The procedures in the selection of good performing and stable genotypes are complicated by the phenomenon of genotype by environment interaction to recommend new sorghum genotypes for different environments. Therefore, 49 genotypes (hybrids + varieties) were tested at five locations in a simple lattice design with two replications during the 2016 main cropping season to estimate the magnitude and nature of GEI for yield and yield related traits and to determine yield stability of striga resistant sorghum genotypes in the dry lowland areas of Ethiopia. The result of the combined analysis of variance for grain yield revealed very highly significant (Pâ‰¤0.001) difference among environment (E), genotype (G) and genotype Ã— environment interaction (GEI). Based on the combined ANOVA over locations, the mean grain yield of environments ranged from 588 kg ha-1 in Humera to 4508 kg ha-1 in Sheraro. The highest yield was obtained from ESH-1 (3278 kg ha-1), while the lowest was from K5136 (735 kg ha-1) and the average grain yield of genotypes was 2184 kg ha-1. Different stability models were used in measuring of genotype stability such as AMMI Stability Value (ASV), Yield Stability Index (YSI), coefficient of regression (bi) and deviation from regression (S2di). Yield was significantly correlated with bi (0.91), r2 (0.55) and ASV (-0.56), while it was not correlated with S2di (-0.26). The non-significant correlation among yield and stability statistics indicated that, stability statistics provide information that cannot be collected from average yield. The high positive correlation among mean grain yield and stability parameters is expected as the values of these parameters were higher for high yielding genotypes and the vice versa. Highly correlated stability parameters indicate that they can measure stability similarly. There were inconsistencies with the univariate stability parameters used, which created uncertainty to select or recommend the stable genotypes. The main problem of selection of superior genotypes in Ethiopia is the unpredictable weather changes from year to year and the variations of agro-ecologies leading to high contributor to genotype x environment interactions. Therefore, as the data is from one year, it is necessary to repeat the experiment across locations at least for one year to identify locations where the genotypes to be tested.
Keywords: ASV,GEI, Sorghum bicolor L., Hybrid, YSI