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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
23/08/2018 |
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Data da última atualização: |
28/08/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
FARIA, L. C. de; MELO, P. G. S.; SOUZA, T. L. P. O. de; PEREIRA, H. S.; MELO, L. C. |
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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. |
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Título: |
Efficiency of methods for genetic progress estimation in common bean breeding using database information. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Euphytica, v. 214, n. 9, article 164, Sept. 2018. |
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ISSN: |
1573-5060 |
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DOI: |
10.1007/s10681-018-2246-8 |
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Idioma: |
Inglês |
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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 |
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Palavras-Chave: |
Genetic grain; Linear regression; Mixed models. |
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Thesagro: |
Arroz; Feijão; Melhoramento Genético Vegetal; Phaseolus Vulgaris; Regressão Linear; Seleção Genética. |
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Thesaurus Nal: |
Beans; Grain yield. |
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Categoria do assunto: |
G Melhoramento Genético |
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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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Embrapa Arroz e Feijão (CNPAF) |
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| 5. |  | MATTOSO, L. H. C. Using nanotechnology to develop natural polymer composites. In: INTERNATIONAL MACROMOLECULAR COLLOQUIUM - IMC, 11.; INTERNATIONAL SYMPOSIUM ON NATURAL POLYMERS AND COMPOSITES - ISNaPol, 6., 2007, Gramado, RS. Natural polymers and composites. Resumos... [São Carlos: ABPol, 2007]. não paginado. 1 CD-ROM.| Tipo: Resumo em Anais de Congresso |
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