Identifying Baicalin Concentration in Scutellaria Spray Drying Powder With Disturbed Terahertz Spectra Based on Gaussian Mixture Model.

Abstract

Baicalin concentration is concerned in manufacture of scutellaria spray drying powder as a traditional Chinese medicine, and the quality control based on high-performance liquid chromatography is inconvenience. In this study, terahertz time domain spectroscopy was employed to achieve quality control of scutellaria spray drying powder; however, an acute difficulty was found that terahertz spectra overlapped due to the disturbance in both content matrix and measurement error. In this study, similar terahertz spectra of scutellaria spray drying powder were classified with the help of Gaussian mixture model and built a classifier based on probability feature instead of spectral features conventionally employed in previous investigations. To explore the feasibility of GMM, principal component analysis was given, indicating that it is possible to train GMM with original features and proper principal components. Probable advantage of training GMM based on PCA feature was discussed and so it was with the capacity of the model to identify the linear combined spectra by comparing the performance of GMM and a decision tree model. Above all, the reason why GMM shows potential in the analysis of TCM terahertz spectra was illustrated by comparing the thought of discriminative model and generative model. This study implied that generative model may have natural advantage of overcoming the inherent disturbance of terahertz spectroscopy, which would be promising in future studies.