Fingerprint analysis of Lingzhi (Ganoderma) strains by high-performance liquid chromatography coupled with chemometric methods

A high-performance liquid chromatography (HPLC)-based system has been developed for generating chemical fingerprints of Lingzhi (Ganoderma). Data were evaluated statistically using hierarchical cluster analysis (HCA) and discriminant analysis (DA) in order to classify the samples and to identify key categorizing parameters. Fifteen representative Lingzhi strains (13 Ganoderma lucidum strains and one strain each of G. sinense and G. resinaceum), were separated into three groups using HCA at a rescaled distance of 10, thereby confirming divisions based on morphological characteristics. Furthermore, the 13 G. lucidum strains were separated into three groups at a rescaled distance of 5, which was consistent with previous results based on antagonism tests. Two types of discriminant functions were generated using six selected predictor variables. To our knowledge, this is the first demonstration of the feasibility and advantages of employing chromatographic fingerprinting, combined with HCA and DA, for the accurate identification and validation of feedstock strains used in the production of Lingzhi-based health foods and supplements.