Abstract
SummaryCommercially grown US Runner peanuts from 10 cultivars comprising 151 samples over two recent crop years contained 10.54 ± 1.50 mg α‐tocopherol (T)/100 g kernel, 0.31 ± 0.12 β‐T, 10.93 ± 2.04 γ‐T and 0.76 ± 0.31 δ‐T. Box plots revealed segregations in tocopherol levels for normal, mid and high oleic cultivars as well as production years among the cultivars. Correlation coefficients indicated positive relationships between β‐ and γ‐T (r = 0.436, P < 0.001) and γ‐ and δ‐T (r = 0.437, P < 0.001) but no relationship between α‐ and γ‐T (r = −0.032). Principal component analysis of tocopherol contents simplified the data set and revealed two significant principal components (PCs) (PC1 and PC2), which together accounted for 72.6% of the total variance in the data. Eigen analysis of the correlation matrix loadings of the PCs revealed that PC1 was mainly contributed to by α‐, β‐ and δ‐T, whereas PC2 was by γ‐T. This study clearly demonstrates that using a chemometric approach to analyse raw data can provide scientists with more information concerning the variation in peanut cultivars than by simply reporting the means and standard deviations of HPLC results.
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