| 光谱学与光谱分析 |
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| Online Analysis of Dynamic Trend Regression and Endpoint Determination for Chinese Traditional Medicine Extraction Process Based on Ultraviolet spectroscopy |
| LIU Wei, DAI Lian-kui* |
| State Key Laboratory of Industrial Control Technology，Zhejiang University，Hangzhou 310027，China |
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Abstract With the transition of Chinese traditional medicine manufacture industry, modernization has become the inexorable tendency in its future development. However, during the current Chinese traditional medicine producing process, the lack of online monitoring leads to the lagging of quality detection, as well as quality differences between products. In this paper, aiming at realizing online monitoring and end point automatic determination for Chinese traditional medicine (CTM) extraction unit, which is one of the most important units in CTM producing, ultraviolet (UV) spectroscopy is applied to build UV absorbance dynamic model based on the Lambert-Beer law and the CTM extraction kinetic model which presents a new method of UV absorbance dynamic analysis and endpoint determination, including curve regression, robustness analysis and endpoint calculation. In the experiment for online monitoring homalomena occulta extraction, the online UV spectral collection system for CTM extraction, developed by our laboratory, was applied for spectral collection; meanwhile, solid component contents in the offline samples were measured as reference. During the analysis, first of all, we pretreated the spectrum collected in the current period with interpolation and smoothing, and calculated the mean value within a UV region of 230.2～400 nm to form an absorbance mean value sequence with data obtained in the early measurements; then we verified the linear correlation between the sequence of absorbance and the concentrations of effective component in the solution, the linear correlation coefficient equals 0.982 8, showing a high linearity between UV spectra and solid component contents; finally, we regressed the absorbance mean value sequence with the dynamic model, analyzing its robustness and the extraction endpoint. Experimental results demonstrate that, the robustness analysis could recognize the bad points of measurement during the regression process, and improve the consistency between the regression and the original curves, raising its squared correlation coefficient to more than 0.99; meanwhile, with endpoint determination, we shortened the homalomena occulta extraction process from the original manually set 180 to 122 min effectively. The experiment above proves that this method with UV spectroscopy realizes online monitoring and automatic endpoint determination for the CTM extraction process, and is of significant importance for stabilizing production as well as improving economic benefit.
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Received: 2016-01-14
Accepted: 2016-05-06
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Corresponding Authors:
DAI Lian-kui
E-mail: lkdai@iipc.zju.edu.cn
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