Genetic parameter estimates for live weight and daily live weight gain obtained for Nellore bulls in a test station using different models

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dc.contributor.authorBaldi, Fernando [UNESP]
dc.contributor.authorAlbuquerque, Lucia Galvão de [UNESP]
dc.contributor.authordos Santos Goncalves Cyrillo, Joslaine Noely
dc.contributor.authorBranco, Renata Helena
dc.contributor.authorde Oliveira Junior, Braz Costa
dc.contributor.authorZerlotti Mercadante, Maria Eugenia
dc.contributor.institutionCtr Pesquisa Pecuaria Corte
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionCATI SAA SP
dc.contributor.institutionNatl Council Technol & Sci Dev
dc.contributor.institutionINCT CA
dc.date.accessioned2014-05-20T13:19:12Z
dc.date.available2014-05-20T13:19:12Z
dc.date.issued2012-03-01
dc.description.abstractThe objective of this study was to estimate (co)variance components and genetic parameters for live weight (LW) and daily live weight gain (LWG) of Nellore bulls in a test station using multi-trait and random regression models. In addition, breeding values for these traits were predicted by multi-trait and random regression analyses, and the rank of animals based on breeding values was compared with the current selection criterion of the test station (own performance). A total of 4758 Nellore bulls tested in a central station of the Beef Cattle Research Center (CPPC) between 1978 and 2007, including 2211 bulls from the CPPC herd and 2547 from commercial herds, were used. During the test, four LWs were recorded at intervals of 56 days (LW1d, LW56d. LW112d and LW168d). LWG was calculated as the difference between two consecutive weights for three periods: 1 to 55 (LWG(1)), 56 to 111 (LWG(2)), and 112 to 168 (LWG(3)) days on test. For LW and LWG, the multi-trait model included the fixed effects of contemporary group (year-month of birth), dam age class, and animal age at recording as covariate. For random regression analysis, direct additive genetic and animal permanent environmental effects were modeled using linear, quadratic and cubic polynomial functions. Residual variances for LW and LWG were modeled using a step function with 1 or 3 classes, respectively. Contemporary group (year-month of birth and month of recording) and dam age class were included as fixed effects. The (co)variance components were estimated by the Restricted Maximum Likelihood method using the WOMBAT software. According to model comparison criterion, the model including cubic and quadratic Legendre polynomials to fit genetic and animal permanent environmental effects, respectively, was the most appropriate to describe the covariance structure of LW. For LWG, the BIC value indicated that the model including quadratic and linear Legendre polynomials was the most appropriate to fit genetic and animal permanent environmental effects, respectively. The variance component and genetic parameter estimates for LW and LWG obtained by random regression and multi-trait analyses were similar. Random regression on Legendre polynomials of days on test was more appropriate than multi-trait models to describe the genetic variation of growth traits in station-tested Nellore bulls. Selection based on breeding values for LWG during the test would result in the selection of bulls different from those chosen if final weight is applied as a selection criterion. (C) 2011 Elsevier B.V. All rights reserved.en
dc.description.affiliationCtr Pesquisa Pecuaria Corte, Inst Zootecnia, BR-14160000 Sertaozinho, SP, Brazil
dc.description.affiliationUNESP, Fac Ciencias Agr & Vet, BR-14884000 Jaboticabal, SP, Brazil
dc.description.affiliationCATI SAA SP, BR-16200043 Birigui, SP, Brazil
dc.description.affiliationNatl Council Technol & Sci Dev, CNPq Scholarship, BR-71605001 Brasilia, DF, Brazil
dc.description.affiliationINCT CA, BR-36570000 Vicosa, MG, Brazil
dc.description.affiliationUnespUNESP, Fac Ciencias Agr & Vet, BR-14884000 Jaboticabal, SP, Brazil
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.format.extent148-156
dc.identifierhttp://dx.doi.org/10.1016/j.livsci.2011.11.009
dc.identifier.citationLivestock Science. Amsterdam: Elsevier B.V., v. 144, n. 1-2, p. 148-156, 2012.
dc.identifier.doi10.1016/j.livsci.2011.11.009
dc.identifier.fileWOS000300807200018.pdf
dc.identifier.issn1871-1413
dc.identifier.lattes5866981114947883
dc.identifier.urihttp://hdl.handle.net/11449/4967
dc.identifier.wosWOS:000300807200018
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofLivestock Science
dc.relation.ispartofjcr1.204
dc.relation.ispartofsjr0,730
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectBeef cattleen
dc.subjectHeritabilityen
dc.subjectNellore breeden
dc.subjectPerformance testen
dc.subjectRank correlationen
dc.subjectRandom regression modelsen
dc.titleGenetic parameter estimates for live weight and daily live weight gain obtained for Nellore bulls in a test station using different modelsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
unesp.author.lattes5866981114947883
unesp.author.orcid0000-0002-2030-7590[2]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências Agrárias e Veterinárias, Jaboticabalpt
unesp.departmentZootecnia - FCAVpt

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Jaboticabal - FCAV - Faculdade de Ciências Agrárias e Veterinárias