Evidence map›Paper›PMID 41764436›Full record

ArticleBMC microbiology2026

Effects of different planting patterns on potato rhizosphere soil microbial composition and yield.

Xiaoting Wang, Qingqing Hou, Fan Li, Liming Wang, Xiaoyan Zhang, Ruping Yang, Muhammad Aqeel, Chunhui Tang, Guangrong Chen

Abstract read
In one paragraph

Article in BMC microbiology, 2026. 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

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

1 citing paper in PubMed.

  1. 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.

Xiaoting Wang *Institute of Dryland Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou Gansu, 730070, China.
Qingqing Hou *State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China.
Fan LiState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China.
Liming WangInstitute of Dryland Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou Gansu, 730070, China.
Xiaoyan ZhangInstitute of Dryland Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou Gansu, 730070, China.
Ruping YangInstitute of Dryland Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou Gansu, 730070, China.
Muhammad AqeelState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China.
Chunhui TangInstitute of Dryland Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou Gansu, 730070, China.
Guangrong ChenInstitute of Dryland Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou Gansu, 730070, China. chengr516@163.com.

Funding

the Key Laboratory of Water Resources Efficient Utilization in Dryland Farming Areas of Gansu Province 2024HNS08the Major Agricultural Biological Breeding Project 2023ZD0403506the National Natural Science Foundation of China 32260325the National research and technology system of soybean project CARS04-CES17
6 · The paper itself

Abstract

backgroundPotato is a crucial dual-purpose crop, serving both as a staple food and vegetable in Northwest China. However, the prevalence of continuous monocropping has increasingly exacerbated continuous cropping obstacles in the region. While numerous studies have explored effective strategies for mitigating these obstacles, the impact of different cropping systems on potato yield and rhizosphere microbial communities remain insufficiently understood.

methods16 S rRNA and internal transcribed spacer (ITS) MiSeq sequencing methods to elucidate the impact of different planting patterns, including continuous potato monocropping (PM), potato-soybean rotation (PS), intercropping with continuous cropping of potatoes and soybeans (IC), and intercropping with rotation of potatoes and soybeans (IR) on potato yield and rhizosphere soil microbial communities.

resultsPotato yield varied significantly among different cropping systems, with the PM system producing the lowest yields, whereas the IR and PS systems achieved the highest. Planting patterns exerted a pronounced influence on bacterial α‑diversity, with all indices (Shannon, the number of observed OTUs, Chao1, and ACE) reaching their minimum values under PM, while fungal α‑diversity remained largely unaffected. β-diversity analysis showed that the first two PCoA axes cumulatively explained 49.66% and 31.30% of the variation in bacterial and fungal communities, respectively. Conversely, bacterial community composition showed limited sensitivity to planting patterns, whereas fungal community composition varied significantly among patterns. Across all treatments, the dominant bacterial phyla included Proteobacteria, Actinobacteria, Bacteroidetes, Gemmatimonadetes, Acidobacteria, Firmicutes, and Rhodobacteriota; whereas the dominant fungal phyla were Ascomycota, Basidiomycota, Chytridiomycota, and Glomeromycota. The LEfSe analysis results further showed that the principal biomarkers of the bacterial community under the PS planting pattern belonged to the Bacteroidia, Alphaproteobacteria and Gammaproteobacteria. For fungal community, the biomarkers enriched under different planting patterns were affiliated with the phylum Basidiomycota. Different planting patterns also restructured rhizosphere microbial co-occurrence network. Bacterial co-occurrence network under PM cropping systems exhibited lower node number compared to other planting patterns, whereas fungal network under the IR planting displayed higher stability. Structural Equation Modeling (SEM) further indicated that planting patterns, bacterial diversity, and fungal diversity promoted potato yield, whereas bacterial complexity exerted a suppressive effect. Among these factors, planting pattern emerged as the strongest determinants of potato yield.

conclusionThe increased yield under crop rotation and intercropping systems may be mediated by the modulation of soil microbial communities, specifically by increasing microbial diversity and reducing network complexity.

Indexed as

AgricultureRhizosphereSoil MicrobiologySolanum tuberosumBacteriaBiodiversityChinaFungiGlycine maxMicrobiotaRNA, Ribosomal, 16SSoilRNA, Ribosomal, 16SSoildifferent planting patternsmicrobial communitiesPotatorhizosphere soils

Identifiers

PMID41764436
PMCPMC13059583

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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.