الملخص
Near-infrared (NIR) was used as rapid analysis method to identify the sulfur fumigated Puerariae Lobatae Radix. NIR spectra of the cross-sectional and longitudinal selection of samples were acquired. Principal component analysis was conducted. The samples were randomly selected. The different pretreatment methods were compared. Discriminant models were established for every type of spectra to calculate the recognition rate. The orthogonal test and nonparametric test were used to test data normality. The result showed that absorbance values of different sections were different due to the different structure, and the raw spectra were analyzed by PCA method. The result founded that the cumulative contribution rate was arrived at 99.2% while the PC numbers were arrived at 3. The pretreatment method based on the MSC + 1D + Savitzky-Golay was the best to establish the model. For the 50 models constructed with cross-section and longitudinal spectra and total spectra, the recognition rate were (94.4 ± 0.66)%, (94.4 ± 0.66)%, (95.3 ± 0.65)%, respectively, and no difference was observed. The NIR method could be used to identify the sulfur fumigated Puerariae Lobatae Radix.
الموضوعات
Chemistry, Pharmaceutical , Methods , Discriminant Analysis , Drugs, Chinese Herbal , Chemistry , Fumigation , Pueraria , Chemistry , Spectroscopy, Near-Infrared , Sulfur , Chemistryالملخص
Near-infrared (NIR) diffuse reflectance spectroscopy was used to analyze the impact of multi-class particle size of Chinese material medica (CMM) based on the spectral characteristics in overtone and combination region. Several types of CMM (60, 80, 100,120 mesh) were subjected to NIR spectra analysis. Spectral reproducibility was examined after sample repackage. The result showed that the effects of particle size on the NIR spectra were different according to different bands, in the combination region and first combination-overtone region. Spectroscopy intensity was proportional to the particle size and influence of particle size was greater as the wavelength increased. While in the second combination-overtone region, it was inversely proportional to particle size. To the sampling loading error, the result indicated that when the mesh number was larger than 60 mesh, the error was small. The appropriate particle size was clarified to guarantee the accuracy and reliability of NIR diffuse reflectance spectroscopy in CMM.
الموضوعات
Drugs, Chinese Herbal , Materia Medica , Particle Size , Spectroscopy, Near-Infrared , Methodsالملخص
The on-line monitor for the changes in the content of baicalin in Scutellariae Radix formula particles during the extraction process was conducted by using near infrared spectroscopy (NIR). High performance liquid chromatography (HPLC) was used as a reference method. Kennard-Stone (KS) was used to divide sample sets, so as to compare different pretreatment methods. The synergy interval partial least squares (SiPLS) was used to screen out modeling wave band to establish partial least-squares models. The relative error method was applied to predict forecast set samples of Scutellariae Radix in three extraction phases. The results showed that the model established by Savitzky-Golay smoothing with 11 points (SG11 points) was the best, with the root mean square with cross validation (RMSECV), root mean square error of correction (RMSEC) and root mean square error of prediction (RMSEP) of baicalin of 0.092 7, 0.134 4 and 0.114 8, respectively, the determination coefficient R2 of greater than 0.99, and the relative error of baicalin content of less than 5%. This indicates that the on-line near infrared reflectance spectroscopy could be applied in on-line monitor and quality control of the extraction process of Scutellariae Radix formula particles.