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Determination of morphological group from infrared spectra of crude extracts of medicinal plants by SIMCA pattern recognition
Author(s) -
Zhang Liang,
Ying Han,
Zhang ZhengXing,
Sheng LongSheng,
An DengKui
Publication year - 1994
Publication title -
phytochemical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 72
eISSN - 1099-1565
pISSN - 0958-0344
DOI - 10.1002/pca.2800050310
Subject(s) - chemistry , tripterygium wilfordii , bark (sound) , pattern recognition (psychology) , crude drug , chromatography , artificial intelligence , medicine , physics , alternative medicine , pathology , computer science , acoustics
This paper reports a new method of classification and identification of medicinal plants by pattern recognition within the infrared spectra of crude extracts. The spectra of solvent extracts of 29 samples of Tripterygium wilfordii and T. hypoglaucum were examined for information concerning chemical classes. The Shannon information content for each wavelength channel was calculated for the absorption spectra, and the 9 wavelength channels with the highest information content were retained as a compressed basis set for SIMCA pattern recognition. The inherent class structure of the data showed two major groups, T. wilfordii root and T. wilfordii bark. Classification accuracy was 95.0% for the classes.