Study On The Quality Control Of Panax Notoginseng Based On FTIR Combined With Chemometrics

Traditional Chinese medicine (TCM) have been guided under the theory of Chinese medicine were used for prevention, diagnosis, treatment and adjusting human body’s function. How to ensure the efficacy and quality of TCM is the core problem in the further research and development, and it is directly related to the safety and effectiveness of clinical medication. Modern studies have indicated that the chemical compositions of TCM were complicated and it performed the pharmacologic effects of multi-targets and multi-channels based on the synergy of multi-components.Besides that, the change of producing area, climate, sunshine, soil, water and other conditions will impact on the secondary metabolites of TCM. Chemical fingerprint technology based on the overall chemical information research complex system can reflect the comprehensive information of the sample, and it associated with the holistic concept of TCM. Combining with chemometrics methods, chemical fingerprint have been widely used in the classification study of geographical origins,growing years, authenticity, and rapid detection of effective component contents of TCM, offers a lot of theoretical and practice basis for the scientific and rational utilization of TCM.This paper based on the study of Panax notoginseng (Burk.) F. H. Chen, is the daodi medicinal herb in Yunnan Province, PR China. Fourier transform infrared(FTIR) was used to establish the chemical fingerprints of P. notoginseng, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM)algorithm were used for mining the chemical information in FTIR of different areas and underground part samples, and quickly identifying them. The contents of saponins, total flavonids and total polysaccharides were determined by high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC) and ultraviolet-visible spectroscopy (UV-Vis), we set the date of FTIR spectra as variable X and the effective component contents set as variable Y, combined with regression analysis to built prediction models for the rapid detection of effective component contents. In order to provide a rapid and effective method for the comprehensive quality control and ensure the scientific, reasonable medicinal use of P. notoginseng, the result are as following:(1) FTIR spectra of P. notoginseng originated from five regions were collected,and the content of notoginsenoside Ri, ginsenoside Rg1, ginsenoside Re, and ginsenoside Rbi were detected. The results showed that the utilization of FTIR combined with SVM could effectively identify different origins of P. notoginseng with the accuracy of 94.29% in regional classification, and 97.14% in daodi original identification. In orthogonal single collection partial least squares regression(OSC-PLSR) model, correlation coefficient (R2) and root mean square error of estimation (RMSEE) of calibration set was 0.9418 and 4.5307, R2 and root mean square error of validation set (RMSEP) was 0.9623 and 3.8559, respectively. It indicated that the OSC-PLSR combined with FTIR could rapid quality assessment of P. notoginseng.(2) FTIR spectra of the main root, rhizome and fibrous root powder of P.notoginseng were collected, and UPLC used for measuring the content of notoginsenoside R1, ginsenoside Rg1, ginsenoside Rbi and ginsenoside Rd of samples.Results showed that, the content of total four saponins were the highest in rhizome,were 1.8 times and 4.6 times higher than that of main root and fibrous root,respectively. FTIR combined with SVM could effectively identify the main root,rhizome and fibrous root powder of P. notoginseng with the accuracy of 100%.OSC-PLSR could accurately predict the content of 4 kind saponins of P. notoginseng,and the predicted content closed to UPLC measurement.(3) The total flavonoids content of P. notoginseng was determinated by UV-Vis,FTIR spectra combined with chemometrics, as a rapid prediction model of total flavonoids content was established. The results showed that samples collected from three daodi producing areas of Wenshan, Luoping, and Shilin counties contained higher content of total flavonoids (more than 7 mg/g) than other areas. After the same points of Savitsky-Golay (SG) smoothing, the model predictive ability of 2D is better than that of 1D. In all prediction models, the 2D+SG 7+OSC-PLSR (Rpre2 = 0.9761,RMSEP = 0.3252) and 2D+SG 11+OSC-PLSR (Rpre2=0.9469, RMSEP=0.3820)model showed an excellent predictive effect, the value of RMSEP was below 0.4, and the predicted values were close to the detection values.(4) The total polysaccharides content of P. notoginseng was determined by UV-Vis and phenol sulfuric acid reaction, and a prediction model of total polysaccharides content was based on FTIR spectra combined with support vector regression (SVR). The results showed that the samples from Qiubei, Shizong and Mengzi origins contained higher content of total polysaccharides (more than 25 mg/g)than other producing origins. By analyzing RMSEE and 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. PSO model showed an excellent predictive effect with RMSEP and Rpre2 of 3.1206 and 83.13% respectively, which indicated the predicted values were close to the UV-Vis detection values.(5) The contents of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re,ginsenoside Rb1, total flavonids and total polysaccharides were determined, and the entire quality evaluation model was established by technique for order preference by similarity to ideal solution (TOPSIS). The results showed that, the averaged Ci of samples from Wenshan, Honghe, Yuxi, Kunming and Qujing were 0.3002, 0.3411,0.2795, 0.3387 and 0.3230, respectively. It indicated that the overall quality of P.notoginseng from different origins of Yunnan Province was similar, and there were few differences between the overall qualities of samples from Wenshan which is the daodi region of P. notoginseng and the other ones. The Ci values of S46, S16 and S33 topped the list of all samples, which showed that the overall qualities of these three samples were excellent, and they can be used as the dominant provenances for the further study.