Quantification of Argan Oil (Argania spinosa L.) Adulterated with Avocado, Flaxseed, Walnut, and Pumpkin Oils Using Fourier-Transform Infrared Spectroscopy and Advanced Chemometric and Machine Learning Techniques

The increasing trend in the popularity of argan oil (AGO), a multi-beneficial health and cosmetic product, can leave it prone to adulteration. The overall goal of this study was to utilize an attenuated total reflectance Fourier-transform infrared spectroscopic and chemometric methods, including partial least squares (PLS), principal component regression (PCR), and artificial neural network (ANN) for the authentication of AGO in the presence of other oil adulterants, avocado oil (AVO), pumpkin seed oil (PSO), flaxseed oil (FSO), and walnut seed oil (WNO). All three chemometrics methods were able to effectively quantify the FSO adulterant concentration across all statistical models, with the most optimal results in the ANN model as applied in the testing set data (RMSEP = 1.454 %v/v, R2 = 0.821). Comparable results were also obtained for PLS (RMSEP = 1.727 %v/v, R2 = 0.807) and PCR (RMSEP = 1.731 %v/v, R2 = 0.846).