Full Length Research Paper
The experiment was carried out to access the inter relationship of genotypes in their oil yield with seed yield, oil content and other yield components and to determine cluster of white seeded sesame genotypes and environments based on their oil yield. Seventeen sesame genotypes were tested at six environments in northern Ethiopia during 2015 main season. The experiment was laid out in Randomized Complete Block Designs (RCBD) with three replications across all the environments. Seed yield had a significant and positive correlation (P≤0.01) with number of branches (r = 0.414) and number of capsules (r =0.468). Positive correlation seed yield with number of capsules and number of capsules indicated that better yield can obtain from highly branched plants and high number of capsules because the number of capsules increases with the degree of branching. Seed yield was negative significant correlated with days to maturity (r =-0.500) and flowering time (r = -0.626), significant at (p≤0.05) and (p≤0.01), respectively. The negative association between seed yield and days to flowering and maturity indicated that moisture stress after flowering might have caused relatively a yield reduction in the late maturing genotypes. Whereas, the early flowering and early maturing genotypes can escape the moister stress conditions. Based on the cluster analysis of 17 white seeded sesame genotypes classified in to different four distinct clusters. Cluster II, III and IV had high mean yield, oil content and oil yield than the other clusters. Genotypes grouped in those clusters had also greater genetic divergence important for farther yield, oil yield and oil content improvement program breeding in northern Ethiopia. Sesame growing environments also clustered in to four groups. Environments grouped in Cluster I, II and IV had high seed yield, oil content and oil yield. Hence, environments grouped in those clusters are important for seed yield, oil content and oil yield production improvement program in the study areas.
Key words: Cluster analysis, correlation, dendrogram.
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