Quality control and original discrimination of Ganoderma lucidum based on high-performance liquid chromatographic fingerprints and combined chemometrics methods

In this paper, the feasibility and advantages of employing high-performance liquid chromatographic (HPLC) fingerprints combined with chemometrics methods for quality control of the cultured fruiting bodies of Ganoderma lucidum were investigated and demonstrated for the first time. In order to compare the HPLC fingerprints chromatograms between G. lucidum from different origins, the similarities of all the 60 samples and relative peak areas of 19 characteristic compounds were firstly calculated respectively. Then different pattern recognition procedures, including hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares-discrimination analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) were applied to classify the G. lucidum samples according to their cultivated origins. Consistent results were obtained to show that G. lucidum samples could be successfully grouped in accordance with the province of origin. Furthermore, four marker constituents were screened out to be the most discriminant variables, which could be applied to accurate discrimination and quality control of G. lucidum by quantitative analysis. Finally, the chemical properties of those samples were also investigated to find out the differences of quality between them. Ranked in decreasing order, the quality of the G. lucidum can be arranged as Jinzhai/Huangshan, Shandong followed by Zhejiang samples. Our results revealed that the developed method has potential perspective for the original discrimination and quality control of G. lucidum.