Evidence map›Paper›PMID 29621291›Full record

ArticlePloS one2018

Fungal community profiles in agricultural soils of a long-term field trial under different tillage, fertilization and crop rotation conditions analyzed by high-throughput ITS-amplicon sequencing.

Loreen Sommermann, Joerg Geistlinger, Daniel Wibberg, Annette Deubel, Jessica Zwanzig, Doreen Babin, Andreas Schlüter, Ingo Schellenberg

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
15.5field-weighted citation impact, top 1% of its field
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

38 citing papers in PubMed, 109 citations in OpenAlex.

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  16. Integrated management of fruit trees andFrontiers in microbiology · 2024
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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

8 authors at 3 institutions in 1 country.

Loreen SommermannInstitute of Bioanalytical Sciences (IBAS), Anhalt University of Applied Sciences, Bernburg, Saxony-Anhalt, Germany.ORCID 0000-0002-6293-877X
Joerg GeistlingerInstitute of Bioanalytical Sciences (IBAS), Anhalt University of Applied Sciences, Bernburg, Saxony-Anhalt, Germany.
Daniel WibbergCenter for Biotechnology (CeBiTec), Genome Research of Industrial Microorganisms (GRIM), Bielefeld University, Bielefeld, North Rhine-Westphalia, Germany.
Annette DeubelDepartment of Agriculture, Ecotrophology and Landscape Development, Anhalt University of Applied Sciences, Bernburg, Saxony-Anhalt, Germany.
Jessica ZwanzigInstitute of Bioanalytical Sciences (IBAS), Anhalt University of Applied Sciences, Bernburg, Saxony-Anhalt, Germany.
Doreen BabinInstitute for Epidemiology and Pathogen Diagnostics, Julius-Kühn-Institut-Federal Research Centre for Cultivated Plants (JKI), Braunschweig, Lower Saxony, Germany.
Andreas SchlüterCenter for Biotechnology (CeBiTec), Genome Research of Industrial Microorganisms (GRIM), Bielefeld University, Bielefeld, North Rhine-Westphalia, Germany.
Ingo SchellenbergInstitute of Bioanalytical Sciences (IBAS), Anhalt University of Applied Sciences, Bernburg, Saxony-Anhalt, Germany.
Anhalt University of Applied Sciences · DEBielefeld University · DEJulius Kühn-Institut · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fungal communities in agricultural soils are assumed to be affected by soil and crop management. Our intention was to investigate the impact of different tillage and fertilization practices on fungal communities in a long-term crop rotation field trial established in 1992 in Central Germany. Two winter wheat fields in replicated strip-tillage design, comprising conventional vs. conservation tillage, intensive vs. extensive fertilization and different pre-crops (maize vs. rapeseed) were analyzed by a metabarcoding approach applying Illumina paired-end sequencing of amplicons generated by two recently developed primer pairs targeting the two fungal Internal Transcribed Spacer regions (ITS1, ITS2). Analysis of 5.1 million high-quality sequence reads uncovered a diverse fungal community in the two fields, composed of 296 fungal genera including 3,398 Operational Taxonomic Units (OTUs) at the 97% sequence similarity threshold. Both primer pairs detected the same fungal phyla (Basidio-, Asco-, Zygo-, Glomero- and Chytridiomycota), but in different relative abundances. OTU richness was higher in the ITS1 dataset, while ITS2 data were more diverse and of higher evenness. Effects of farming practice on fungal community structures were revealed. Almost two-thirds of the fungal genera were represented in all different soil treatments, whereas the remaining genera clearly responded to farming practice. Principal Component Analysis revealed four distinct clusters according to tillage practice and pre-crop. Analysis of Variance (ANOVA) substantiated the results and proved significant influences of tillage and pre-crop, while fertilization had the smallest and non-significant effect. In-depth analysis of putative phytopathogenic and plant beneficial fungal groups indicated distinct responses; for example Fusarium was significantly enriched in the intensively fertilized conservation tillage variants with the pre-crop maize, while Phoma displayed significant association with conventional tillage and pre-crop rapeseed. Many putative plant beneficial fungi also reacted differentially to farming practice with the most distinct responders identified among the Glomeromycota (arbuscular mycorrhizal fungi, AMF).

Indexed as

Soil MicrobiologyAgricultureCrop ProductionCrops, AgriculturalFarmsFungiGermanyMycorrhizaeSoilSoil

Identifiers

PMID29621291
PMCPMC5886558
OpenAlexW2795534348

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.