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Recently, Traditional Chinese Medicines (TCMs), having a rich history in China for their use in maintaining health and treating disease, have gained popularity worldwide. However, their modernization and globalization are impeded due to their “multi-component, multi-pathway, and multi-target” properties. Chemometrics, a comprehensive product of statistics, computers, and information, is an interfacial discipline that extracts practical information from large chemical and biochemical datasets, beneficial to overcome TCMs restrictions. This review summarized key research findings on the basis and application of TCMs according to their components, authenticity, processing conditions, geographical origin, pharmacological activity, and metabolomics based on recent studies. Here, we discussed the benefits and shortcomings of cluster analysis, principal component analysis, soft independent modeling of class analogy, artificial neural networks, support vector machine, partial least squares-discriminant analysis, data fusion and calibration, and the appropriate application of these methods in different fields of TCMs. This review aimed to provide a basic understanding of the role and perspectives of chemometrics in the spectroscopic and chromatographic analysis of TCMs.
Dai et al. (Tue,) studied this question.