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dc.contributor.authorSavegnago, R. P.
dc.contributor.authorRosa, G. J M
dc.contributor.authorValente, B. D.
dc.contributor.authorHerrera, L. G G
dc.contributor.authorCarneiro, R. L R
dc.contributor.authorSesana, R. C.
dc.contributor.authorEl Faro, L.
dc.contributor.authorMunari, D. P.
dc.date.accessioned2014-05-27T11:30:42Z
dc.date.available2014-05-27T11:30:42Z
dc.date.issued2013-09-19
dc.identifierhttp://dx.doi.org/10.3168/jds.2013-6708
dc.identifier.citationJournal of Dairy Science.
dc.identifier.issn0022-0302
dc.identifier.issn1525-3198
dc.identifier.urihttp://hdl.handle.net/11449/76596
dc.description.abstractThe objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.en
dc.language.isoeng
dc.relation.ispartofJournal of Dairy Science
dc.sourceScopus
dc.subjecteigenvalue
dc.subjectLegendre polynomial
dc.subjectpersistency
dc.subjectrandom regression
dc.titleEstimates of genetic parameters and eigenvector indices for milk production of Holstein cowsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.identifier.doi10.3168/jds.2013-6708
dc.identifier.wosWOS:000325664800048
dc.rights.accessRightsAcesso restrito
dc.identifier.scopus2-s2.0-84883870660
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências Agrárias e Veterinárias, Jaboticabalpt
dc.identifier.lattes6064277731903249
unesp.author.lattes6064277731903249
dc.relation.ispartofjcr2.749
dc.relation.ispartofsjr1,350
dc.relation.ispartofsjr1,350
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