Effect of thermal oxidation on detection of adulteration at low concentrations in extra virgin olive oil: Study based on laser-induced fluorescence spectroscopy combined with KPCA–LDA

The fluorescence spectra of oil samples were obtained by laser-induced fluorescence spectroscopy and thermal oxidation stoichiometry at room temperature and 80 °C respectively. The Support Vector Machine, combined with Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), could distinguish pure extra virgin olive oils (EVOO) from oils adulterated with 2% soybean oil, with a recognition rate of 100%. Besides, as the intensity of the fluorescence spectra and concentration of the adulterants showed a non-linear relationship, linear dimension reduction methods may lead to overlapping of the different adulterated concentrations features, resulting in large errors in quantifying adulteration. In this paper, Kernel Principal Component Analysis-Linear Discriminant Analysis (KPCA-LDA) was applied instead of PCA-LDA to extract fluorescence spectra features, and a Partial Least Squares Regression model was established, which could quantify adulterants such as low percentages of soybean oil in EVOO. The coefficient of determination and root mean squared error were 0.92 and 2.72%, respectively.