Exploring Geographical Differentiation of the Hoelen Medicinal Mushroom, Wolfiporia extensa (Agaricomycetes), Using Fourier-Transform Infrared Spectroscopy Combined with Multivariate Analysis.

In this study the geographical differentiation of dried sclerotia of the medicinal mushroom Wolfiporia extensa, obtained from different regions in Yunnan Province, China, was explored using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate data analysis. The FT-IR spectra of 97 samples were obtained for wave numbers ranging from 4000 to 400 cm-1. Then, the fingerprint region of 1800-600 cm-1 of the FT-IR spectrum, rather than the full spectrum, was analyzed. Different pretreatments were applied on the spectra, and a discriminant analysis model based on the Mahalanobis distance was developed to select an optimal pretreatment combination. Two unsupervised pattern recognition procedures- principal component analysis and hierarchical cluster analysis-were applied to enhance the authenticity of discrimination of the specimens. The results showed that excellent classification could be obtained after optimizing spectral pretreatment. The tested samples were successfully discriminated according to their geographical locations. The chemical properties of dried sclerotia of W. extensa were clearly dependent on the mushroom's geographical origins. Furthermore, an interesting finding implied that the elevations of collection areas may have effects on the chemical components of wild W. extensa sclerotia. Overall, this study highlights the feasibility of FT-IR spectroscopy combined with multivariate data analysis in particular for exploring the distinction of different regional W. extensa sclerotia samples. This research could also serve as a basis for the exploitation and utilization of medicinal mushrooms.