10th U6+ Consortium of African Universities International Conference

Wheat (Triticum aestivum L.) is an important food security crop in Kenya, but its productivity is constrained by a relatively narrow genetic base and environmental influences on trait expression. This study evaluated genetic variability, genotype × environment (G×E) interaction, heritability, genetic advance, and trait associations among five wheat genotypes comprising two parental lines and three mutation-derived lines. Field experiments were conducted in a randomized complete block design with three replications across six environments representing three locations in Kenya over two consecutive growing seasons. Grain yield, plant height, days to heading, days to maturity, tillers per plant, grains per spike, and thousand-kernel weight were evaluated. Variance components were estimated using restricted maximum likelihood (REML), while broad-sense heritability, expected genetic advance, and Pearson correlation analyses were performed to evaluate the genetic control of agronomic traits, estimate selection potential, and determine relationships among traits. Significant (P < 0.001) genotypic, environmental, and genotype × environment effects were observed for grain yield, indicating substantial genetic variability and differential responses among genotypes across environments. Grain yield exhibited moderate broad-sense heritability (H² = 0.62), with variance components of σ²G = 0.014, σ²GE = 0.021, and σ²e = 0.018. Mean grain yield ranged from 2.55 to 2.85 t ha⁻¹, with the mutant genotype NJM1 recording the highest yield (2.85 t ha⁻¹), exceeding its parental line NJP (2.55 t ha⁻¹). Grain yield was positively correlated with thousand-kernel weight (r = 0.42), while plant height and thousand-kernel weight exhibited stronger genetic control and greater potential for phenotypic selection. All the analyses were performed in R using several specialized packages. These findings demonstrate that mutation breeding generated useful genetic variability and that integrating multi-environment evaluation with heritability and genetic advance analyses provides a useful approach for identifying superior wheat genotypes for breeding in Kenya.