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Proceedings Paper

Fast discrimination of danshen from different geographical areas by NIR spectroscopy and advanced cluster analysis method
Author(s): Ning Li; Yan Wang; Kexin Xu
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Paper Abstract

Near infrared (NIR) diffuse reflection spectroscopy has been an effective way to perform quantitative analysis without the requirement of sample pretreatnient. In this paper, NIR Fourier transform infrared (FTIR) spectroscopy has been introduced to probe spectral features of traditional Chinese medicine Danshen. Infrared fingerprint spectra of Danshen can be established. Influence of differentiation of spectrum is also discussed. After pretreatment and derivation on the spectral data, methods of principal analysis (PCA), soft independent modeling of class analogy (SIMCA) and Artificial Neural Network (ANN) are combined to sort the geographical origins of 53 samples by local modeling. The result show that, as a basis of the other two methods, PCA is a more efficient one for identifying the geographical origins of Danshen. Combining SIMCA with PCA, an effective model is built to analyze the data after normalization and differentiation, the correct identification rate reaches above 90%. Then 36 samples are chosen as training set while other 17 samples being verifying set. Using ANN-based Back Propagation method, after proper training of BP network, the origins of Danshen are completely classified. Therefore, combined with advanced mathematical analysis, NIR diffuse spectroscopy can be a novel and rapid way to accurately evaluate the origin of Chinese medicine, and also to accelerate the modernization process of Chinese drugs.

Paper Details

Date Published: 27 October 2006
PDF: 7 pages
Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 604725 (27 October 2006); doi: 10.1117/12.710981
Show Author Affiliations
Ning Li, Tianjin Univ. (China)
Yan Wang, Tianjin Univ. (China)
Kexin Xu, Tianjin Univ. (China)

Published in SPIE Proceedings Vol. 6047:
Fourth International Conference on Photonics and Imaging in Biology and Medicine
Kexin Xu; Qingming Luo; Da Xing; Alexander V. Priezzhev; Valery V. Tuchin, Editor(s)

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