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

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Standard

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, Abdelazize ; Vander Heyden, Yvan .

I: Food Chemistry, 2022.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

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. https://doi.org/10.1016/j.foodchem.2022.132565

APA

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, [132565]. https://doi.org/10.1016/j.foodchem.2022.132565

Vancouver

Kharbach M, Yu H, Kamal R, Marmouzi I, Alaoui K, Vercammen J o.a. Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics. Food Chemistry. 2022. 132565. https://doi.org/10.1016/j.foodchem.2022.132565

Author

Kharbach, Mourad ; Yu, Huiwen ; Kamal, Rabie ; Marmouzi, Ilias ; Alaoui, Katim ; Vercammen, Joeri ; Bouklouze, Abdelazize ; Vander Heyden, Yvan . / Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics. I: Food Chemistry. 2022.

Bibtex

@article{f0a55d7f69cc4e5a8da696331802bc1b,
title = "Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics",
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.",
author = "Mourad Kharbach and Huiwen Yu and Rabie Kamal and Ilias Marmouzi and Katim Alaoui and Joeri Vercammen and Abdelazize Bouklouze and {Vander Heyden}, Yvan",
year = "2022",
doi = "10.1016/j.foodchem.2022.132565",
language = "English",
journal = "Food Chemistry",
issn = "0308-8146",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Authentication of extra virgin Argan oil by selected-ion flow-tube mass-spectrometry fingerprinting and chemometrics

AU - Kharbach, Mourad

AU - Yu, Huiwen

AU - Kamal, Rabie

AU - Marmouzi, Ilias

AU - Alaoui, Katim

AU - Vercammen, Joeri

AU - Bouklouze, Abdelazize

AU - Vander Heyden, Yvan

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

U2 - 10.1016/j.foodchem.2022.132565

DO - 10.1016/j.foodchem.2022.132565

M3 - Journal article

C2 - 35245834

JO - Food Chemistry

JF - Food Chemistry

SN - 0308-8146

M1 - 132565

ER -

ID: 271973406