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.
Dominance
Hedonic
Masking
Odor interaction
Partial addition
Synergy
Journal
Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995
Informations de publication
Date de publication:
Jun 2021
Jun 2021
Historique:
received:
08
03
2021
revised:
06
05
2021
accepted:
07
05
2021
entrez:
27
5
2021
pubmed:
28
5
2021
medline:
28
5
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 34041322
doi: 10.1016/j.dib.2021.107143
pii: S2352-3409(21)00427-3
pmc: PMC8144660
doi:
Types de publication
Journal Article
Langues
eng
Pagination
107143Informations de copyright
© 2021 The Author(s). Published by Elsevier Inc.
Déclaration de conflit d'intérêts
The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article.
Références
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