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| Registros recuperados : 191 | |
| Registros recuperados : 191 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio-Norte. |
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Data corrente: |
23/06/2020 |
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Data da última atualização: |
11/12/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
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. |
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Afiliação: |
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. |
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Título: |
Fitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Semina: Ciências Agrárias, v. 41, n. 2, p. 545-558, mar./abr. 2020. |
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ISSN: |
1679-0359 |
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DOI: |
10.5433/1679-0359.2020v41n2p545 |
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Idioma: |
Inglês |
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Conteúdo: |
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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Palavras-Chave: |
Curva média; Modelagem residual; Modelo linear. |
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Thesagro: |
Parâmetro Genético; Regressão Linear. |
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Thesaurus NAL: |
Linear models. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/214168/1/FittingFixedRegressionCurvesNelloreSemina2020.pdf
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Marc: |
LEADER 02088naa a2200289 a 4500
001 2123435
005 2020-12-11
008 2020 bl uuuu u00u1 u #d
022 $a1679-0359
024 7 $a10.5433/1679-0359.2020v41n2p545$2DOI
100 1 $aCAVALCANTE, D. H.
245 $aFitting of fixed regression curves with different residual variance structures for Nellore cattle growth modeling.$h[electronic resource]
260 $c2020
520 $aDifferent 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.
650 $aLinear models
650 $aParâmetro Genético
650 $aRegressão Linear
653 $aCurva média
653 $aModelagem residual
653 $aModelo linear
700 1 $aSOUSA JÚNIOR, S. C.
700 1 $aSILVA, L. P.
700 1 $aMALHADO, C. H. M.
700 1 $aMARTINS FILHO, R.
700 1 $aAZEVEDO, D. M. M. R.
700 1 $aCAMPELO, J. E. G.
773 $tSemina: Ciências Agrárias$gv. 41, n. 2, p. 545-558, mar./abr. 2020.
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Embrapa Meio-Norte (CPAMN) |
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