A new non-destructive and rapid method was developed to discriminate the coating process of Rukuaixiao tablets mainly based the support vector machine (SVM) with the near-infrared spectroscopy (NIRs). After the samples that differ in the sugar-coat were acquired, the sample set partitioning based on joint x-y distance (SPXY) method was used to select the training sets and internal principal component analysis (internal PCA) was to select the optimal wavelength. The discrimination model was developed based on support vector machine (SVM), and varieties of pre-processing methods were compared. The results showed that the accuracy of the prediction set was 98.81%. It is concluded that the accuracy of the method is high to use for the quality evaluation of tablet's coating process.
Algorithms ; Clinical Laboratory Techniques ; standards ; Clinical Protocols ; standards ; Drugs, Chinese Herbal ; analysis ; Medicine, Chinese Traditional ; standards ; Medicine, East Asian Traditional ; methods ; Principal Component Analysis ; Spectrophotometry, Infrared ; methods ; Spectroscopy, Near-Infrared ; methods ; Tablets ; analysis