Revista: | Acta scientiarum. Agronomy |
Base de datos: | PERIÓDICA |
Número de sistema: | 000459909 |
ISSN: | 1679-9275 |
Autores: | Volpato, Leonardo1 Rocha, João Romero do Amaral Santos de Carvalho2 Alves, Rodrigo Silva2 Ludke, Willian Hytalo1 Borém, Aluízio1 Silva, Felipe Lopes da1 |
Instituciones: | 1Universidade Federal de Vicosa, Departamento de Fitotecnia, Vicosa, Minas Gerais. Brasil 2Universidade Federal de Vicosa, Departamento de Biologia Geral, Vicosa, Minas Gerais. Brasil |
Año: | 2021 |
Volumen: | 43 |
País: | Brasil |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Experimental, analítico |
Resumen en inglés | The selection of superior genotypes of soybean entails a simultaneous evaluation of a number of favorable traits that provide a comparatively superior yield. Disregarding the population effect in the statistical model may compromise the estimate of variance components and the prediction of genetic values. The present study was undertaken to investigate the importance of including population effect in the statistical model and to determine the effectiveness of the index based on factor analysis and ideotype design via best linear unbiased prediction (FAI-BLUP) in the selection of erect, early, and high-yielding soybean progenies. To attain these objectives, 204 soybean progenies originating from three populations were examined for various traits of agronomic interest. The inclusion of the population effect in the statistical model was relevant in the genetic evaluation of soybean progenies. To quantify the effectiveness of the FAI-BLUP index, genetic gains were predicted and compared with those obtained by the Smith-Hazel and Additive Genetic indices. The FAI-BLUP index was effective in the selection of progenies with balanced, desirable genetic gains for all traits simultaneously. Therefore, the FAI-BLUP index is an adequate tool for the simultaneous selection of important traits in soybean breeding |
Disciplinas: | Agrociencias |
Palabras clave: | Leguminosas, Genotipo-ambiente, Soya, Análisis factorial |
Keyword: | Legumes, Genotype-environment, Soybean, Factor analysis |
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