Genetic Parameters for Racing Performance of Thoroughbred Horses Using Bayesian Linear and Thurstonian Models

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dc.contributor.authorMonteiro da Gama, Manuela Pires
dc.contributor.authorAspilcueta Borquis, Rusbel Raul [UNESP]
dc.contributor.authorAraujo Neto, Francisco Ribeiro de
dc.contributor.authorOliveira, Henrique Nunes de [UNESP]
dc.contributor.authorFernandes, Gisele Machado
dc.contributor.authorSilveira da Mota, Marcilio Dias [UNESP]
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionInst Fed Goiano
dc.date.accessioned2018-11-26T16:48:14Z
dc.date.available2018-11-26T16:48:14Z
dc.date.issued2016-07-01
dc.description.abstractThe objective of this study was to estimate genetic parameters for rank in Thoroughbred horses using a Bayesian linear model (BLM) and a Thurstonian model (TM) to provide data that contribute to the selection and consequent genetic improvement of the breed in Brazil. Data were provided by the company Turf Total Ltda and consisted of 250,809 records for rank obtained from 40,300 horses and from 34,316 Thoroughbred races (distances of 1,000, 1,300, 1,600, and 2,000 m) that occurred between 1992 and 2011 on six tracks. The rank records at each distance were considered different traits and were submitted to single-trait analysis using BLM and TM. Fixed effects included sex, age, post-position, race, and level of difficulty. The heritability estimates for rank ranged from 0.228 to 0.032 when BLM was used and from 0.293 to 0.047 when TM was used. These estimates tended to decrease with increasing race distance in the two analyses. The TM estimated higher heritability for rank than BLM, indicating the possible use of this model in selection programs of Thoroughbred racehorses in Brazil. Published by Elsevier Inc.en
dc.description.affiliationUniv Sao Paulo, Fac Med Ribeirao Preto, Dept Genet, Ave Bandeirantes 3900, BR-14049900 Sao Paulo, Brazil
dc.description.affiliationUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Campus Jaboticabal, Sao Paulo, Brazil
dc.description.affiliationInst Fed Goiano, Dept Ciencia Anim, Campus Rio Verde, Rio Verde, Go, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Campus Jaboticabal, Sao Paulo, Brazil
dc.format.extent39-43
dc.identifierhttp://dx.doi.org/10.1016/j.jevs.2016.03.021
dc.identifier.citationJournal Of Equine Veterinary Science. New York: Elsevier Science Inc, v. 42, p. 39-43, 2016.
dc.identifier.doi10.1016/j.jevs.2016.03.021
dc.identifier.fileWOS000378818500007.pdf
dc.identifier.issn0737-0806
dc.identifier.urihttp://hdl.handle.net/11449/161682
dc.identifier.wosWOS:000378818500007
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofJournal Of Equine Veterinary Science
dc.relation.ispartofsjr0,390
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectEquine
dc.subjectHeritability
dc.subjectGibbs sampling
dc.subjectTMCLA
dc.titleGenetic Parameters for Racing Performance of Thoroughbred Horses Using Bayesian Linear and Thurstonian Modelsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.

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