[Raman spectroscopy fluorescence background correction and its application in clustering analysis of medicines]

During Raman spectroscopy analysis, the organic molecules and contaminations will obscure or swamp Raman signals. The present study starts from Raman spectra of prednisone acetate tablets and glibenclamide tables, which are acquired from the BWTek i-Raman spectrometer. The background is corrected by R package baselineWavelet. Then principle component analysis and random forests are used to perform clustering analysis. Through analyzing the Raman spectra of two medicines, the accurate and validity of this background-correction algorithm is checked and the influences of fluorescence background on Raman spectra clustering analysis is discussed. Thus, it is concluded that it is important to correct fluorescence background for further analysis, and an effective background correction solution is provided for clustering or other analysis.