胃苏颗粒浓缩过程近红外快速定量检测方法的建立

Rapid Detection Method Based on Near-infrared Spectroscopy for the Quantification Determination During the Concentration Process of Weisu Granules

目的:建立胃苏颗粒浓缩过程主要药效成分及密度的定量矫正模型,实现生产过程在线监控。方法:采用近红外光谱技术(NIRS)结合偏最小二乘法(PLS)分别建立柚皮苷、橙皮苷、新橙皮苷和密度的定量矫正模型。结果:柚皮苷、橙皮苷、新橙皮苷和密度定量矫正模型的相关系数(R)分别为0.998 6,0.996 6,0.999 0,0.999 6;矫正集误差均方根(RMSEC)分别为0.032,0.010 6,0.008 5,0.002 5;交叉验证集误差均方根(RMSECV)分别为0.047 5,0.011 3,0.023 7,0.002 8;测试集预测误差均方根(RMSEP)依次为0.031,0.005 8,0.013 4,0.001 5。结论:所建的模型可以用于胃苏颗粒浓缩过程中柚皮苷、橙皮苷、新橙皮苷和密度的在线定量测定。

Objective: To establish the quantified calibration models for the main effective components and their densities during the concentration process of Weisu granules to realize the on-line monitoring of production process. Methods: Based on the near infrared reflectance spectroscopy( NIRS),partial least squares( PLS) regression models were developed to rapidly detect the contents of naringin,hesperidin and neohesperidin,and their densities as well. Results: In the quantitative models of naringin,hesperidin and neohesperidin and their densities,the correlation coefficients( R) of determination were 0.998 6,0.996 6,0.999 0 and0.999 6;the root mean square errors of calibration( RMSEC) were 0.032,0.010 6,0.008 5 and 0.002 5,respectively;the root mean square errors of cross-validation( RMSECV) were 0.047 5,0.011 3,0.023 7 and 0.002 8,respectively;the root mean square errors of prediction( RMSEP) were 0.031,0.005 8,0.013 4 and 0.001 5,respectively. Conclusion: The above models can be used to rapidly detect the contents of naringin,hesperidin and neohesperidin and their densities during the concentration process of Weisu granules.