Application of Grey-correlated Spectral Region Selection in Analysis of Near-infrared Spectra  

作　　者：ZHANG Yong XIE Yun-fei ZHAO Bing 

机构地区：[1]Guanghua College of Changchun University, Changchun 130117, P. R. China [2]State Key Laboratory for Supramolecular Structure and Material, College of Chemistry, Jilin University, Changchun 130012, P. R. China

出　　处：《Chemical Research in Chinese Universities》2011年第6期924-928,共5页高等学校化学研究（英文版）

基　　金：Supported by the Key Projects in the National Science&Technology Pillar Program,China(No.2007BAI38B03);the Development Program of the Science and Technology of Jilin Province,China(Nos.200705C07,20075020);the 11th Five-Year Key Project of Jilin Province Education Department,China(No.[2010]205)

摘　　要：The optimal selection method of spectral region based on the grey correlation analysis was applied in the analysis of near-infrared（NIR） spectra. In order to compute ＂characteristic＂ spectral region, 160 samples of tobacco were surveyed by NIR. Next, the whole spectral region was randomly divided into six regions, and the values of association coefficients and correlation orders of different regions were computed for total sugar, reducing sugar and nicotine. Moreover, two regions that owned the largest value of association coefficient were regarded as ＂characteristic＂ spectral region of a model. Finally, the quantitative analysis models of different components were established via the partial least squares method, and the common selection methods of spectral region were compared. The simulation results indicate that the models to choose the spectral region based on grey correlation analysis are more effective than the common selection methods of spectral region, the optimized time of algorithm is shorter, the prediction precision of the models is higher and generalization ability for quantitative analysis results is stronger. This research can provide the support for the quantitative analysis models of NIR spectra and new idea for commercial analysis software of NIR. So, it has a high application value in the analysis of NIR spectra.The optimal selection method of spectral region based on the grey correlation analysis was applied in the analysis of near-infrared（NIR） spectra. In order to compute ＂characteristic＂ spectral region, 160 samples of tobacco were surveyed by NIR. Next, the whole spectral region was randomly divided into six regions, and the values of association coefficients and correlation orders of different regions were computed for total sugar, reducing sugar and nicotine. Moreover, two regions that owned the largest value of association coefficient were regarded as ＂characteristic＂ spectral region of a model. Finally, the quantitative analysis models of different components were established via the partial least squares method, and the common selection methods of spectral region were compared. The simulation results indicate that the models to choose the spectral region based on grey correlation analysis are more effective than the common selection methods of spectral region, the optimized time of algorithm is shorter, the prediction precision of the models is higher and generalization ability for quantitative analysis results is stronger. This research can provide the support for the quantitative analysis models of NIR spectra and new idea for commercial analysis software of NIR. So, it has a high application value in the analysis of NIR spectra.

关 键 词：Near-infrared spectroscopy Grey correlation analysis Correlation degree Partial least square 

分 类 号：O657.33[理学—分析化学] N94[理学—化学]