Evidence map›Paper›PMID 40312727›Full record

ArticleEnvironmental microbiome2025

Small-scale heterogeneity of soil properties in farmland affected fava beans growth through rhizosphere differential metabolites and microorganisms.

Linbin Wang, Yufeng Wu, Zhi-Bo Zhao, Tingsheng Jia

Abstract read
In one paragraph

Article in Environmental microbiome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

  1. The Influence of Pre-Harvest Application ofFoods (Basel, Switzerland) · 2026
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Linbin Wang *College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China.
Yufeng Wu *College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China.
Zhi-Bo ZhaoCollege of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China. zhaozhibo@bjut.edu.cn.
Tingsheng JiaCollege of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China.

Funding

The Youth Program of the National Natural Science Foundation of China 52100207
6 · The paper itself

Abstract

backgroundSoil heterogeneity has been acknowledged to influence plant growth, with the small-scale soil heterogeneity always being overlooked in practice. It remains unclear how rhizosphere soil biotics and abiotics respond to soil heterogeneity and how rhizosphere interactions influence crop growth.

resultsIn this study, we planted fava beans in a farmland around an e-waste dismantling site, and a distinct boundary (row spacing is 30 cm) was observed in the field during the flowering stage, which divided fava beans phenotypes into two distinct groups (Big vs Little) based on the differences in biomass and height. Soil total concentrations of As, B, Co, Cr, Cu, Pb, Sr, Zn, Ni, Cd and soil pH significantly differed in the rhizosphere of fava beans in the two adjacent rows, which were located on either side of the boundary, with a row-spacing of 30 cm. Random Forest analysis demonstrated that these differentiated soil properties (soil pH, total As, B, Cd, Co, Cr, Cu, Mo, Ni and Zn) substantially influenced fava beans growth (height and biomass). Metagenomic sequencing showed that microbial taxa were significantly enriched their abundance in rhizosphere soils between the two groups of fava beans, with eukaryotic taxa being more sensitively affected. A total of 20 metabolites including coniferyl alcohol, jasmonic acid, resveratrol, and L-aspartic acid, etc. were significantly correlated with fava beans growth. These metabolites were significantly enriched in 15 metabolic pathways (nucleotide metabolism, pyrimidine metabolism, purine metabolism, biosynthesis of plant secondary metabolites, lysine biosynthesis, etc.). Furthermore, 11 microbial genera involved in these metabolic pathways, and these genera were differentially enriched between the two groups and significantly correlated with fava beans growth.

conclusionsOverall, the integrated analysis of multi-omics revealed that soil properties heterogeneity at small-scale altered the rhizosphere differential microorganisms and metabolites, which functionally influenced fava beans growth and tolerance to environmental stress. Notably, even soil heterogeneity at such a small spatial scale can cause significant differences in plant growth, and the comprehensive explorations utilizing multi-omics techniques provide novel insights to the field management, which is crucial for the survival and sustainable development of humanity.

Indexed as

ElementsFava beansMulti-omicsSmall-scaleSoil heterogeneity

Identifiers

PMID40312727
PMCPMC12044778

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LicenceCC BY-NC-ND
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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.