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Abstract: We have developed a set of chemometric methods to address two critical issues in quality control of a precious traditional Chinese medicine (TCM), dong’;e Ejiao (DEEJ). Based on near infrared (NIR) spectra of multiple samples, the genuine manufacturer of DEEJ, e.g. dong’;e Ejiao Co., Ltd., was accurately identified among 21 suppliers by the fingerprint method using Hotelling T², distance to Model X (DModX), and similarity match value (SMV) as discriminate criteria. Soft independent modeling of the class analogy algorithm led to a misjudgment ratio of 6.2%, suggesting that the fingerprint method is more suitable for manufacturer identification. For another important feature related to clinical efficacy of DEEJ, storage time, the partial least squares-discriminant analysis (PLS-DA) method was applied with a satisfactory misjudgment ratio (15.6%) and individual prediction error around 1 year. Our results demonstrate that NIR spectra comprehensively reflect the essential quality information of DEEJ, and with the aid of proper chemometric algorithms, it is able to identify genuine manufacturer and determine accurate storage time. The overall results indicate the promising potential of NIR spectroscopy as an effective quality control tool for DEEJ and other precious TCM products.

The manuscript describes methods to evaluate two critical issues including manufacturer identification and storage time in quality control of Dong'e E-Jiao (DEEJ). This approach provides convenient methods for identifying the manufacturer and storage time. Moreover, it also has great potential to promote the traditional Chinese medicine quality control in the future. The manuscript has new approach and original content which should be interesting to the readership. The subject is quite important, has practical implication and paper is interesting.

基于近红外光谱技术的东阿阿胶生产厂家和存放时间鉴定方法研究

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