Estimates of genetic divergence in cowpea by multivariate analysis in different environments

• Autor(a) principal: Ribeiro, Larissa Pereira
• Data de Publicação: 2019
• Outros Autores: Evangelista, Jeniffer Santana Pinto Coelho, Damacena, Michelle Brandão, Elizeu, Arthur Mayrink, Coelho, Igor Ferreira, Rodrigues, Erina Vitório, Teodoro, Paulo Eduardo, Bhering, Leonardo Lopes
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Bioscience journal (Online)
• DOI: 10.14393/BJ-v35n6a2019-42406
• Texto Completo: https://seer.ufu.br/index.php/biosciencejournal/article/view/42406
• topic: Vigna unguiculata L.; dissimilarity; UPGMA; Tocher.; Vigna unguiculata L.; Dissimilaridade.; UPGMA.; Tocher.

Cowpea is a legume of great importance in the Brazilian nutrition, mainly in the Northeast region. Despite the low yield of Brazilian cowpea, the species presents a genetic potential to be explored. Thus, this work aimed to characterize the genetic diversity of cowpea genotypes by agronomic traits and select genotypes for possible crosses by multivariate analysis. Four value for cultivation and use tests were carried out with cowpea genotypes in 2005 and 2006, in the municipalities of Aquidauana, Chapadão do Sul, and Dourados, in the state of Mato Grosso do Sul. The experimental design was a complete randomized block with 20 genotypes and four replications. The evaluated traits were value for cultivation, plant lodging, pod length, grain weight of five pods, number of grains per pod, pod weight, severity of powdery mildew, and grain yield. To estimate the genetic diversity among the genotypes, the optimization methods of Tocher and UPGMA were used. The generalized distance of Mahalanobis was used as a dissimilarity measure. The clustering methods revealed genetic variability among the cowpea genotypes evaluated. The methods used formed a different number of groups for each environment. Genotypes TE97-309G-24, MNC99-542F-5, BRS Paraguaçu, BRS Paraguaçu, BR 17-Gurguéia, and CNC x 409-11F-P2 can be used to obtain promising combinations and high genetic variability.