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A novel infrared spectral preprocessing method based on self-deconvolution and differentiation in the frequency domain

文献类型：期刊论文

作者Shan, Peng3,5; Liu, Junyi4,5; He, Zhonghai3,5; Peng, Silong2; Wang, Fei1; Liu, Chengzhao5; Zhou, Zheng5
刊名VIBRATIONAL SPECTROSCOPY
出版日期2023-07-01
卷号127页码:11
ISSN号0924-2031
关键词Spectral preprocessing Quantitative analysis Fourier transform Infrared spectroscopy
DOI10.1016/j.vibspec.2023.103562
通讯作者Liu, Junyi(3101668490@qq.com)
英文摘要Spectral preprocessing is a crucial step before establishing a multivariate calibration model for Fourier transform infrared (FTIR) spectroscopic analysis. However, a single preprocessing method has limited effects, such as insufficient noise reduction or limited resolution improvement. As two classical preprocessing methods, Fourier self-deconvolution (FSD) and Fourier filtering and differentiation (FFD) have their benefits and drawbacks. FSD has low noise but limited resolution, while FFD could improve resolution and eliminate baseline simultaneously, but is susceptive to noise. By combining FSD and FFD, we design a novelty resolution enhancement method, termed Fourier self-deconvolution differentiation (FSDD), which can significantly improve spectral resolution with good noise and baseline robustness. Partial least squares regression (PLS) is combined with five preprocessing methods, FSD, FFD, direct derivation (DD), Savitsky-Golay smoothing and derivation (SGSD), and FSDD, to analyze the albiflorin dataset and the & gamma;-polyglutamic acid (& gamma;-PGA) fermentation dataset. Compared with other preprocessing methods, FSDD obtained the optimum performance merits, including root mean squared error of prediction (RMSEP), determination coefficient (R2), and Mean Absolute Error (MAE).
WOS关键词SPECTROSCOPY ; REGRESSION
资助项目National Natural Science Foundation of China[61601104] ; Natural Science Foun-dation of Hebei Province[F2017501052] ; Fundamental Research Funds for the Central Universities[N2023021] ; Science and Technology Project of General Administration of Cus-toms[2020HK215]
WOS研究方向Chemistry ; Spectroscopy
语种英语
出版者ELSEVIER
WOS记录号WOS:001050778100001
资助机构National Natural Science Foundation of China ; Natural Science Foun-dation of Hebei Province ; Fundamental Research Funds for the Central Universities ; Science and Technology Project of General Administration of Cus-toms
源URL[http://ir.ia.ac.cn/handle/173211/54050]  
专题自动化研究所_智能制造技术与系统研究中心_多维数据分析团队
通讯作者Liu, Junyi
作者单位1.Technol Ctr Qinhuangdao Customs, Qinhuangdao 066004, Hebei, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Hebei Key Lab Micronano Precis Opt Sensing & Measu, Qinhuangdao 066004, Hebei, Peoples R China
4.143 Tai Shan Rd, Qin Huang Dao 066004, Peoples R China
5.Northeastern Univ, Coll Informat Sci & Engn, Shenya 110819, Liaoning, Peoples R China
推荐引用方式
GB/T 7714		 Shan, Peng,Liu, Junyi,He, Zhonghai,et al. A novel infrared spectral preprocessing method based on self-deconvolution and differentiation in the frequency domain[J]. VIBRATIONAL SPECTROSCOPY,2023,127:11.
APA Shan, Peng.,Liu, Junyi.,He, Zhonghai.,Peng, Silong.,Wang, Fei.,...&Zhou, Zheng.(2023).A novel infrared spectral preprocessing method based on self-deconvolution and differentiation in the frequency domain.VIBRATIONAL SPECTROSCOPY,127,11.
MLA Shan, Peng,et al."A novel infrared spectral preprocessing method based on self-deconvolution and differentiation in the frequency domain".VIBRATIONAL SPECTROSCOPY 127(2023):11.

入库方式： OAI收割

来源：自动化研究所

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