Untargeted identification of adulterated Sanqi powder by near-infrared spectroscopy and one-class model

Sanqi is a widely used traditional Chinese medicines (TCM) for its outstanding efficacy. In Chinese market, Sanqi powder is the goal of counterfeiting for a long time. Investigation of Sanqi authenticity is very important in both economic and public health terms. The present work aims at studying the feasibility of combining near-infrared (NIR) spectroscopy with relief-based variable selection and class-modeling for identifying adulterated Sanqi powder. A total of 209 samples including pure and mixed samples, were prepared. Principal component analysis (PCA) was applied for exploratory analysis. The relief algorithm was used to rank all variables, based on which only the first 100 most informative variables were picked out for subsequent class-modeling. By optimizing the parameters such as the number of components, type I and type II errors, the final one-class models were constructed on the training set and evaluated on the test set. Such a procedure is simple and is more in line with actual need. The performance of the models is acceptable. The results indicate that NIR spectroscopy combined with class-modeling and relief-based variable selection is feasible for identifying the adulteration of Sanqi powder.