Abstract: High performance liquid chromatography (HPLC)-based system was utilized for generating chemical fingerprints of 11 Ganoderma strains. The data were statistically evaluated by using chemometric methods in order to classify the samples. The similarities of all the 11 samples and the relative peak areas of 13 common peaks were newly calculated separately. Then different chemometrics methods including hierarchical cluster analysis (HCA), principal component analysis (PCA) and discriminate analysis (DA) were applied to classify the G. lucidum samples. Consistent results show that the application of HPLC fingerprint coupled with powerful chemometrics analysis in the discrimination and classification of Ganoderma is a reliable and scientific approach.

Key words: chemometrics, classification, fingerprint, Ganoderma , high performance liquid chromatography (HPLC)