Evidence map›Paper›PMID 31614834›Full record

ArticleFoods (Basel, Switzerland)2019

Effect of Product Involvement on Panels' Vocabulary Generation, Attribute Identification, and Sample Configurations in Beer.

Line Elgaard, Line A Mielby, Hildegarde Heymann, Derek V Byrne

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

4 authors.

Line ElgaardDepartment of Food Science, Faculty of Science and Technology, Aarhus University, DK-5792 Aarslev, Denmark. len@food.au.dk.
Line A MielbyDepartment of Food Science, Faculty of Science and Technology, Aarhus University, DK-5792 Aarslev, Denmark. lineh.mielby@food.au.dk.
Hildegarde HeymannDepartment of Food Science and Technology and Viticulture & Enology, University of California, Davis, CA 95616-5270, USA. hheymann@ucdavis.edu.
Derek V ByrneDepartment of Food Science, Faculty of Science and Technology, Aarhus University, DK-5792 Aarslev, Denmark. derekv.byrne@food.au.dk.

Funding

Carlsbergfondet CF16-0009
6 · The paper itself

Abstract

The aim of this study was to compare the performance of two semi-trained panels with different degrees of self-reported beer involvement in terms of beer consumption pattern. The two panels were beer non-drinkers (indicating willingness to taste beer) and craft-style beer drinkers. Eleven modified beer samples were evaluated during three separate tasks by both panels. The tasks were (1) a vocabulary generation on a sample level, (2) an attribute identification task with a list of attributes to choose from, and (3) a descriptive analysis. The performance of the two panels was evaluated and compared using three parameters, as follows: Descriptive similarity, attribute knowledge similarity, and perceptual similarity. The results showed that the craft-style beer drinkers generated the most precise vocabulary and correctly identified more attributes, compared to the beer non-drinkers. Furthermore, the sample sensory spaces generated by the two panels were different before the training period, but were perceptually similar post training. To conclude, the beer consumption pattern influenced all aspects of panel performance before training, with the craft-style panel performing better than the non-drinkers panel. However, the panels' performance became more similar after a short period of training sessions.

Indexed as

attribute learningbeerproduct involvementsensory descriptive analysisvocabulary generation

Identifiers

PMID31614834
PMCPMC6835354

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.