Evidence map›Paper›PMID 25542031›Full record

ArticlePloS one2014

A model to explain plant growth promotion traits: a multivariate analysis of 2,211 bacterial isolates.

Pedro Beschoren da Costa, Camille E Granada, Adriana Ambrosini, Fernanda Moreira, Rocheli de Souza, João Frederico M dos Passos, Letícia Arruda, Luciane M P Passaglia

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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  2. Transcriptome analysis ofMicrobiology spectrum · 2026
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  6. Host genotype-driven shifts in theFrontiers in microbiology · 2025
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  7. OftenFrontiers in microbiology · 2025
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  13. Article
  14. Influence of phenotypic variation ofFrontiers in microbiology · 2024
    Article
  15. Journal of fungi (Basel, Switzerland) · 2023
    Article
  16. Article
  17. Article
  18. Article
  19. Tools and challenges to exploit microbial communities in agriculture.Current research in microbial sciences · 2021
    Review
  20. 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

8 authors.

Pedro Beschoren da CostaDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Camille E GranadaUNIVATES, Lajeado, RS, Brazil.
Adriana AmbrosiniDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Fernanda MoreiraDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Rocheli de SouzaDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
João Frederico M dos PassosDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Empresa de Pesquisa e Extensão Agropecuária de Santa Catarina (EPAGRI), Lages, SC, Brazil.
Letícia ArrudaDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Luciane M P PassagliaDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant growth-promoting bacteria can greatly assist sustainable farming by improving plant health and biomass while reducing fertilizer use. The plant-microorganism-environment interaction is an open and complex system, and despite the active research in the area, patterns in root ecology are elusive. Here, we simultaneously analyzed the plant growth-promoting bacteria datasets from seven independent studies that shared a methodology for bioprospection and phenotype screening. The soil richness of the isolate's origin was classified by a Principal Component Analysis. A Categorical Principal Component Analysis was used to classify the soil richness according to isolate's indolic compound production, siderophores production and phosphate solubilization abilities, and bacterial genera composition. Multiple patterns and relationships were found and verified with nonparametric hypothesis testing. Including niche colonization in the analysis, we proposed a model to explain the expression of bacterial plant growth-promoting traits according to the soil nutritional status. Our model shows that plants favor interaction with growth hormone producers under rich nutrient conditions but favor nutrient solubilizers under poor conditions. We also performed several comparisons among the different genera, highlighting interesting ecological interactions and limitations. Our model could be used to direct plant growth-promoting bacteria bioprospection and metagenomic sampling.

Indexed as

Plant DevelopmentRhizosphereSoil MicrobiologyBacteriaBacterial Physiological PhenomenaModels, BiologicalMultivariate AnalysisPlant Growth RegulatorsPlantsPrincipal Component AnalysisSiderophoresPlant Growth RegulatorsSiderophores

Identifiers

PMID25542031
PMCPMC4277451

What OpenQuestion 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 OpenQuestion graph.