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2. |  | PASSAFARO, T. L.; FRAGOMENI, B. de O.; GONÇALVES, D. R.; MORAES, M. M. de; TORAL, F. L. B. Análise genética de peso em um rebanho de bovinos Nelore. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 51, n. 2, p. 149-158, fev. 2016. Título em inglês: Genetic analysis of body weight in a Nellore cattle herd. Biblioteca(s): Embrapa Unidades Centrais. |
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3. |  | SCALEZ, D. C. B.; FRAGOMENI, B. de O.; COSTA, P. S. T. da; PASSAFARO, T. L.; TORAL, F. L. B.; ALENCAR, M. M. de. Polinômios para modelar a trajetória de crescimento de tourinhos em provas de ganho em peso. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 48., 2011, Belém. O Desenvolvimento da produção animal e a responsabilidade frente a novos desafios - anais. Belém: SBZ: UFRA, 2011. Biblioteca(s): Embrapa Pecuária Sudeste. |
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5. |  | LOPES, F. B.; MAGNABOSCO, C. de U.; PASSAFARO, T. L.; BRUNES, L. C.; COSTA, M. F. O. e; EIFERT, E. da C.; NARCISO, M. G.; ROSA, G. J. M.; LOBO, R. B.; BALDI, F. Improving genomic prediction accuracy for meat tenderness in Nellore cattle using artificial neural networks. Journal of Animal Breeding and Genetics, v. 137, n. 5, 2020. p. 438-448 Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Cerrados. |
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Registros recuperados : 5 | |
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Registro Completo
Biblioteca(s): |
Embrapa Pecuária Sudeste. |
Data corrente: |
19/10/2018 |
Data da última atualização: |
11/01/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
SCALEZ, D. C. B.; FRAGOMENI, B. de O.; SANTOS, D. C. C. dos; PASSAFARO, T. L.; ALENCAR, M. M. de; TORAL. F. L. B. |
Afiliação: |
Daiane Cristina Becker Scalez, UFMT; Breno de Oliveira Fragomeni, UFMG; Dalinne Chrystian Carvalho dos Santos, UFMG; Tiago Luciano Passafaro, UFMG; MAURICIO MELLO DE ALENCAR, CPPSE; Fabio Luiz Buranelo Toral, UFMG. |
Título: |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Revista Brasileira de Zootecnia, v. 47, p. 1-9, 2018. |
DOI: |
10.1590/rbz4720150300 |
Idioma: |
Inglês |
Conteúdo: |
The objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattle. |
Palavras-Chave: |
Bovinos de corte. |
Thesagro: |
Gado de Corte. |
Thesaurus NAL: |
Animal breeding; Beef cattle; Genetic correlation. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/184758/1/RamdomRegressionModels.pdf
|
Marc: |
LEADER 02136naa a2200253 a 4500 001 2097795 005 2019-01-11 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1590/rbz4720150300$2DOI 100 1 $aSCALEZ, D. C. B. 245 $aRandom regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests.$h[electronic resource] 260 $c2018 520 $aThe objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattle. 650 $aAnimal breeding 650 $aBeef cattle 650 $aGenetic correlation 650 $aGado de Corte 653 $aBovinos de corte 700 1 $aFRAGOMENI, B. de O. 700 1 $aSANTOS, D. C. C. dos 700 1 $aPASSAFARO, T. L. 700 1 $aALENCAR, M. M. de 700 1 $aTORAL. F. L. B. 773 $tRevista Brasileira de Zootecnia$gv. 47, p. 1-9, 2018.
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Embrapa Pecuária Sudeste (CPPSE) |
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