Exploring the links between colours and tastes/flavours

Journal article

The colour and other visual appearance properties of food and drink constitute a key factor determining consumer acceptance and choice behaviour. Not only do consumers associate specific colours with particular tastes and flavours, but adding or changing the colour of food and drink can also dramatically affect taste/flavour perception. Surprisingly, even the colour of cups, cutlery, plates, packages, and the colour of the environment itself, have also been shown to influence multisensory flavour perception. The taste/flavour associations that we hold with colour are context-dependent, and are often based on statistical learning (though emotional mediation may also play a role). However, to date, neither the computational principles constraining these ubiquitous crossmodal effects nor the neural mechanisms underpinning the various crossmodal associations (or correspondences) that have been documented between colours and tastes/flavours have yet been established. It is currently unclear to what extent such colour-taste/flavour correspondences ought to be explained in terms of semantic congruency (i.e., statistical learning), and/or emotional mediation. Bayesian causal inference has become an increasingly important tool in helping researchers to understand (and predict) the multisensory interactions between the spatial senses of vision, audition, and touch. However, a network modelling approach may be of value moving forward. As made clear by this review, there are substantial challenges, both theoretical and practical, that will need to be overcome by those wanting to apply computational approaches both to understanding the integration of the chemical senses in the case of multisensory flavour perception, and to understanding the influence of colour thereon.

Authors: Spence, C; Levitan, CA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Society for Imaging Science and Technology
• Journal: Journal of Perceptual Imaging
• Volume: 5
• Pages: 000408-1 - 000408-16
• Article number: jpi0149
• Publication date: 2022-02-01
• Acceptance date: 2021-11-01
• DOI: 10.2352/j.percept.imaging.2022.5.000408
• EISSN: 2575-8144
• Language: English
• Keywords: crossmodal; multisensory; flavour; colour; crossmodal correspondences; FFR; Bayesian causal inference