Evaluation of yield performance of early maturing soybean (Glycine max L. Merill) genotypes in Ethiopia by using GGE Biplot model

Genotype main effect and genotype by environment interaction biplot analysis is the best fit model for which-won-where pattern analysis, genotype, and test environment evaluation. Hence, the aim of this study was to identify stable and high-yielding soybean genotypes for production in diverse environments by using the genotype main effect and genotype by environment biplot stability model. Eighteen soybean genotypes were evaluated across six environments during the 2019 cropping season by using a randomized complete block design with four replications. Among evaluated environments and genotypes, Tiro-afeta gave the highest yield (3.71 t ha -1); while Humera gave the lowest yield (1.37 t ha-1), and genotype JM-HAR/PR142-15-SB gave the highest mean grain yield of 2.9 t ha -1 across the six locations. Based on the information generated from the GGE biplot, Tiro Afeta and Areka were identified as ideal environments, whereas genotypes PR-143-(14), JM-HAR/G99-15-SD-2 and JM-HAR/PR142-15-SB were ideal genotype. The ‘which won where' biplot of the GGE analysis revealed that the six environments grouped into three different mega-environments with different winning genotypes. Among the testing environments, Areka, Sirinka and Humera grouped into one mega environment; while Tiro afeta grouped into the second mega environment and Jimma and Hawasa were classified into the third mega environment with the winning genotypes JM-HAR/PR142-15-SB, PR-143-(14) and KS4895 for each mega environment, respectively. Based on the GGE biplot stability model used in the study, JM-HAR/G99-15-SD-2, JM-HAR/PR142-15SB, and PR-143-(14) were high yielder and stable genotypes. Hence, these genotypes were recommended for variety verification and release after additional evaluation for more seasons.