Data/hora: 01/06/2024 13:24:35

Biblioteca(s): | Embrapa Arroz e Feijão.
Data corrente: | 23/08/2018
Data da última atualização: | 28/08/2018
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.
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
Registro original: | Embrapa Arroz e Feijão (CNPAF)
Exemplares: | CNPAF - (35250-1) - UPC - AP - DD - 2018 -  - 2018 - DIS