Evidence map›Paper›PMID 34378980›Full record

ArticlemSphere2021

Local Network Properties of Soil and Rhizosphere Microbial Communities in Potato Plantations Treated with a Biological Product Are Important Predictors of Crop Yield.

Nabeel Imam, Ignacio Belda, Beatriz García-Jiménez, Adrian J Duehl, James R Doroghazi, Daniel E Almonacid, Varghese P Thomas, Alberto Acedo

Abstract read
In one paragraph

Article in mSphere, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Short impact on soil microbiome of aFrontiers in plant science · 2024
    Article
  7. Article
  8. Review
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.

Nabeel Imam *Biome Makers Inc., West Sacramento, California, USA.
Ignacio Belda *Biome Makers Inc., West Sacramento, California, USA.
Beatriz García-JiménezBiome Makers Inc., West Sacramento, California, USA.
Adrian J DuehlBayer U.S., Chesterfield, Missouri, USA.
James R DoroghaziBayer U.S., Cary, North Carolina, USA.
Daniel E AlmonacidBiome Makers Inc., West Sacramento, California, USA.
Varghese P ThomasBayer U.S., West Sacramento, California, USA.
Alberto AcedoBiome Makers Inc., West Sacramento, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the effectiveness and potential mechanism of action of agricultural biological products under different soil profiles and crops will allow more precise product recommendations based on local conditions and will ultimately result in increased crop yield. This study aimed to use bulk soil and rhizosphere microbial composition and structure to evaluate the potential effect of a Bacillus amyloliquefaciens inoculant (strain QST713) on potatoes and to explore its relationship with crop yield. We implemented next-generation sequencing (NGS) and bioinformatics approaches to assess the bacterial and fungal biodiversity in 185 soil samples, distributed over four different time points-from planting to harvest-from three different geographical locations in the United States. In addition to location and sampling time (which includes the difference between bulk soil and rhizosphere) as the main variables defining the microbiome composition, the microbial inoculant applied as a treatment also had a small but significant effect in fungal communities and a marginally significant effect in bacterial communities. However, treatment preserved the native communities without causing a detectable long-lasting effect on the alpha- and beta-diversity patterns after harvest. Using information about the application of the microbial inoculant and considering microbiome composition and structure data, we were able to train a Random Forest model to estimate if a bulk soil or rhizosphere sample came from a low- or high-yield block with relatively high accuracy (84.6%), concluding that the structure of fungal communities gives us more information as an estimator of potato yield than the structure of bacterial communities.

Indexed as

Crops, AgriculturalRhizosphereSoil MicrobiologyAgricultural InoculantsAgricultureBacteriaBiological ProductsFungiHigh-Throughput Nucleotide SequencingMicrobiotaRNA, Ribosomal, 16SSoilSolanum tuberosumUnited StatesBiological ProductsRNA, Ribosomal, 16SSoilagricultural biologicalmachine learningsoil microbiomeyield prediction

Identifiers

PMID34378980
PMCPMC8386434

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.