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A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology

文献类型：期刊论文

作者Feng, Chun1,2; Zhao, Nanjing1,3; Yin, Gaofang1,3; Gan, Tingting1,3; Yang, Ruifang1,3; Chen, Min1,2; Duan, Jingbo1,3; Hu, Yuxia4
刊名SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
出版日期2022-04-05
卷号270
ISSN号1386-1425
关键词Spectral separation Bacteria Monte carlo Principal component analysis Backpropagation neural networks Multi-wavelength transmission spectrum
DOI10.1016/j.saa.2021.120852
通讯作者Zhao, Nanjing(njzhao@aiofm.ac.cn) ; Yin, Gaofang(gfyin@aiofm.ac.cn)
英文摘要Previously, we successfully realized the identification of a single species of bacteria based on the multi-wavelength transmission spectrum of bacteria. The current research is focused on realizing the spectral analysis of mixed bacteria. Principal component analysis-Monte Carlo (PCA-MC) model was developed for the implementation of spectral separation of mixed bacteria by obtaining the ratio of components. And, the separated spectrum was regarded as the model input of the neural network concentration inversion model to obtain the concentration of each bacteria in the mix. Mean relative errors in component analysis of mixing S.aureus with K.pneumoniae, mixing S.aureus with S.typhimurium twice, mixing K.pneumoniae with S.typhimurium are 3%, 2%, 3.9% and 6.1%, respectively. The coefficient of determination (R-2) of validation set and test set are 0.9947 and 0.9954 in concentration inversion model. The results show that this method can quickly and accurately determine the component ratio and concentration information in the mixed bacteria. A new method was proposed to separate the spectrum of mixed bacteria effectively and measure its concentration quickly, which makes a big step forward in the detection and online monitoring of waterborne microbial contamination based on multi-wavelength transmission spectroscopy. (C) 2022 Elsevier B.V. All rights reserved.
WOS关键词NEURAL-NETWORK ; CLASSIFICATION ; MODEL
资助项目National Natural Science Foundation of China[61875254] ; National Natural Science Foundation of China[61705237] ; National Natural Science Foundation of China[61805254] ; National Natural Science Foundation of China[62105002] ; Major science and technology project of Anhui Province[202003a07020007] ; Educational Commission of AnHui Province of China[KJ2020A0471]
WOS研究方向Spectroscopy
语种英语
出版者PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号WOS:000751750600002
资助机构National Natural Science Foundation of China ; Major science and technology project of Anhui Province ; Educational Commission of AnHui Province of China
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/127542]  
专题中国科学院合肥物质科学研究院
通讯作者Zhao, Nanjing; Yin, Gaofang
作者单位1.Chinese Acad Sci, Anhui Inst Opt & Fine, Mech, Key Lab Environm Opt & Technol, Hefei 230026, Peoples R China
2.Univ Sci & Technol China, Hefei 230026, Peoples R China
3.Key Lab Opt Monitoring Technol Environm, Hefei 230031, Anhui, Peoples R China
4.Anhui Jianzhu Univ, Hefei 230031, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Feng, Chun,Zhao, Nanjing,Yin, Gaofang,et al. A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology[J]. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,2022,270.
APA Feng, Chun.,Zhao, Nanjing.,Yin, Gaofang.,Gan, Tingting.,Yang, Ruifang.,...&Hu, Yuxia.(2022).A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology.SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,270.
MLA Feng, Chun,et al."A new method for detecting mixed bacteria based on multi-wavelength transmission spectroscopy technology".SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 270(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

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