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Identification of soy sauce using high-field asymmetric waveform ion mobility spectrometry combined with machine learning

文献类型：期刊论文

作者Jin, Jiao1,3; Liu, Youjiang1; Li, Shan1,3; Hu, Jun1,3; Liu, Shaomin1,2; Chen, Chilai1
刊名SENSORS AND ACTUATORS B-CHEMICAL
出版日期2022-08-15
卷号365
关键词Soy sauce FAIMS Volatile organic compounds Classification Machine learning
DOI10.1016/j.snb.2022.131966
通讯作者Chen, Chilai(chlchen@iim.ac.cn)
英文摘要Soy sauce, an important condiment, varies greatly in the brand, geographical distribution, and production processes. We investigated the potential of volatile organic compounds (VOCs) serving as an indicator of soy sauce quality to detect three regions and two production technologies of Chinese soy sauce. An analytical method named high-field asymmetric waveform ion mobility spectrometry (FAIMS) was utilized for acquiring sample data. Wavelet packet decomposition (WPD) and principal component analysis (PCA) were used to extract the features of FAIMS data. 4 machine learning models were trained using these features, and the optimal parameters were obtained by a grid search. The scatter plots of the optimal two features we selected showed that the different regions and production technologies of soy sauce had obvious clustering trends. For the identification of different regions and production technologies, the training score, test score, and average cross-validation score of the optimal model were all 100%. Furthermore, the learning curves indicated that the optimal model obtained good performance and had low prediction errors. It was concluded that FAIMS combined with a suitable machine learning algorithm can successfully classify different regions and production technologies of Chinese soy sauce.
WOS关键词VOLATILE COMPOUNDS ; GEOGRAPHIC REGION ; UV-FAIMS ; CLASSIFICATION ; FERMENTATION
资助项目National Natural Science Foundation of China[61871367] ; Youth Innovation Promotion Association of the Chinese Academy of Sciences[2013213] ; National Natural Science Foundation for Young Scientists of China[41805017]
WOS研究方向Chemistry ; Electrochemistry ; Instruments & Instrumentation
语种英语
出版者ELSEVIER SCIENCE SA
WOS记录号WOS:000798279900002
资助机构National Natural Science Foundation of China ; Youth Innovation Promotion Association of the Chinese Academy of Sciences ; National Natural Science Foundation for Young Scientists of China
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/131077]  
专题中国科学院合肥物质科学研究院
通讯作者Chen, Chilai
作者单位1.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
2.Guangxi Univ, Sch Elect Engn, Guangxi Key Lab Intelligent Control & Maintenance, Nanning 530004, Peoples R China
3.Univ Sci & Technol China, Hefei 230026, Peoples R China
推荐引用方式
GB/T 7714		 Jin, Jiao,Liu, Youjiang,Li, Shan,et al. Identification of soy sauce using high-field asymmetric waveform ion mobility spectrometry combined with machine learning[J]. SENSORS AND ACTUATORS B-CHEMICAL,2022,365.
APA Jin, Jiao,Liu, Youjiang,Li, Shan,Hu, Jun,Liu, Shaomin,&Chen, Chilai.(2022).Identification of soy sauce using high-field asymmetric waveform ion mobility spectrometry combined with machine learning.SENSORS AND ACTUATORS B-CHEMICAL,365.
MLA Jin, Jiao,et al."Identification of soy sauce using high-field asymmetric waveform ion mobility spectrometry combined with machine learning".SENSORS AND ACTUATORS B-CHEMICAL 365(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

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