Genetic trends in the expected progeny difference of the asymptotic weight of Nelore females

Abstract

There are few studies on weight covering the full life cycle of Zebu cattle, and there is no entire growth description or mean growth pattern for animals belonging to this breed. In order to provide such data, 1,158 Nelore females born between 1985 and 1995 were weighed 14,563 times from birth to full growth maturity, in ten herds spread over seven Brazilian states. The Von Bertalanffy, Brody, logistic and Gompertz non-linear models were used to obtain the asymptotic weights (A) and the maturation rates (K). The (co)variance and breeding value components for A and K were obtained by using the multiple trait derivative free restricted maximum likelihood method under the animal model. Genetic trends were calculated in function of the mean expected progeny differences (EPD) for the trait (A or K) divided by the number of animals according to their year of birth. The genetic trends of the expected progeny difference with reference to the date of birth of the cows were, on average, -6.5g y -1 for A and 2.0g y -1 for K, close to zero as confirmed by the low (0.0023 to 0.003) coefficient of regression values. The curve parameters are recommended as a selection criterion to reach precocity and avoid adult weight increase in the female herd.

Growth Curve Prediction of Holstein-Fresian Bulls Using Different Non-Linear Model Functions

“…Growth curve study in cattle has mainly used non-linear models that relate the animal weights to ages (Garnero et al, 2006;Forni et al, 2009;Souza et al, 2010).…”

Nonlinear models for fitting growth curves of Nellore cows reared in the Amazon Biome

“…Growth curve study in cattle has mainly used non-linear models that relate the animal weights and ages (Garnero et al, 2006;Forni et al, 2009;Souza et al, 2010). The advantages of growth curves in animal production include: a) summarizing, in three or four parameters, the most important characteristics of the population, because some parameters of the non-linear models used have biological interpretation; b) assessing the treatment response profile over time; c) identifying the heaviest animals at younger ages in a population by investigating the relationship between growth curve parameter K and the limit weight of the animal or asymptotic weight (A); and d) obtaining the individual within and among variance, that is of great interest in genetic assessments (Freitas, 2005).…”