Feng Yangna, Zhu Xinyan, Wang Yuanzhong
Medicinal Plants Research Institute, Yunnan Academy of Agricultural Science, Kunming, 650200, China.
College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming, 650500, China.
J Pharm Anal. 2025 Feb;15(2):101103. doi: 10.1016/j.jpha.2024.101103. Epub 2024 Sep 13.
To ensure the safety and efficacy of Chinese herbs, it is of great significance to conduct rapid quality detection of Chinese herbs at every link of their supply chain. Spectroscopic technology can reflect the overall chemical composition and structural characteristics of Chinese herbs, with the multi-component and multitarget characteristics of Chinese herbs. This review took the genus as an example, and applications of spectroscopic technology with machine learning (ML) in supply chain of the genus from seeds to medicinal materials were introduced. The specific contents included the confirmation of germplasm resources, identification of growth years, cultivar, geographical origin, and original processing and processing methods. The potential application of spectroscopic technology in genus was pointed out, and the prospects of combining spectroscopic technology with blockchain were proposed. The summary and prospects presented in this paper will be beneficial to the quality control of the genus in all links of its supply chain, so as to rationally use the genus resources and ensure the safety and efficacy of medication.
为确保中药材的安全性和有效性，在其供应链的各个环节对中药材进行快速质量检测具有重要意义。光谱技术能够反映中药材的整体化学成分和结构特征，符合中药材的多成分、多靶点特性。本综述以[属名]为例，介绍了光谱技术与机器学习（ML）在[属名]从种子到药材的供应链中的应用。具体内容包括种质资源的确认、生长年份、品种、地理来源以及初加工和加工方法的鉴定。指出了光谱技术在[属名]中的潜在应用，并提出了光谱技术与区块链相结合的前景。本文的总结和展望将有助于[属名]在其供应链各环节的质量控制，从而合理利用[属名]资源，确保用药的安全性和有效性。
