Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
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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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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1794503493674860544 |