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Biblioteca(s): |
Embrapa Pecuária Sul. |
Data corrente: |
08/01/2019 |
Data da última atualização: |
08/01/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
PICCOLI, M. L.; BRITO, L. F.; BRACCINI, J.; BRITO, F. V.; CARDOSO, F. F.; COBUCI, J. A.; SARGOLZAEI, M.; SCHENKEL, F. S. |
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. |
Título: |
A comprehensive comparison between single- and two-step GBLUP methods in a simulated beef cattle population. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Canadian Journal of Animal Science, v. 98, n. 3, p. 565-575, Sept. 2018. |
DOI: |
dx.doi.org/10.1139/cjas-2017-0176 |
Idioma: |
Inglês |
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 |
Thesagro: |
Gado de Corte; Genoma; Melhoramento Genético Animal; Seleção. |
Categoria do assunto: |
-- |
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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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
Data corrente: |
25/06/2018 |
Data da última atualização: |
10/01/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
MAMEDE, M. C.; TEBALDI, N. D.; MOTA, L. C. B. M.; MARTINS, O. M.; COELHO, L. |
Afiliação: |
MORGANA C. MAMEDE, UFU; NILVANIRA D. TEBALDI, UFU; LARA C. B. M. MOTA, UFU; OLINDA MARIA MARTINS, Cenargen; LÍSIAS COELHO, UFU. |
Título: |
Detection of Pantoea ananatis in corn seeds on semi-selective medium. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Tropical Plant Pathology, v. 43, p. 254-256, 2018. |
DOI: |
10.1007/s40858-017-0203-z |
Idioma: |
Inglês |
Palavras-Chave: |
PCR; White spot. |
Thesagro: |
Zea Mays. |
Thesaurus NAL: |
Etiology. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/178938/1/Mamede2018-Article-DetectionOfPantoeaAnanatisInCo.pdf
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Marc: |
LEADER 00616naa a2200217 a 4500 001 2092726 005 2019-01-10 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1007/s40858-017-0203-z$2DOI 100 1 $aMAMEDE, M. C. 245 $aDetection of Pantoea ananatis in corn seeds on semi-selective medium.$h[electronic resource] 260 $c2018 650 $aEtiology 650 $aZea Mays 653 $aPCR 653 $aWhite spot 700 1 $aTEBALDI, N. D. 700 1 $aMOTA, L. C. B. M. 700 1 $aMARTINS, O. M. 700 1 $aCOELHO, L. 773 $tTropical Plant Pathology$gv. 43, p. 254-256, 2018.
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Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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