Phenotypic Stability Analysis of Oil Yield in Sesame (Sesamum indicum L.) Verities across the Awash Valleys in Ethiopia

Abstract

A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yield in sesame varieties and to identify stable and promising varieties for general and specific adaptations. The experiment was carried out at three locations across the areas of the Awash Valley in Ethiopia; namely Assaita, Melkassa and Werer over two seasons during the 2011 cropping and 2012 off seasons. Ten improved sesame varieties were planted in a randomized complete block design (RCBD) replicated trice in each location and year. Analysis of variance using AMMI model revealed significant differences (P<0.01) for genotype, environment, GEI and interaction principal component (IPCA1), suggesting differential response of varieties across testing environments and the need for stability analysis. Stability analysis using Biplot graph and AMMI stability value were done to further shed light on the GEI of oil yield. The study revealed that the environment Wr1 (Werer season-I) had relatively little interaction effects with above average mean oil yield per environment. Hence, it can be recommended as ideal environment for growing the present set of sesame genotypes for breeding programme. Ranking of genotypes based on the different stability indices identified the varieties Adi and Serkamo to be the most stable genotypes across all environments. Therefore, these varieties can be recommended as promising cultivars for oil yield of sesame across diverse agro-ecologies of the Awash Valley to exploit their yield potential. On the other hand, the two high yielding varieties Abasena and Tate were found to be highly interactive and they are recommended for cultivation under favorable environmental conditions for oil yield. Moreover, the study indicated that high performance of genotypes for oil yield recorded in season two (2012). Hence, the off season generally is suggested as the best environment for oil yield of sesame across the areas of the Awash Valley. In this study, AMMI analysis with two IPCA was the best predictive model to reveal the maximum GEI for oil yield in sesame.