The variability of 2420 plants of tetraploid (2n = 4x = 28, AABB genome) wheat germplasm representing 121 accessions from Ethiopia were evaluated for 23 agro-morphological traits at Debre Zeit Agricultural Research Center area, Akaki substation, during the 2003 main season using multivariate methods. This enabled to assess the extent and pattern of variation of the germplasm with respect to regions, altitude classes and species and to identify the major traits contributing to the diversity. The first three and two principal components explained about 83 and 80% of the total variance among regions and altitudinal class, respectively. In the first principal component plant height, days to heading, the length and density of the spike, and kernel color were the most important traits contributing to variation that explained about 50% of regional variance. Cluster analysis grouped the accessions into 15 clusters, with 9 accessions remaining ungrouped. Based on the observed patterns of variation, it is concluded that there exists great variation in the germplasm, which provides opportunities to be utilized for genetic improvement.

A total of 4,840 entries of tetraploid wheat germplasm collections representing 121 accessions from Ethiopia were evaluated for phenologic and qualitative trait diversity. The objectives were to assess the diversity patterns of the germplasm with respect to regions, species and altitudinal class. High values of Shannon-Weaver Diversity Index (H 0 ) were recorded for most traits in each region, altitudinal classes, and species. Monomorphism was also high at accession levels. Both H 0 and Nei's gene diversity value for the entire data set (total gene diversity H T = 0.572; the within accessions gene diversity H S = 0.112; and gene diversity among accessions D ST = 0.460) showed the variation for the trait is mainly among accessions/populations rather than within accessions/population. The least mean H 0 value over all the traits used for the study was obtained from released varieties (among the origin groups) and Triticum dicoccon (among species). Triticum durum exhibit the highest H 0 for a number of traits. Accessions collected from altitudinal class III (2401-2800 m a.s.l.) and class II (2001-2400 m a.s.l.) showed the highest H 0 values for a valuable number of traits. Thus classifications using various phenology and qualitative traits enable to identify adaptation of a genotype and would improve the evaluation of genotype for potential adaptation.

A collection of 120 Ethiopian tetraploid wheat accessions was analysed for high-molecular weight (HMW) glutenin subunit, low-molecular weight (LMW) glutenin subunit and omega gliadin composition by SDS–PAGE. For the HMW glutenin subunits, a new allelic variant, 2****, was detected which has not been previously described at the Glu-A1 locus. A high proportion of Glu-A1x banding pattern was observed in durum wheat. For the Glu-B1 locus four different banding patterns were detected. Among those HMW glutenin subunits, 7+8 were the most common, while subunits 14+15 and 6+8 were found to be rare. A high degree of variation was evident for the LMW glutenin subunits and D-zone omega gliadins. The association of the composition of the gluten with quality has been discussed. This wide variation can be used in improving the quality of wheat and to widen its genetic base.

Improving crop adaptation and stability across diverse and changing environmental conditions is essential to increasing grain yield per unit area. In turn, this contributes to meeting the increasing global food demand. Nevertheless, a number of factors challenge the efficiency of crop improvement programs, of which genotype-by-environment interaction (GEI) is one of the major factors. This study aimed to evaluate the performance and phenotypic stability of 385 Ethiopian durum wheat landraces and 35 cultivars; assess the pattern of genotype by environment interaction (GEI) effect, and identify stable and high-yielding landraces or cultivars using the additive main effect and multiplicative interaction (AMMI) and genotype main effect plus genotype by environment interaction biplot (GGE-biplot). The experiment was laid out in an alpha lattice design with two replications at five test sites (Akaki, Chefe Donsa, Holeta, Kulumsa, and Sinana). The combined analysis of variance revealed highly significant effects (P ≤ 0.01) of environments (E), genotype (G), and GEI on a phenotypic variation of traits evaluated, including grain yield. For all traits, the amount of phenotypic variance and GEI explained by the GGE biplot was higher than in AMMI2, but both exhibited significant effects of E and GEI on the genotypes. The AMMI model identified G169, G420, G413, G139, G415, G416, G417, and G418 as stable genotypes across testing sites. Whereas, the GGE biplot identified G169, G420, G415, G139, G106, G412, G413, and G417 as both high-yielding and stable across test sites. Hence, genotypes identified as stable and high yielding in the present study could be used in a durum wheat breeding program aimed at identifying genes and molecular markers associated with the crop’s productivity traits as well as developing stable and high-yielding cultivars for use in East Africa and beyond.