University of Oulu

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

Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics

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Author: Kharbach, Mourad1,2,3; Yu, Huiwen4; Kamal, Rabie5;
Organizations: 1Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland
2Department of Food and Nutrition, P.O. Box 66, FI-00014, University of Helsinki, Finland
3Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090 Brussels, Belgium
4Chemometrics and Analytical Technology, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg, Denmark
5Pharmacodynamics Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Morocco
6Biopharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Morocco
7Interscience Expert Center (IS-X), Avenue Jean-Etienne Lenoir 2, 1348 Louvain-la-Neuve, Belgium
8Industrial Catalysis and Adsorption Technology (INCAT), Faculty of Engineering and Architecture, Ghent University, Valentin Vaerwyckweg 1, 9000, Ghent, Belgium
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe20230928137737
Language: English
Published: Elsevier, 2022
Publish Date: 2023-09-28
Description:

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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Series: Food chemistry
ISSN: 0308-8146
ISSN-E: 1873-7072
ISSN-L: 0308-8146
Volume: 383
Article number: 132565
DOI: 10.1016/j.foodchem.2022.132565
OADOI: https://oadoi.org/10.1016/j.foodchem.2022.132565
Type of Publication: A1 Journal article – refereed
Field of Science: 415 Other agricultural sciences
Subjects:
Funding: The authors are grateful for the financial support of Fonds Wetenschappelijk Onderzoek - Vlaanderen (FWO-Vlaanderen) (GO38816N) and VLIR-UOS (Team project-VLIR 345 MA2017). They also acknowledge the support of the “Mohammed VI Foundation for Research and Protection of the Argan Tree”.
Copyright information: © 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/