Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics
Kharbach, Mourad; Yu, Huiwen; Kamal, Rabie; Marmouzi, Ilias; Alaoui, Katim; Vercammen, Joeri; Bouklouze, Abdelaziz; Vander Heyden, Yvan (2022-02-25)
Kharbach, M., Yu, H., Kamal, R., Marmouzi, I., Alaoui, K., Vercammen, J., Bouklouze, A., & Vander Heyden, Y. (2022). Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics. Food Chemistry, 383, 132565. https://doi.org/10.1016/j.foodchem.2022.132565
© 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe20230928137737
Tiivistelmä
Abstract
Recognized for its nutritional and therapeutic use, extra-virgin Argan Oil (EVAO) is frequently adulterated. Selected-Ion Flow-Tube Mass Spectrometry (SIFT-MS) spectra were applied to quantify adulterants (i.e., Argan oil of lower quality (LQAO), olive oil (OO), and sunflower oil (SO)) in EVAO. Four data sets, i.e., using H₃O⁺, NO⁺, O2⁺ radical dot reagent ions, and the combined data were considered. Soft independent modelling of class analogy (SIMCA), and partial least squares discriminant analysis (PLS-DA) were assessed to distinguish adulterated- from pure EVAO. The effectiveness of SIFT-MS associated with PLS and support vector machine (SVM) regression to quantify trace adulterants in EVAO was evaluated. Variable Importance in Projection (VIP), and interval-PLS (iPLS) were also investigated to extract useful features. Different models were built to predict the EVAO authenticity and the degree of adulteration. High accuracy was achieved. SIFT-MS spectra handled with the appropriate chemometric tools were found suitable for the quality evaluation of EVAO.
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