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采用选定离子流管质谱指纹图谱分析和化学计量学方法对特级初榨阿甘油进行鉴定。

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

机构信息

Research Unit of Mathematical Sciences, University of Oulu, FI-90014 Oulu, Finland; Department of Food and Nutrition, P.O. Box 66, FI-00014, University of Helsinki, Finland; Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090 Brussels, Belgium.

Chemometrics and Analytical Technology, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg, Denmark.

出版信息

Food Chem. 2022 Jul 30;383:132565. doi: 10.1016/j.foodchem.2022.132565. Epub 2022 Feb 25.

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 HO, NO, O 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.

摘要

特级初榨阿甘(Argan)油(EVAO)因其营养价值和治疗用途而广受欢迎,但也经常被掺假。本研究采用选择离子流管质谱(SIFT-MS)技术对掺杂物(即低质量阿甘油(LQAO)、橄榄油(OO)和葵花籽油(SO))进行定量分析。本研究共考虑了 4 个数据集,即分别使用 HO、NO、O 反应离子,以及综合数据。通过软独立建模分类分析(SIMCA)和偏最小二乘判别分析(PLS-DA)来区分掺假和纯 EVAO。此外,还评估了 SIFT-MS 与偏最小二乘(PLS)和支持向量机(SVM)回归相结合定量检测 EVAO 中痕量掺杂物的效果。还研究了变量重要性投影(VIP)和区间偏最小二乘(iPLS)以提取有用特征。建立了不同的模型来预测 EVAO 的真实性和掺假程度。结果表明,SIFT-MS 光谱结合适当的化学计量学工具,可用于评估 EVAO 的质量。

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