Random regression analyses using B-spline functions to model growth of Nellore cattle
被引:18
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作者:
Boligon, A. A.
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Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, Brazil
Boligon, A. A.
[1
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Mercadante, M. E. Z.
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Estacao Expt Zootecnia Sertaozinho, Inst Zootecnia, BR-14160000 Sao Paulo, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, Brazil
Mercadante, M. E. Z.
[2
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Lobo, R. B.
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Univ Sao Paulo, Dept Genet, Fac Med Ribeirao Preto, BR-14049900 Sao Paulo, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, Brazil
Lobo, R. B.
[3
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Baldi, F.
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Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, Brazil
Baldi, F.
[1
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Albuquerque, L. G.
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Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, Brazil
Albuquerque, L. G.
[1
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机构:
[1] Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Sao Paulo, Brazil
[2] Estacao Expt Zootecnia Sertaozinho, Inst Zootecnia, BR-14160000 Sao Paulo, Brazil
[3] Univ Sao Paulo, Dept Genet, Fac Med Ribeirao Preto, BR-14049900 Sao Paulo, Brazil
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.
机构:
Univ New England, Anim Genet & Breeding Unit, Armidale, NSW 2351, AustraliaUniv New England, Anim Genet & Breeding Unit, Armidale, NSW 2351, Australia
机构:University of New England,Animal Genetics and Breeding Unit (AGBU is a joint venture between the NSW Department of Primary Industries and the University of New England.)
机构:
Univ Sao Paulo, ESALQ, Programa Posgrad Estat & Expt Agron, BR-13418900 Piracicaba, SP, Brazil
UFMS, Depto Ciencias Exatas, BR-79620080 Tres Lagoas, MS, BrazilUniv Sao Paulo, ESALQ, Depto Ciencias Exatas, BR-13418900 Piracicaba, SP, Brazil
Macedo, Osmar Jesus
Barbin, Decio
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Univ Sao Paulo, ESALQ, Depto Ciencias Exatas, BR-13418900 Piracicaba, SP, BrazilUniv Sao Paulo, ESALQ, Depto Ciencias Exatas, BR-13418900 Piracicaba, SP, Brazil
Barbin, Decio
Mourao, Gerson Barreto
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Univ Sao Paulo, ESALQ, Depto Ciencias Exatas, BR-13418900 Piracicaba, SP, BrazilUniv Sao Paulo, ESALQ, Depto Ciencias Exatas, BR-13418900 Piracicaba, SP, Brazil