1P-58 PDF
Componential analysis of edible oils by multivariate analysis of ASAP-MS
Short Abstract: In this study, we have developed a new classification method of edible oils using multivariate analysis. Edible oils are known as a mixture of triglycerides constructed from the various fatty acids. There is an increasing interest in the classification method which distinguishes the variance of the unsaturation degree of the fatty acids. ASAP-MS is critically useful for rapid and simple analysis of the oils, but it is supposed to be difficult to determine the components by only comparing with each simple mass spectrum. On the other hand, multivariate analysis which is useful to analyze complex mixture at a time has been applied as a powerful method to diverse analytic fields. Therefore, we embarked on our study to provide a new effective analytical manner of the oils. The results suggested that principal component analysis (PCA) of edible oils mainly indicated the difference of fatty acid moiety, and are closely similar to that from multivariate analysis by NMR with components analysis by GC/MS.