Evidence map›Paper›PMID 38545860›Full record

ArticlePlant signaling & behavior2024

Common bean under different water availability reveals classifiable stimuli-specific signatures in plant electrome.

Gabriel R A de Toledo, Gabriela N Reissig, Luiz G S Senko, Danillo R Pereira, Arlan F da Silva, Gustavo M Souza

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plant signaling & behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Gabriel R A de ToledoLaboratory of Plant Cognition and Electrophysiology, Department of Botany, Institute of Biology, Federal University of Pelotas, Pelotas, Brazil.
Gabriela N ReissigLaboratory of Plant Cognition and Electrophysiology, Department of Botany, Institute of Biology, Federal University of Pelotas, Pelotas, Brazil.
Luiz G S SenkoLaboratory of Plant Cognition and Electrophysiology, Department of Botany, Institute of Biology, Federal University of Pelotas, Pelotas, Brazil.
Danillo R PereiraSão Paulo State University, Presidente Prudente, Brazil.
Arlan F da SilvaDepartment of Physics, Federal University of Pelotas, Pelotas, Brazil.
Gustavo M SouzaLaboratory of Plant Cognition and Electrophysiology, Department of Botany, Institute of Biology, Federal University of Pelotas, Pelotas, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant electrophysiology has unveiled the involvement of electrical signals in the physiology and behavior of plants. Spontaneously generated bioelectric activity can be altered in response to changes in environmental conditions, suggesting that a plant's electrome may possess a distinct signature associated with various stimuli. Analyzing electrical signals, particularly the electrome, in conjunction with Machine Learning (ML) techniques has emerged as a promising approach to classify characteristic electrical signals corresponding to each stimulus. This study aimed to characterize the electrome of common bean (

Indexed as

PhaseolusPlant LeavesWaterWaterComplexitymachine learningosmotic stressplant electrical activitysalinitysmall vector machine

Identifiers

PMID38545860
PMCPMC10984121

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.