A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment
Electronic nose (E-nose) and electronic tongue (E-tongue) can mimic the sensory perception of human smell and taste, and they are widely applied in tea quality evaluation by utilizing the fingerprints of response signals representing the overall information of tea samples. The intrinsic part of huma...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469530/ https://www.ncbi.nlm.nih.gov/pubmed/28467364 http://dx.doi.org/10.3390/s17051007 |
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author | Zhi, Ruicong Zhao, Lei Zhang, Dezheng |
author_facet | Zhi, Ruicong Zhao, Lei Zhang, Dezheng |
author_sort | Zhi, Ruicong |
collection | PubMed |
description | Electronic nose (E-nose) and electronic tongue (E-tongue) can mimic the sensory perception of human smell and taste, and they are widely applied in tea quality evaluation by utilizing the fingerprints of response signals representing the overall information of tea samples. The intrinsic part of human perception is the fusion of sensors, as more information is provided comparing to the information from a single sensory organ. In this study, a framework for a multi-level fusion strategy of electronic nose and electronic tongue was proposed to enhance the tea quality prediction accuracies, by simultaneously modeling feature fusion and decision fusion. The procedure included feature-level fusion (fuse the time-domain based feature and frequency-domain based feature) and decision-level fusion (D-S evidence to combine the classification results from multiple classifiers). The experiments were conducted on tea samples collected from various tea providers with four grades. The large quantity made the quality assessment task very difficult, and the experimental results showed much better classification ability for the multi-level fusion system. The proposed algorithm could better represent the overall characteristics of tea samples for both odor and taste. |
format | Online Article Text |
id | pubmed-5469530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54695302017-06-16 A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment Zhi, Ruicong Zhao, Lei Zhang, Dezheng Sensors (Basel) Article Electronic nose (E-nose) and electronic tongue (E-tongue) can mimic the sensory perception of human smell and taste, and they are widely applied in tea quality evaluation by utilizing the fingerprints of response signals representing the overall information of tea samples. The intrinsic part of human perception is the fusion of sensors, as more information is provided comparing to the information from a single sensory organ. In this study, a framework for a multi-level fusion strategy of electronic nose and electronic tongue was proposed to enhance the tea quality prediction accuracies, by simultaneously modeling feature fusion and decision fusion. The procedure included feature-level fusion (fuse the time-domain based feature and frequency-domain based feature) and decision-level fusion (D-S evidence to combine the classification results from multiple classifiers). The experiments were conducted on tea samples collected from various tea providers with four grades. The large quantity made the quality assessment task very difficult, and the experimental results showed much better classification ability for the multi-level fusion system. The proposed algorithm could better represent the overall characteristics of tea samples for both odor and taste. MDPI 2017-05-03 /pmc/articles/PMC5469530/ /pubmed/28467364 http://dx.doi.org/10.3390/s17051007 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhi, Ruicong Zhao, Lei Zhang, Dezheng A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment |
title | A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment |
title_full | A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment |
title_fullStr | A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment |
title_full_unstemmed | A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment |
title_short | A Framework for the Multi-Level Fusion of Electronic Nose and Electronic Tongue for Tea Quality Assessment |
title_sort | framework for the multi-level fusion of electronic nose and electronic tongue for tea quality assessment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469530/ https://www.ncbi.nlm.nih.gov/pubmed/28467364 http://dx.doi.org/10.3390/s17051007 |
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