Phcog.Net logo
Submit

BROWSE ALL JOURNALS

    SEE ALL 6 JOURNALS
    Pharmacognosy MagazineNOW IN
    Article

    On‑line quantitative monitoring of liquid‑liquid extraction of Lonicera japonica and Artemisia annua using near‑infrared spectroscopy and chemometrics

    Sha Wu2, Ye Jin3, Qian Liu4, Qi-an Liu4, Jianxiong Wu4, Yu-an Bi4, Zhengzhong Wang4, Wei Xiao2,4★★ Corresponding author

    1. 1College of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100102, China.
    2. 2College of Pharmaceutical Science, Zhejiang University, Hangzhou, 310058, China.
    3. 3National Key Laboratory of Pharmaceutical New Technology for Chinese Medicine, Kanion Pharmaceutical Corporation, Lianyungang, 222000, China.

    CORRESPONDENCE

    Wei Xiao

    College of Pharmaceutical Science, Zhejiang University, Hangzhou, 310058, China.

    xw_kanion@163.com

    Received: 23-09-2014; Revised: 14-11-2014.

    Volume 11, Issue 43 · pp. 643–650 · PUBLISHED 10 July 2015 · DOI: 10.4103/0973-1296.160465

    View on Pharmacogn. Mag. original site ↗

    ABSTRACT

    Background: Liquid‑liquid extraction of Lonicera japonica and Artemisia annua (JQ) plays a significant role in manufacturing Reduning injection. Many process parameters may influence liquid‑liquid extraction and cause fluctuations in product quality. Objective: To develop a near‑infrared (NIR) spectroscopy method for on‑line monitoring of liquid‑liquid extraction of JQ. Materials and Methods: Eleven batches of JQ extraction solution were obtained, ten for building quantitative models and one for assessing the predictive accuracy of established models. Neochlorogenic acid (NCA), chlorogenic acid (CA), cryptochlorogenic acid (CCA), isochlorogenic acid B (ICAB), isochlorogenic acid A (ICAA), isochlorogenic acid C (ICAC) and soluble solid content (SSC) were selected as quality control indicators, and measured by reference methods. NIR spectra were collected in transmittance mode. After selecting the spectral sub‑ranges, optimizing the spectral pretreatment and neglecting outliers, partial least squares regression models were built to predict the content of indicators. The model performance was evaluated by the coefficients of determination (R2), the root mean square errors of prediction (RMSEP) and the relative standard error of prediction (RSEP). Results: For NCA, CA, CCA, ICAB, ICAA, ICAC and SSC, R2 was 0.9674, 0.9704, 0.9641, 0.9514, 0.9436, 0.9640, 0.9809, RMSEP was 0.0280, 0.2913, 0.0710, 0.0590, 0.0815, 0.1506, 1.167, and RSEP was 2.32%, 4.14%, 3.86%, 5.65%, 7.29%, 6.95% and 4.18%, respectively. Conclusion: This study demonstrated that NIR spectroscopy could provide good predictive ability in monitoring of the content of quality control indicators in liquid‑liquid extraction of JQ.

    KEYWORDS

    Open in new tab

    REFERENCES

    As published

    Showing references and in-text citations exactly as published.

      Cite this article

      SELECT FORMAT

      Wu, S., Jin, Y., Liu, Q., Liu, Q., Wu, J., Bi, Y., Wang, Z., & Xiao, W. (2015). On‑line quantitative monitoring of liquid‑liquid extraction of Lonicera japonica and Artemisia annua using near‑infrared spectroscopy and chemometrics. Pharmacognosy Magazine, 11(43), 643–650. https://doi.org/10.4103/0973-1296.160465