Evaluation of sunflower (Helianthus annuus L.) genotypes for quantitative traits and character association of seed yield and yield components at Oromia region, Ethiopia

Sunflower is one of the most important oil crops in Ethiopia in terms of edible oil and holds significant promise for improvement and development improved varieties. The present study was initiated to study the genetic diversity and performance of sunflower genotypes that enables to harness its seed yield and oil content improvement by using 25 genotypes including two standard checks namely Russian black and Oissa at Holeta Agricultural research center by using simple lattice design. The genotypes characterized for different agro-morphological traits and oil content. The analyses of variances have revealed highly significant difference among the genotypes for all the characters. The data revealed that sufficient variability was present among sunflower genotypes considered under this study. High Phenotypic coefficient variation, Genotypic coefficient variation and estimates of heritability (broad sense) were obtained for seed yield, oil content, oil yield, and thousand seed weight while the above parameters were found to be less compared to characters. High heritability accompanied with high genetic advance, as per percentages of mean was observed in case of seed yield, oil content, oil yield per plot, harvest index, head diameter and plant height suggesting importance of additive genetic action in the inheritance of these characters. While, high heritability coupled with moderate genetic advance was observed for days to maturity and days to 50% flowering, seed yield per plant, leaf number and reproductive phase. These indicate that the traits were controlled by additive gene action. Days to maturity, oil yield, seed yield per plant, head diameter and reproductive phase revealed positive association and had positive direct effect of seed yield. Based on genetic distance (D2 value), the genotypes under this study were grouped into two clusters indicating wider genetic diversity among the genotypes. Among the two clusters, cluster II represented the largest genotypes (18) followed by cluster I (4) genotypes and cluster S1, S2, and S3 genotypes. The clustering pattern indicated the absence of relationship between genetic diversity and geographical origin of genotypes. The maximum inter-cluster distance was observed between cluster I (D2 = 6.85). Out of the thirteen traits four significant principal components (PCs) exhibited more than 1 Eigen value and showed about 80.2% variability among the genotypes studied. The first PC accounted 41% of the variances that implies greater proportion of variable information explained by PC1. This indicates that any improvement of these characters would result in a substantial increment of seed yield.