Open AccessEstimativas de parâmetros genéticos, correlações e índices de seleção para seis caracteres agronômicos em linhagens F8 de soja
Author(s) -
Wallace de Sousa Leite,
Bruno Ettore Pavan,
Carlos Humberto Aires Matos Filho,
Francisco de Alcântara Neto,
Cleidismar Barbosa de Oliveira,
Francisco Solano Feitosa
Publication year - 2016
Publication title -
comunicata scientiae
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.238
H-Index - 12
eISSN - 2177-5133
pISSN - 2176-9079
DOI - 10.14295/cs.v7i3.1176
Subject(s) - heritability , randomized block design , biology , grain yield , point of delivery , horticulture , selection (genetic algorithm) , crop , genetic gain , genetic variation , agronomy , genetics , artificial intelligence , computer science , gene
This study aimed to estimate genetic and phenotypic parameters and provide knowledge for breeding programs aiming at the selection of the main characters of assessment in soybeans. The experiment was installed in Sabia farm, located at ‘Serra das Laranjeiras” , in the municipality of Currais, Piaui, Brazil, during the 2011/2012 crop year using a randomized block design with 27 genotypes and three repetitions. The evaluated variables were: height at flowering (APF), height at maturity (APM), pod insertion height (AIV), grain yield (PG), number of nodes (NN) and number of pods (NV). The obtained heritability coefficients were from medium to high, for all evaluated characters, ranging from 0.53 to 0.94, for grain yield and plant height at flowering, respectively. These high heritability were confirmed by the high degree of genetic variation and the CVg/CVe ratio, indicating a high prospect of success for the phenotypic selection. The higher positive genetic correlations and the significant (P <0.01) were observed between grain yield and the variables number of nodes (0.807**) and number of pods (0.781**), indicating that the selection of plants with higher number of nodes and pods could result in more productive plants. The Williams-based index presented the highest percentage of gain with the selection offor the grain yield (21.84%) variable.