Integrating multi-environment and path coefficient analysis for the identification of yellow rust-resistant bread wheat (Triticum aestivum L.) genotypes

Rapid turnover of varieties and limited access to rust-resistant wheat varieties across agroecologies are due to the rapid mutation of yellow rust pathogens. This study aimed to identify high-yielding, yellow rust-resistant genotypes and assess the severity of yellow rust across wheat growth stages. 150 bread wheat genotypes were evaluated using an alpha lattice design with two replications at three locations across two major wheat-producing areas of Ethiopia (Arsi and North Shewa) during the 2022 and 2023 main cropping seasons. A mixed-model analysis was conducted in R. The ANOVA results revealed highly significant (< 0.001) effects of genotype, year, and location interactions, thereby highlighting strong seasonal and environmental influences on yellow rust incidence and other traits. Yellow rust severity varied markedly across growth stages, with the highest disease pressure observed at the dough and heading stages. Thirteen genotypes at Kulumsa and 64 genotypes at Enewari showed high yellow rust severity, indicating the occurrence of different virulence spectra in the environments under study and the need for multiple-environment screening for a valid assessment of resistance to yellow rust. Path coefficient analysis further revealed that thousand kernel weight has the strongest direct positive effect (0.43) on grain yield. The coefficient of infection (CI) exhibits both direct (-0.29) and indirect negative effects, highlighting the significance of resistance in sustaining productivity. In conclusion, 16 high-yielding and yellow rust-resistant genotypes were identified as promising candidates for future wheat improvement.