Exploring the Genetic Potential and Genotype × Environment Interaction of Winter Wheat Genotypes (Triticum aestivum L.) Under Irrigated and Heat Stress Conditions - Binod Panthi; Mukti Ram Poudel; Shivalal Nyaupane; Priyanka Kunwar (International Journal of Genomics)
Wheat is a major cereal crop essential for eradicating hunger and ensuring global food security, but its productivity is limited by abiotic stresses, particularly heat stress. To address this, a multienvironment field experiment was conducted across four environments (two under normal sowing conditions and two under heat-stressed conditions) to evaluate 20 winter wheat genotypes in the western Terai region of Nepal. Combined ANOVA and AMMI analysis revealed that environmental conditions significantly affected grain yield (GY) and its attributing traits (p<0.01), with a 24.74% reduction in yield under heat stress compared to normal irrigated conditions. Heritability and genetic advance indicated high genetic potential for days to booting (DTB), days to anthesis (DTA), spike length (SL), and thousand grain weight (TGW) under irrigated conditions, while DTB, plant height (Ph), SL, net spikes per meter square (NSPMS), TGW, and net grains per spike (NGPS) showed strong potential under heat stress. Correlation and path analyses revealed that GY was negatively correlated with DTB and positively correlated with Ph, NSPS, net spike weight (NSW), and TGW under irrigated conditions, while it was positively correlated with Ph, NSPS, and NGPS under heat stress (p<0.05). Therefore, based on MGIDI analysis, NL 1417, NL 1387, and NL 1413 were identified as ideal genotypes under irrigated conditions due to earlier booting, taller Ph, more spikelets, higher spike weight, and GY. Under heat stress, Bhrikuti, BL 4919, and NL 1417 were most ideal, showing taller Ph, more spikelets and grains per spike, and higher GY. AMMI biplot analysis revealed that NL 1346 and NL 1420 were specifically adapted genotypes to heat stress and irrigated conditions, respectively. Similarly, the “which-won-where” model of the GGE biplot identified NL 1346 as a high-yielding genotype under irrigated conditions and BL 4919 under heat stress. Mean versus stability analysis ranked BL 4919 as the most ideal genotype, combining high yield with wide adaptability. These findings highlight key traits and genotypes for developing climate-resilient and high-yielding wheat varieties.