RESUMEN
To develop a method for the rapid monitoring of five components during the alcohol precipitation process of Shenzhiling oral solution using near infrared spectroscopy(NIRS).The contents of five components detemined by high performance liquid chromatography(HPLC) were used as the reference values, and the NIRS based partial least square regression(PLSR) models were used to monitor the concentrations of paeoniflorin, albiflorin, liquiritin, cinnamic acid and glycyrrhizic acid during the alcohol precipitation process of Shenzhiling oral solution, which were optimized and verified through comparing of different spectral pre-processing and variables selection methods. Determination coefficients(Rcal2 and Rpred2), root mean squares error of prediction (RMSEP), root mean squares error of calibration(RMSEC) and ratiao of performance to deviation(RPD) were applied to evaluate the performance of the models, and the corresponding values were 0.993 3 and 0.997 6, 0.084 9 gâ¢L⻹, 0.073 3 gâ¢L⻹ and 14.7 for paeoniforin; 0.991 4, 0.992 7, 0.028 1 gâ¢L⻹, 0.030 5 gâ¢L⻹ and 10.2 for albiforin; 0.955 3, 0.976 1, 0.012 0 gâ¢L⻹, 0.012 3 gâ¢L⻹ and 5.1 for liquiritin; 0.958 8, 0.990 3, 0.003 89 gâ¢L⻹, 0.002 89 gâ¢L⻹ and 7.1 for cinnamic acid; 0.982 0, 0.986 3, 0.053 8 gâ¢L⻹, 0.059 0 gâ¢L⻹, 7.2 for glycyrrhizic acid, respectively. The results indicated that the presented approach was effectively for the quantitative monitoring of the alcohol precipitation process of Shenzhiling oral solution.
Asunto(s)
Medicamentos Herbarios Chinos/normas , Espectroscopía Infrarroja Corta , Calibración , Precipitación Química , Etanol , Análisis de los Mínimos CuadradosRESUMEN
As one very precious traditional Chinese medicine (TCM), Huoshan Dendrobium has not only high price, but also significant pharmaceutical efficacy. However, different species of Huoshan Dendrobium exhibit considerable difference in pharmaceutical efficacy, so rapid and absolutely non-destructive discrimination of Huoshan Dendrobium nobile according to different species is crucial to quality control and pharmaceutical effect. In this study, as one type of miniature near-infrared (NIR) spectrometer, MicroNIR 1700 was used for absolutely nondestructive determination of NIR spectra of 90 batches of Dendrobium from five species of differ- ent commodity grades. The samples were intact and not smashed. Soft independent modeling of class analogy (SIMCA) pattern recognition based on principal component analysis (PCA) was used to classify and recognize different species of Dendrobium samples. The results indicated that the SIMCA qualitative models established with pretreatment method of standard normal variate transformation (SNV) in the spectra range selected by Qs method had 100% recognition rates and 100% rejection rates. This study demonstrated that a rapid and absolutely non-destructive analytical technique based on MicroNIR 1700 spectrometer was developed for successful discrimination of five different species of Huoshan Dendrobium with acceptable accuracy.