Spectroscopy and Spectral Analysis, Volume. 33, Issue 1, 74(2013)
Quantitative Models for Baicalin Content Using NIR Technology for the Study of Shang Jie Plaster
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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JIANG Bo-hai, WANG Qing, WANG Shi-sheng, CAI Rui, ZHAO Wei-jie. Quantitative Models for Baicalin Content Using NIR Technology for the Study of Shang Jie Plaster[J]. Spectroscopy and Spectral Analysis, 2013, 33(1): 74
Received: Mar. 30, 2012
Accepted: --
Published Online: Feb. 4, 2013
The Author Email: Bo-hai JIANG (jbhjby198571@163.com)