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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/111672
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dc.contributor.authorDiaz, I. D. P. S.-
dc.contributor.authorCrews, D. H.-
dc.contributor.authorEnns, R. M.-
dc.date.accessioned2014-12-03T13:08:53Z-
dc.date.accessioned2016-10-25T20:09:27Z-
dc.date.available2014-12-03T13:08:53Z-
dc.date.available2016-10-25T20:09:27Z-
dc.date.issued2014-06-01-
dc.identifierhttp://dx.doi.org/10.1111/jbg.12063-
dc.identifier.citationJournal Of Animal Breeding And Genetics. Hoboken: Wiley-blackwell, v. 131, n. 3, p. 217-226, 2014.-
dc.identifier.issn0931-2668-
dc.identifier.urihttp://hdl.handle.net/11449/111672-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/111672-
dc.description.abstractA data set based on 50 studies including feed intake and utilization traits was used to perform a meta-analysis to obtain pooled estimates using the variance between studies of genetic parameters for average daily gain (ADG); residual feed intake (RFI); metabolic body weight (MBW); feed conversion ratio (FCR); and daily dry matter intake (DMI) in beef cattle. The total data set included 128 heritability and 122 genetic correlation estimates published in the literature from 1961 to 2012. The meta-analysis was performed using a random effects model where the restricted maximum likelihood estimator was used to evaluate variances among clusters. Also, a meta-analysis using the method of cluster analysis was used to group the heritability estimates. Two clusters were obtained for each trait by different variables. It was observed, for all traits, that the heterogeneity of variance was significant between clusters and studies for genetic correlation estimates. The pooled estimates, adding the variance between clusters, for direct heritability estimates for ADG, DMI, RFI, MBW and FCR were 0.32 +/- 0.04, 0.39 +/- 0.03, 0.31 +/- 0.02, 0.31 +/- 0.03 and 0.26 +/- 0.03, respectively. Pooled genetic correlation estimates ranged from -0.15 to 0.67 among ADG, DMI, RFI, MBW and FCR. These pooled estimates of genetic parameters could be used to solve genetic prediction equations in populations where data is insufficient for variance component estimation. Cluster analysis is recommended as a statistical procedure to combine results from different studies to account for heterogeneity.en
dc.format.extent217-226-
dc.language.isoeng-
dc.publisherWiley-Blackwell-
dc.sourceWeb of Science-
dc.subjectGenetic parametersen
dc.subjectmultivariate analysisen
dc.subjectpooled estimatesen
dc.titleCluster and meta-analyses of genetic parameters for feed intake traits in growing beef cattleen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionColorado State Univ-
dc.description.affiliationState Univ Sao Paulo, Dept Anim Sci, Sao Paulo, Brazil-
dc.description.affiliationColorado State Univ, Dept Anim Sci, Ft Collins, CO 80523 USA-
dc.description.affiliationUnespState Univ Sao Paulo, Dept Anim Sci, Sao Paulo, Brazil-
dc.identifier.doi10.1111/jbg.12063-
dc.identifier.wosWOS:000335958000008-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofJournal of Animal Breeding and Genetics-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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