Odor descriptive ratings can predict some odor-color associations in different color features of hue or lightness

Author:

Tamura Kaori1,Okamoto Tsuyoshi2

Affiliation:

1. Department of Information and Systems Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

2. Faculty of Arts and Science, Kyushu University, Fukuoka, Japan

Abstract

Background Olfactory information can be associated with color information. Researchers have investigated the role of descriptive ratings of odors on odor-color associations. Research into these associations should also focus on the differences in odor types. We aimed to identify the odor descriptive ratings that can predict odor-color corresponding formation, and predict features of the associated colors from the ratings taking into consideration the differences in the odor types. Methods We assessed 13 types of odors and their associated colors in participants with a Japanese cultural background. The associated colors from odors in the CIE L*a*b* space were subjectively evaluated to prevent the priming effect from selecting color patches. We analyzed the data using Bayesian multilevel modeling, which included the random effects of each odor, for investigating the effect of descriptive ratings on associated colors. We investigated the effects of five descriptive ratings, namely Edibility, Arousal, Familiarity, Pleasantness, and Strength on the associated colors. Results The Bayesian multilevel model indicated that the odor description of Edibility was related to the reddish hues of associated colors in three odors. Edibility was related to the yellow hues of colors in the remaining five odors. The Arousal description was related to the yellowish hues in two odors. The Strength of the tested odors was generally related to the color lightness. The present analysis could contribute in investigating the influence of the olfactory descriptive rating that anticipates the associated color for each odor.

Funder

2019 QR Program

Wakaba 405 Challenge

2022 Research Support Program for Young Scientists in Fukuoka Institute of Technology

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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