Evidence map›Paper›PMID 42293443›Full record

ArticleData in brief2026

Field-based and close-range multispectral imaging dataset for Huanglongbing (HLB) detection in orange trees: A resource for machine learning and digital agriculture.

Letícia Rosim Porto, Florent Abdelghafour, Antonio Maria Garcia Tommaselli, Nilton Nobuhiro Imai

Abstract read
In one paragraph

Article in Data in brief, 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.

Letícia Rosim PortoSão Paulo State University, Unesp, Presidente Prudente, Brazil.
Florent AbdelghafourITAP, INRAE, Institute Agro, University Montpellier, Montpellier, France.
Antonio Maria Garcia TommaselliSão Paulo State University, Unesp, Presidente Prudente, Brazil.
Nilton Nobuhiro ImaiSão Paulo State University, Unesp, Presidente Prudente, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article presents a multispectral imaging dataset dedicated to training a machine learning algorithm for the in situ detection of Huanglongbing (HLB). HLB, also known as citrus greening disease, is a major pathology caused by the bacterial pathogen

Indexed as

CitricultureCitrus greeningDeep learningDisease monitoringPlant diseaseProximal sensingVNIR

Identifiers

PMID42293443
PMCPMC13264198

What OpenQuestion holds

Textmetadata
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.