Detection and quantification of extra virgin olive oil adulteration by other grades of olive oil using front-face fluorescence spectroscopy and different multivariate analysis techniques.

This study explores the use of front-face fluorescence spectroscopy to detect extra virgin olive oil (EVOO) adulteration with lower-grade olive oils (virgin, ordinary virgin, lampante virgin, refined, and pomace) at 5-50 % adulteration levels. Emission spectra were analyzed using principal component analysis, factorial discriminant analysis, and partial least square discriminant analysis (PLS-DA) at excitation wavelengths of 270, 290, and 430 nm. PLS-DA at 430 nm provided the best results, achieving 100 % classification accuracy and perfectly separating 12 groups of pure and adulterated samples. For purity prediction, regression models (partial least squares, principal component, and support vector machine) applied to emission spectra data yielded high R values of 0.995, 0.96, and 0.98 at 430 nm, 290 nm, and 270 nm, respectively, with a low prediction error of 1.09 %. These findings confirm the method's high accuracy for detecting and quantifying EVOO adulteration.