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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
06/12/2011 |
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Data da última atualização: |
06/12/2011 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
TEIXEIRA, S. M.; MILHOMEM, A. V.; RIBEIRO, G. C.; BÉRGOLI, Ê.; MOLIN, M.; VEGRO, C. L.; GARCIA, R. D. C.; FRANZIN, M. A. P.; ASSUMPÇÃO, R.; FELIPE, M. P.; MILHOMEM, S. V. |
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Afiliação: |
SÔNIA MILAGRES TEIXEIRA, SAPC; UFG; ASSOCIAÇÃO BRASILEIRA DO CAFÉ; INCAPE; CETCAF; IEA-SAA; Bosista Embrapa Café; DERAL-PR; IEA-SAA; EMATER-MG; Bolsista Embrapa Café. |
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Título: |
Custos de produção na cafeicultura brasileira. |
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Ano de publicação: |
2002 |
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Fonte/Imprenta: |
In: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 2., 2001, Vitória. Anais... Brasília, DF: Embrapa Café, 2002. |
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Idioma: |
Português |
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Thesagro: |
Cafeicultura; Produção. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/49420/1/Custos-de-producao-na-cafeicultura.pdf
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Marc: |
LEADER 00735nam a2200241 a 4500
001 1908679
005 2011-12-06
008 2002 bl uuuu u00u1 u #d
100 1 $aTEIXEIRA, S. M.
245 $aCustos de produção na cafeicultura brasileira.$h[electronic resource]
260 $aIn: SIMPÓSIO DE PESQUISA DOS CAFÉS DO BRASIL, 2., 2001, Vitória. Anais... Brasília, DF: Embrapa Café$c2002
650 $aCafeicultura
650 $aProdução
700 1 $aMILHOMEM, A. V.
700 1 $aRIBEIRO, G. C.
700 1 $aBÉRGOLI, Ê.
700 1 $aMOLIN, M.
700 1 $aVEGRO, C. L.
700 1 $aGARCIA, R. D. C.
700 1 $aFRANZIN, M. A. P.
700 1 $aASSUMPÇÃO, R.
700 1 $aFELIPE, M. P.
700 1 $aMILHOMEM, S. V.
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Registro original: |
Embrapa Café (CNPCa) |
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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
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
23/02/2023 |
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Data da última atualização: |
06/09/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
CARRARA, E. R.; PEIXOTO, M. G. C. D.; SILVA, A. A. da; BRUNELI, F. A. T.; VENTURA, H. T.; ZADRA, L. E. F.; JOSAHKIAN, L. A.; VERONEZE, R.; LOPES, P. S. |
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Afiliação: |
EULA REGINA CARRARA, Universidade Federal de Viçosa; MARIA GABRIELA CAMPOLINA D PEIXOTO, CNPGL; ALESSANDRA ALVES DA SILVA, Universidade Estadual Paulista; FRANK ANGELO TOMITA BRUNELI, CNPGL; HENRIQUE TORRES VENTURA, Associação Brasileira dos Criadores de Zebu; LENIRA EL FARO ZADRA, Centro Brasileiro de Melhoramento Genético do Guzerá; LUIZ ANTÔNIO JOSAHKIAN, Associação Brasileira dos Criadores de Zebu; RENATA VERONEZE, Universidade Federal de Viçosa; PAULO SÁVIO LOPES, Universidade Federal de Viçosa. |
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Título: |
Genomic prediction in Brazilian Guzerá cattle: application of a single-step approach to productive and reproductive traits. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Tropical Animal Health and Production, v. 55, article 48, 2023. |
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DOI: |
https://doi.org/10.1007/s11250-023-03484-9 |
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Idioma: |
Inglês |
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Conteúdo: |
This study aimed to investigate the feasibility of genomic prediction for productive and reproductive traits in Guzerá cattle using single-step genomic best linear unbiased prediction (ssGBLUP). Evaluations included the 305-day cumulative yields (frst lactation, in kg) of milk, lactose, protein, fat, and total solids; adjusted body weight (kg) at the ages of 450, 365, and 210 days; and age at frst calving (in days), from a database containing 197,283 measurements from Guzerá males and females born between 1954 and 2018. The pedigree included 433,823 animals spanning up to 14 overlapping generations. A total of 1618 animals were genotyped. The analyses were performed using ssGBLUP and traditional BLUP methods. Predictive ability and bias were accessed using cross-validation: predictive ability was similar between the methods and ranged from 0.27 to 0.47 for the genomic-based model and from 0.30 to 0.45 for the pedigree-based model; the bias was also similar between the methods, ranging from 0.88 to 1.35 in the genomic-based model and from 0.96 to 1.41 in the pedigree-based model. The individual accuracies of breeding values were evidently increased in the genomic evaluation, with values ranging from 0.41 to 0.56 in the genomic-based model and from 0.26 to 0.54 in the pedigree-based model. Even based on a small number of genotyped animals and a small database for some traits, the results suggest that ssGBLUP is feasible and may be applied to national genetic evaluation of the breed to increase the accuracy of breeding values without greatly impacting predictive ability and bias. MenosThis study aimed to investigate the feasibility of genomic prediction for productive and reproductive traits in Guzerá cattle using single-step genomic best linear unbiased prediction (ssGBLUP). Evaluations included the 305-day cumulative yields (frst lactation, in kg) of milk, lactose, protein, fat, and total solids; adjusted body weight (kg) at the ages of 450, 365, and 210 days; and age at frst calving (in days), from a database containing 197,283 measurements from Guzerá males and females born between 1954 and 2018. The pedigree included 433,823 animals spanning up to 14 overlapping generations. A total of 1618 animals were genotyped. The analyses were performed using ssGBLUP and traditional BLUP methods. Predictive ability and bias were accessed using cross-validation: predictive ability was similar between the methods and ranged from 0.27 to 0.47 for the genomic-based model and from 0.30 to 0.45 for the pedigree-based model; the bias was also similar between the methods, ranging from 0.88 to 1.35 in the genomic-based model and from 0.96 to 1.41 in the pedigree-based model. The individual accuracies of breeding values were evidently increased in the genomic evaluation, with values ranging from 0.41 to 0.56 in the genomic-based model and from 0.26 to 0.54 in the pedigree-based model. Even based on a small number of genotyped animals and a small database for some traits, the results suggest that ssGBLUP is feasible and may be applied to national genetic evaluation of the ... Mostrar Tudo |
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Palavras-Chave: |
Predição genômica. |
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Thesagro: |
Bovino; Gado Guzerá; Raça; Reprodução Animal. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 02508naa a2200289 a 4500
001 2151876
005 2023-09-06
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11250-023-03484-9$2DOI
100 1 $aCARRARA, E. R.
245 $aGenomic prediction in Brazilian Guzerá cattle$bapplication of a single-step approach to productive and reproductive traits.$h[electronic resource]
260 $c2023
520 $aThis study aimed to investigate the feasibility of genomic prediction for productive and reproductive traits in Guzerá cattle using single-step genomic best linear unbiased prediction (ssGBLUP). Evaluations included the 305-day cumulative yields (frst lactation, in kg) of milk, lactose, protein, fat, and total solids; adjusted body weight (kg) at the ages of 450, 365, and 210 days; and age at frst calving (in days), from a database containing 197,283 measurements from Guzerá males and females born between 1954 and 2018. The pedigree included 433,823 animals spanning up to 14 overlapping generations. A total of 1618 animals were genotyped. The analyses were performed using ssGBLUP and traditional BLUP methods. Predictive ability and bias were accessed using cross-validation: predictive ability was similar between the methods and ranged from 0.27 to 0.47 for the genomic-based model and from 0.30 to 0.45 for the pedigree-based model; the bias was also similar between the methods, ranging from 0.88 to 1.35 in the genomic-based model and from 0.96 to 1.41 in the pedigree-based model. The individual accuracies of breeding values were evidently increased in the genomic evaluation, with values ranging from 0.41 to 0.56 in the genomic-based model and from 0.26 to 0.54 in the pedigree-based model. Even based on a small number of genotyped animals and a small database for some traits, the results suggest that ssGBLUP is feasible and may be applied to national genetic evaluation of the breed to increase the accuracy of breeding values without greatly impacting predictive ability and bias.
650 $aBovino
650 $aGado Guzerá
650 $aRaça
650 $aReprodução Animal
653 $aPredição genômica
700 1 $aPEIXOTO, M. G. C. D.
700 1 $aSILVA, A. A. da
700 1 $aBRUNELI, F. A. T.
700 1 $aVENTURA, H. T.
700 1 $aZADRA, L. E. F.
700 1 $aJOSAHKIAN, L. A.
700 1 $aVERONEZE, R.
700 1 $aLOPES, P. S.
773 $tTropical Animal Health and Production$gv. 55, article 48, 2023.
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