title: Identification of Chinese medicinal fungus Cordyceps sinensis by depth-profiling mid-infrared photoacoustic spectroscopy.
abstract: With increased demand for Cordyceps sinensis it needs rapid methods to meet the challenge of identification raised in quality control. In this study Cordyceps sinensis from four typical natural habitats in China was characterized by depth-profiling Fourier transform infrared photoacoustic spectroscopy. Results demonstrated that Cordyceps sinensis samples resulted in typical photoacoustic spectral appearance, but heterogeneity was sensed in the whole sample; due to the heterogeneity Cordyceps sinensis was represented by spectra of four groups including head, body, tail and leaf under a moving mirror velocity of 0.30cms-1. The spectra of the four groups were used as input of a probabilistic neural network (PNN) to identify the source of Cordyceps sinensis, and all the samples were correctly identified by the PNN model. Therefore, depth-profiling Fourier transform infrared photoacoustic spectroscopy provides novel and unique technique to identify Cordyceps sinensis, which shows great potential in quality control of Cordyceps sinensis.
authors.affiliation: State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China. Electronic address: chwdu@issas.ac.cn.
authors.forename: Changwen
authors.initials: C
authors.lastname: Du
authors.affiliation: State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China.
authors.forename: Jianmin
authors.initials: J
authors.lastname: Zhou
authors.affiliation: Traditional Chinese Medicine Institute, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
authors.forename: Jianfeng
authors.initials: J
authors.lastname: Liu
mesh_terms: D032661:Cordyceps / Q000737:chemistry*; D008516:Medicine, Chinese Traditional; D015233:Models, Statistical; D016571:Neural Networks, Computer; D061088:Photoacoustic Techniques / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*
keywords: Cordyceps sinensis; Depth-profiling; Identification; Photoacoutic spectroscopy; Principal component analysis; Probabilistic neural network