Fast Nondestructive Identification of Endothelium Corneum Gigeriae Galli Using Visible/Near-Infrared Spectroscopy

作     者：ZHANG Xiao-Yan MENG Yao-Yong ZHANG Hao OU Wen-Juan LIU Song-Hao 张小燕;孟耀勇;张浩;欧文娟;刘颂豪

作者机构：College of BiophotonicsSouth China Normal UniversityGuangzhou 510631 Experimental CenterSouth China Normal UniversityGuangzhou 510006 School of Physics and EngineeringSun Yat-sen UniversityGuangzhou 510725 

出 版 物：《Chinese Physics Letters》 (中国物理快报（英文版）)

年 卷 期：2011年第28卷第12期

页      面：74-77页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：Supported by the National Natural Science Foundation of China under Grant No 60878063 the Program from Traditional Chinese Medicine Bureau of Guangdong Province(2008233) 

主　　题：network Infrared qualitative 

摘      要：Vis/NIR spectroscopy,in combination with partial least square(PLS)analysis and a back-propagation neural network,is investigated to identify endothelium corneum gigeriae galli(ECGG).The spectral features of ECGGs and their counterfeits are reasonably differentiated in vis/NIR region,which provides enough qualitative information to establish the relationship between the spectra and samples for *** pretreatment of the spectral data,cross validation is implemented for extracting the best number of principal *** the calibration and validation set are performed *** PLS and back propagation neural network(BPNN)model gives the BPNN to be 0.9941 and the root mean square residual(RMSR)to be 0.0775 for the calibration set,and the multiple correlation coefficient(MCC)to 0.9874 and the RMSE to 0.1134 for the validation *** the PLS and BPNN model is reliable and *** testing,a recognition accuracy of 100%is *** present study could offer a new approach for fast and nondestructive discrimination of ECGG and its counterfeit.