Evidence map›Paper›PMID 42841780›Full record

ReviewPlant signaling & behavior2026

Advances in plant electrostimulation: from cellular and molecular mechanisms to agricultural applications.

Yu Dong, Ye Tian, Jingxuan Pan, Weiwen Qiu, Xinyu Zhou, Yangyang Xie, Mei Liu, Juntao Wang, Fengru Gao, Liang Jin and 3 more

Abstract readReview
In one paragraph

Review in Plant signaling & behavior, 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

13 authors.

Yu DongCollege of Life Science and Technology, Heilongjiang Bayi Agricultural University, Daqing, People's Republic of China.ORCID 0009-0005-3031-9076
Ye TianInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.
Jingxuan PanCollege of Life Science and Technology, Heilongjiang Bayi Agricultural University, Daqing, People's Republic of China.
Weiwen QiuNew Zealand Institute for Bioeconomy Science Limited, Hamilton, New Zealand.
Xinyu ZhouInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.
Yangyang XieCollege of Life Science and Technology, Heilongjiang Bayi Agricultural University, Daqing, People's Republic of China.
Mei LiuInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.
Juntao WangSchool of Agriculture and Environment, Institute of Agriculture, University of Western Australia, Perth, WA, Australia.
Fengru GaoInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.
Liang JinInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.
Dan WeiInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.
Yanhong WangCollege of Life Science and Technology, Heilongjiang Bayi Agricultural University, Daqing, People's Republic of China.
Qiang XiaoInstitute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrical stimulation is an emerging physical strategy for agricultural regulation that applies electric fields or currents with defined parameters to modulate plant growth, development, and rhizosphere processes. Owing to its residue-free nature, environmental compatibility, and high controllability, electrical stimulation has considerable potential to improve crop yield and quality while enhancing tolerance to abiotic and biotic stresses, making it increasingly relevant to sustainable agriculture. This review critically synthesizes the mechanisms and applications of electrical stimulation across cellular and molecular, physiological and metabolic, whole-plant, and field scales. Particular emphasis is placed on distinguishing continuous or quasi-continuous stimulation from high-voltage pulsed treatments, which differ in membrane-level mechanisms, reversibility, and safety profiles. Three interrelated factors are identified as central to its effectiveness: regulation of membrane potential and ion transport, root-targeted modulation of plant-soil interactions, and context-dependent matching of stimulation parameters with specific biological responses. We further highlight that translating laboratory-scale benefits into reliable field applications will require intelligent delivery systems capable of stable, scalable, energy-efficient, and feedback-controlled operation under variable environmental conditions. Future research should prioritize multiscale investigation of molecular mechanisms, standardized evaluation of stimulation parameters, development of smart and synergistic regulation platforms, and validation across diverse crops, soils, and production systems. These advances will facilitate the practical deployment of electrical stimulation technologies and support their integration into sustainable and precision agriculture.

Indexed as

AgricultureElectric StimulationCrops, Agriculturalbioelectrical signalcrop stress tolerancemembrane potentialPlant electrostimulationrhizosphere regulationsustainable agriculture

Identifiers

PMID42841780
PMCPMC13652059

What OpenQuestion holds

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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.