Multiple adulteration detection of olive oils by Raman spectroscopy

The increasing prevalence of multiple adulteration in olive oil, which undermines product authenticity and market integrity, necessitates the development of advanced detection methods. In this study, a portable Raman spectrometer was employed to address this issue, with adulterant mixtures designed using a D-optimal mixture approach to ensure representative blending. The results showed that principal component analysis (PCA) was unable to distinguish between authentic and adulterated samples, whereas partial least squares-discriminant analysis (PLS-DA) successfully differentiated the two groups. These findings demonstrate the technical feasibility of combining Raman spectroscopy with PLS-DA for detecting complex olive oil adulteration, offering a promising basis for portable, rapid authentication tools to counter increasingly sophisticated fraud in the edible oil industry.