Abordagem genética e multivariada na performance agronômica de genótipos de soja oriundos de diferentes genealogias

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Gomez, Guillermo Marcelo [UNESP]
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11449/110322
Resumo: The objectives of the present study were to: (i) evaluate the genotypic performances of 45 soybean genotypes with the future finality of recommendation of varieties for the State of São Paulo, Brazil; (ii) determine the stability and adaptability of the 45 genotypes utilizing the Wricke’s ecovalence, AMMI (additive main effects and multiplicative interaction analysis), GGE-Biplot and MHPRVG (harmonic mean of the relative performance of genotypic values) methods; (iii) evaluate the phenotypic, genotypic and environmental correlations among the traits of 45 genotypes in three environments. The exploration of genotype-byenvironment interaction (GEI) allowed the identification of 21 genotypes with high mean grain yield, representing different relative maturity groups and stability levels to the environments. This group was subdivided by crop cycle, in which the genotypes 18, 36, 20, 34 and 33 were early cycles (108 days – 125 days), while genotypes 11, 22, 44 (CD 219), 24, 23, 14, 32, 1, 12, 39, 30, 38, 7 and 26 were medium cycles (126 days – 135 days) and genotypes 25 and 37 were late cycles (≥ 136 days). The interpretations obtained from the ecovalence, AMMI and GGE-biplot methods were more similar than the interpretations obtained from the MHPRVG method. This was due to the method’s properties, which give more weight to grain yield and little weight to the adaptability and stability parameters. The genotypic and environmental correlations among traits enhanced the interpretations of the genotype x environmental interactions