Evidence map›Paper›PMID 40718998›Full record

ReviewThe Plant cell2025

Potential and challenges for application of microbiomes in agriculture.

Charles Copeland, Paul Schulze-Lefert, Ka-Wai Ma

Abstract readReview
In one paragraph

Review in The Plant cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Review
  2. Plant signaling & behavior · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Towards an integrated molecular understanding of plant hormones.Journal of integrative plant biology · 2026
    Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Rethinking microbial biopesticide development and uptake.World journal of microbiology & biotechnology · 2026
    Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Inhibitory Effect ofJournal of fungi (Basel, Switzerland) · 2026
    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

3 authors.

Charles CopelandDepartment of Plant Microbe Interactions, Max Planck Institute for Plant Breeding Research, Cologne 50829, Germany.ORCID 0000-0001-8535-8615
Paul Schulze-LefertDepartment of Plant Microbe Interactions, Max Planck Institute for Plant Breeding Research, Cologne 50829, Germany.ORCID 0000-0002-8978-1717
Ka-Wai MaInstitute of Plant and Microbial Biology, Academia Sinica, Taipei 115201, Taiwan.ORCID 0000-0001-6968-9844

Funding

Academia Sinica AS-IAIA-114-L04Alexander von Humboldt foundationDeutsche ForschungsgemeinschaftMax Planck Society
6 · The paper itself

Abstract

The plant microbiome can promote plant health and productivity through a multitude of mechanisms. Our understanding of plant-microbiome interaction relies on descriptive natural surveys and experiments performed under simplified laboratory environments. While reductionist approaches are essential to understand mechanisms of plant-microbiome interactions, they risk missing emergent community properties seen in nature. To bridge the gap between basic research and real-world deployment of the microbiome for translational application, one has to consider functional association as well as ecologic principles governing interspecies and interkingdom interactions. In this review, we discuss the beneficial potential of plant microbiomes to enhance plant growth, nutrition, stress tolerance, pathogen protection, and commercial value through the modulation of taste and flavors, using examples from model plants and agriculturally important crops. We then discuss how microbial invasion and persistence in standing communities, trade-offs under multiple stressors, and community instability under host- and environment-imposed modulation should be considered in the rational design of microbial inocula, followed by a scrutiny of the method of microbial delivery. We synthesize ideas on how multiomic data, including genomics, transcriptomes, and metabolomics, can be leveraged to identify strains or target genes of interest for functional studies and how machine learning algorithms can be incorporated to enable prediction of plant-microbiome interactions. Microbiome-based strategies hold promise for improvements in agriculture. Despite the intrinsic complexity of the underlying interactions, interdisciplinary approaches are constantly providing insight into microbiome functioning and assembly principles, which is key toward knowledge-based engineering of the microbiome for increased and sustainable crop performance.

Indexed as

AgricultureCrops, AgriculturalMicrobiotaPlants

Identifiers

PMID40718998
PMCPMC12379898

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.