Beijing Kaiyuan Shengshi Science and Technology Development Co.

Jinan, China

Beijing Kaiyuan Shengshi Science and Technology Development Co.

Jinan, China

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Wang D.,Beijing Research Center for Agricultural Standards and Testing | Pan L.-G.,Beijing Research Center for Agricultural Standards and Testing | Wang J.-H.,Beijing Research Center for Agricultural Standards and Testing | Li A.,Beijing Research Center for Agricultural Standards and Testing | And 3 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014

In the present paper, the micro-NIR spectrometer with the splitter of linear variable filter was used to develop the recognition models of the West Lake Longjing tea and the ordinary flat tea of the year 2012 and 2013. The NIR spectral data of different years and different storage times were decomposed by PCA algorithm. The PLS-DA models were developed by the representative samples selected by the mathematical characteristics of PCA-scores' distribution in order to analyze the reason for the inadaptability of the models according to mathematical principles and find out the solution for its correction. Being examined by the external validation set, the adaptability of the authenticity identification model was enhanced effectively. The result of this research indicated that, for the West Lake Longjing tea and the ordinary flat tea, the correct recognition rate of the model developed by all different-year samples' NIR spectral data would be enhanced effectively. The model developed by the NIR spectral data of different storage time samples indicated that the physicochemical properties of the ordinary flat tea have changed remarkably after cryopreservation for 3 months, while the physicochemical properties of the West Lake Longjing tea are relatively stable. The model adaptabilities for different years and different storage times were studied according to the mathematical perspective of the principal component characteristics of spectral data. After the authenticity identification model of West Lake Longjing tea was developed, the prediction accuracy was enhanced effectively. This research would provide reference for not only the application of NIR spectroscopy in quality grading and safety of agricultural products, but also the enhancement of the prediction accuracy of the NIR grading models for agricultural products.


Hu T.,Shandong University | Yang H.-L.,Shandong University | Tang Q.,Anhui University | Zhang H.,Beijing Kaiyuan Shengshi Science and Technology Development Co. | And 7 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014

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 different 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.


Wang F.,Shandong University | Jiang W.,Shandong University | Li C.,Shandong University | Zhang H.,Beijing Kaiyuan Shengshi Science and Technology Development Co. | And 4 more authors.
Journal of Innovative Optical Health Sciences | Year: 2015

As an important process analysis tool, near infrared spectroscopy (NIRS) has been widely used in process monitoring. In the present work, the feasibility of NIRS for monitoring the moisture content of human coagulation factor VIII (FVIII) in freeze-drying process was investigated. A partial least squares regression (PLS-R) model for moisture content determination was built with 88 samples. Different pre-processing methods were explored, and the best method found was standard normal variate (SNV) transformation combined with 1st derivation with Savitzky-Golay (SG) 15 point smoothing. Then, four different variable selection methods, including uninformative variable elimination (UVE), interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and manual method, were compared for eliminating irrelevant variables, and iPLS was chosen as the best variable selection method. The correlation coefficient (R), correlation coefficient of calibration set (Rcal), correlation coefficient of validation set (Rval), root mean square errors of cross-validation (RMSECV) and root mean square errors of prediction (RMSEP) of PLS model were 0.9284, 0.9463, 0.8890, 0.4986% and 0.4514%, respectively. The results showed that the model for moisture content determination has a wide range, good linearity, accuracy and precision. The developed approach was demonstrated to be a potential for monitoring the moisture content of FVIII in freeze-drying process. © 2015 The Author(s).


Wang P.,Shandong University | Wang P.,Shenyang Pharmaceutical University | Zhang H.,Beijing Kaiyuan Shengshi Science and Technology Development Co. | Yang H.,Shandong University | And 2 more authors.
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2014

Near-infrared (NIR) spectroscopy has been developed into an indispensable tool for both academic research and industrial quality control in a wide field of applications. The feasibility of NIR spectroscopy to monitor the concentration of puerarin, daidzin, daidzein and total isoflavonoid (TIF) during the extraction process of kudzu (Pueraria lobata) was verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and derivative. Partial least square regression (PLSR) was used to establish calibration models. Three different variable selection methods, including correlation coefficient method, interval partial least squares (iPLS), and successive projections algorithm (SPA) were performed and compared with models based on all of the variables. The results showed that the approach was very efficient and environmentally friendly for rapid determination of the four quality indices (QIs) in the kudzu extraction process. This method established may have the potential to be used as a process analytical technological (PAT) tool in the future. ©2014 Elsevier Ltd. All rights reserved.


PubMed | Beijing Kaiyuan Shengshi Science and Technology Development Co., Shenyang Pharmaceutical University and Shandong University
Type: | Journal: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy | Year: 2014

Near-infrared (NIR) spectroscopy has been developed into an indispensable tool for both academic research and industrial quality control in a wide field of applications. The feasibility of NIR spectroscopy to monitor the concentration of puerarin, daidzin, daidzein and total isoflavonoid (TIF) during the extraction process of kudzu (Pueraria lobata) was verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and derivative. Partial least square regression (PLSR) was used to establish calibration models. Three different variable selection methods, including correlation coefficient method, interval partial least squares (iPLS), and successive projections algorithm (SPA) were performed and compared with models based on all of the variables. The results showed that the approach was very efficient and environmentally friendly for rapid determination of the four quality indices (QIs) in the kudzu extraction process. This method established may have the potential to be used as a process analytical technological (PAT) tool in the future.

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