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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
19/02/2013 |
Data da última atualização: |
19/03/2024 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
WOHLRES-VIANA, S.; BERNARDO, K. B.; CUNHA, A. C. L. M.; REIS, D. R. de L.; ARASHIRO, E. K. N.; MACHADO, M. A.; VIANA, J. H. M. |
Afiliação: |
SABINE WOHLRES-VIANA, UFJF; K. B. BERNARDO, UFJF; ANA CAROLINA L. M. CUNHA, CES/JF; DANIELE RIBEIRO DE LIMA REIS, CNPGL; E. K. N. ARASHIRO, UFMG; MARCO ANTONIO MACHADO, CNPGL; JOAO HENRIQUE MOREIRA VIANA, CNPGL. |
Título: |
Identification of SNPs in the luteinizing hormone receptor transcript of Gyr (Bos indicus) granulosa cells. |
Ano de publicação: |
2012 |
Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE GENÉTICA, 58., 2012, Foz do Iguaçu. Resumos... Foz do Iguaçú: Sociedade Brasileira de Genética, 2012. |
Idioma: |
Inglês |
Palavras-Chave: |
Foliculogenese; LHR; Ponto de mutaçao; Transcrição. |
Thesagro: |
Bovino. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/949948/1/Identification-of-SNPs-in-the-luteinizing.pdf
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Marc: |
LEADER 00790nam a2200229 a 4500 001 1949948 005 2024-03-19 008 2012 bl uuuu u00u1 u #d 100 1 $aWOHLRES-VIANA, S. 245 $aIdentification of SNPs in the luteinizing hormone receptor transcript of Gyr (Bos indicus) granulosa cells.$h[electronic resource] 260 $aIn: CONGRESSO BRASILEIRO DE GENÉTICA, 58., 2012, Foz do Iguaçu. Resumos... Foz do Iguaçú: Sociedade Brasileira de Genética$c2012 650 $aBovino 653 $aFoliculogenese 653 $aLHR 653 $aPonto de mutaçao 653 $aTranscrição 700 1 $aBERNARDO, K. B. 700 1 $aCUNHA, A. C. L. M. 700 1 $aREIS, D. R. de L. 700 1 $aARASHIRO, E. K. N. 700 1 $aMACHADO, M. A. 700 1 $aVIANA, J. H. M.
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Embrapa Gado de Leite (CNPGL) |
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![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
23/08/2018 |
Data da última atualização: |
28/08/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
FARIA, L. C. de; MELO, P. G. S.; SOUZA, T. L. P. O. de; PEREIRA, H. S.; MELO, L. C. |
Afiliação: |
LUIS CLAUDIO DE FARIA, CNPAF; PATRICIA GUIMARÃES SANTOS MELO, UFG; THIAGO LIVIO PESSOA OLIV DE SOUZA, CNPAF; HELTON SANTOS PEREIRA, CNPAF; LEONARDO CUNHA MELO, CNPAF. |
Título: |
Efficiency of methods for genetic progress estimation in common bean breeding using database information. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Euphytica, v. 214, n. 9, article 164, Sept. 2018. |
ISSN: |
1573-5060 |
DOI: |
10.1007/s10681-018-2246-8 |
Idioma: |
Inglês |
Conteúdo: |
The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993-2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha-1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha-1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods. MenosThe final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993-2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha-1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha-1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadju... Mostrar Tudo |
Palavras-Chave: |
Genetic grain; Linear regression; Mixed models. |
Thesagro: |
Arroz; Feijão; Melhoramento Genético Vegetal; Phaseolus Vulgaris; Regressão Linear; Seleção Genética. |
Thesaurus NAL: |
Beans; Grain yield. |
Categoria do assunto: |
G Melhoramento Genético |
Marc: |
LEADER 02508naa a2200325 a 4500 001 2094462 005 2018-08-28 008 2018 bl uuuu u00u1 u #d 022 $a1573-5060 024 7 $a10.1007/s10681-018-2246-8$2DOI 100 1 $aFARIA, L. C. de 245 $aEfficiency of methods for genetic progress estimation in common bean breeding using database information.$h[electronic resource] 260 $c2018 520 $aThe final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993-2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha-1 per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha-1 per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods. 650 $aBeans 650 $aGrain yield 650 $aArroz 650 $aFeijão 650 $aMelhoramento Genético Vegetal 650 $aPhaseolus Vulgaris 650 $aRegressão Linear 650 $aSeleção Genética 653 $aGenetic grain 653 $aLinear regression 653 $aMixed models 700 1 $aMELO, P. G. S. 700 1 $aSOUZA, T. L. P. O. de 700 1 $aPEREIRA, H. S. 700 1 $aMELO, L. C. 773 $tEuphytica$gv. 214, n. 9, article 164, Sept. 2018.
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