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Diallel analysis of cowpea (Vigna unguiculata (L.) Walp.) genotypes under water deficit stress.

Vincent EzinThibaut A W TossouIfagbémi Bienvenue ChabiAdam Ahanchede
Published in: BMC plant biology (2023)
Combining ability is referred to as the hybridization value of the parental genotypes involved in the crossing to develop hybrids. The best parents are selected through combining ability methods and subsequently used to produce high yielding and resistant hybrids. Thus, the objectives of this study were to (i) understand the nature and action of genes controlling water deficit tolerance, and (ii) identify superior genotypes from the genetic breadth provided by hybridization in cowpea. Twenty-four genotypes were subjected to normal irrigation and water deficit condition to examine combining ability, genotypic and phenotypic correlations for traits directly related to water deficit (proline and chlorophylls), grain yield and yield components. The results showed the presence of the action of additive and non-additive genes under both water regime conditions. However, there was the predominance of the action of additive genes for most of the traits studied under both conditions. The parents KVX61-1, IT06K242-3, IT07K-211-1-8, Kpodjiguèguè, IT99K-573-1-1, Tawa and IT97K-206-1-1 were observed to be good general combiners for proline content, chlorophyll content and traits associated with yield, while KVX61-1 × KVX396-18, IT06K242-3 × KVX396-18, IT07K-211-1-1 × KVX396-18, Kpodjiguèguè x KVX396-18, KVX61 -1 × IT97K-206-1-1, IT06K242-3 × IT97K-206-1-1, IT07K-211-1-1 × IT97K-206-1-1 and Kpodjiguèguè x IT97K-206-1-1 were proven to be the best specific combiners for traits directly related to water deficit tolerance and yield. It should be noted that number of days to pod maturity, pod length, number of pods per plant and weight of hundred seeds were highly heritable traits in this study.
Keyphrases
  • genome wide
  • dna methylation
  • body mass index
  • weight loss
  • physical activity
  • bioinformatics analysis
  • transcription factor
  • drug induced
  • quantum dots
  • heat stress
  • genome wide identification