复方苦参注射液渗漉过程的近红外光谱在线检测方法

 目的 以复方苦参注射液的渗漉过程为研究对象，利用近红外光谱分析技术，建立一种可用于复方苦参注射液渗漉过程在线检测的方法。方法 利用流通池和远程光纤连接渗漉设备和近红外光谱仪，在线采集渗漉液的近红外光谱，以总生物碱含量的HPLC测定值及固体总量测定值为对照值，用偏最小二乘法（PLS）建立近红外光谱与对照值之间的校正模型，并对渗漉过程的未知样品进行含量预测。结果 建立的定量模型准确性较高，总生物碱与固体总量校正模型的相关系数分别为0.997 9和0.996 0，校正均方根误差 (RMSEC) 分别为0.072 1 g·L^-1和0.081 1%。经外部验证，预测值与测定值之间的相关系数分别为0.991 5和0.999 0，预测均方根误差 (RMSEP) 分别为0.195 0 g·L^-1和0.068 1%。结论 本方法方便快速、准确可靠，可用于复方苦参注射液渗漉过程的在线检测。

An on-Line Near-Infrared Spectroscopy Approach for Content Determination in the Percolation Process of Compound Kushen Injection

OBJECTIVE To develop an on-line analysis method based on near infrared spectroscopy (NIRS) for monitoring the percolation process of compound Kushen injection traditional Chinese medicines. METHODS Samples and correlative spectra were collected with online equipment in percolation process. The contents of total alkaloids and total solids measured with standard methods were used as reference values. Multivariate calibration models based on partial least squares (PLS) algorithm were developed to correlate the spectra and the reference values. RESULTS The correlation coefficients of the calibration models for total alkaloids and total solids were 0.997 9 and 0.996 0 with root mean square errors (RMSECs) of 0.072 1 g·L^-1 and 0.081 1%， respectively. External validation samples collected on-line were used to evaluate the quantitative models. The correlation coefficients between the predicted value and the reference value were 0.991 5 and 0.999 0 with root mean square errors of prediction (RMSEPs) of 0.195 0 g·L^-1 and 0.068 1%， respectively. CONCLUSION The presented method is rapid， accurate and reliable， which can be used for monitoring the percolation process of compound Kushen injection.