Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model
1 Embrapa Cerrado / Capes, Road GO-462, km 12, Rural Area, PO Box 179, CEP: 75375-000, Santo Antônio de Goiás, Brazil
2 Embrapa Cerrado/CNPq, Brasília, DF, Brazil
3 Program in Animal Biology, Universidade de Brasília, Brasília, DF, Brazil
4 Program in Animal Science, Federal University of Goiás, Goiânia, GO, Brazil
5 Brazilian Society of Breeders and Researchers, Ribeirão Preto, São Paulo, Brazil
SpringerPlus 2012, 1:49 doi:10.1186/2193-1801-1-49Published: 20 November 2012
This study was carried out to estimate (co)variance components and genetic parameters for live weight of Nellore cattle from Performance Test of Young Bulls using random regression models. Data of weights and ages of 925 weaned males was used. The animal model included the fixed effect of contemporary group, age of the animal at weighing as a covariate and as random effects it was considered the effect of additive genetic and permanent environment of the animal. The residue was modeled considering four classes of variances. The models were compared based on the Bayesian information criteria of Akaike and Schwartz. The model polynomial of fourth and sixth order for the direct additive genetic effects and permanent environment of the animal, respectively was the most appropriate to describe the changes in the variances of the weights during the period in which the animals participating in the performance test young bulls. Heritability estimates showed moderate magnitudes and indicated that direct selection will promote improvement of selection criteria adopted. Furthermore, due to high positive correlation between the estimated weights, it was suggested selecting the best animals before at 365 days of age, because it is the period in which the animals have a higher growth rate and thus you can select animals heavier and less delayed.