Evidence map›Paper›PMID 40078553›Full record

ArticleFrontiers in microbiology2025

Understanding the microbiome-crop rotation nexus in karst agricultural systems: insights from Southwestern China.

Bin Wang, Nianjie Shang, Xinwei Feng, Zongling Hu, Pengfei Li, Yi Chen, Binbin Hu, Mengjiao Ding, Junju Xu

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Bin Wang *College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, China.
Nianjie Shang *Institute of Crop Germplasm Resources, Guizhou Academy of Agricultural Sciences, Guiyang, China.
Xinwei FengGuizhou Tobacco Company Qiannan Company, Duyun, China.
Zongling HuYunnan Tobacco Company Wenshan Prefecture Company, Wenshan Zhuang and Miao Autonomous Prefecture, Yunnan, China.
Pengfei LiYunnan Tobacco Company Wenshan Prefecture Company, Wenshan Zhuang and Miao Autonomous Prefecture, Yunnan, China.
Yi ChenYunnan Academy of Tobacco Agricultural Sciences, Kunming, China.
Binbin HuYunnan Academy of Tobacco Agricultural Sciences, Kunming, China.
Mengjiao DingCollege of Tobacco Science, Guizhou University, Guiyang, China.
Junju XuCollege of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding how soil properties and microbial communities respond to crop rotation is essential for the sustainability of agroecosystems. However, there has been limited research on how crop rotation alters below-ground microbial communities in soils with serious bacterial wilt within the karst agricultural system. This study investigated the effects of continuous planting of corn, tobacco, and tobacco-corn rotation on soil microbial communities in the karst regions of Southwestern China. High-throughput sequencing was used to evaluate the responses of the soil microbial community structure to crop monoculture and rotation patterns. As expected, the tobacco-corn rotation mitigated the negative effects of continuous cropping and reduced soil acidification. The tobacco-corn rotation also significantly altered the composition of microbial communities and promoted plant growth by fostering a higher abundance of beneficial microorganisms. The predominant bacteria genera

Indexed as

crop rotationkarst agricultural systemmicrobiome assemblysoil microbial communitiessoil physicochemical properties

Identifiers

PMID40078553
PMCPMC11897573

What OpenQuestion holds

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Registered trials

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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.