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| Prediction of Total Polysaccharides Content in P. notoginseng Using FTIR Combined with SVR |
| LI Yun1,2,3, ZHANG Ji1,2, LIU Fei4, XU Fu-rong3, WANG Yuan-zhong1,2*, ZHANG Jin-yu1,2,3* |
1. Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China
2. Yunnan Technical Center for Quality of Chinese Materia Medica, Kunming 650200, China
3. College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, China
4. Yuxi Normal University, Yuxi 653100, China |
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Abstract The multi-component synergy is one of the important pathways for the pharmacological effects of traditional Chinese medicine (TCM) due to the complicated chemical compositions. Therefore, it is necessary to control and reflect the quality of TCM comprehensively in order to ensure its efficacy and safety. In Chinese Pharmacopoeia, the contents of three saponins were selected as indicators to ensure the quality of P. notoginseng. However, a single type indicator was limited to evaluate the quality of P. notoginseng comprehensively. In this study, the total polysaccharides content of P. notoginseng was determined by using ultraviolet-visible (UV-Vis) spectroscopy and phenol sulfuric acid reaction, and a prediction model of total polysaccharides content was established to provide some basic researches for rapid and comprehensive quality assessment of P. notoginseng based on Fourier transform infrared (FTIR) spectroscopy combined with support vector regression (SVR). In addition, a total of 60 FTIR spectra of P. notoginseng originated from 12 regions were collected. The absorbance of UV-Vis spectra at 490 nm which was contributed by polysaccharide extraction solution was recorded, and the content of total polysaccharides was calculated based on standard linear equation of glucose. Moreover, optimization procedures of spectra data were calculated by second derivative (2D), orthogonal signal correction (OSC), wavelet transform (WT), and variable importance for the projection (VIP). 2/3 of the 60 individuals were selected to develop the calibration set by using SPXY algorithm, and the rest samples were used as validation set. Calibration set data was used to establish the SVR model and grid search, genetic algorithm (GA) and particle swarm optimization algorithm (PSO) were used for screening optimal parameters which were utilized to verify the accuracy and reliability of the SVR model. Results showed that: (1) Maximum absorption peaks of glucose and total polysaccharides were both at 490 nm, and therefore the absorbance of UV-Vis spectra at 490 nm could be used for calculating the content of total polysaccharides. (2) The P. notoginseng from Qiubei, Shizong and Mengzi origins contained higher content of total polysaccharides (more than 25 mg·g-1) than other producing origins. (3) By analyzing the root mean square error of estimation (RMSEE) and the root mean square error of prediction (RMSEP) of optimization model, we found that the grid search model were under-fitting and the GA model were over-fitting compared with PSO model. (4) PSO model showed an excellent predictive effect with RMSEP and R2pre of 3.120 6 and 83.13% respectively, which indicated the predicted values were close to the detection values. The result indicated that FTIR combined with PSO-SVR could accurately predict the content of total polysaccharides, which could provide a research basis for the comprehensive quality control as well as ensure the stable, safe and effective medicinal use of P. notoginseng.
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Received: 2016-05-09
Accepted: 2017-01-18
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Corresponding Authors:
WANG Yuan-zhong, ZHANG Jin-yu
E-mail: boletus@126.com; jyzhang2008@126.com
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