Application of chemometrics approaches to determine the virgin sesame oil adulterants using FTIR spectral data

Abstract

A methodology based on Fourier transform infrared spectroscopy with attenuated total reflectance sampling technique, combined with multivariate analysis, was developed to monitor the adulteration of extra virgin sesame oil with groundnut oil and palm oil. Principal components regression (PCR), Hierarchical Cluster Analysis, (HCA) and discriminant analysis (LDA) are used to quantify the percentage of adulteration based on spectral data, using different proportion of the samples. The wave numbers associated with the biochemical differences among several types of edible oils have been investigated using chemometric tools.