| ORIGINAL ARTICLE |
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| Year : 2019 | Volume
: 15
| Issue : 63 | Page : 479-486 |
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Rapid and simultaneous analysis of five free anthraquinone contents in rhubarb during the stir-frying with rice wine process by near infrared reflectance spectroscopy
Xingyi Chen1, Jintao Xue2, Weiying Wang1, Bihua Ma1, Guo Huang3, Yu Chen4, Liming Ye1
1 Department of Pharmaceutical Analysis, West China School of Pharmacy, Sichuan University, Sichuan, China
2 Department of TCM, School of Pharmacy, Xinxiang Medical University, Henan, China
3 Department of Application, Sichuan Vspec Technologies Co., Ltd., Sichuan, China
4 Department of Pharmacy, West China Hospital, Sichuan University, Sichuan, China
Correspondence Address:
Liming Ye
West China School of Pharmacy, Sichuan University, No. 17 People's South Road, Chengdu 610041, Sichuan
China
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/pm.pm_562_18
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Background: The active ingredients of Traditional Chinese Medicines (TCMs) vary greatly with the degree of stir-frying; so, rapid analysis of the active content is very important for the processing of TCMs. Objective: In this study, near infrared reflectance (NIR) spectroscopy was used to develop a new method for the rapid online analysis of five free anthraquinones (aloe-emodin, rhein, emodin, chrysophanol, and physcion) during the stir-frying process for rhubarb. Materials and Methods: With partial least-squares (PLSs) and artificial neural networks (ANN) regression, calibration models were generated based on five free anthraquinone contents, as measured by high-performance liquid chromatography. Results: The results indicated that the 2 types of models were robust, accurate, and repeatable for five free anthraquinones. Moreover, PLS as the linear model was more suitable for developing the NIR models of the five free anthraquinones than ANN. The performance of the optimal models was achieved as follows: the coefficient of determination for prediction (R2pre) for aloe-emodin, rhein, emodin, chrysophanol, and physcion was 0.9161, 0.9699, 0.9655, 0.9611, and 0.9724, respectively; the root mean square error of prediction was 0.0251, 0.0445, 0.3333, 0.0862, and 0.0211, respectively. Conclusion: The established NIR models could apply to determine the content of five free anthraquinones in rhubarb. This work demonstrated that NIR may be an effective online analysis method to reflect the quality of TCM industrial manufacturing processes.
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