Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) wh...

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Main Authors: A.A. Boligon, M.E.Z. Mercadante, R.B. Lôbo, F. Baldi, L.G. Albuquerque
Format: Article
Language:English
Published: Elsevier 2012-01-01
Series:Animal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1751731111001534
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author A.A. Boligon
M.E.Z. Mercadante
R.B. Lôbo
F. Baldi
L.G. Albuquerque
author_facet A.A. Boligon
M.E.Z. Mercadante
R.B. Lôbo
F. Baldi
L.G. Albuquerque
author_sort A.A. Boligon
collection DOAJ
description The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.
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spelling doaj.art-eb9185f76e2842a5915473c1c80c6f832022-12-21T18:22:47ZengElsevierAnimal1751-73112012-01-0162212220Random regression analyses using B-spline functions to model growth of Nellore cattleA.A. Boligon0M.E.Z. Mercadante1R.B. Lôbo2F. Baldi3L.G. Albuquerque4Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, CEP 14884-900, São Paulo, BrazilInstituto de Zootecnia, Estação Experimental de Zootecnia de Sertãozinho, 14160-000 Sertãozinho, São Paulo, BrazilDepartamento de Genética, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14049-900 Ribeirão Preto, São Paulo, BrazilDepartamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, CEP 14884-900, São Paulo, BrazilDepartamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, CEP 14884-900, São Paulo, BrazilThe objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.http://www.sciencedirect.com/science/article/pii/S1751731111001534growth curvecovariance functionssegmented polynomialsNellore cattle
spellingShingle A.A. Boligon
M.E.Z. Mercadante
R.B. Lôbo
F. Baldi
L.G. Albuquerque
Random regression analyses using B-spline functions to model growth of Nellore cattle
Animal
growth curve
covariance functions
segmented polynomials
Nellore cattle
title Random regression analyses using B-spline functions to model growth of Nellore cattle
title_full Random regression analyses using B-spline functions to model growth of Nellore cattle
title_fullStr Random regression analyses using B-spline functions to model growth of Nellore cattle
title_full_unstemmed Random regression analyses using B-spline functions to model growth of Nellore cattle
title_short Random regression analyses using B-spline functions to model growth of Nellore cattle
title_sort random regression analyses using b spline functions to model growth of nellore cattle
topic growth curve
covariance functions
segmented polynomials
Nellore cattle
url http://www.sciencedirect.com/science/article/pii/S1751731111001534
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