Identification of Stress-Resilient Maize Progenies under Drought and Low Nitrogen in West Africa Using Genotype × Environment Analysis and Multi-Trait Selection Indices

Abidemi Talabi, Idris Ishola Adejumobi , Wende Mengesha, Silvestro Meseka, Baffour Badu-Apraku, M.A.B Fakorede, John Derera

Maize productivity in West Africa is severely constrained by recurrent drought and low soil nitrogen availability, which results in strong environmental heterogeneity and complex genotype × environment interactions (G×E). Identifying breeding materials that combine productivity, stress resilience, and stability therefore requires analytical approaches that integrate multi-trait and multi-environment information. In this study, 250 full-sib maize progenies generated using a North Carolina Design I mating scheme were evaluated under managed drought and low-nitrogen conditions across multiple environments in Nigeria to identify superior crosses for population improvement. Linear mixed models were used to estimate variance components and obtain best linear unbiased predictions (BLUPs) for genotypic performance. Principal component analysis revealed that grain yield, flowering dates, and plant architecture contributed differentially to phenotypic variation, highlighting the multidimensional nature of stress adaptation. Selection of superior progenies was conducted using four complementary approaches including grain yield BLUPs, multi-trait genotype–ideotype distance index (MGIDI), multi-trait stability index (MTSI), and Rank-Sum index integrating genotype rankings across methods. BLUP-based selection produced the highest mean grain yield (2.86 t ha⁻¹), followed by the Rank-Sum index (2.84 t ha⁻¹), MTSI (2.81 t ha⁻¹), and MGIDI (2.80 t ha⁻¹), compared with the overall reference population mean of 2.74 t ha⁻¹. Twenty-one out of 63 progenies selected using 25% selection intensity were consistently identified across multiple selection strategies, indicating robust performance of the progenies across productivity and stability criteria. The integration of G×E analysis with complementary multi-trait selection approaches provides a practical framework for identifying superior progenies for advancement within drought- and nitrogen-tolerant maize populations and for the development of climate-resilient cultivars adapted to stress-prone environments in West Africa.