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ABSTRACT
Boletus edulis and Boletus tomentipes are two well-known mushroom species which are widely consumed in Yunnan province due to their high nutritional and medicinal values. Fourier transform mid-infrared spectroscopy can determine exclusive spectra fingerprint of a sample and further analyse its quality when combined with appropriate chemometrics. In this study, identification and discrimination of B. edulis and B. tomentipes mushrooms from different geographical locations were performed based on Fourier transform mid-infrared spectroscopy and chemometrics. Principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis allowed us to identify and discriminate mushroom samples depending on their unique metabolic spectral fingerprints. The range of 1800–400 cm−1, which exhibited major characteristics of mushroom samples was selected for next analysis. The unsupervised principal component analysis and hierarchical cluster analysis showed that mushroom samples from different geographical locations could be effectively identified. Furthermore, the supervised partial least squares discriminant analysis method was used to predict unknown mushroom samples successfully based on developed calibration model. In conclusion, these results indicated that Fourier transform mid-infrared technique combined with appropriate chemometrics can be used as an effective and rapid strategy for quality control of B. edulis and B. tomentipes mushrooms with respect to their geographical locations. In addition, this technique also can be applied in other mushroom species for this purpose when coupled with reasonable chemometrics.
Funding
This work was supported by National Natural Science Foundation of China (numbers 31460538, 31660591, and 21667031).
