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Genetic divergence among cowpea accessions using phenotypic, molecular, and nutritional traits

  • Angela Maria dos Santos Pessoa,
  • Cândida Hermínia Campos de Magalhães Bertini,
  • Leslyene Maria de Freitas,
  • Paulo Marcelo de Sousa Queiroz,
  • Eveline Nogueira Lima,
  • Mailson Monteiro do Rêgo

摘要

Vigna unguiculata is a species consumed by people in various parts of the world due to its high nutrient and protein contents. Data regarding phenotypic, genotypic and nutritional characterization analyzed individually and together (multivariate analysis) enable the selection of accessions to form a base population with greater accuracy. This study aimed to identify the traits that contribute to genetic divergence in a cowpea collection for green (immature) grains and indicate promising accessions for hybridization, based on individual and joint data analysis. A total of 36 cowpea accessions and two cultivars of the four evaluated are biofortified (BRS Aracê and BRS Tumucumaque). The phenotypic and genotypic characterizations were carried out at the Federal University of Ceará, and the nutritional characterization at the Federal University of Paraíba and Embrapa Agroindústria Tropical. Nine morpho-agronomic traits of plants and green pods were evaluated. Ten inter-simple sequence repeat (ISSR) primers were used to evaluate the polymorphism of the studied accessions and seven nutritional traits (DM, CP, P, K, Ca, Fe, and Zn). The traits of days to fruiting, green pod length, grain mass per green pod, zinc, protein, and phosphorus contribute to genetic divergence in cowpea accessions. There is genetic variability among cowpea accessions based on morpho-agronomic, molecular, and nutritional traits. Accessions CE0070, CE0189, CE0206, CE0207, CE0313, CE0796, CE0925, CE0999, and CE1007 and cultivars BRS Aracê and BRS Tumucumaque are recommended as potential parents for hybridization and a subsequent segregating generation to continue the genetic improvement program for green grain production and biofortification. Joint data analysis is an efficient tool to detect genetic diversity in cowpea accessions.