Multi-environment trials have a fundamental role in selection of the best genotypes across different environments before its commercial release. This study was carried out to identify high-yielding stable sunflower genotypes using the graphical method of the GGE biplot. For this purpose, 11 new hybrids along with four cultivars were evaluated in a randomized complete block design with four replications across 8 environments (combination of years and locations) during 2018–2020 growing seasons. The results indicated that genotype (G), environment (E) and genotype × environment (G×E) effects were significant for oil yield. The G, E and G×E interaction effects accounted for 51.94, 9.50 and 18.67% of the total variation, respectively. Results of biplot analysis showed that the first and second principle components accounted 45.9% and 20.4%, respectively, and in total 66.3% of oil yield variance. GGE biplot analysis indicated two major mega-environments of sunflower testing locations in Iran. Based on the hypothetical ideal genotype biplot, the genotypes G3 and G5 were better than the other genotypes for oil yield and stability, and had the high general adaptation to all environments. Ranking of genotypes based on the ideal genotype from the most appropriate to most inappropriate genotypes is as follows: G5 ˃ G3 ˃ G8 ˃ G14 ˃ G6 ˃ G2 ˃ G13 ˃ G12 ˃ G10 ˃ G11 ˃ G1 ˃ G7 ˃ G4 ˃ G15 ˃ G9. Furthermore, ranking the environments based on the ideal environment introduced Sari location as the best environment. Therefore, the Sari location can be used as suitable test location for selecting superior genotypes of sunflower in Iran. Generally, our results showed the efficiency of the graphical method of the GGE biplot for selection of the genotypes that are stable, high yielding, and responsive.

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