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基于气相色谱-轨道阱高分辨质谱联用技术和化学计量学的指纹图谱分析揭示百里香的产地、加工和挥发性标志物用于鉴定。

Fingerprinting based on gas chromatography-Orbitrap high-resolution mass spectrometry and chemometrics to reveal geographical origin, processing, and volatile markers for thyme authentication.

机构信息

Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agrifood Biotechnology (CIAIMBITAL), Agrifood Campus of International Excellence (ceiA3), University of Almeria, E-04120 Almeria, Spain.

出版信息

Food Chem. 2022 Nov 1;393:133377. doi: 10.1016/j.foodchem.2022.133377. Epub 2022 Jun 2.

DOI:10.1016/j.foodchem.2022.133377
PMID:35691070
Abstract

Thyme is an aromatic herb traditionally used for food purposes due to its organoleptic characteristics and medicinal properties, which is highly susceptible to food fraud. In this study, GC-HRMS-based fingerprinting was applied for the first time to determine the geographical traceability of thyme based on different origins (Spain, Poland, and Morocco), as well as to assess its processing by comparing sterilized vs. non-sterilized thyme. Unsupervised chemometric methods (PCA and HCA) revealed a predominant influence of the geographical origin on thyme fingerprints rather than processing effects. Supervised PLS-DA and OPLS-DA were used for discrimination purposes, revealing high predictive ability for further samples (100%), and allowing the identification of differential compounds (markers). A total of 24 markers were putatively identified (13 metabolites were confirmed) belonging to different classes: monoterpenoids, diterpenoids, sesquiterpenoids, alkenylbenzenes, and other miscellaneous compounds. This study outlines the potential of combining untargeted analysis by GC-HRMS with chemometrics for thyme authenticity and traceability.

摘要

百里香是一种芳香草本植物,因其感官特性和药用特性而被传统上用于食品用途,但其非常容易受到食品欺诈的影响。在这项研究中,首次应用基于 GC-HRMS 的指纹图谱法来确定百里香的地理溯源性,依据其不同的产地(西班牙、波兰和摩洛哥),并通过比较灭菌和非灭菌的百里香来评估其加工过程。无监督化学计量学方法(PCA 和 HCA)表明,地理起源对百里香指纹图谱的影响主要大于加工效果。有监督的 PLS-DA 和 OPLS-DA 用于区分目的,对进一步的样本具有很高的预测能力(100%),并允许识别差异化合物(标志物)。共推测出 24 种标志物(13 种代谢物得到证实),属于不同类别:单萜类、二萜类、倍半萜类、烯基苯和其他杂类化合物。本研究概述了结合 GC-HRMS 的非靶向分析与化学计量学用于百里香真实性和可追溯性的潜力。

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