Multi-environment trial (MET) evaluation of bread wheat (Triticum aestivum L.) genotypes across the highlands of Ethiopia using factor analytic mixed models
Abstract
This study evaluated 37 multi-environment trials (METs) comprising 787 bread wheat genotypes, using Alpha lattice and partially replicated designs across the highland agro-ecological zones of Ethiopia from 2021 to 2024. The study identified significant phenotypic variation, with grain yields ranging from 1.54 to 7.39 t ha⁻¹ across environmental trials. The genotypes EBW170049 and EBW170074 appeared as superior performers, yielding 5.31 t ha⁻¹ and 5.17 t ha⁻¹, respectively, while 65% of the genotypes exceeded the 4.5 t ha⁻¹ productivity threshold. The superior performance of EBW170049 was complemented by strong grain quality parameters, with HLW of 70.37 kg hl-1 and TKW of 38.46 g, suggesting a stable and efficient grain-filling period. A Factor Analytic Mixed Model (FAMM) captured over 99.9% of the cumulative genetic variance, facilitating a precise decomposition of environmental interactions. Broad-sense heritability reached 99.16% for days to heading and 98.16% for grain yield in high-potential sites, although environmental sensitivity reduced plant height heritability to 52.65% in strained locations. Trait-based environmental clustering helped delineate principal mega-environments and identified specific trial outliers. The finding revealed that early-to-medium maturity demonstrated by superior genotypes serves as a critical terminal stress-escape strategy. Furthermore, top-performing genotypes generally exhibited medium plant height as lodging resistance potential. Regarding biotic stress, genotypes EBW170051 and EBW170058 showed superior yellow rust resistance, while EBW222276 remained resistant to stem rust. Overall, the study confirmed high genetic gain potential and demonstrated that FAMM-based MET analysis is a robust framework for identifying superior genotypes and enhancing productivity and climate resilience in bread wheat breeding programs. Int. J. Agril. Res. Innov. Tech. 16(1): 96-113, June 2026