基于近红外光谱技术的黄柏药材定量分析

目的:建立一种能够同时快速测定黄柏药材中小檗碱和黄柏碱含量的方法。方法:以HPLC所测样品中小檗碱和黄柏碱的含量为参考值,利用近红外光谱分析技术,将参考值与样品的近红外光谱进行关联,采用偏最小二乘法(PLS)建立黄柏中小檗碱和黄柏碱的定量分析模型。结果:所建立的小檗碱和黄柏碱的定量分析模型的内部交叉验证决定系数(R2)分别为0.997 13,0.989 23,校正均方差(RMSEC)分别为0.082 3,0.021 5,验证均方差(RMSEP)分别为0.071 7,0.016 6,性能指数PI分别为95.6,93.5。结论:利用近红外光谱技术建立的定量分析模型,能够对黄柏药材中小檗碱和黄柏碱的含量进行无损快速测定。

Quantitative Analysis of Phellodendron Bark Based on Near Infrared Spectroscopy

Objective: To establish a method for simultaneous rapid determination of berberine content and phellodendrine content in Phellodendron Bark. Method: With the berberine content and phellodendrine content determined in high performance liquid chromatography (HPLC) as the reference values, near infrared spectra of the samples were associated with the reference values above, and then the quantitative analysis models of berberine and phellodendrine were established by using partial least squares (PLS) method. Result: The correlation coefficient (R²) was 0.99713 and 0.98923 respectively for quantitative analysis model of berberine and phellodendrine. The root mean square error of calibration (RMSEC) was 0.0823 and 0.0215 respectively. The root mean square error of predication (RMSEP) was 0.0717 and 0.0166 respectively. The performance index (PI) was 95.6 and 93.5 respectively. Conclusion: The quantitative analysis model established by using near-infrared spectroscopy is rapid and nondestructive to determine the content of berberine and phellodendrine in Phellodendron Bark.