Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks

doi:10.1016/j.biosystemseng.2020.10.005

	Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks
	Chang, Fangle 2,3; Heinemann, Paul H.1
刊名	BIOSYSTEMS ENGINEERING
	2020-12-01
卷号	200 页码:272-283
关键词	Hedonic tone Electronic nose zNose (TM) Artificial Neural Networks Multi-sensor data fusion
ISSN号	1537-5110
DOI	10.1016/j.biosystemseng.2020.10.005
通讯作者	Chang, Fangle(changfl415@gmail.com)
英文摘要	A Cyranose 320 (eNose) and a Fast Gas Chromatograph (CG) analyser (zNoseTM) were used to measure the headspace odour of solid samples from dairy operations. The measurements of both sensors were trained by Levenberg-Marquardt Back-propagation Neural Network (LMBNN) to match human assessments. A trained human panel was used to assess the odours based on hedonic tone method and provide the model targets. A multi-sensor data fusion approach was developed and applied to integrate the eNose and zNose readings for higher predictive accuracy compared to each sensor alone. Principle Component Analysis, Forward Selection, and Gamma Test were applied to reduce the model input dimensions. Measurement fusion models and information fusion model approaches were applied. The information fusion prediction models were shown to be more accurate than all other models, including single instrument models. The information fusion model based on eNose with Gamma Test data reduction thorn zNose showed the best results of all cases in validation mean square error (0.34 odour units), R value (0.92), probability of the prediction falling within 10% of the target (96%), and probability of the prediction falling within 5% of the target (63%). (C) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.
资助项目	USDA National Institute of Food and Agriculture Federal Appropriations[PEN04547] ; USDA National Institute of Food and Agriculture Federal Appropriations[1001036]
WOS研究方向	Agriculture
语种	英语
出版者	ACADEMIC PRESS INC ELSEVIER SCIENCE
WOS记录号	WOS:000598489200006
资助机构	USDA National Institute of Food and Agriculture Federal Appropriations
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42820]
专题	自动化研究所_博士后
通讯作者	Chang, Fangle
作者单位	1.Penn State Univ, Dept Agr & Biol Engn, 105 Agr Engn Bldg, University Pk, PA 16802 USA 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Zhejiang Univ, Ningbo Res Inst, Ningbo 315000, Peoples R China
推荐引用方式 GB/T 7714	Chang, Fangle,Heinemann, Paul H.. Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks[J]. BIOSYSTEMS ENGINEERING,2020,200:272-283.
APA	Chang, Fangle,&Heinemann, Paul H..(2020).Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks.BIOSYSTEMS ENGINEERING,200,272-283.
MLA	Chang, Fangle,et al."Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks".BIOSYSTEMS ENGINEERING 200(2020):272-283.