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Geographical origin discrimination and polysaccharides quantitative analysis of Radix codonopsis with micro near-infrared spectrometer engine.

Authors :
Wang, Jiayue
Li, Tongtong
Yang, Hailong
Hu, Tian
Nie, Lei
Wang, Fei
AlcalĂ , Manel
Zang, Hengchang
Source :
Journal of Innovative Optical Health Sciences; Jan2018, Vol. 11 Issue 1, p-1, 11p
Publication Year :
2018

Abstract

At present, Tradition Chinese Medicine (TCM) industry in China is in the stage from the empirical development to industrial production. Near infrared (NIR) spectroscopy has been widely used in the quality control of TCM's modernization with its characteristics including rapidness, nondestruction, simplicity, economy, and so on. In this study, as one type of a portable micro NIR spectrometer, Micro NIR 1700 was used to establish the qualitative models for identification of geographical region and authenticity of Radix codonopsis based on discriminant analysis (DA) method. Both of the DA models had better predictive ability with 100% accuracy. In addition, a method for rapid quantitative analysis of polysaccharide in Radix codonopsis was also developed based on Micro NIR 1700 spectrometer with partial least-squares (PLS) algorithm. In the PLS calibration model, the NIR spectra of samples were pretreated with different preprocessing methods and the spectral region was selected with different variable selection methods as well. The performance of the final PLS model was evaluated according to correlation coefficient of calibration (), correlation coefficient of prediction (), root mean squared error of cross validation (RMSECV), and root mean squared of prediction (RMSEP). The values of , , RMSECV, and RMSEP were 0.9775, 0.9602, 2.496, and 2.734g/mL, respectively. This work demonstrated that micro infrared spectrometer could be more convenient and rapid for quality control of Radix codonopsis, and the presented models would be a useful reference for quality control of other similar raw materials of TCM. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17935458
Volume :
11
Issue :
1
Database :
Complementary Index
Journal :
Journal of Innovative Optical Health Sciences
Publication Type :
Academic Journal
Accession number :
126332152
Full Text :
https://doi.org/10.1142/S1793545818500049