Evidence map›Paper›PMID 41669632›Full record

ArticleFrontiers in plant science2025

A hyperspectral imaging and machine learning approach for rapid and non-invasive diagnosis of cassava bacterial blight.

Ian Carlos Bispo Carvalho, Luciellen da Costa Ferreira, Ana Régia de Mendonça Neves, Alice Maria Silva Carvalho, Henrique Póvoa Rodrigues Lima, Maurício Rossato

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. 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
–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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Ian Carlos Bispo CarvalhoUniversidade de Brasília, Brasília, Distrito Federal, Brazil.
Luciellen da Costa FerreiraUniversidade de Brasília, Brasília, Distrito Federal, Brazil.
Ana Régia de Mendonça NevesInstituto Federal de Brasília (IFB), Eixo de Informação e Comunicação, Distrito Federal, Brasília, Brazil.
Alice Maria Silva CarvalhoUniversidade de Brasília, Brasília, Distrito Federal, Brazil.
Henrique Póvoa Rodrigues LimaUniversidade de Brasília, Brasília, Distrito Federal, Brazil.
Maurício RossatoUniversidade de Brasília, Brasília, Distrito Federal, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the use of hyperspectral imaging (HSI) combined with machine learning to detect physiological alterations in cassava leaves caused by

Indexed as

bacterial blightHSIplant diseaseplant physiologyXanthomonas

Identifiers

PMID41669632
PMCPMC12884324

What Socratic 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 Socratic graph.