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
Bayisa Asefa, Berhanu Sime, H. Zegeye et al.· International Journal of Agr...· 0 citations
Bread wheat is a vital crop for Ethiopia’s food security, with expanding cultivation driven by variety development efforts and strategic national initiatives. This study presents a multi-environment trial (MET) analysis to evaluate the genetic performance of 140 unique bread wheat genotypes, using data from 20 trials conducted across Ethiopia’s major wheat-growing regions. Each trial was designed using a row-column design (RCD) arranged in a rectangular array of plots. Four traits —grain yield (GYLD), hectoliter weight (HLW), days to heading (DTH), and thousand kernel weight (TKW) were considered in the analysis. We fitted a factor analytic linear mixed model (FAMM) based on a one-stage approach. Spatial models were fitted to account for field trends, while factor analytic (FA) model was used to model genotype-by-environment (G × E) effects. Model comparisons showed that the FA model consistently outperformed the diagonal (DIAG) model across all traits, offering greater flexibility capturing the variation in G × E effects. Heritability estimates were generally high, especially for DTH, which also showed strong genetic correlations across environments highlighting its reliability as a selection trait. In contrast, yield-related traits exhibited complex G × E patterns and variable heritability, reflecting their polygenic nature and environmental sensitivity. While the highest-yielding check variety, Balcha, retained its lead in GYLD, three genotypes—EBW202104, EBW202110, and EBW193155—demonstrated stable and competitive performance across environments for multiple traits, particularly grain quality and maturity. This makes them strong candidates for varietal release and registration for commercial production in Ethiopia. Future research should integrate genomic and environmental data.
N. Geleta, Tarekegn Argaw, Bayisa Asefa et al.· Discover Agriculture· 0 citations
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
The experiment was conducted during July–November in 2023 main cropping season at Kulumsa Agricultural Research Center to assess the extent of genetic variability and the association among traits in bread wheat genotypes. Analysis of variance revealed significant genetic variation (p<0.01) among genotypes for seven of the nine studied characters. Grain yield exhibited the widest range, varying from 891(EBW232651) to 1682.5 (EBW232625) kg ha-1, with an average of 1325.96 kg ha-1. Encouragingly, 78% of studied genotypes exhibited superior grain yield compared to check Balcha (1242.5 kg ha-1). A moderate range of PCV and GCV were obtained for agronomic score, grain yield and thousand kernel weight, offer the most significant potential for improvement through selection. The high broad-sense heritability observed for days to heading days to maturity, hectoliter weight and thousand kernel weight, and traits with high GAM viz. grain yield and agronomic score, suggested a significant role of additive gene action in controlling these traits. Grain yield exhibited strong positive and highly significant correlations (p<0.01) at both genotypic (rg) and phenotypic (rp) levels with Agronomic Score, Thousand kernel weight and hectoliter weight. Grain yield displayed a strong negative and highly significant correlation (p<0.01) at both genotypic and phenotypic levels with yellow rust severity. The negative correlation with yellow rust severity emphasized the need to prioritize resistance breeding to protect yield potential from this disease. This finding suggested that selecting for improved agronomic score, hectoliter weight, and thousand kernel weight could be effective indirect selection strategies for enhancing grain yield in this breeding population.
Demeke Zewdu, Gadisa Alemu, Ruth Duga et al.· International Journal of Bio...· 0 citations
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