STUDY OF USING ATR-FTIR SPECTROSCOPY AND MULTIVARIATE STATISTICAL (MSA) TECHNIQUES TO CLASSIFY SESAME PRODUCTS IN VIETNAM

Abstract

The research objective of this paper is to find a fast and reliable method for classification of sesame
products, with the aim of trademarks protection. The Fourier-transform infrared spectroscopy (FTIR)
and the multivariate statistical techniques including Principle Component Analysis (PCA) and Linear
Discriminant Analysis (LDA) were used. The spectral band data were simplified by selecting peak
coordinates prior to being processed by the multivariate statistical techniques. This method has
classified 15 samples of whole-seed sesame products in Vietnam markets, including 8 white sesame
samples and 7 black sesame samples collected from supermarkets, local markets and food suppliers in
Hanoi. Research results showed that the task of evaluating and classifying sesame products on the
market of each sesame brand has been successful. Two principle component analysis (PCA) and linear
discriminant analysis (LDA) methods supported each other in this task.