Comparative study of three fingerprint analytical approaches based on spectroscopic sensors and chemometrics for the detection and quantification of argan oil adulteration.

Background: Argan oil is one of the purest and rarest oils in the world, so that the addition of any further product is strictly prohibited by international regulations. Consequently, it is necessary to establish reliable analytical methods to ensure its authenticity. In this study, three multivariate approaches have been developed and validated using fluorescence, UV-visible, and attenuated total reflectance Fourier transform mid-infrared (FT-MIR) spectroscopies.

Results: The application of a partial least squares discriminant analysis model showed an accuracy of 100%. The quantification of adulteration have been evaluated using partial least squares (PLS) regression. The PLS model developed from fluorescence spectroscopy provided the best results for the calibration and cross-validation sets, as it showed the highest R (0.99) and the lowest root mean square error of calibration and cross-validation (0.55, 0.79). The external validation of the three multivariate approaches by the accuracy profile shows that these approaches guarantee reliable and valid results of 0.5-32%, 7-32%, and 10-32% using fluorescence, FT-MIR and UV-visible spectroscopies respectively.

Conclusion: This study confirmed the feasibility of using spectroscopic sensors (routine technique) for rapid determination of argan oil falsification. © 2021 Society of Chemical Industry.