化学模式识别方法在中药质量控制研究中的应用进展

Application progress on chemical pattern recognition in quality control of Chinese materia medica

化学计量学是以计算机和近代计算技术为基础的一门新兴交叉学科,在中药鉴别、定性表征、质量控制、组效关系等研究中均具有广泛应用,尤其在中药的质量控制与评价研究中具有重要意义。综述近年来化学计量学中化学模式识别方法,包括2种无监督模式识别方法(聚类分析、主成分分析)和4种有监督模式识别方法(簇类独立软模式法、偏最小二乘法判别分析、支持向量机、人工神经网络),并从产地、基原、炮制、真伪等多个方面总结了化学模式识别方法在中药质量控制研究中的应用。

Chemometrics is a new cross discipline based on computer and modern technology. It has been widely used in the research of Chinese materia medica（CMM） identification, qualitative characterization, quality control, and group-effect relationship, especially in quality control and evaluation of CMM. In this paper, the application and progress of chemical pattern recognition methods in chemometrics for quality control of CMM in recent years are reviewed. Two unsupervised pattern recognition methods（cluster analysis and principal component analysis） and four supervised pattern recognition methods（soft independent modeling of class analogy, partial least-squares discriminant analysis, support vector machine, and artificial neural network） are described. This paper reviews application of chemical pattern recognition in quality control of CMM from different aspects, including growing areas, herbal origin, processing, identification of the authenticity, etc.