Evidence map›Paper›PMID 35741975›Full record

ArticleFoods (Basel, Switzerland)2022

An Explorative Analysis of the Influence of Landscape Visual Aesthetic Quality on Food Preferences in Italy: A Pilot Study.

Tiziano Tempesta, Daniel Vecchiato

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tiziano TempestaDepartment of Land, Environment, Agriculture and Forestry (TESAF), Università degli Studi di Padova, 35020 Legnaro, PD, Italy.ORCID 0000-0002-6445-4744
Daniel VecchiatoDepartment of Land, Environment, Agriculture and Forestry (TESAF), Università degli Studi di Padova, 35020 Legnaro, PD, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As some previous research has highlighted, landscape characteristics are useful for improving the market share of some food products and the market power of companies in the agrifood sector. The purpose of this study is to verify whether the visual aesthetic quality of the landscape can influence food preferences and the willingness to pay for agrifood products. To this end, the preferences of 64 participants for three types of juice (orange, peach and pear) were analysed through a blind tasting experiment. Each participant tasted three pairs of fruit juices, one for each type of juice. The juices belonging to each pair were the same, but before tasting, the participants were shown two photos portraying the orchards where the fruits were produced, so participants were induced to think that the juices were different. The landscape associated with each pair of photographs had a different visual aesthetic quality (high or low). Participants were asked to provide three measures while tasting the juices: their overall juice assessment using a seven-point hedonic scale, the visual aesthetic quality of the photos on a seven-point Likert scale, and their willingness to pay as a percentage variation of the price that they usually pay to buy fruit juices. According to our results, the mean overall liking score and the mean willingness to pay percentage variation for the juices associated with a preferred landscape was higher and statistically different. Despite the need for further research, our results suggest that landscape acts as a proxy for quality in the evaluation of some food products and that the use of landscape photos could be a valid marketing strategy in agribusiness.

Indexed as

beveragejuicelandscapelikingpreferenceswillingness to pay

Identifiers

PMID35741975
PMCPMC9222271

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.