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Registro Completo |
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
17/01/2005 |
Data da última atualização: |
29/11/2016 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
LOPES, S. da C.; LAMEIRA, O. A.; FORTES, G. R. L. |
Afiliação: |
SEBASTIÃO DA CUNHA LOPES, BOLSISTA CNPQ; OSMAR ALVES LAMEIRA, CPATU; GERSON RENAN DE LUCES FORTES, CPACT. |
Título: |
Comparação de procedimentos para descontaminação de explantes de mogno (Swietenia macrophylla King). |
Ano de publicação: |
2003 |
Fonte/Imprenta: |
Revista de Ciências Agrárias, Belém, n. 40, p. 63-71, jul./dez. 2003. |
Idioma: |
Português |
Palavras-Chave: |
Assepsia; Folhas. |
Thesagro: |
Cultura de Tecido; Mogno. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/83259/1/Revista-p63.pdf
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Marc: |
LEADER 00553naa a2200181 a 4500 001 1405679 005 2016-11-29 008 2003 bl uuuu u00u1 u #d 100 1 $aLOPES, S. da C. 245 $aComparação de procedimentos para descontaminação de explantes de mogno (Swietenia macrophylla King). 260 $c2003 650 $aCultura de Tecido 650 $aMogno 653 $aAssepsia 653 $aFolhas 700 1 $aLAMEIRA, O. A. 700 1 $aFORTES, G. R. L. 773 $tRevista de Ciências Agrárias, Belém$gn. 40, p. 63-71, jul./dez. 2003.
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Embrapa Amazônia Oriental (CPATU) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
10/08/2021 |
Data da última atualização: |
10/08/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
SILVA, H. T.; LOPES, P. S.; COSTA, C. N.; SILVA, F. F.; SILVA, D. A.; SILVA, A. A.; THOMPSON, G.; CARVALHEIRA, J. |
Afiliação: |
Universidade Federal de Viçosa; Universidade Federal de Viçosa; CLAUDIO NAPOLIS COSTA, CNPGL; Universidade Federal de Viçosa; Universidade Federal de Viçosa; Universidade Federal de Viçosa; GERTRUDE THOMPSON, Universidade do Porto; JÚLIO CARVALHEIRA, Universidade do Porto. |
Título: |
Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Journal of Dairy Research, v. 87, p. 37-44, 2021. |
DOI: |
https://doi.org/10.1017/S0022029919000931 |
Idioma: |
Inglês |
Conteúdo: |
We investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model. MenosWe investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two m... Mostrar Tudo |
Palavras-Chave: |
Desempenho reprodutivo; Holstein cattle; Model evaluation. |
Thesagro: |
Bovino; Fertilidade; Gado Holandês; Reprodução Animal. |
Thesaurus NAL: |
Autocorrelation; Reproductive performance. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
Marc: |
LEADER 02624naa a2200325 a 4500 001 2133403 005 2021-08-10 008 2021 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1017/S0022029919000931$2DOI 100 1 $aSILVA, H. T. 245 $aAutoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle.$h[electronic resource] 260 $c2021 520 $aWe investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model. 650 $aAutocorrelation 650 $aReproductive performance 650 $aBovino 650 $aFertilidade 650 $aGado Holandês 650 $aReprodução Animal 653 $aDesempenho reprodutivo 653 $aHolstein cattle 653 $aModel evaluation 700 1 $aLOPES, P. S. 700 1 $aCOSTA, C. N. 700 1 $aSILVA, F. F. 700 1 $aSILVA, D. A. 700 1 $aSILVA, A. A. 700 1 $aTHOMPSON, G. 700 1 $aCARVALHEIRA, J. 773 $tJournal of Dairy Research$gv. 87, p. 37-44, 2021.
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