Rapid Determination of the Moisture Content of the Original Medicinal Materials of Lanqin Oral Solution by Near-infrared Spectroscopy Coupled with Chemometric Algorithms

OBJECTIVE To establish a rapid quantification method of moisture contents in the raw materials of Lanqin oral solution, Isatidis Radix, Gardeniae Fructus, Phellodendri Chinensis Cortex, Scutellariae Radix and Sterculiae Lychnophorae Semen by near-infrared spectroscopy(NIRs), and the feasibility of an universal moisture content model was investigated. METHODS Preprocessing methods were applied to optimize the model, and competitive adaptive reweighted sampling (CARS) was chosen for key variable screening. Exclusive and universal partial least square regression(PLSR) models for five medicinal materials were constructed. RESULTS The Rc values of CARS-PLS models were higher than 0.96, and the RSEP values were lower than 5%. Compared with the exclusive model, the prediction accuracy of the universal model was slightly lower, but it still met the application requirements. In addition, the predictive ability of the model was verified by paired t-test, and there was no significant difference between the predicted values and the reference values. CONCLUSION The overall results showed that the combination of NIRs and chemometrics to establish an universal model was a reliable method, which can be applied for rapid detection of the moisture content of the five medicinal materials of Lanqin oral solution. For moisture content detection, the universal model of medicinal materials is simpler than the exclusive model, and it is more in line with high-efficiency production requirements.