Screening Method for Argan Oil Adulteration with Vegetable Oils: An Online HPLC Assay with Postcolumn Detection Utilizing Chemometric Multidata Analysis

Abstract

This study is focused on examining the tocopherol isomers (alpha-, gamma-, and delta-) fingerprinting by online RP-HPLC analysis with post column detection using CUPRAC (cupric reducing antioxidant capacity) methodology for argan oil authenticity. The proposed online assay was validated with good precision, reproducibility, and linearity. Sixteen argan oil samples (100% pure-certified and other commercial argan oils), possible adulterating vegetable oils (i.e., olive, sunflower, corn, and soya oils), and virgin argan oil blended with olive, sunflower, corn, and soya oils at levels of 5%, 10%, 15%, and 20% were analyzed. Spectrophotometric CUPRAC, DPPH, and ABTS assays were applied. Discrimination of fraudulent argan oils from virgin samples was performed by utilizing orthogonal partial least-squares discriminant analysis (OPLS-DA) regression modeling with good sensitivity and specificity. We suggested [gamma-toc/alpha-toc] value as a new first screening adulteration factor (AF) that could be used to assess fraudulent argan oil samples. The distinct decrement in AF value was observed by the increase of adulteration rate. The AF values for virgin argan oils were ranged from 11.8 (lower limit) to 18.6 (upper limit). The presence of beta-sitosterol detected in commercial argan oils (with AF values out of limit values) was evaluated as fraudulent which was in accordance with the proposed assay. Our method enabled the detection of argan oil samples at adulteration levels of >5% in the case of sunflower, olive, and soya oils, >15% in the case of corn oil. This method may be an alternative and specific assay for the authentication and quality detection of commercial argan oils.