ArticleBMC microbiology2026
Effects of different planting patterns on potato rhizosphere soil microbial composition and yield.
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.
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1 citing paper in PubMed.
- Microbiome-metabolome interaction reveals rhizosphere ecological, bioactive, and antioxidant responses ofFrontiers in microbiology · 2026Article
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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.
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