[en] We aimed to evaluate different orders of fixed and random effects in random regression models (RRM) based on Legendre orthogonal polynomials as well as to verify the feasibility of these models to describe growth curves in Nellore cattle. The proposed RRM were also compared to multi-trait models (MTM). Variance components and genetic parameters estimates were performed via REML for all models. Twelve RRM were compared through Akaike (AIC) and Bayesian (BIC) information criteria. The model of order three for the fixedcurve and four for all random effects (direct genetic, maternal genetic, permanent environment, and maternal permanent environment) fits best. Estimates of direct genetic, maternal genetic, maternal permanent environment, permanent environment, phenotypic and residual variances were similar between MTM and RRM. Heritability estimates were higher via RRM. We presented perspectives for the use of RRM for genetic evaluation of growth traits in Brazilian Nellore cattle. In general, moderate heritability estimates were obtained for the majority of studied traits when using RRM. Additionally, the precision of these estimates was higher when using RRM instead of MTM. However, concerns about the variance components estimates in advanced ages via Legendre polynomial must be taken into account in future studies.
Disciplines :
Animal production & animal husbandry
Author, co-author :
Bastos Teixeira, Bruno
REIS MOTA, Rodrigo ; Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Ingénierie des productions animales et nutrition
Barbosa Lôbo, Raysildo
Pinheiro da Silva, Luciano
Policarpo Souza Carneiro, Antônio
Gomes da Silva, Felipe
da Costa Caetano, Giovanni
Fonseca e Silva, Fabyano
Language :
English
Title :
Genetic Evaluation of Growth Traits in Nellore Cattle through Multi-trait and Random Regression Models
Publication date :
2018
Journal title :
Czech Journal of Animal Science
ISSN :
1212-1819
eISSN :
1805-9309
Publisher :
Czech Academy of Agricultural Sciences, Praha, Czechia
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