Partial Least Squares-Discriminant Analysis Classification for Patchouli Oil Adulteration Detection by Fourier Transform Infrared Spectroscopy in Combination with Chemometrics.

This study aims to test chemometrically partial least squares-discriminant analysis (PLS-DA) classification models to detect the adulteration of patchouli oil (PO) with gurjun balsam oil (GBO) by utilization of Fourier transform infrared spectroscopy. Unsupervised analysis was tested using the pattern recognition method using the principal component analysis model against the original spectrum at wavenumbers 4000-500 cm and at the fingerprint area (1800-600 cm). Model testing was also carried out on the spectrum that had been pre-processed using the standard normal variate, second derivative Savitzky-Golay, and normalization approaches.