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Fast Nondestructive Identification of Endothelium Corneum Gigeriae Galli Using Visible/Near-Infrared Spectroscopy |
| ZHANG Xiao-Yan1, MENG Yao-Yong1,2**, ZHANG Hao1,3, OU Wen-Juan1, LIU Song-Hao1
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1College of Biophotonics, South China Normal University, Guangzhou 510631
2Experimental Center, South China Normal University, Guangzhou 510006
3School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510725
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ZHANG Xiao-Yan, MENG Yao-Yong, ZHANG Hao et al 2011 Chin. Phys. Lett. 28 120701 |
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Abstract 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 identification. After pretreatment of the spectral data, cross validation is implemented for extracting the best number of principal components. Then the calibration and validation set are performed well. The 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 set. Thus the PLS and BPNN model is reliable and practicable. Through testing, a recognition accuracy of 100% is achieved. The present study could offer a new approach for fast and nondestructive discrimination of ECGG and its counterfeit.
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07.57.Ty
07.05.Mh
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Received: 25 April 2011
Published: 29 November 2011
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| PACS: |
07.57.Ty
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(Infrared spectrometers, auxiliary equipment, and techniques)
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07.05.Mh
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(Neural networks, fuzzy logic, artificial intelligence)
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81.70.Fy
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(Nondestructive testing: optical methods)
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