Chemometric Discrimination of the Geographical Origin of Rheum tanguticum by Stable Isotope Analysis

文献类型： 外文期刊

第一作者： Nuralykyzy, Bayan

作者： Nuralykyzy, Bayan;Nie, Jing;Mei, Hanyi;Li, Chunlin;Rogers, Karyne M.;Zhang, Yongzhi;Yuan, Yuwei;Nuralykyzy, Bayan;Nie, Jing;Mei, Hanyi;Li, Chunlin;Rogers, Karyne M.;Zhang, Yongzhi;Yuan, Yuwei;Zhou, Guoying;Zhao, Shuo;Rogers, Karyne M.

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关键词： rhubarb; chemometrics; geographical origin; stable isotopes; isotope ratio mass spectrometry

期刊名称：FOODS （ 影响因子：5.1； 五年影响因子：5.6 ）

ISSN：

年卷期： 2024 年 13 卷 19 期

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收录情况： SCI

摘要： Rheum tanguticum is one of the primary rhubarb species used for food and medicinal purposes, and it has recently been gaining more attention and recognition. This research represents the first attempt to use stable isotopes and elemental analysis via IRMS to identify the geographical origin of Rheum tanguticum. A grand total of 190 rhubarb samples were gathered from 38 locations spread throughout the provinces of Gansu, Sichuan, and Qinghai in China. The carbon content showed a decreasing trend in the order of Qinghai, followed by Sichuan, and then Gansu. Nitrogen content was notably higher, with Qinghai and Sichuan displaying similar levels, while Gansu had the lowest nitrogen levels. Significant differences were noted in the delta 13C (-28.9 to -26.5 parts per thousand), delta 15N (2.6 to 5.6 parts per thousand), delta 2H (-120.0 to -89.3 parts per thousand), and delta 18O (16.0 parts per thousand to 18.8 parts per thousand) isotopes among the various rhubarb cultivation areas. A significant negative correlation was found between %C and both longitude and humidity. Additionally, delta 13C and delta 15N isotopes were negatively correlated with longitude, and delta 15N showed a negative correlation with humidity as well. delta 2H and delta 18O isotopes exhibited a strong positive correlation with latitude, while significant negative correlations were observed between delta 2H and delta 18O isotopes and temperature, precipitation, and humidity. The LDA, PLS-DA, and k-NN models all exhibited strong classification performance in both the training and validation sets, achieving accuracy rates between 82.1% and 91.7%. The combination of stable isotopes, elemental analysis, and chemometrics provides a reliable and efficient discriminant model for accurately determining the geographical origin of R. tanguticum in different regions. In the future, the approach will aid in identifying the geographical origin and efficacy of rhubarb in other studies.

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