Chemometric approach to fatty acid profiles in Runner-type peanut cultivars by principal component analysis (PCA)

Abstract: The fatty acid profiles of commercially-grown Runner-type peanut cultivars (i.e., 10 cultivars, n =151) collected over two production years (2005 and 2006) were determined by gas–liquid chromatography. Eight major fatty acids were identified in the sample set including palmitic (C16:0), stearic (C18:0), oleic (C18:1, ω9), linoleic (C18:2, ω6), arachidic (C20:0), gondoic (C20:1, ω9), behenic (C22:0), and lignoceric (C24:0) acids. Based on the oleic to linoleic acid (O/L) ratio, these cultivars were denoted as normal, mid-, and high-oleic peanut types. Correlation coefficients (r) between the eight major fatty acids identified were generated and revealed an inverse association between oleic and linoleic acids (r =–0.997, P <0.001), while oleic acid and linoleic acid were positively correlated to gondoic acid (r =0.818, P <0.001) and palmitic acid (r =0.967, P <0.001), respectively. Principal component analysis (PCA) of the fatty acid data yielded three significant PCs (i.e., eigenvalues⩾1), which together account for 87.18% of the total variance in the data set; with PC1 contributing 60.45% of the total. Eigen analysis of the correlation matrix loadings of the three significant PCs revealed that PC1 was mainly contributed to by palmitic, oleic, linoleic, and gondoic acids; PC2, by behenic acid; and PC3, by lignoceric acid. The score plot generated between PC1 and PC2 successfully segregated normal, mid- and high-oleic peanut cultivars, while the PC1–PC3 plot segregated normal and the combination of mid- and high-oleic acid cultivars. [Copyright &y& Elsevier]