摘要
为深入推进和实现中医药现代化,建立一种既尊重中医理论又顺应时代发展的中药材质量控制体系尤为重要。自古以来,中药材的色、气、味等外观性状是用于辨别其真伪及质量好坏的重要标准之一。目前对中药外观性状的研究逐渐从主观的“辨状论质”转向了能够提供客观数据支持的人工智能感官技术,根据模拟感官的不同,智能感官技术又可以分为电子眼、电子鼻、电子舌、电子耳和电子皮肤等。本文梳理了5种人工智能感官技术的原理以及在中药质量评价中的应用,介绍了基于智能感官的中药质量控制体系的研究现状和未来发展趋势,以期为中药材质量控制体系的升级和现代化发展提供参考。
In order to further promote and achieve the modernization of traditional Chinese medicine,it is particularly important to establish a quality control system of traditional Chinese medicine which not only respects the theory of traditional Chinese medicine but also conforms to the development of the times.Since ancient times,the appearance character of traditional Chinese medicine,such as color,gas and taste,is one of the important criteria to distinguish its authenticity and quality.At present,the research on the appearance of traditional Chinese medicine has gradually shifted from subjective"evaluation of quality from appearance traits"to artificial intelligence sensory technology which can provide objective data support.According to the different simulated senses,intelligent sensory technology can be divided into electronic eyes,electronic nose,electronic tongue,electronic ear and electronic skin.This paper combs the principles of five kinds of artificial intelligence sensory technology and their application in the quality evaluation of traditional Chinese medicine,introduces the research status and future development trend of the quality control system of traditional Chinese medicine based on intelligent sense,in order to provide a reference for the upgrade and modern development of the quality control system of traditional Chinese medicine.
作者
江如蓝
雷结语
陈文礼
徐新军
JIANG Rulan;LEI Jieyu;CHEN Wenli;XU Xinjun(School of Pharmaceutical Science,Sun Yat-Sen University,Guangzhou 510006,China;Department of Pharmacy,The Fifth Affiliated Hospital of Sun Yat-sen University,Zhuhai 519000,Guangdong Province,China)
出处
《药学前沿》
CAS
2024年第11期550-556,共7页
China Pharmacist
基金
国家重点研发计划青年科学家项目——乡村产业共性关键技术研发与集成应用(2023YFD1601400)。
关键词
智能感官
外观性状
辨状论质
质量控制
品质评价
中药识别
成分检测
深度学习
多源信息融合
图像识别技术
人工智能
Intelligence sense
Appearance character
Quality evaluation through character identification
Quality control
Quality evaluation
Identification of Chinese traditional medicine
Component detection
Deep learning
Multi-source information fusion
Image recognition technology
Artificial intelligence