Evidence map›Paper›PMID 39279853›Full record

ArticleaBIOTECH2024

Decoding the microbiome for sustainable agriculture.

Kai Sun, Wei Zhang, Xiaolin Wang, Chuan-Chao Dai

Abstract readEditorial
In one paragraph

Article in aBIOTECH, 2024. 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. Review
  4. Article
  5. Article
  6. Review
  7. AM fungi modulate organic nitrogen preference ofFrontiers in plant science · 2025
    Article
  8. 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

4 authors.

Kai SunJiangsu Key Laboratory for Pathogens and Ecosystems, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China.
Wei ZhangJiangsu Key Laboratory for Pathogens and Ecosystems, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China.
Xiaolin WangGuangdong Provincial Key Laboratory of Plant Molecular Breeding, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 China.ORCID 0000-0003-3675-945X
Chuan-Chao DaiJiangsu Key Laboratory for Pathogens and Ecosystems, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, 210023 China.ORCID 0000-0002-0980-0018

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Root-associated microbiota profoundly affect crop health and productivity. Plants can selectively recruit beneficial microbes from the soil and actively balance microbe-triggered plant-growth promotion and stress tolerance enhancement. The cost associated with this is the root-mediated support of a certain number of specific microbes under nutrient limitation. Thus, it is important to consider the dynamic changes in microbial quantity when it comes to nutrient condition-induced root microbiome reassembly. Quantitative microbiome profiling (QMP) has recently emerged as a means to estimate the specific microbial load variation of a root microbiome (instead of the traditional approach quantifying relative microbial abundances) and data from the QMP approach can be more closely correlated with plant development and/or function. However, due to a lack of detailed-QMP data, how soil nutrient conditions affect quantitative changes in microbial assembly of the root-associated microbiome remains poorly understood. A recent study quantified the dynamics of the soybean root microbiome, under unbalanced fertilization, using QMP and provided data on the use of specific synthetic communities (SynComs) for sustaining crop productivity. In this editorial, we explore potential opportunities for utilizing QMP to decode the microbiome for sustainable agriculture.

Indexed as

Microbial loadQuantitative microbiome profilingSustainable agricultureSynComsUnbalanced fertilization

Identifiers

PMID39279853
PMCPMC11399370

What OpenQuestion holds

Textmetadata
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.