ABSTRACT
The quantity of biomass, glucose concentration and ethanol concentration are important parameters in ethanol fermentation. Traditional methods are usually based on samples for off-line measurement, which not only requires multiple instruments for test and analysis but also consumes notable time and effort, and therefore is inconvenient for real-time process control and optimization. In this study, an in-situ detection method based on the near-infrared (NIR) spectroscopy is proposed for measuring the above process parameters in real time. The in-situ measurement is carried out by using an immersion type NIR spectroscopy. A multi-output prediction model for simultaneously estimating the quantity of glucose, biomass and ethanol is established based on a multi-output least-squares support vector regression algorithm. The experimental results show that the proposed method can precisely measure the quantity of glucose, biomass and ethanol during the ethanol fermentation process. Compared to the existing partial-least-squares method for modeling and prediction of individual components, the proposed method could evidently improve the measurement accuracy and reliability.
Subject(s)
Ethanol , Fermentation , Least-Squares Analysis , Reproducibility of Results , Spectroscopy, Near-InfraredABSTRACT
Objective To develop a rapid method for the detection of toxic adulterant (diethylene glycol) in pharmaceuti-cal excipient (glycerol) .Method The detection sensitivity of Raman/near infrared (NIR) spectroscopy combined with moving window correlation coefficient (MWCC) method was evaluated .Results The detection sensitivity of Raman spectroscopy was superior to that of NIR spectroscopy and with the assistance of MWCC method ;the sensitivity had been further improved . Conclusion Raman spectroscopy has the potential to become the effective method in the on-site detection of toxic adulterant in pharmaceutical excipient .
ABSTRACT
Objective To set up a new method for fast determining and identifying Xintong Oral Liquid by acousto-optic tunable filter-near infrared(AOTF-NIR)spectroscopy.Methods Identifying method by NIR spectroscopy combined with principal component analysis(PCA),and determining model of qualitative and quantitative analyses based on PLS1 algorithm.Results The XT-C identifying model could be used to identify Xintong Oral Liquid,the determining model of qualitative and quantitative analyses with better accuracy,RMSEP of the models for puerarin was 0.137 1,the determination coefficients was R2=0.984 5.The correlation coefficient of the true value and predication value from validation was r2=0.996 4.The average recovery of the predication set was 101.9%.RSD for precision was 1.98%,RSD for stability was 1.57%.Conclusion The method is a quick and simple assay technique with low cost,which is able to be used in the qualitative and quantitive analyses on Xintong Oral Liquid.
ABSTRACT
Objective Near-infrared (NIR) spectroscopy was used as a fast analytical technique in the ethanol reflux-extraction process of red ginseng. Methods The NIR spectra of the extracting solution of red ginseng were obtained and the reference measurements of the active constituent in the extracting solution were performed by the colorimetric method. Firstly, the interference information in the spectra was detected by orthogonal signal correction (OSC) method. Then a calibration model between NIR spectra and reference measurements was established by partial least square regression. Results The results showed that the predictive accuracy of NIR calibration model used for the determination of ginsenoside in ethanol extracting process of red ginseng was good. Conclusion NIR Spectroscopy could be applied to the fast analysis for ethanol extracting processes of red ginseng.
ABSTRACT
Objective Near-infrared (NIR) reflectance spectroscopy was used to develop a fast quality assessment method by simultaneous material identification and moisture quantification of Radix Ginseng Rubra (RGR). Methods The sample was identified by the comparison of its spectrum with a standard NIR spectral library. Similarity measurement was used as the discriminating parameter. The moisture content of sample was quantified by a partial least square (PLS) calibration model, correlative spectrum calculation was used for wavelength selection and multiplicative signal correction (MSC) was applied for pretreatment in the calibration model. Primary reference data were obtained using the traditional loss on drying (LOD) method. Results The NIR library can distinguish RGR from the counterfeit successfully. The optimized eight-factor PLS calibration model of NIR spectra has a high correlation coefficient (R=(0.999 7).) Conclusion The proposed method is rapid, accurate and can be used routinely in the traditional Chinese materia medica manufacturers for quality control of raw materials.