Raman Spectroscopy Fluorescence Background Correction and Its Application in Clustering Analysis of Medicines
CHEN Shan1, LI Xiao-ning1, LIANG Yi-zeng1*, ZHANG Zhi-min1, LIU Zhao-xia2, ZHANG Qi-ming2, DING Li-xia2, YE Fei3
1. Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, China 2. National Institute for the Control of Pharmaceutical and Biological Products, Beijing 100050, China 3. B &W Tek, Inc. Shanghai 2204-2205 Mingshen Plaza,Shanghai 200233, China
Abstract: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.
[1] TIAN Guo-hui, CHEN Ya-jie, FENG Qing-mao(田国辉, 陈亚杰, 冯清茂). Chemical Engineer(化学工程师), 2008, 22(1): 34. [2] DOU Yan-li, ZHANG Wan-xi, ZHANG Yu-jie, et al(窦艳丽, 张万喜, 张玉杰, 等). Chinese Journal of Analytical Chemistry(分析化学), 2006, 34(11): 1615. [3] SUN Su-qin, ZHOU Qun, ZHANG Xuan, et al(孙素琴, 周 群, 张 宣, 等). Chinese Journal of Analytical Chemistry(分析化学), 2000, 28(2): 211. [4] CHEN Xiu-li, WANG Gui-wen, LIU Jun-xian, et al(陈秀丽, 王桂文, 刘军贤, 等). Journal of Instrumental Analysis(分析测试学报), 2009, 28(4): 403. [5] O’Grady A, Dennis A C, Denvir D, et al. Analytical Chemistry, 2001, 73(9): 2058. [6] Zhang Z M, Chen S, Liang Y Z, et al. Journal of Raman Spectroscopy, 2009, http://doi.wiley.com/10.1002/jrs.2500. [7] Hu Y G, Jiang T, Shen A G, et al. Chemometrics and Intelligent Laboratory Systems, 2007, 85(1): 94. [8] Gan F, Ruan G H, Mo J Y. Chemometrics and Intelligent Laboratory Systems, 2006, 82(1-2): 59. [9] Breiman L. Machine Learning, 2001, 45(1): 5. [10] Breiman L, Friedman J, Olshen R, et al. Classification and Regression Trees, Wadsworth and Brooks, Monterey, CA, 1984. [11] Breiman L. Machine Learning, 1996, 24(2): 123. [12] Efron B. The Annals of Statistics, 1979, 7(1): 1. [13] Efron B, Tibshirani J R. An Introduction to the Bootstrap, London: Chapman & Hall, 1997.