The experiment was conducted during May to December, 2024–2025 main seasons at mid-altitude bread wheat growing agro-ecologies of Ethiopia to study the agronomic performance, genotype-by-environment (G×E) interactions, heritability, cluster and correlation of bread wheat breeding genotypes across 11 multi-environment trials (METs).Utilizing an alpha lattice and partially replicated design, the study employed Factor Analytic Mixed Models (FAMM) and GGE biplot analysis to partition variance, GxE and identify drivers of yield stability. Grain yield ranged significantly from 1.60 to 6.50 t ha-1, underscoring substantial phenotypic plasticity across the environments. Results indicated that 55.80% of genotypes exceeded the grand mean yield, 77% yielded above 4.5 t ha-1, and 20% outperformed the standard check “Melka.” While grain yield exhibited high heritability (H2) ranged 16.48%–92.19%), traits like days to heading (DTH) and plant height (PHT) remained genetically stable (H2 > 85%). GGE biplot analysis partitioned testing sites into distinct mega-environments, identifying locations 25BWOPNMKU, 24BWPNMAB and 25BWOPNMAA as the most discriminative testing sites for selection. Although genotype EBW190004 achieved the highest mean yield (5.52 t ha-1), it showed high environmental sensitivity. Conversely, EBW190128 and EBW190063 were the most stable genotypes. Notably, EBW222059 appeared as the promising candidate for regional release, balancing high productivity (5.44 t ha-1) with exceptional resilience in moisture-constrained environments. Furthermore, the study confirmed high potential for genetic gain and demonstrated that the FAMM-based MET analysis provided a robust framework for identifying superior genotypes in bread wheat breeding programs across the mid-altitude regions of Ethiopia.
Bayisa Asefa, Berhanu Sime, Habtemriam Zegeye et al.· International Journal of Bio...· 0 citations
This study was conducted during May to December, 2022 at Kulumsa and Melkassa, in Ethiopia, evaluated 49 CIMMYT-introduced genotypes including the check variety across two locations using an alpha lattice design. The Combined analysis of variance revealed highly significant genetic variability for most of the traits, including grain yield (GYLD), thousand kernel weight (TKW) and hectoliter weight (HLW).Genotypes EBW222059, EBW222088 and EBW222079 were the top yielders, consistently outperforming the check. High genotypic (GCV) and Phenotypic (PCV) coefficients of variation for GYLD (22.24% and 24.42%) and TKW (13.38% and 15.32%) at Kulumsa indicated a strong genetic base for improvement. Very high broad-sense heritability for grain yield (83%) and days to heading (92%), coupled with high genetic advance as a percent of mean (GAM) for grain yield (41.72%), suggested the predominance of additive gene action, making phenotypic selection highly effective. However, maturity traits and plant height showed significant environmental influence, rendering direct selection for these traits ineffective. Correlation analysis confirmed that grain yield was strongly and positively associated with TKW and HLW at both genotypic and phenotypic levels. These results demonstrated that selecting for heavier, denser grains was a reliable strategy for yield enhancement. The study concluded that the identified elite genotypes should advance to multi-environment stability trials, while TKW and HLW should be prioritized as key selection markers to accelerate the development of high-yielding, adaptable wheat varieties. Thus, genetic variability in these genotypes could be exploited to enhance bread wheat yields under high-temperature conditions of Ethiopia.
Bayisa Asefa, Berhanu Sim, Demeke Zewdu et al.· International Journal of Eco...· 0 citations
