Assessment of Genetic Diversity of Cultivated Sunflower in Terms of Oil Content, Fatty Acid Compositions and Seed Traits

Abstract

Abstract Sunflower (Helianthus annuus L.) cultivated accessions contains useful genes encoding different phenotypic characteristic through which the origin of sunflower oil could be hypothesized. Those genes could be later used for future breeding programs for providing better quality sunflower oil. The objective of the current study is to discriminate genetic diversity of cultivated sunflower seeds collection through the statistical methods such as PCA (principal component analysis) and Pearson correlation analysis for two characters; seed oil content and fatty acid composition. Materials and methods: In the present study, the genetic diversity of 107 cultivated accessions of Helianthus annuus L. was studied for fatty acid composition and oil content. Pearson correlation and Principal Component Analysis (PCA) were used to determine the correlation between the studied parameters. A dendrogram using Ward’s method and the squared Euclidean distance coefficient was produced. The results showed that the average seed oil content in the accessions was 29.51 % with a profile of 7.23 % palmitic acid (PAL), 5.04 % stearic acid (STE), 36.85 % oleic acid (OLE) and 50.85 % linoleic acid (LIN). The highest oil content was found in accession Hopi Dye (43.66 %). High levels of OLE were observed in the Csehszlovakiai “B” (60.14 %) and Vk-47 (55.73 %) accessions. On the other hand, Fuksinka 10 and Georgia accessions had the lowest mean PAL values (4.98 %) and STE (1.81 %), respectively. Palmitoleic acid (PALM) was identified in 29 accessions and linolenic acid (LIL) in 32 accessions, the highest in Gonondu (0.86 %) and Oleisty Borovskil (0.76 %), respectively. A significant negative relationship between OLE, STE and saturated fatty acids (SFA) with oil content was observed. The Pearson correlation of unsaturated fatty acids to saturated fatty acids ratio (UFA/SFA ratio) with oil content was positive and significant. In the PCA analysis, four major principal components (PCs) were identified, accounting for 87.19 % of the total variations. In PC1, PAL and STE (with positive coefficients) and UFA/SFA ratio (with negative coefficients), had the highest loadings, which determined 41.33 % of the total variations. In PC 2, OLE (with negative coefficient) and LIN (with positive coefficient), had the highest values. According to the dendrogram of the accessions, they were grouped into seven distinct clusters and the accessions in clusters 4 and 7 contained high UFA and low SFA values. The findings of this study showed that there is a significant genetic diversity among the accessions, which can be used to maximize heterosis in sunflower breeding programs.