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  • Title: [Quantitative models for Baicalin content using NIR technology for the study of Shang Jie plaster].
    Author: Jiang BH, Wang Q, Wang SS, Cai R, Zhao WJ.
    Journal: Guang Pu Xue Yu Guang Pu Fen Xi; 2013 Jan; 33(1):74-7. PubMed ID: 23586228.
    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 x 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 x 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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