ABSTRACT
Objective To determine the content of baicalin in Radix Scutellariae granule from different manufacturers using near infrared spectroscopy(NIRS)technology. Methods Utilizing NIRS combined with partial least squares,and simultaneously opti?mizing the pretreatment methods and the range of spectrum,the quantitative model of baicalin in Radix Scutellarie granules was estab?lished. Results In the model correlation coefficient(R2)was 0.9702,root-mean-square error of calibration(RMSEC)was 0.555,and root-mean-square error of predict(RMSEP)was 1.05. Conclusion In this paper,rapid quality analysis method of Radix Scutellariae granules from different manufacturers is studied using NIRS technology. The model can predict the content of baicalin nondestructively and rapidly. It can give some reference for researching the quality control of Radix Scutellariae granules .
ABSTRACT
Biomass is an important parameter reflecting the fermentation dynamics. Real-time monitoring of biomass can be used to control and optimize a fermentation process. To overcome the deficiencies of measurement delay and manual errors from offline measurement, we designed an experimental platform for online monitoring the biomass during a 1,3-propanediol fermentation process, based on using the fourier-transformed near-infrared (FT-NIR) spectra analysis. By pre-processing the real-time sampled spectra and analyzing the sensitive spectra bands, a partial least-squares algorithm was proposed to establish a dynamic prediction model for the biomass change during a 1,3-propanediol fermentation process. The fermentation processes with substrate glycerol concentrations of 60 g/L and 40 g/L were used as the external validation experiments. The root mean square error of prediction (RMSEP) obtained by analyzing experimental data was 0.341 6 and 0.274 3, respectively. These results showed that the established model gave good prediction and could be effectively used for on-line monitoring the biomass during a 1,3-propanediol fermentation process.
ABSTRACT
Objective To determine the content of baicalin in Radix Scutellariae granule from different manufacturers using near infrared spectroscopy(NIRS)technology. Methods Utilizing NIRS combined with partial least squares, and simultaneously optimizing the pretreatment methods and the range of spectrum, the quantitative model of baicalin in Radix Scutellarie granules was established. Results In the model correlation coefficient(R2)was 0.9702, root-mean-square error of calibration(RMSEC)was 0.555, and root-mean-square error of predict(RMSEP)was 1.05. Conclusion In this paper, rapid quality analysis method of Radix Scutellariae granules from different manufacturers is studied using NIRS technology. The model can predict the content of baicalin nondestructively and rapidly. It can give some reference for researching the quality control of Radix Scutellariae granules.
ABSTRACT
The growing interest of the pharmaceutical industry in Near Infrared-Chemical Imaging (NIR-CI) is a result of its high usefulness for quality control analyses of drugs throughout their production process (particularly of its non-destructive nature and expeditious data acquisition).In this work,the concentration and distribution of the major and minor components of pharmaceutical tablets are determined and the spatial distribution from the internal and external sides has been obtained.In addition,the same NIR-CI allowed the coating thickness and its surface distribution to be quantified.Images were processed to extract the target data and calibration models constructed using the Partial Least Squares (PLS) algorithms.The concentrations of Active Pharmaceutical Ingredient (API) and excipients obtained for uncoated cores were essentially identical to the nominal values of the pharmaceutical formulation.But the predictive ability of the calibration models applied to the coated tablets decreased as the coating thickness increased.
ABSTRACT
Objective:To study the application of partial least squares (PLS) in spectrophotometry,and to simultaneously determine four synthetic food colors with PLS.Methods:? max for Tartrazine,sunset yellow,ponocean 4R and amaranth were 428?2nm,482?2nm,508?2nm,520?2nm respectively,which revealed significant overlapping of simultaneous determination of mixture of four synthetic food colors by spectrophotometry,whithout any preliminary chemical separation.Results:The mean recoveries and relative standard deviation(RSD) for each sample were 100.6%,100.5%,99.5%,101.1% and 1.28%,1.11%,1.01%,1.96%,respectively.The actual results of two kinds of samples were also satisfactory.Conclusion:The patial least squares may provide a new approach to determination of the content from multi-component spectroscpic data whithout any preliminary chemical separation.