Evidence map›Paper›PMID 42195832›Full record

ArticleFoods (Basel, Switzerland)2026

Food Origin Authenticity Using Deep Learning and Citizen Science: Bananas Case Study.

Nikolaos Fragkos, Yamine Bouzembrak, Sara Wilhelmina Erasmus, Filipi Miranda Soares

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nikolaos FragkosInformation Technology, Wageningen University, Wageningen University and Research, 6700 HB Wageningen, The Netherlands.ORCID 0009-0001-2623-7706
Yamine BouzembrakInformation Technology, Wageningen University, Wageningen University and Research, 6700 HB Wageningen, The Netherlands.ORCID 0000-0001-8028-0847
Sara Wilhelmina ErasmusFood Quality and Design, Wageningen University and Research, P.O. Box 17, 6700 AA Wageningen, The Netherlands.ORCID 0000-0003-4372-0326
Filipi Miranda SoaresMathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), University of Montpellier, INRAE & Institut Agro, 2 Place Pierre Viala, Montpellier Cedex 2, 34060 Montpellier, France.ORCID 0000-0002-0674-7960

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces an Artificial Intelligence (AI)-based proof-of-concept approach to tackle food fraud by using convolutional neural networks (CNNs) and citizen science-generated imagery to predict the country of origin of Cavendish banana cultivars (

Indexed as

artificial intelligenceconvolutional neural networkcrowdsourced datafood fraudRGB image

Identifiers

PMID42195832
PMCPMC13205795

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.