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The role of expectancy in sensory and hedonic evaluation: The case of smoked salmon ice-cream
Open accessAbstract
Our experience of flavour involves integration of multiple sensory inputs, and the hedonic evaluation of this complex flavour experience is important in determination of food choice. The appearance of food also generates expectations about food flavour, and past work suggests that these expectations if confirmed enhance the flavour experience. What is less clear is what happens when cues prior to ingestion predict a flavour which is in marked contrast to the actual flavour characteristics. To test this, we conducted three experiments where expectations about food flavour were generated by plausible but inaccurate food labels for a highly novel food, smoked-salmon ice-cream. In Experiment 1, the experience of the food in the mouth generated strong dislike when labelled as ice-cream, but acceptance when labelled as frozen savoury mousse. Labelling the food as ice-cream also resulted in stronger ratings of how salty and savoury the food was than when labelled as a savoury food. Experiment 2 confirmed these findings, and also found that an uninformative label also resulted in acceptable liking ratings. Experiment 3 explicitly tested the effect of labels on flavour expectation, and confirmed that the ice-cream label generated strong expectations of a sweet, fruity flavour, consistent with the visual appearance of the ice-cream, but in marked contrast to the flavour of salty fish. As in Experiments 1 and 2, liking was minimal when the food was tasted after the ice-cream label condition, but liking was acceptable in the other label conditions. These data show that the contrast between expected and actual sensory qualities can result in a strong negative affective response and enhancement of the unexpected sensory qualities.
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“Yeomans et al. [200] found that a salmon-based mousse that looked like strawberry ice cream evoked a negative hedonic reaction when participants wrongly assumed it was strawberry ice cream.”
From The Role of Intrinsic and Extrinsic Sensory Factors in Sweetness Perception of Food and Beverages: A Review (2019) · cites this paper as [200]
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Metadata
- Authors
- Yeomans, M. R., Chambers, L., Blumenthal, H., & Blake, A.
- Affiliations
- University of Sussex (GB)
- Firmenich (Switzerland) (CH)
- Corresponding author
- Yeomans, Martin R.
- Venue
- Food Quality and Preference
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 19
- Issue
- 6
- Pages
- 565-573
- ISSN
- 0950-3293 (ISSN-L)
- OpenAlex
- W2049678539
- Cited by
- 350
- References
- 40
- Citations by year
- 2026: 17 · 2025: 17 · 2024: 28 · 2023: 17 · 2022: 44 · 2021: 17 · 2020: 14 · 2019: 25 · 2018: 19 · 2017: 14 · 2016: 25 · 2015: 22 · 2014: 19 · 2013: 16 · 2012: 22
- FWCI
- 17.63
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Licence
- Locations
- Food Quality and Preference (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Sussex Research Online (University of Sussex) (submittedVersion)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Food Science › Sensory Analysis and Statistical Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Life Sciences › Neuroscience › Sensory Systems › Olfactory and Sensory Function Studies
- Keywords
- food labeling, sensory evaluation, hedonic evaluation, novel foods, liking, visual appearance, food choice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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