the frequency of the daily milk; regression coefficients for each class of age-season (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and the permanent environmental effects. The heritability estimates obtained using the random regression models ranged from 0.122 to 0.291. The random regression model which used the fourth order Legendre polynomials was the model which better described the genetic variation of the milk yield, according to AIC test.

genetic parameters; heritability


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