Quantitative Analysis of Panax ginseng by FT-NIR Spectroscopy.

Near-infrared spectroscopy (NIRS), a rapid and efficient tool, was used to determine the total amount of nine ginsenosides in Panax ginseng. In the study, the regression models were established using multivariate regression methods with the results from conventional chemical analytical methods as reference values. The multivariate regression methods, partial least squares regression (PLSR) and principal component regression (PCR), were discussed and the PLSR was more suitable. Multiplicative scatter correction (MSC), second derivative, and Savitzky-Golay smoothing were utilized together for the spectral preprocessing. When evaluating the final model, factors such as correlation coefficient (R (2)) and the root mean square error of prediction (RMSEP) were considered. The final optimal results of PLSR model showed that root mean square error of prediction (RMSEP) and correlation coefficients (R (2)) in the calibration set were 0.159 and 0.963, respectively. The results demonstrated that the NIRS as a new method can be applied to the quality control of Ginseng Radix et Rhizoma.

[Nondestructive recognization of mountain cultivated ginseng and garden cultivated ginseng by FTIR microspectroscopy].

Fourier transform infrared (FTIR) microspectroscopy technology is the combination of the FTIR spectrometer and the microscope. This technology is of simple preparation of the samples, can be used in micro-area analysis and micro-samples, and reflect the nature of the samples spectra. Panax ginseng include mountain cultivated ginseng (MCG), garden cultivated ginseng (GCG) and mountain wild ginseng (MWG), but the excavation of MWG is prohibited in China. So, only MCG and GCG were collected and recorded in Chinese pharmacopoeia. In this study, we developed a discriminant analysis (DA) method for recognition of MCG and GCG using FTIR microspectroscopy technology. Twenty MCG samples and twenty four GCG samples were obtained, and their spectra of IR microspectroscopy were collected. Then 33 samples were randomly selected into calibration set and the remaining 11 of the samples were selected into validation set. The authors optimized the pretreatment method, the principal components, the modeling region and the scanning parts when developing the models. The optimized model of discriminant analysis was developed using the pretreatment multiplicative scatter correction (MSC) + Savitzky-Golay filter (SG) smoothing, the region 3 932.14-669.18 cm(-1), 4 principal components and the rhizome part. The accuracy of the optimized model got up to 100%. The result demonstrated that infrared microspectroscopy technology combined with DA is of simple operation, rapid, nondestructive and effective, and can be applied to recognize MCG and GCG.

[Nondestructive identification of the root of mountain cultivation ginseng and growth years by near infrared spectroscopy].

Mountain cultivation ginseng (MCG) and garden cultivation ginseng (GCCG) were identified by near infrared spectroscopy, so were MCG of different growth years. 96 MCG samples of different growth years, including 24 of fifteen years and 72 of ten years, and 177 GCG samples were collected. After the near infrared spectra of these samples were collected, discriminant analysis was used to distinguish MCG and GCG, so was MCG of different years. After the original spectra were pretreated, discriminant analysis models of MCG and GCG, MCG of different growth years were developed respectively with selected principa component numbers in full spectra region. The correct discrimination rate of two groups of model was both 100%. The propose methods are accurate, fast and nondestructive, and can be applied to the quality control of MCG. It has an important significance for building market image of MCG.