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

被引:7
作者
Kharbach, Mourad [1 ,2 ,3 ]
Yu, Huiwen [4 ]
Kamal, Rabie [5 ]
Marmouzi, Ilias [6 ]
Alaoui, Katim [5 ]
Vercammen, Joeri [7 ,8 ]
Bouklouze, Abdelaziz [6 ]
Vander Heyden, Yvan [3 ]
机构
[1] Univ Oulu, Res Unit Math Sci, FI-90014 Oulu, Finland
[2] Univ Helsinki, Dept Food & Nutr, POB 66, FI-00014 Helsinki, Finland
[3] Vrije Univ Brussel VUB, Dept Analyt Chem Appl Chemometr & Mol Modelling, Laarbeeklaan 103, B-1090 Brussels, Belgium
[4] Univ Copenhagen, Fac Sci, Chemometr & Analyt Technol, Rolighedsvej 26, DK-1958 Frederiksberg, Denmark
[5] Univ Mohammed V Rabat, Fac Med & Pharm, Lab Pharmacol & Toxicol, Pharmacodynam Res Team, Rabat, Morocco
[6] Univ Mohammed V Rabat, Fac Med & Pharm, Lab Pharmacol & Toxicol, Biopharmaceut & Toxicol Anal Res Team, Rabat, Morocco
[7] Intersci Expert Ctr IS X, Ave Jean Etienne Lenoir 2, B-1348 Louvain La Neuve, Belgium
[8] Univ Ghent, Fac Engn & Architecture, Ind Catalysis & Adsorpt Technol INCAT, Valentin Vaerwyckweg 1, B-9000 Ghent, Belgium
关键词
Extra virgin Argan oil; Oil fraud; Selected-Ion Flow-Tube Mass Spectrometry; Volatile organic compounds; Oil authentication; Adulteration; SIFT-MS; VOLATILE COMPOUNDS; ADULTERATION; CLASSIFICATION; REGRESSION; QUALITY; ORIGIN; FRUITS; TOOL;
D O I
10.1016/j.foodchem.2022.132565
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
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+, O-2(+center 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.
引用
收藏
页数:12
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