Genetic parameters for post weaning growth of Nellore cattle using polinomyals and trigonometric functions in random regression models

Abstract

Covariance functions and random regression models have been considered as an alternative for data adjustment, in sequence, stemming from the same animal along time and which presents a structured pattern of covariance. Aiming to evaluate the performance of random regression models based on the Legendre, modified Jacobi and trigonometric functions, data concerning the weights of Nellore breed animals were used from birth to the 800 th day of life, in models that assumed direct additive and animal permanent environmental effects coefficients. The Schwarz Bayesian information criterion (BIC) led to the selection of the models Legendre of order six (ML6), Jacobi of order five (MJ5) and trigonometric of order six (MT6), the ML6 model presenting the lowest BIC. At the extremity of the interval, the MJ5 model presented lower variance of component estimates than those obtained through the ML6 model, however the estimates were in accordance to the medium part of the interval; while the estimates from the MT6 model were oscillating and different from those obtained through the other models. At the extremity of the interval, the heritability coefficient estimates ( ) obtained through the MJ5 model were lower than those obtained through the ML6 model, however, in the medium part of the interval, they were in accordance, remaining between 0.2 and 0.3. The values obtained through the MT6 model were different from those obtained through the other models, remaining between 0.35 and 0.40 on the first 285 th days and then dropping to 0.01 on the 800 th days of life. The means of the estimated growth curves started to distance from the data mean tendency from the 470 th days on, and in this interval, the MT6 model was the most suitable. Key words: additive variance, heritability, Jacobi, Legendre, longitudinal data PARÂMETROS GENÉTICOS PARA CRESCIMENTO PÓS-DESMAME DE BOVINOS NELORE POR MEIO DE FUNÇÕES POLINOMIAIS E TRIGONOMÉTRICAS EM MODELOS DE REGRESSÃO ALEATÓRIARESUMO: O uso de funções de covariância e regressão aleatória tem sido considerado como uma alternativa para o ajuste de dados longitudinais com estrutura de covariância padrão, pois são mensurados no mesmo animal ao longo do tempo. Com objetivo de avaliar o desempenho dos modelos de regressão aleatória nas bases de funções de Legendre, de Jacobi modificada e as trigonométricas, os dados referentes aos pesos de animais da raça Nelore do nascimento aos 800 dias foram analisados com modelos que assumiram coeficientes de efeito aditivo direto e de ambiente permanente de animal. O critério de informação Bayesiano de Schwarz (BIC) conduziu a seleção dos modelos Legendre de ordem seis (ML6), Jacobi de ordem cinco (MJ5) e trigonométrica de ordem seis (MT6), dos quais, ML6 foi o modelo com o menor BIC. O modelo MJ5 apresentou estimativas de componentes de variância abaixo das estimativas obtidas pelo modelo ML6 nos extremos do intervalo e estimativas muito próximas no seu interior. Já as estimativas do modelo MT6 foram oscilantes e distintas das estimativas obtidas pelo...

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