Multienvironment Evaluation of Early‐Maturing Cowpea Genotypes for Yield Performance Under Rainfed Conditions

Genotype × environment interaction (GEI) continues to pose a major challenge in crop improvement, as it influences the stability of yield expression and complicates the identification of genotypes with consistent performance across diverse environments. In this study, a set of early‐maturing cowpea genotypes was evaluated under multiple rainfed environments in Niger to identify lines combining high productivity and stable performance. Significant ( p   < 0.001) effects of genotype, environment, and their interaction were observed for all measured traits, highlighting the strong influence of environmental variability on genotype performance. Grain yield (GY) ranged from 237.8 to 3125.0 kg ha ⁻¹ with a mean of 973.41 kg/ha. The additive main effects and multiplicative interaction (AMMI) model explained 89.4% of GEI variation through IPCA1 (74.9%) and IPCA2 (14.5%). The first two principal components of the genotype main effects plus GEI (GGE) biplot captured a substantial share of the total variation, with PC1 explaining 66.22% and PC2 contributing 23.83%, together accounting for 90.05% of the observed variability. Environment E1 (Tarna‐2022) was the most discriminating environment, while E2 and E5 were the most representative for selecting broadly adapted genotypes. The WAASB index identified G1, G7, and G19 as combining above‐average yield with high stability, while G2 was the highest‐yielding genotype, although it was strongly responsive to the environment. G1 and G7 are promising candidates for further multienvironment evaluation and require validation in balanced multilocation and multiyear trials before any deployment decision; they may also serve as parental lines for future cowpea improvement programs in Niger and similar rainfed agroecological zones of West Africa.