Evidence map›Paper›PMID 42040993›Full record

ArticlePlant phenomics (Washington, D.C.)2025

Detecting nematodes in potato plants an explainable machine learning approach for detection of potato cyst nematode infections using hyperspectral imaging.

Janez Lapajne, Nik Susič, Andrej Vončina, Barbara Gerič Stare, Nicole Viaene, Jonathan Van Beek, David Nuyttens, Saša Širca, Uroš Žibrat

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plant phenomics (Washington, D.C.), 2025. 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

9 authors.

Janez LapajnePlant Protection Department, Agricultural Institute of Slovenia, Hacquetova ulica 17, Ljubljana, 1000, Ljubljana, Slovenia.
Nik SusičPlant Protection Department, Agricultural Institute of Slovenia, Hacquetova ulica 17, Ljubljana, 1000, Ljubljana, Slovenia.
Andrej VončinaPlant Protection Department, Agricultural Institute of Slovenia, Hacquetova ulica 17, Ljubljana, 1000, Ljubljana, Slovenia.
Barbara Gerič StarePlant Protection Department, Agricultural Institute of Slovenia, Hacquetova ulica 17, Ljubljana, 1000, Ljubljana, Slovenia.
Nicole ViaenePlant Sciences Unit, Flanders Research Institute for Agriculture, Fisheries, and Food, Burgemeester Van Gansberghelaan 96, Merelbeke, 9820, Belgium.
Jonathan Van BeekTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries, and Food, Burgemeester Van Gansberghelaan 115, Bus 1, Merelbeke, 9820, Belgium.
David NuyttensTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries, and Food, Burgemeester Van Gansberghelaan 115, Bus 1, Merelbeke, 9820, Belgium.
Saša ŠircaPlant Protection Department, Agricultural Institute of Slovenia, Hacquetova ulica 17, Ljubljana, 1000, Ljubljana, Slovenia.
Uroš ŽibratPlant Protection Department, Agricultural Institute of Slovenia, Hacquetova ulica 17, Ljubljana, 1000, Ljubljana, Slovenia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Potato cyst nematodes pose a major threat to potato cultivation, with infestations often going undetected for years. Early and accurate detection is crucial for effective management, necessitating reliable, large-scale monitoring methods. Hyperspectral imaging shows great promise for non-invasive nematode detection, yet distinguishing between biotic (e.g., nematodes) and abiotic (e.g., drought) stressors remains a challenge. This study investigated the stress responses of potato plants to potato cyst nematodes

Indexed as

DetectionGloboderaHyperspectral imagingMachine learningPotatoPotato cyst nematodesSolanum tuberosum

Identifiers

PMID42040993
PMCPMC13109338

What OpenQuestion holds

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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.