A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics
文献类型：期刊论文
| 作者 | Huang, Yu-shi2,3; An, Ya-ling2; Zheng, Yue-yuan3; Zhao, Wen-jie2; Song, Chun-qian2; Zhang, Li-jie2; Chen, Jie-ting3; Tang, Zi-jun3; Feng, Lin2; Li, Zhen-wei2 |
| 刊名 | JOURNAL OF CHROMATOGRAPHY A
 |
| 出版日期 | 2025-03-29 |
| 卷号 | 1745页码:12 |
| 关键词 | Citrus herbs Discrimination LC-MS Machine learning Differential markers |
| ISSN号 | 0021-9673 |
| DOI | 10.1016/j.chroma.2025.465747 |
| 通讯作者 | Guo, De-an(daguo@simm.ac.cn) |
| 英文摘要 | Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiation methods. For the first time, this study constructed automated discrimination models for 16 citrus species (239 batches) while previous studies focused on a limited number of species. Seven machine learning models -Tree, Discriminant, Support Vector Machine, K-Nearest Neighbor, Ensemble, Neural Network, and Partial least squares discriminant analysis-were compared, with the Ensemble model achieving 100% accuracy in the test set. 16 Orthogonal partial least squares discriminant analysis models were constructed to screen and identify 53 differential markers. These markers were successfully utilized to determine the absence or presence of specified components in the 20 citrus products. This study provides a comprehensive solution for the quality control of citrus herbs, enabling the differentiation of raw herbs and processed slices, as well as the identification of complex systems such as Chinese patent medicines. |
| WOS关键词 | AURANTII FRUCTUS IMMATURUS |
| 资助项目 | National Natural Science Foundation of China[82130111] ; Qi-Huang Chief Scientist Project of National Administration of Traditional Chinese Medicine |
| WOS研究方向 | Biochemistry & Molecular Biology ; Chemistry |
| 语种 | 英语 |
| WOS记录号 | WOS:001423329700001 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/316290]  |
| 专题 | 中国科学院上海药物研究所 |
| 通讯作者 | Guo, De-an |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai Res Ctr Modernizat Tradit Chinese Med, Natl Engn Res Ctr TCM Standardizat Technol, Haike Rd 501, Shanghai 201203, Peoples R China 2.Chinese Acad Sci, Zhongshan Inst Drug Discovery, Shanghai Inst Mat Med, Zhongshan 528400, Peoples R China 3.Guangdong Pharmaceut Univ, Sch Pharm, Dept Pharmaceut, East Outer Ring Rd 280, Guangzhou 510006, Guangdong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Yu-shi,An, Ya-ling,Zheng, Yue-yuan,et al. A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics[J]. JOURNAL OF CHROMATOGRAPHY A,2025,1745:12. |
| APA | Huang, Yu-shi.,An, Ya-ling.,Zheng, Yue-yuan.,Zhao, Wen-jie.,Song, Chun-qian.,...&Guo, De-an.(2025).A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics.JOURNAL OF CHROMATOGRAPHY A,1745,12. |
| MLA | Huang, Yu-shi,et al."A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics".JOURNAL OF CHROMATOGRAPHY A 1745(2025):12. |
入库方式： OAI收割
来源：上海药物研究所
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