Identification of tea varieties by mid-infrared diffuse reflectance spectroscopy coupled with a possibilistic fuzzy c-means clustering with a fuzzy covariance matrix

摘要

Mid-infrared diffuse reflectance spectroscopy was used to rapidly and nondestructively identify tea varieties together with the proposed possibilistic fuzzy c-means (PFCM) clustering with a fuzzy covariance matrix. The mid-infrared diffuse reflectance spectra of 96 tea samples with three different varieties (Emeishan Maofeng, Level 1, and Level 6 Leshan trimeresurus) were acquired using the FTIR-7600 infrared spectrometer. First, multiplicative scatter correction was implemented to pretreat the spectral data. Second, principal component analysis was employed to compress the mid-infrared diffuse reflectance spectral data after preprocessing. Third, linear discriminant analysis was utilized for extracting the identification information required by the fuzzy clustering algorithms. Ultimately, the fuzzy c-means (FCM) clustering, the allied fuzzy c-means (AFCM) clustering, the PFCM clustering, and the PFCM clustering with a fuzzy covariance matrix were used to cluster the processed spectral data, respectively. The highest identification accuracy of the PFCM clustering with a fuzzy covariance matrix reached at 100% compared with those of FCM (96.7%), AFCM (94.9%), PFCM (96.3%), and partial least squares discrimination analysis (PLS-DA) algorithm (33.3%). It is sufficiently demonstrated that the mid-infrared diffuse reflectance spectroscopy coupled with the PFCM clustering with a fuzzy covariance matrix was a valid method for identifying tea varieties. Practical applications The variety of tea is vitally important to evaluate tea quality in the tea market. Mid-infrared diffuse reflectance spectroscopy is deemed to be a convenient, rapid, accurate, and nondestructive detection technology in comparison with the traditional methods. In this article, the proposed PFCM clustering with a fuzzy covariance matrix coupled with mid-infrared diffuse reflectance spectroscopy can be used to determine tea varieties quickly and correctly. The experimental results indicate the application potential in tea quality examination and fake tea products discrimination.