DocumentCode :
2682892
Title :
Fast Determination of Active Components in Scutellaria Extract by NIRS Combined with PLS
Author :
Bai, Yan ; Zhang, Wei ; Xie, Cai-xia ; Wang, Xing ; Chen, Zhi-hong ; Gong, Hai-yan
Author_Institution :
Pharm. Coll., Henan Univ. of Traditional Chinese Med., Zhengzhou, China
fYear :
2012
fDate :
28-30 May 2012
Firstpage :
1034
Lastpage :
1037
Abstract :
In this paper, the three active components in Scutellaria Extract were rapidly determinate by near-infrared reflectance spectroscopy (NIRS). 100 samples of Scutellaria Extract from 12 different pharmaceutical factories were divided into a calibration set (80 samples) and a validation set (20 samples). In combination with the practical least square (PLS), the quantitative calibration models were established, involving baicalin, baicalein and wogonin. The correlation coefficient of cross-validation (R2cv) was 0.99481, 0.99867 and 0.99484 for baicalin, baicalein and wogonin, the root-mean-square error of calibration (RMSEC) was 0.440, 0.0225 and 0.0111, the root-mean-square error of cross-validation (RMSECV) was 2.259, 0.0553 and 0.0483. The validation samples were used to evaluate the performance of the models, the correlation coefficient of prediction (r2) was 0.9882, 0.9965 and 0.9909, the root-mean-square error of prediction (RMSEP) was 0.486, 0.0271 and 0.0110. The results indicated that NIRS can provide a simple and accurate way in the determination of the baicalin, baicalein and wogonin content in Scutellaria Extract.
Keywords :
biological techniques; calibration; correlation methods; infrared spectra; least mean squares methods; least squares approximations; medicine; molecular biophysics; organic compounds; pharmaceuticals; reflectivity; Scutellaria extract; baicalein; baicalin; calibration set; cross-validation correlation coefficient; near-infrared reflectance spectroscopy; partical least square; pharmaceutical factories; quantitative calibration models; root-mean square error; validation set; wogonin; Calibration; Correlation; Load modeling; Predictive models; Reflectivity; Spectral analysis; Spectroscopy; near-infrared reflectance spectroscopy; partical least square; quantitative calibration model; scutellaria extract;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Biotechnology (iCBEB), 2012 International Conference on
Conference_Location :
Macao
Print_ISBN :
978-1-4577-1987-5
Type :
conf
DOI :
10.1109/iCBEB.2012.223
Filename :
6245303
Link To Document :
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