Evidence map›Paper›PMID 32824086›Full record

ReviewFoods (Basel, Switzerland)2020

Sensorial Perception of Astringency: Oral Mechanisms and Current Analysis Methods.

Mariana A Pires, Lorenzo M Pastrana, Pablo Fuciños, Cristiano S Abreu, Sara M Oliveira

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Study on the astringent mechanism ofFood chemistry: X · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

5 authors.

Mariana A PiresInternational Iberian Nanotechnology Laboratory-Av. Mestre José Veiga s/n, 4715-330 Braga, Portugal.
Lorenzo M PastranaInternational Iberian Nanotechnology Laboratory-Av. Mestre José Veiga s/n, 4715-330 Braga, Portugal.
Pablo FuciñosInternational Iberian Nanotechnology Laboratory-Av. Mestre José Veiga s/n, 4715-330 Braga, Portugal.
Cristiano S AbreuCenter for Microelectromechanical Systems, University of Minho, Azurém, 4800-058 Guimarães, Portugal.ORCID 0000-0002-4878-6159
Sara M OliveiraInternational Iberian Nanotechnology Laboratory-Av. Mestre José Veiga s/n, 4715-330 Braga, Portugal.ORCID 0000-0002-8901-9757

Funding

ERDF and CCDR-N NORTE-01-0145-FEDER-000019FCT UID/EEA/04436/2019Marie Skłodowsk-Curie Research and Innovation Staff Exchange H2020-MSCA-RISE-778388
6 · The paper itself

Abstract

Understanding consumers' food choices and the psychological processes involved in their preferences is crucial to promote more mindful eating regulation and guide food design. Fortifying foods minimizing the oral dryness, rough, and puckering associated with many functional ingredients has been attracting interest in understanding oral astringency over the years. A variety of studies have explored the sensorial mechanisms and the food properties determining astringency perception. The present review provides a deeper understanding of astringency, a general view of the oral mechanisms involved, and the exciting variety of the latest methods used to direct and indirectly quantify and simulate the astringency perception and the specific mechanisms involved.

Indexed as

astringencylubricationoral mechanismsprotein-food interactionssalivary proteinssensorial perception

Identifiers

PMID32824086
PMCPMC7465539

What OpenQuestion holds

Textmetadata
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.