Full Text:   <1116>

Summary:  <360>

Suppl. Mater.: 

CLC number: R917

On-line Access: 2017-05-04

Received: 2016-03-29

Revision Accepted: 2016-07-21

Crosschecked: 2017-04-19

Cited: 0

Clicked: 1908

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE B 2017 Vol.18 No.5 P.383-392


Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS)

Author(s):  Yu Luo, Wen-long Li, Wen-hua Huang, Xue-hua Liu, Yan-gang Song, Hai-bin Qu

Affiliation(s):  Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   wshlwl@zju.edu.cn

Key Words:  Near infrared spectroscopy, Codonopsis Radix, Alcohol precipitation, Real-time release testing, Multi-components quantification

Yu Luo, Wen-long Li, Wen-hua Huang, Xue-hua Liu, Yan-gang Song, Hai-bin Qu. Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS)[J]. Journal of Zhejiang University Science B, 2017, 18(5): 383-392.

@article{title="Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS)",
author="Yu Luo, Wen-long Li, Wen-hua Huang, Xue-hua Liu, Yan-gang Song, Hai-bin Qu",
journal="Journal of Zhejiang University Science B",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS)
%A Yu Luo
%A Wen-long Li
%A Wen-hua Huang
%A Xue-hua Liu
%A Yan-gang Song
%A Hai-bin Qu
%J Journal of Zhejiang University SCIENCE B
%V 18
%N 5
%P 383-392
%@ 1673-1581
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1600141

T1 - Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS)
A1 - Yu Luo
A1 - Wen-long Li
A1 - Wen-hua Huang
A1 - Xue-hua Liu
A1 - Yan-gang Song
A1 - Hai-bin Qu
J0 - Journal of Zhejiang University Science B
VL - 18
IS - 5
SP - 383
EP - 392
%@ 1673-1581
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1600141

A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.


结论:实现了党参醇沉上清液中4类指标的近红外光谱快速分析法,所建党参炔苷、总黄酮、色素和固含量模型的预测均方根误差(RMSEP)值分别为1.22 µg/ml、10.50 µg/ml、1.43 µg/ml和0.433%。


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Draper, N.R., Smith, H., 1998. Applied Regression Analysis. Wiley Interscience, New York, p.338-339.

[2]Engel, J., Gerretzen, J., Szymanska, E., et al., 2013. Breaking with trends in pre-processing? TrAC Trends Anal. Chem., 50:96-106.

[3]Fearn, T., Riccioli, C., Garrido-Varo, A., et al., 2009. On the geometry of SNV and MSC. Chemom. Intell. Lab. Syst., 96(1):22-26.

[4]Geladi, P., Kowalski, B.R., 1986. Partial least-squares regression:

[5]a tutorial. Anal. Chim. Acta, 185:1-17.

[6]Gong, X.C., Zhang, Y., Pan, J.Y., et al., 2014a. Optimization of the ethanol recycling reflux extraction process for saponins using a design space approach. PLoS ONE, 9(12):e114300.

[7]Gong, X.C., Li, Y., Qu, H.B., 2014b. Removing tannins from medicinal plant extracts using an alkaline ethanol precipitation process: a case study of Danshen injection. Molecules, 19(11):18705-18720.

[8]Han, H.F., Zhang, L., Zhang, Y., et al., 2013. Rapid analysis of the in-process extract solutions of compound E Jiao oral liquid using near infrared spectroscopy and partial least-squares regression. Anal. Methods, 5(19):5272-5278.

[9]He, J.Y., Zhu, S., Komatsu, K., 2014. HPLC/UV analysis of polyacetylenes, phenylpropanoid and pyrrolidine alkaloids in medicinally used Codonopsis species. Phytochem. Anal., 25(3):213-219.

[10]He, Q., Zhu, E.Y., Wang, Z.T., et al., 2004. Flavones isolated from Codonopsis xundianensis. J. Chin. Pharm. Sci., 13(3):212-213.

[11]Huang, H.X., Qu, H.B., 2011. In-line monitoring of alcohol precipitation by near-infrared spectroscopy in conjunction with multivariate batch modeling. Anal. Chim. Acta, 707(1-2):47-56.

[12]ICH (International Council for Harmonisation), 2009. ICH Harmonised Tripartite Guideline Q8(R2): Pharmaceutical Development, Current Step 4 version.

[13]Islam, M.T., Scoutaris, N., Maniruzzaman, M., et al., 2015. Implementation of transmission NIR as a PAT tool for monitoring drug transformation during HME processing. Eur. J. Pharm. Biopharm., 96:106-116.

[14]Kim, E.Y., Kim, J.A., Jeon, H.J., et al., 2014. Chemical fingerprinting of Codonopsis pilosula and simultaneous analysis of its major components by HPLC-UV. Arch. Pharm. Res., 37(9):1148-1158.

[15]Koh, G.Y., Chou, G.X., Liu, Z.J., 2009. Purification of a water Extract of Chinese sweet tea plant (Rubus suavissimus S. Lee) by alcohol precipitation. J. Agric. Food Chem., 57(11):5000-5006.

[16]Li, B.X., Wei, Y.H., Duan, H.G., et al., 2012. Discrimination of the geographical origin of Codonopsis pilosula using near infrared diffuse reflection spectroscopy coupled with random forests and k-nearest neighbor methods. Vib. Spectrosc., 62:17-22.

[17]Li, W.L., Cheng, Z.W., Wang, Y.F., et al., 2013. A study on the use of near-infrared spectroscopy for the rapid quantification of major compounds in Tanreqing injection. Spectrochim. Acta Part A, 101:1-7.

[18]Li, W.L., Han, H.F., Zhang, L., et al., 2015. A feasibility study on the non-invasive analysis of bottled compound E Jiao oral liquid using near infrared. Sens. Actuators B, 211: 131-137.

[19]Li, W.L., Han, H.F., Zhang, L., et al., 2016. Manufacturer identification and storage time determination of “Dong’e Ejiao” using near infrared spectroscopy and chemometrics. J. Zhejiang Univ.-Sci. B (Biomed. & Biotechnol.), 17(5):382-390.

[20]National Commission of Chinese Pharmacopoeia, 2015. Pharmacopoeia of the People’s Republic of China. Chemical Industry Press, Beijing, p.264 (in Chinese).

[21]Norris, K.H., Williams, P.C., 1984. Optimization of mathematical treatments of raw near-infrared signal in the measurement of protein in hard red spring wheat. I. Influence of particle size. Cereal Chem., 61(2):158-165.

[22]Qiao, C.F., He, Z.D., Han, Q.B., et al., 2007. The use of lobetyolin and HPLC-UV fingerprints for quality assessment of Radix Codonopsis. J. Food Drug Anal., 15(3): 258-264.

[23]Rinnan, A., van den Berg, F., Engelsen, S.B., 2009. Review of the most common pre-processing techniques for near-infrared spectra. TrAC Trends Anal. Chem., 28(10):1201-1222.

[24]Savitzky, A., Golay, M.J.E., 1964. Smoothing and differentiation of data by simplified least squares procedure. Anal. Chem., 36(8):1627-1639.

[25]Shi, J.Y., Zou, X.B., Zhao, J.W., et al., 2012. Determination of total flavonoids content in fresh Ginkgo biloba leaf with different colors using near infrared spectroscopy. Spectrochim. Acta Part A, 94:271-276.

[26]Valderrama, P., Braga, J.W.B., Poppi, R.J., 2007. Variable selection, outlier detection, and figures of merit estimation in a partial least-squares regression multivariate calibration model. A case study for the determination of quality parameters in the alcohol industry by near-infrared spectroscopy. J. Agric. Food Chem., 55(21):8331-8338.

[27]Wang, F., Jiang, W., Li, C., et al., 2015. Application of near infrared spectroscopy in monitoring the moisture content in freeze-drying process of human coagulation factor VIII. J. Innov. Optheal. Sci., 8(6):1550034.

[28]Wang, P., Yu, Z., 2015. Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: a review. J. Pharm. Anal., 5(5):277-284.

[29]Wang, P., Zhang, H., Yang, H., et al., 2015. Rapid determination of major bioactive isoflavonoid compounds during the extraction process of kudzu (Pueraria lobata) by near-infrared transmission spectroscopy. Spectrochim Acta Part A, 137(137C):1403-1408.

[30]Workman, J., Weyer, L., 2008. Practical Guide to Interpretive Near-Infrared Spectroscopy. CRC Press, New York, p.56.

[31]Wu, Y.J., Jin, Y., Ding, H.Y., et al., 2011. In-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz based on qualitative and quantitative uses of near-infrared spectroscopy. Spectrochim. Acta Part A, 79(5):934-939.

[32]Xu, Z.L., Huang, W.H., Gong, X.C., et al., 2015. Design space approach to optimize first ethanol precipitation process of Dangshen. Chin. J. Chin. Mater. Med., 40(22):4411-4416. http://dx.doi.10.4268/cjcmm20152217

[33]Zhao, G.P., Dai, S., Chen, R.S., 2006. Dictionary of Chinese Traditional Medicine. Shanghai Scientific and Technical Publishers, Shanghai, p.2578-2579 (in Chinese).

[34]List of electronic supplementary materials

[35]Fig. S1 Scree plot: results of different latent variables for regression models

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE