Statistical Evaluation of Triacylglycerol Composition in Plant Oils Based on High-Performance Liquid Chromatography−Atmospheric Pressure Chemical Ionization Mass Spectrometry Data

Abstract

The statistical evaluation of triacylglycerol profiles in plant oils based on high-performance liquid chromatography mass spectrometry (HPLC/MS) analysis enables the differentiation of various plant oils on the basis of the multidimensional data matrix. A data set of 93 oil samples from 60 varieties of plants composed from 355 triacylglycerols is evaluated using the principal component analysis. Analyzed samples are resolved in the principal component analysis plot, and similarities among some types of plant oils are visualized by the formation of clusters. The authentication of plant oils is tested with model samples of olive oil adulterated with sunflower oil at different concentration levels. Our HPLC/MS method using the statistical multivariate data analysis of a large data matrix enables a clear identification of adulterated olive oils already from 1% of added sunflower oil as an adulterant.