Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.

Detalhes bibliográficos
Autor(a) principal: CAVALCANTE, D. H.
Data de Publicação: 2020
Outros Autores: SOUSA JÚNIOR, S. C., SILVA, L. P., MALHADO, C. H. M., MARTINS FILHO, R., AZEVEDO, D. M. M. R., CAMPELO, J. E. G.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1123435
Resumo: Different polynomial functions were tested for mean trajectory modeling with different residual variance structures. A total of 15,148 weight records of 3,115 Nellore Mocho cattle with ages between 1 and 660 days, raised in northern Brazil. First, the mean trajectory of cattle growth curve was fitted by a fixed regression using orthogonal polynomials with orders ranging from two to seven. Analyses were performed using the least-squares method, disregarding animal and/ or maternal random effects. Then, the best model was evaluated using different residual variance structures and homogeneous and heterogeneous classes. We considered as fixed effects those of groups of contemporary and of dam age at birth (as linear and quadratic covariate). The random model part included animal and maternal effects (direct genetic and permanent environments). We concluded that the estimates of variance components and genetic parameters were affected by both fixed regression curve polynomial order and residual variance structure. Moreover, random regression model considering an order-four polynomial function with a fixed curve and six-class residual variance showed better fits.
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spelling Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.Curva médiaModelagem residualModelo linearParâmetro GenéticoRegressão LinearLinear modelsDifferent polynomial functions were tested for mean trajectory modeling with different residual variance structures. A total of 15,148 weight records of 3,115 Nellore Mocho cattle with ages between 1 and 660 days, raised in northern Brazil. First, the mean trajectory of cattle growth curve was fitted by a fixed regression using orthogonal polynomials with orders ranging from two to seven. Analyses were performed using the least-squares method, disregarding animal and/ or maternal random effects. Then, the best model was evaluated using different residual variance structures and homogeneous and heterogeneous classes. We considered as fixed effects those of groups of contemporary and of dam age at birth (as linear and quadratic covariate). The random model part included animal and maternal effects (direct genetic and permanent environments). We concluded that the estimates of variance components and genetic parameters were affected by both fixed regression curve polynomial order and residual variance structure. Moreover, random regression model considering an order-four polynomial function with a fixed curve and six-class residual variance showed better fits.Diego Helcias Cavalcante, UFPI, Bom Jesus, PI.; Severino Cavalcante Sousa Júnior, UFPI, Parnaíba, PI; Luciano Pinheiro Silva, UFC, Fortaleza, CE; Carlos Henrique Mendes Malhado, UESB, Jequié, BA; Raimundo Martins Filho, UFCA, Juazeiro do Norte, CE; DANIELLE MARIA MACHADO R AZEVEDO, CPAMN; José Elivalto Guimarães Campelo, UFPI, Teresina, PI.CAVALCANTE, D. H.SOUSA JÚNIOR, S. C.SILVA, L. P.MALHADO, C. H. M.MARTINS FILHO, R.AZEVEDO, D. M. M. R.CAMPELO, J. E. G.2020-06-24T11:11:20Z2020-06-24T11:11:20Z2020-06-232020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleSemina: Ciências Agrárias, v. 41, n. 2, p. 545-558, mar./abr. 2020.1679-0359http://www.alice.cnptia.embrapa.br/alice/handle/doc/112343510.5433/1679-0359.2020v41n2p545enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2020-06-24T11:11:27Zoai:www.alice.cnptia.embrapa.br:doc/1123435Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542020-06-24T11:11:27falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542020-06-24T11:11:27Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
title Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
spellingShingle Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
CAVALCANTE, D. H.
Curva média
Modelagem residual
Modelo linear
Parâmetro Genético
Regressão Linear
Linear models
title_short Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
title_full Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
title_fullStr Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
title_full_unstemmed Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
title_sort Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
author CAVALCANTE, D. H.
author_facet CAVALCANTE, D. H.
SOUSA JÚNIOR, S. C.
SILVA, L. P.
MALHADO, C. H. M.
MARTINS FILHO, R.
AZEVEDO, D. M. M. R.
CAMPELO, J. E. G.
author_role author
author2 SOUSA JÚNIOR, S. C.
SILVA, L. P.
MALHADO, C. H. M.
MARTINS FILHO, R.
AZEVEDO, D. M. M. R.
CAMPELO, J. E. G.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Diego Helcias Cavalcante, UFPI, Bom Jesus, PI.; Severino Cavalcante Sousa Júnior, UFPI, Parnaíba, PI; Luciano Pinheiro Silva, UFC, Fortaleza, CE; Carlos Henrique Mendes Malhado, UESB, Jequié, BA; Raimundo Martins Filho, UFCA, Juazeiro do Norte, CE; DANIELLE MARIA MACHADO R AZEVEDO, CPAMN; José Elivalto Guimarães Campelo, UFPI, Teresina, PI.
dc.contributor.author.fl_str_mv CAVALCANTE, D. H.
SOUSA JÚNIOR, S. C.
SILVA, L. P.
MALHADO, C. H. M.
MARTINS FILHO, R.
AZEVEDO, D. M. M. R.
CAMPELO, J. E. G.
dc.subject.por.fl_str_mv Curva média
Modelagem residual
Modelo linear
Parâmetro Genético
Regressão Linear
Linear models
topic Curva média
Modelagem residual
Modelo linear
Parâmetro Genético
Regressão Linear
Linear models
description Different polynomial functions were tested for mean trajectory modeling with different residual variance structures. A total of 15,148 weight records of 3,115 Nellore Mocho cattle with ages between 1 and 660 days, raised in northern Brazil. First, the mean trajectory of cattle growth curve was fitted by a fixed regression using orthogonal polynomials with orders ranging from two to seven. Analyses were performed using the least-squares method, disregarding animal and/ or maternal random effects. Then, the best model was evaluated using different residual variance structures and homogeneous and heterogeneous classes. We considered as fixed effects those of groups of contemporary and of dam age at birth (as linear and quadratic covariate). The random model part included animal and maternal effects (direct genetic and permanent environments). We concluded that the estimates of variance components and genetic parameters were affected by both fixed regression curve polynomial order and residual variance structure. Moreover, random regression model considering an order-four polynomial function with a fixed curve and six-class residual variance showed better fits.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-24T11:11:20Z
2020-06-24T11:11:20Z
2020-06-23
2020
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Semina: Ciências Agrárias, v. 41, n. 2, p. 545-558, mar./abr. 2020.
1679-0359
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1123435
10.5433/1679-0359.2020v41n2p545
identifier_str_mv Semina: Ciências Agrárias, v. 41, n. 2, p. 545-558, mar./abr. 2020.
1679-0359
10.5433/1679-0359.2020v41n2p545
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1123435
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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