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Polynomials to model the growth of young bulls in performance tests

Published online by Cambridge University Press:  10 January 2014

D. C. B. Scalez ,
B. O. Fragomeni ,
T. L. Passafaro ,
I. G. Pereira  and
F. L. B. Toral
D. C. B. Scalez
Affiliation:
Faculdade de Agronomia, Medicina Veterinária e Zootecnia, Universidade Federal de Mato Grosso, Avenida Fernando Correa da Costa, 2367, CEP 78060-900, Cuiabá/MT, Brazil
B. O. Fragomeni
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais (DZOO/EV/UFMG), Avenida Antônio Carlos, 6627, Caixa Postal 567, CEP 31270-901, Belo Horizonte/MG, Brazil.
T. L. Passafaro
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais (DZOO/EV/UFMG), Avenida Antônio Carlos, 6627, Caixa Postal 567, CEP 31270-901, Belo Horizonte/MG, Brazil.
I. G. Pereira
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais (DZOO/EV/UFMG), Avenida Antônio Carlos, 6627, Caixa Postal 567, CEP 31270-901, Belo Horizonte/MG, Brazil.
F. L. B. Toral*
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais (DZOO/EV/UFMG), Avenida Antônio Carlos, 6627, Caixa Postal 567, CEP 31270-901, Belo Horizonte/MG, Brazil.
*
†E-mail: flbtoral@ufmg.br
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Abstract

The use of polynomial functions to describe the average growth trajectory and covariance functions of Nellore and MA (21/32 Charolais+11/32 Nellore) young bulls in performance tests was studied. The average growth trajectories and additive genetic and permanent environmental covariance functions were fit with Legendre (linear through quintic) and quadratic B-spline (with two to four intervals) polynomials. In general, the Legendre and quadratic B-spline models that included more covariance parameters provided a better fit with the data. When comparing models with the same number of parameters, the quadratic B-spline provided a better fit than the Legendre polynomials. The quadratic B-spline with four intervals provided the best fit for the Nellore and MA groups. The fitting of random regression models with different types of polynomials (Legendre polynomials or B-spline) affected neither the genetic parameters estimates nor the ranking of the Nellore young bulls. However, fitting different type of polynomials affected the genetic parameters estimates and the ranking of the MA young bulls. Parsimonious Legendre or quadratic B-spline models could be used for genetic evaluation of body weight of Nellore young bulls in performance tests, whereas these parsimonious models were less efficient for animals of the MA genetic group owing to limited data at the extreme ages.

Keywords

B-splinesbeef cattlelegendrerandom regression
Type
Full Paper
Information
animal , Volume 8 , Issue 3 , March 2014 , pp. 370 - 378
Copyright
© The Animal Consortium 2014 

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