Evidence map›Paper›PMID 37630572›Full record

ArticleMicroorganisms2023

Crop Productivity Boosters: Native Mycorrhizal Fungi from an Old-Growth Grassland Benefits Tomato (

Liz Koziol, James D Bever

Abstract read
In one paragraph

Article in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

2 authors.

Liz KoziolKansas Biological Station and Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66047, USA.
James D BeverKansas Biological Station and Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66047, USA.ORCID 0000-0003-4068-3582

Funding

Division of Biological Infrastructure 1556664Division of Biological Infrastructure 2120153Division of Environmental Biology 1738041NSF Partnerships for Innovation 2016549Office of Integrative Activities 1656006
6 · The paper itself

Abstract

This paper investigates the response of five tomato and five pepper varieties to native arbuscular mycorrhizal (AM) fungal inoculation in an organic farming system. The field experiment was conducted across a growing season at a working organic farm in Lawrence, KS, USA. The researchers hypothesized that native AM fungi inoculation would improve crop biomass production for both crop species, but that the magnitude of response would depend on crop cultivar. The results showed that both crops were significantly positively affected by inoculation. AM fungal inoculation consistently improved total pepper biomass throughout the experiment (range of +2% to +8% depending on the harvest date), with a +3.7% improvement at the final harvest for inoculated plants. An interaction between pepper variety and inoculation treatment was sometimes observed, indicating that some pepper varieties were more responsive to AM fungi than others. Beginning at the first harvest, tomatoes showed a consistent positive response to AM fungal inoculation among varieties. Across the experiment, AM fungi-inoculated tomatoes had +10% greater fruit biomass, which was driven by a +20% increase in fruit number. The study highlights the potential benefits of using native AM fungi as a soil amendment in organic farmed soils to improve pepper and tomato productivity.

Indexed as

annual cropsarbuscular mycorrhizal fungibiofertilizerscultivarsgenotypic and phenotypic variationinoculationorganic farmingsymbiosisvegetables

Identifiers

PMID37630572
PMCPMC10457834

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.