光谱学与光谱分析 |
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Quantitative Models for Baicalin Content Using NIR Technology for the Study of Shang Jie Plaster |
JIANG Bo-hai, WANG Qing, WANG Shi-sheng, CAI Rui, ZHAO Wei-jie* |
School of Pharmaceutical Science and Technology,Dalian State Key Laboratory of Fine Chemical Engineering,Dalian University of Technology,Dalian 116023,China |
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Abstract A dynamic prediction model for the content of Baicalin in Shang Jie plasters extract solutions was developed using near-infrared spectroscopy in transmission mode. Sixty five spectra were obtained through near-infrared transmission mode during extracting process. Refering to the content of Baicalin performed by reversed-phase high performance liquid chromatography (HPLC), the calibration model was developed with the application of partial least squares regression algorithm (PLSR). The constructed model was validated by 30 samples; some parameters of the calibration model were optimized by cross-validation. The root mean square error (RMSECV) of Baicalin was 0.006 8 mg·g-1, the correlation coefficient (R) was 0.9991, and the optimal dimension factor was 8; After predicted by test set, the root mean square error (RMSEP) and correlation coefficient (R) of prediction obtained were 0.009 2 mg·g-1 and 0.998 7 respectively. This work demonstrated that NIR spectroscopy combined with PLS could be used for the determination of Baicalin in Shang Jie plasters extract.
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Received: 2012-03-30
Accepted: 2012-05-20
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Corresponding Authors:
ZHAO Wei-jie
E-mail: jbhjby198571@163.com
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