Weight evaluation of Tabapuã cattle raised in northeastern Brazil using random-regression models

M.R Oliveira,R Martins Filho,C Malhado,D.M Azevêdo,L Pires,S Sousa Júnior

doi:10.1590/1678-4162-9070

Abstract

ABSTRACT The objective of this study is to compare random-regression models used to describe changes in evaluation parameters for growth in Tabapuã bovine raised in the Northeast of Brazilian. The M4532-5 random-regression model was found to be best for estimating the variation and heritability of growth characteristics in the animals evaluated. Estimates of direct additive genetic variance increased with age, while the maternal additive genetic variance demonstrated growth from birth to up to nearly 420 days of age. The genetic correlations between the first four characteristics were positive with moderate to large ranges. The greatest genetic correlation was observed between birth weight and at 240 days of age (0.82). The phenotypic correlation between birth weight and other characteristics was low. The M4532-5 random-regression model with 39 parameters was found to be best for describing the growth curve of the animals evaluated providing improved selection for heavier animals when performed after weaning. The interpretation of genetic parameters to predict the growth curve of cattle may allow the selection of animals to accelerate slaughter procedures.

Highlights

Brazil is a major producer of the world's food, with favorable climatic conditions and soil for livestock production, especially for cattle
Parameters, for example, that characterize the growth curve of animals, based on their weights at different ages are extremely useful. Such longitudinal data are commonly analyzed with infinite-dimensional models, such as random regression (MRA), as they monitor the average-growth curve of the
Considering the criteria of Akaike (AIC) and Bayesian Schwarz (BIC), the M4532-5 randomregression model that takes into account direct and maternal genetic and direct and maternal permanent environmental effects, respectively, with five classes of residual variance and 39 parameters, was considered the best fit model for description of estimates of variance and heritability of the growth characteristics of the animals evaluated (Table 2)

Summary

Introduction

Brazil is a major producer of the world's food, with favorable climatic conditions and soil for livestock production, especially for cattle. In 2012, the country possessed approximately 211 million animals, of which, around 140 million were suitable for meat production (Sistema..., 2012). The use of animal breeding tools is of importance, especially for the selection of geneticallysuperior animals with characteristics of economic importance. Parameters, for example, that characterize the growth curve of animals, based on their weights at different ages are extremely useful. Such longitudinal data are commonly analyzed with infinite-dimensional models, such as random regression (MRA), as they monitor the average-growth curve of the

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Results

Conclusion