Evidence map›Paper›PMID 38405363›Full record

ArticleCurrent research in food science2024

Unveiling aromas: Virtual reality and scent identification for sensory analysis.

Abdul Hannan Bin Zulkarnain, Dalma Radványi, Dorina Szakál, Zoltán Kókai, Attila Gere

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Current research in food science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.9field-weighted citation impact, top 10% of its field
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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. 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

5 authors at 2 institutions in 1 country.

Abdul Hannan Bin ZulkarnainInstitute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, H-1118, Budapest, Villányi út. 29-31, Hungary.
Dalma RadványiDepartment of Hospitality, Faculty of Commerce, Hospitality and Tourism, Budapest Business University, H-1045, Budapest, Alkotmány utca 9-11., Hungary.
Dorina SzakálDepartment of Hospitality, Faculty of Commerce, Hospitality and Tourism, Budapest Business University, H-1045, Budapest, Alkotmány utca 9-11., Hungary.
Zoltán KókaiInstitute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, H-1118, Budapest, Villányi út. 29-31, Hungary.
Attila GereInstitute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, H-1118, Budapest, Villányi út. 29-31, Hungary.
Magyar Agrár- és Élettudományi Egyetem · HUBudapest University of Economics and Business · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sensory analysis is crucial for optimizing experiences in various fields, including food, cosmetics, and product design. Traditional methods can be inefficient and imprecise. This study introduces a novel approach by blending Virtual Reality (VR) technology with scent identification techniques. The aim is to investigate whether the visual representation of food products affects scent perception. Limited research has explored the use of VR in scent identification, which is especially relevant when altering the food environment setting. A virtual sensory laboratory was developed to mimic MATE's sensory booth. Sixty participants, all MATE students, were involved in this study. This method offers a potential means to streamline scent identification and reduce human bias in sensory analysis. In summary, the combination of VR technology and scent identification presents a fresh methodological approach to sensory analysis, where both scent and exposure are influenced by the environment or imagery. This concept delves into cross-modal correspondences and the role of sensory cues in shaping our perception of food odours within the VR setting.

Indexed as

AromaMultiple factor analysisSmelling testVirtual sensory laboratoryVisual

Identifiers

PMID38405363
PMCPMC10883831
OpenAlexW4391849008

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.