Abstract
INTRODUCTION: Agricultural management practices strongly influence soil microbiomes, with broad implications for ecosystem function. Yet, the combined phenotypic and compositional dynamics of rhizosphere microbial communities across conventional and organic farming systems remain poorly characterized, underscoring the need for integrated approaches to understand how management decisions drive microbial assembly and function. METHODS: We investigated microbial communities associated with conventionally and organically cultivated horticultural crops across multiple farms in New York State. To capture both taxonomic and functional dimensions, community composition was characterized using 16S rRNA gene sequencing, and phenotypic traits were assessed with a newly developed single-cell Raman microspectroscopy (SCRS) approach. This dual strategy allowed us to link microbial identity with metabolic potential and adaptive traits. RESULTS: Farming practice significantly shaped microbiome clustering, independent of site or plant species. SCRS-based phenotyping revealed distinct biochemical profiles: organic systems favored lipid-accumulating phenotypes linked to energy storage and stress resilience, whereas conventional systems promoted carbon-rich phenotypes associated with rapid assimilation and biomass production. Network analysis identified Pseudomonas and nitrogen-fixing taxa as ecological hubs in conventional systems, while organic soils were enriched in Bacilli class plant growth-promoting rhizobacteria (e.g., Tumebacillus, Bacillus, Paenibacillus, Brevibacillus) and contained microorganisms bearing antibiotic resistance genes. DISCUSSION: Our findings highlighted that management regimes drive distinct microbial functional traits and community structures. By integrating genotypic and phenotypic analyses, particularly microbial phenotyping via SCRS, we uncovered adaptive traits that differentiate conventional and organic systems, offering new insight into how plant production practices shape microbial assembly and ecological function.