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Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model
As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038490/ https://www.ncbi.nlm.nih.gov/pubmed/32012652 http://dx.doi.org/10.3390/s20030686 |
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author | Liu, Jingjing Zuo, Mingxu Low, Sze Shin Xu, Ning Chen, Zhiqing Lv, Chuang Cui, Ying Shi, Yan Men, Hong |
author_facet | Liu, Jingjing Zuo, Mingxu Low, Sze Shin Xu, Ning Chen, Zhiqing Lv, Chuang Cui, Ying Shi, Yan Men, Hong |
author_sort | Liu, Jingjing |
collection | PubMed |
description | As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human’s descriptive language, making food detection technology a step closer to human perception. |
format | Online Article Text |
id | pubmed-7038490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70384902020-03-09 Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model Liu, Jingjing Zuo, Mingxu Low, Sze Shin Xu, Ning Chen, Zhiqing Lv, Chuang Cui, Ying Shi, Yan Men, Hong Sensors (Basel) Article As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human’s descriptive language, making food detection technology a step closer to human perception. MDPI 2020-01-27 /pmc/articles/PMC7038490/ /pubmed/32012652 http://dx.doi.org/10.3390/s20030686 Text en © 2020 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 Liu, Jingjing Zuo, Mingxu Low, Sze Shin Xu, Ning Chen, Zhiqing Lv, Chuang Cui, Ying Shi, Yan Men, Hong Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model |
title | Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model |
title_full | Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model |
title_fullStr | Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model |
title_full_unstemmed | Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model |
title_short | Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model |
title_sort | fuzzy evaluation output of taste information for liquor using electronic tongue based on cloud model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038490/ https://www.ncbi.nlm.nih.gov/pubmed/32012652 http://dx.doi.org/10.3390/s20030686 |
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