Chemometric approach to fatty acid profiles in soybean cultivars by principal component analysis (PCA)

Abstract

The purpose of this study was to investigate the fatty acid profiles in 18 soybean cultivars grown in Korea. A total of eleven fatty acids were identified in the sample set, which was comprised of myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1, ω7), stearic (C18:0), oleic (C18:1, ω9), linoleic (C18:2, ω6), linolenic (C18:3, ω3), arachidi c (C2 0:0), gondo i c (C2 0:1, ω9), behenic (C2 2:0), and lignoceric (C2 4:0) acids by gas - liquid chromatog - raphy with flame ionization detector (GC-FID). Based on their color, yellow-, black-, brown-, and green-colored cultivars were denoted. Correlation coefficients (r) between the nine major fatty acids identified (two trace fatty acids, myristic and palmitoleic, were not included in the study) were generated and revealed an inverse association between oleic and linoleic acids (r=-0.94, p<0.05), while stearic acid was positively correlated to arachidic acid (r=0.72, p<0.05). Principal component analysis (PCA) of the fatty acid data yielded four significant principal components (PCs; i.e., eigenvalues>1), which to g ether acc ount fo r 8 1.49 % o f the total varianc e in the data set; with PC1 contributing 28.16% of the total. Eigen analysis of the correlation matrix loadings of the four significant PCs revealed that PC1 was mainly contributed to by oleic, linoleic, and gondoic acids, PC2 by stearic, linolenic and arachidic acids, PC3 by be henic and lignoceric acids, and PC4 by palmi ti c aci d. The score plots generated between PC1-PC2 and PC3-PC4 segregated soybean cultivars based on fatty acid composition.