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Registro Completo |
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
17/12/2007 |
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Data da última atualização: |
18/02/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MAZZUCO, H. |
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Afiliação: |
Helenice Mazzuco, Embrapa Suínos e Aves. |
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Título: |
Bem-estar animal na cadeia avícola de postura. |
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Ano de publicação: |
2007 |
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Fonte/Imprenta: |
AveWorld, n. 29, p. 24-29, ago./set. 2007. |
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Idioma: |
Português |
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Notas: |
Projeto n. 03.06.62.000-03. |
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Palavras-Chave: |
Cadeia avícola; Instalação. |
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Thesagro: |
Bem-Estar. |
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Thesaurus Nal: |
Aves. |
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Categoria do assunto: |
-- |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/443654/1/digitalizar0001.pdf
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Marc: |
LEADER 00469naa a2200169 a 4500
001 1443654
005 2016-02-18
008 2007 bl uuuu u00u1 u #d
100 1 $aMAZZUCO, H.
245 $aBem-estar animal na cadeia avícola de postura.$h[electronic resource]
260 $c2007
500 $aProjeto n. 03.06.62.000-03.
650 $aAves
650 $aBem-Estar
653 $aCadeia avícola
653 $aInstalação
773 $tAveWorld$gn. 29, p. 24-29, ago./set. 2007.
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Registro original: |
Embrapa Suínos e Aves (CNPSA) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sul. Para informações adicionais entre em contato com cppsul.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pecuária Sul. |
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Data corrente: |
08/01/2019 |
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Data da última atualização: |
08/01/2019 |
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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: |
PICCOLI, M. L.; BRITO, L. F.; BRACCINI, J.; BRITO, F. V.; CARDOSO, F. F.; COBUCI, J. A.; SARGOLZAEI, M.; SCHENKEL, F. S. |
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Afiliação: |
Mario L. Piccoli, UFRGS; Luiz F. Brito, University of Guelph; José Braccini, UFRGS; Fernanda V. Brito, GenSys; FERNANDO FLORES CARDOSO, CPPSUL; Jaime A. Cobuci, UFRGS; Mehdi Sargolzaei, University of Guelph; Flávio S. Schenkel, University of Guelph. |
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Título: |
A comprehensive comparison between single- and two-step GBLUP methods in a simulated beef cattle population. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Canadian Journal of Animal Science, v. 98, n. 3, p. 565-575, Sept. 2018. |
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DOI: |
dx.doi.org/10.1139/cjas-2017-0176 |
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Idioma: |
Inglês |
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Conteúdo: |
The statistical methods used in the genetic evaluations are a key component of the process and can be best compared by using simulated data. The latter is especially true in grazing beef cattle production systems, where the number of proven bulls with highly reliable estimated breeding values is limited to allow for a trustworthy validation of genomic predictions. Therefore, we simulated data for 4980 beef cattle aiming to compare single-step genomic best linear unbiased prediction (ssGBLUP), which simultaneously incorporates pedigree, phenotypic, and genomic data into genomic evaluations, and two-step GBLUP (tsGBLUP) procedures and genomic estimated breeding values (GEBVs) blending methods. The greatest increases in GEBV accuracies compared with the parents? average estimated breeding values (EBVPA) were 0.364 and 0.341 for ssGBLUP and tsGBLUP, respectively. Direct genomic value and GEBV accuracies when using ssGBLUP and tsGBLUP procedures were similar, except for the GEBV accuracies using Hayes? blending method in tsGBLUP. There was no significant or slight bias in genomic predictions from ssGBLUP or tsGBLUP (using VanRaden?s blending method), indicating that these predictions are on the same scale compared with the true breeding values. Overall, genetic evaluations including genomic information resulted in gains in accuracy >100% compared with the EBVPA. In addition, there were no significant differences between the selected animals (10% males and 50% females) by using ssGBLUP or tsGBLUP. MenosThe statistical methods used in the genetic evaluations are a key component of the process and can be best compared by using simulated data. The latter is especially true in grazing beef cattle production systems, where the number of proven bulls with highly reliable estimated breeding values is limited to allow for a trustworthy validation of genomic predictions. Therefore, we simulated data for 4980 beef cattle aiming to compare single-step genomic best linear unbiased prediction (ssGBLUP), which simultaneously incorporates pedigree, phenotypic, and genomic data into genomic evaluations, and two-step GBLUP (tsGBLUP) procedures and genomic estimated breeding values (GEBVs) blending methods. The greatest increases in GEBV accuracies compared with the parents? average estimated breeding values (EBVPA) were 0.364 and 0.341 for ssGBLUP and tsGBLUP, respectively. Direct genomic value and GEBV accuracies when using ssGBLUP and tsGBLUP procedures were similar, except for the GEBV accuracies using Hayes? blending method in tsGBLUP. There was no significant or slight bias in genomic predictions from ssGBLUP or tsGBLUP (using VanRaden?s blending method), indicating that these predictions are on the same scale compared with the true breeding values. Overall, genetic evaluations including genomic information resulted in gains in accuracy >100% compared with the EBVPA. In addition, there were no significant differences between the selected animals (10% males and 50% females) by using ss... Mostrar Tudo |
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Thesagro: |
Gado de Corte; Genoma; Melhoramento Genético Animal; Seleção. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02337naa a2200265 a 4500
001 2103229
005 2019-01-08
008 2018 bl uuuu u00u1 u #d
024 7 $adx.doi.org/10.1139/cjas-2017-0176$2DOI
100 1 $aPICCOLI, M. L.
245 $aA comprehensive comparison between single- and two-step GBLUP methods in a simulated beef cattle population.$h[electronic resource]
260 $c2018
520 $aThe statistical methods used in the genetic evaluations are a key component of the process and can be best compared by using simulated data. The latter is especially true in grazing beef cattle production systems, where the number of proven bulls with highly reliable estimated breeding values is limited to allow for a trustworthy validation of genomic predictions. Therefore, we simulated data for 4980 beef cattle aiming to compare single-step genomic best linear unbiased prediction (ssGBLUP), which simultaneously incorporates pedigree, phenotypic, and genomic data into genomic evaluations, and two-step GBLUP (tsGBLUP) procedures and genomic estimated breeding values (GEBVs) blending methods. The greatest increases in GEBV accuracies compared with the parents? average estimated breeding values (EBVPA) were 0.364 and 0.341 for ssGBLUP and tsGBLUP, respectively. Direct genomic value and GEBV accuracies when using ssGBLUP and tsGBLUP procedures were similar, except for the GEBV accuracies using Hayes? blending method in tsGBLUP. There was no significant or slight bias in genomic predictions from ssGBLUP or tsGBLUP (using VanRaden?s blending method), indicating that these predictions are on the same scale compared with the true breeding values. Overall, genetic evaluations including genomic information resulted in gains in accuracy >100% compared with the EBVPA. In addition, there were no significant differences between the selected animals (10% males and 50% females) by using ssGBLUP or tsGBLUP.
650 $aGado de Corte
650 $aGenoma
650 $aMelhoramento Genético Animal
650 $aSeleção
700 1 $aBRITO, L. F.
700 1 $aBRACCINI, J.
700 1 $aBRITO, F. V.
700 1 $aCARDOSO, F. F.
700 1 $aCOBUCI, J. A.
700 1 $aSARGOLZAEI, M.
700 1 $aSCHENKEL, F. S.
773 $tCanadian Journal of Animal Science$gv. 98, n. 3, p. 565-575, Sept. 2018.
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Embrapa Pecuária Sul (CPPSUL) |
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