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A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors
This paper describes data collected on a set of 222 binary mixtures, based on a set of 72 odorants chiefly found in food, rated by 30 selected and trained assessors for odor intensity and pleasantness. The data included odor intensity (IAB) and pleasantness (PAB) of the mixtures, the intensity (IA,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144660/ https://www.ncbi.nlm.nih.gov/pubmed/34041322 http://dx.doi.org/10.1016/j.dib.2021.107143 |
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author | Ma, Yue Tang, Ke Xu, Yan Thomas-Danguin, Thierry |
author_facet | Ma, Yue Tang, Ke Xu, Yan Thomas-Danguin, Thierry |
author_sort | Ma, Yue |
collection | PubMed |
description | This paper describes data collected on a set of 222 binary mixtures, based on a set of 72 odorants chiefly found in food, rated by 30 selected and trained assessors for odor intensity and pleasantness. The data included odor intensity (IAB) and pleasantness (PAB) of the mixtures, the intensity (IA, IB) and the pleasantness (PA, PB) of the two components. Moreover, the intensity (IAmix, IBmix) of the two components’ odor perceived within the mixture are included. The quality of the dataset was evaluated by checking subjects’ performance and by testing repeatability using the 24 duplicated trials for each attribute. This set of experimental data would be especially valuable to investigate theories of odor mixture perception in human and to test new models to predict odor perception of odor mixtures. |
format | Online Article Text |
id | pubmed-8144660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-81446602021-05-25 A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors Ma, Yue Tang, Ke Xu, Yan Thomas-Danguin, Thierry Data Brief Data Article This paper describes data collected on a set of 222 binary mixtures, based on a set of 72 odorants chiefly found in food, rated by 30 selected and trained assessors for odor intensity and pleasantness. The data included odor intensity (IAB) and pleasantness (PAB) of the mixtures, the intensity (IA, IB) and the pleasantness (PA, PB) of the two components. Moreover, the intensity (IAmix, IBmix) of the two components’ odor perceived within the mixture are included. The quality of the dataset was evaluated by checking subjects’ performance and by testing repeatability using the 24 duplicated trials for each attribute. This set of experimental data would be especially valuable to investigate theories of odor mixture perception in human and to test new models to predict odor perception of odor mixtures. Elsevier 2021-05-15 /pmc/articles/PMC8144660/ /pubmed/34041322 http://dx.doi.org/10.1016/j.dib.2021.107143 Text en © 2021 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Ma, Yue Tang, Ke Xu, Yan Thomas-Danguin, Thierry A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
title | A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
title_full | A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
title_fullStr | A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
title_full_unstemmed | A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
title_short | A dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
title_sort | dataset on odor intensity and odor pleasantness of 222 binary mixtures of 72 key food odorants rated by a sensory panel of 30 trained assessors |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144660/ https://www.ncbi.nlm.nih.gov/pubmed/34041322 http://dx.doi.org/10.1016/j.dib.2021.107143 |
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