Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling

Detalhes bibliográficos
Autor(a) principal: Nobre,P.R.C.
Data de Publicação: 2003
Outros Autores: Lopes,P.S., Torres,R.A., Silva,L.O.C., Regazzi,A.J., Torres Júnior,R.A.A., Misztal,I.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Arquivo brasileiro de medicina veterinária e zootecnia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-09352003000400015
Resumo: Growth curves of Nellore cattle were analyzed using body weights measured at ages ranging from 1 day (birth weight) to 733 days. Traits considered were birth weight, 10 to 110 days weight, 102 to 202 days weight, 193 to 293 days weight, 283 to 383 days weight, 376 to 476 days weight, 551 to 651 days weight, and 633 to 733 days weight. Two data samples were created: one with 79,849 records from herds that had missing traits and another with 74,601 from herds with no missing traits. Records preadjusted to a fixed age were analyzed by a multiple trait model (MTM), which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were carried out by a Bayesian method for all nine traits. The random regression model (RRM) included the effects of age of animal, contemporary group, age of dam class, additive direct, permanent environment, additive maternal, and maternal permanent environment. Legendre cubic polynomials were used to describe random effects. MTM estimated covariance components and genetic parameters for birth weight and sequential weights and RRM for all ages. Due to the fact that covariance components based on RRM were inflated for herds with missing traits, MTM should be used and converted to covariance functions.
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spelling Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs samplingbeef cattlemultiple traitrandom regressionGrowth curves of Nellore cattle were analyzed using body weights measured at ages ranging from 1 day (birth weight) to 733 days. Traits considered were birth weight, 10 to 110 days weight, 102 to 202 days weight, 193 to 293 days weight, 283 to 383 days weight, 376 to 476 days weight, 551 to 651 days weight, and 633 to 733 days weight. Two data samples were created: one with 79,849 records from herds that had missing traits and another with 74,601 from herds with no missing traits. Records preadjusted to a fixed age were analyzed by a multiple trait model (MTM), which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were carried out by a Bayesian method for all nine traits. The random regression model (RRM) included the effects of age of animal, contemporary group, age of dam class, additive direct, permanent environment, additive maternal, and maternal permanent environment. Legendre cubic polynomials were used to describe random effects. MTM estimated covariance components and genetic parameters for birth weight and sequential weights and RRM for all ages. Due to the fact that covariance components based on RRM were inflated for herds with missing traits, MTM should be used and converted to covariance functions.Universidade Federal de Minas Gerais, Escola de Veterinária2003-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-09352003000400015Arquivo Brasileiro de Medicina Veterinária e Zootecnia v.55 n.4 2003reponame:Arquivo brasileiro de medicina veterinária e zootecnia (Online)instname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG10.1590/S0102-09352003000400015info:eu-repo/semantics/openAccessNobre,P.R.C.Lopes,P.S.Torres,R.A.Silva,L.O.C.Regazzi,A.J.Torres Júnior,R.A.A.Misztal,I.eng2003-11-12T00:00:00Zoai:scielo:S0102-09352003000400015Revistahttps://www.scielo.br/j/abmvz/PUBhttps://old.scielo.br/oai/scielo-oai.phpjournal@vet.ufmg.br||abmvz.artigo@abmvz.org.br1678-41620102-0935opendoar:2003-11-12T00:00Arquivo brasileiro de medicina veterinária e zootecnia (Online) - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
title Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
spellingShingle Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
Nobre,P.R.C.
beef cattle
multiple trait
random regression
title_short Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
title_full Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
title_fullStr Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
title_full_unstemmed Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
title_sort Analyses of growth curves of Nellore cattle by Bayesian method via Gibbs sampling
author Nobre,P.R.C.
author_facet Nobre,P.R.C.
Lopes,P.S.
Torres,R.A.
Silva,L.O.C.
Regazzi,A.J.
Torres Júnior,R.A.A.
Misztal,I.
author_role author
author2 Lopes,P.S.
Torres,R.A.
Silva,L.O.C.
Regazzi,A.J.
Torres Júnior,R.A.A.
Misztal,I.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Nobre,P.R.C.
Lopes,P.S.
Torres,R.A.
Silva,L.O.C.
Regazzi,A.J.
Torres Júnior,R.A.A.
Misztal,I.
dc.subject.por.fl_str_mv beef cattle
multiple trait
random regression
topic beef cattle
multiple trait
random regression
description Growth curves of Nellore cattle were analyzed using body weights measured at ages ranging from 1 day (birth weight) to 733 days. Traits considered were birth weight, 10 to 110 days weight, 102 to 202 days weight, 193 to 293 days weight, 283 to 383 days weight, 376 to 476 days weight, 551 to 651 days weight, and 633 to 733 days weight. Two data samples were created: one with 79,849 records from herds that had missing traits and another with 74,601 from herds with no missing traits. Records preadjusted to a fixed age were analyzed by a multiple trait model (MTM), which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were carried out by a Bayesian method for all nine traits. The random regression model (RRM) included the effects of age of animal, contemporary group, age of dam class, additive direct, permanent environment, additive maternal, and maternal permanent environment. Legendre cubic polynomials were used to describe random effects. MTM estimated covariance components and genetic parameters for birth weight and sequential weights and RRM for all ages. Due to the fact that covariance components based on RRM were inflated for herds with missing traits, MTM should be used and converted to covariance functions.
publishDate 2003
dc.date.none.fl_str_mv 2003-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-09352003000400015
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-09352003000400015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0102-09352003000400015
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais, Escola de Veterinária
publisher.none.fl_str_mv Universidade Federal de Minas Gerais, Escola de Veterinária
dc.source.none.fl_str_mv Arquivo Brasileiro de Medicina Veterinária e Zootecnia v.55 n.4 2003
reponame:Arquivo brasileiro de medicina veterinária e zootecnia (Online)
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Arquivo brasileiro de medicina veterinária e zootecnia (Online)
collection Arquivo brasileiro de medicina veterinária e zootecnia (Online)
repository.name.fl_str_mv Arquivo brasileiro de medicina veterinária e zootecnia (Online) - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv journal@vet.ufmg.br||abmvz.artigo@abmvz.org.br
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