Classification of Angelica species found in various foods using an LC-QTOF/MS-based metabolomics approach

当归 代谢组学 偏最小二乘回归 传统医学 化学 线性判别分析 色谱法 质谱法 中医药 医学 人工智能 计算机科学 机器学习 病理 替代医学
作者
Su-Jin Ahn,Hyung Joo Kim,Ayoung Lee,Seung-Sik Min,Suncheun Kim
出处
期刊:Food Additives & Contaminants: Part A [Informa]
卷期号:40 (7): 787-796 被引量:1
标识
DOI:10.1080/19440049.2023.2220827
摘要

In Korea, Angelica gigas is commonly known as Danggui. However, two other species on the market, Angelica acutiloba and Angelica sinensis, are also commonly called Danggui. Since the three Angelica species have different biologically active components, thus, different pharmacological activities, clear discrimination between them is needed to prevent their misuse. A. gigas is used not only as a cut or powdered product but also in processed foods, where it is mixed with other ingredients. To discriminate between the three Angelica species, reference samples were analysed as non-targeted using liquid chromatography-quadrupole time of flight/mass spectrometry (LC-QTOF/MS) and a metabolomics approach in which a discrimination model was established by partial least squares-discriminant analysis (PLS-DA). Then, the Angelica species in the processed foods were identified. First, 32 peaks were selected as marker compounds and a discrimination model was created using PLS-DA, and its validation was confirmed. Classification of the Angelica species was undertaken using the YPredPS value, and it was confirmed that all 21 foods examined contained the appropriate Angelica species indicated on the product packaging. Likewise, it was confirmed that all three Angelica species were accurately classified in the samples to which they were added.
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