Genetic parameters and selection indices of cowpea genotypes for green grain production

Abstract

Cowpea is a legume that is grown worldwide and used for different purposes, especially as green grains. However, considering the low availability of cowpea cultivars for green grain production, selecting genotypes that have better traits for this purpose is necessary. In this context, the objective of this study was to estimate genetic parameters and evaluate different selection indices for identifying superior cowpea genotypes and subsidizing cowpea breeding programs focused on green grain production. A field experiment was conducted at the Center of Agricultural Sciences of the Federal University of Ceará (UFC), Ceará, Brazil. The treatments consisted of 42 cowpea genotypes from the Active Germplasm Bank of the UFC. Fourteen traits were used for characterization. The experiment was conducted in an augmented block design with four controls. The data obtained were subjected to analysis of variance, and genetic parameters, correlations, and selection indices were determined. The traits days to flowering (DFL), days to fruiting (DFR), green pod weight (GPW), green pod width (GW), green pod length (GPL), green pod thickness (GPT), number of grains per pod (NGP), and green grain thickness (GGT) showed heritability higher than 70%, indicating that selection in an early generation is favorable. The genetic correlations between the trait pairs DFL×DFR, GPW×GPL, and GW×GGT were higher than the phenotypic and environmental correlations. Genotypes CE-228, CE-688, CE-994, CE-165, CE-796, and BRS-Paraguaçu showed simultaneous superiority for the evaluated traits and are the most appropriate for green grain production.

Selection of superior cowpea lines derived from local cultivars for the Brazilian semiarid region

“…The estimation of important genetic parameters, such as genetic variance and heritability of agronomically important traits, has guided cowpea breeders in the choice of the best breeding strategies (Ongom et al, 2021;Pessoa et al, 2023). Restricted maximum likelihood (REML) and best linear unbiased prediction (BLUP) are considered the most efficient methods for estimating variance components and predicting genetic values, respectively (Resende, 2016).…”