Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 2 de 2
Add filters

Year range
China Journal of Chinese Materia Medica ; (24): 2713-2724, 2023.
Article in Chinese | WPRIM | ID: wpr-981374


The grey correlation-TOPSIS method was used to evaluate the quality of the origin herbs of Lonicerae Japonicae Flos, and the Fourier transform near-infrared(NIR) and mid-infrared(MIR) spectroscopy was applied to establish the identification model of origin herbs of Lonicerae Japonicae Flos by combining chemometrics and spectral fusion strategies. The content of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, secoxyloganin, isoquercitrin, isochlorogenic acid B, isochlorogenic acid A, and isochlorogenic acid C in six origin herbs of Lonicerae Japonicae Flos was determined by high-performance liquid chromatography(HPLC), and their quality was evaluated by the grey correlation-TOPSIS method. The Fourier transform NIR and MIR spectra of six origin herbs of Lonicerae Japonicae Flos(Lonicera japonica, L. macranthoides, L. hypoglauca, L. fulvotomentosa, L. confuse, and L. similis) were collected. At the same time, principal component analysis(PCA), support vector machine(SVM), and spectral data fusion technology were combined to determine the optimal identification method for the origin herbs of Lonicerae Japonicae Flos. There were differences in the quality of the origin herbs of Lonicerae Japonicae Flos. Specifically, there were significant differences between L. japonica and the other five origin herbs(P<0.01). The quality of L. similis was significantly different from that of L. fulvotomentosa, L. macranthoides, and L. hypoglauca(P=0.008, 0.027, 0.01), and there were also significant differences in the quality of L. hypoglauca and L. confuse(P=0.001). The PCA and SVM 2D models based on a single spectrum could not be used for the effective identification of the origin herbs of Lonicerae Japonicae Flos. The data fusion combined with the SVM model further improved the identification accuracy, and the identification accuracy of the mid-level data fusion reached 100%. Therefore, the grey correlation-TOPSIS method can be used to evaluate the quality of the origin herbs of Lonicerae Japonicae Flos. Based on the infrared spectral data fusion strategy and SVM chemometric model, it can accurately identify the origin herbs of Lonicerae Japonicae Flos, which can provide a new method for the origin identification of medicinal materials of Lonicerae Japonicae Flos.

Drugs, Chinese Herbal/chemistry , Flowers/chemistry , Quality Control , Lonicera/chemistry , Chromatography, High Pressure Liquid/methods
Chinese Journal of Experimental Traditional Medical Formulae ; (24): 181-186, 2019.
Article in Chinese | WPRIM | ID: wpr-802252


Objective: To explore the change rules of active ingredients in Phyllanthi Fructus of different storage years,in order to provide theory basis for storage. Method: Seven Phyllanthi Fruatus samples of different storage years were collected. HPLC-UV detection method was established to determine the contents of gallic acid,corilagin,chebulagic acid,ellagic acid and quercetin. Samples were fingerprinted by FT-NIR and identified by PLS-DA model. Result: Gallic acid,which was the bioactive marker in Chinese Pharmacopoeia,had the highest content. It was followed by ellagic acid and chebulagic acid,and corilagin and quercetin had the least content. The components had significant differences between samples of different storage years (P-1 respectively. The contents of chebulagic acid,corilagin and ellagic acid reached a maximum at 4 years of storage,which were 18.85,7.97,21.46 mg·g-1,respectively. FT-NIR data was optimized by MSC+SG (second derivative, the window parameter as 11,and the polynomial order as 3). The classification accuracy was 84.5%. Spectral data reduced to several important potential variables,and was fused with 5 active components based on minimum cross-validation root mean square error,and the classification accuracy increased to 98.8%. Conclusion: The analysis of PLS-DA by HPLC-UV and FT-NIR could effectively explain the accumulation characteristics of active components in Phyllanthi Fruatus. According to the data fusion strategy,PLS-DA model could distinguish samples of different qualities. The results provide a scientific basis for the quality evaluation and identification of Phyllanthi Fruatus.