Abstract
Mahonia bealei (Fort.) Carr. (M. bealei) plays an important role in the treatment of many diseases. In the present study, a comprehensive method combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) for quality evaluation of M. bealei was developed. Similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) were applied to classify and evaluate the samples of wild M. bealei, cultivated M. bealei and its substitutes according to the peak area of 11 components but an accurate classification could not be achieved. PLS-DA was then adopted to select the characteristic variables based on variable importance in projection (VIP) values that responsible for accurate classification. Six characteristics peaks with higher VIP values (≥1) were selected for building the CPR model. Based on the six variables, three types of samples were accurately classified into three related clusters. The model was further validated by a testing set samples and predication set samples. The results indicated the model was successfully established and predictive ability was also verified satisfactory. The established model demonstrated that the developed SFC coupled with PLS-DA method showed a great potential application for quality assessment of M. bealei.
Highlights
Mahonia bealei (Fort.) Carr. (M. bealei) is a well-known traditional Chinese medicine (TCM) and has been used for the treatment of acute dysentery, icteric hepatitis conjunctivitis, etc. [1]
A comprehensive method was developed combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) to evaluate the quality of M. bealei
CPR methods (HCA, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA)) were applied to evaluate the quality based on the 11 chemical compounds
Summary
Mahonia bealei (Fort.) Carr. (M. bealei) is a well-known traditional Chinese medicine (TCM) and has been used for the treatment of acute dysentery, icteric hepatitis conjunctivitis, etc. [1]. The main aim of this study was to establish a reliable method using SFC fingerprints and CPR methods for the quality evaluation of M. bealei. For this purpose, wild M. bealei, cultivated M. bealei and four other M. bealei substitutes were chosen as study objects (Figure 1). Chemical pattern recognition (CPR) methods, such as hierarchical cluster analysis (HCA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) could be considered as of 12 reasonable methods to simplify the complex data [8]. Wang et Hsiao; D: M. duclouxiana Gagnep; E: M. bodinieri Gagnep; F: M. fordii Schneid
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