| 黄鹏宇,张婷,刘昊阳,袁文韬.化学通报,2025,88(12):1298-1308,1297. |
| 化学指纹图谱在中药产地溯源中的研究进展 |
| Research progress of chemical fingerprint in the origin traceability of traditional Chinese medicine |
| 投稿时间：2025-07-14 修订日期：2025-08-22 |
| DOI： |
| 中文关键词: 化学指纹图谱 机器学习 中药 产地溯源 |
| 英文关键词:Chemical fingerprint, Machine learning, Traditional Chinese medicine, Origin traceability |
| 基金项目:公安部应用创新项目(2024yy48)、辽宁省科技厅重点研发项目(民生科技类)(2024JH2/ 102500083)、辽宁省法庭科学重点实验室开 放课题(FTKX2022KF05)和辽宁省大学生创新项目(D20251017509)资助 |
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| 中文摘要: |
| 中药是中华民族的瑰宝，其药用价值高度依赖于产地，产地溯源至关重要。针对中药化学组成复杂、传统仪器分析难以实现有效模式识别的挑战，化学指纹图谱技术凭借其整体性、综合性的表征优势，以及与机器学习高度融合的特点，成为中药产地溯源的核心工具。本文详细阐述了化学指纹图谱的基本概念与关键技术体系，综述了指纹图谱常见的数据获取技术、数据预处理方法、主流机器学习模型、模型评价技术手段及其具体应用实例，期望能为化学指纹图谱在中药产地溯源领域的进一步应用提供一些参考。 |
| 英文摘要: |
| Traditional Chinese Medicine (TCM) is the precious treasure of the Chinese nation, which has medicinal value and is closely related to its geographical origin. Therefore, origin traceability is of paramount importance. Addressing the challenge posed by the complex chemical composition of TCM and the difficulty for traditional instrumental analysis to achieve effective pattern recognition, chemical fingerprinting technology, leveraging its strengths in holistic and comprehensive characterization and its extensive integration with machine learning, has become a core tool for TCM origin traceability. This paper details the fundamental concepts of chemical fingerprinting and its key technology system. It reviews common data acquisition techniques for fingerprints, data preprocessing methods, mainstream machine learning models, and model evaluation techniques. It also summarizes its specific application examples. It is expected that this will provide some reference for the further application of chemical fingerprinting in the field of TCM origin traceability. |
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