A long-term field experiment compared the effects of organic and conventional farming systems on soil microbial diversity. Organic farming increased microbial richness, decreased evenness, and shifted the structure of the soil microbiota compared to conventional systems. These effects were largely due to the use and quality of organic fertilizers, as differences were smaller in conventional systems with integrated fertilization. The plant protection regime had a subordinate impact. Systems without manure had a dispersed, functionally versatile community, while those with organic fertilizer had specific microbial guilds involved in degrading complex organic compounds. High-throughput pyrosequencing revealed specific structural shifts in microbial taxa, offering potential for managing the soil environment by promoting beneficial and suppressing detrimental organisms. The study found that farming systems and crop types significantly influenced bacterial and fungal β-diversity. Bacterial and fungal communities in different farming systems were on average 10% and 13% dissimilar, respectively. Crop type had a stronger effect on fungi than on bacteria. Management effects were accompanied by spatial and temporal variability. The application of FYM (farmyard manure) had the strongest effect on β-diversity, separating data on the first CAP axis with high canonical correlations. Organic versus conventional systems separated data on the second CAP axis. Differences in β-diversity were driven by dissimilarity rather than dispersion in FYM-based systems. Management effects on α-diversity were less robust, but significant shifts were detected. Crop type had no significant effect on α-diversity. FYM-amended soils showed increasing richness and decreasing evenness. CONMIN had the lowest richness and highest evenness, while BIODYN showed the opposite trend. Temporal component significantly influenced most parameters, but the 'time × management' interaction for bacterial richness required cautious interpretation. Soil chemical properties showed the most pronounced differences between the unfertilized system NOFERT and other systems. Soil pH, organic carbon, and total nitrogen were significantly higher in BIODYN. Soil P was higher in CONFYM, and soil Mg was higher in CONMIN. All six chemical parameters were significantly co-correlated, with the strongest correlations between organic carbon and total nitrogen, and between P and K. Taxonomic composition revealed that 1037 bacterial and 592 fungal OTUs were unclassified at the phylum level. The most abundant phyla included Actinobacteria and Acidobacteria, which showed a clear accumulation of management-sensitive OTUs. A bipartite association network showed that 628 significant OTUs were associated with specific farming systems or combinations. These OTUs were broadly distributed across the taxonomic tree, with certain phyla showing clear accumulation of management-sensitive OTUs. Co-correlation networks identified groups where members responded uniformly to specific influences. Networks for Acidobacteria, Actinobacteria, Gemmatimonadetes, and Bacteroidetes had high density, while Basidiomycota and Ascomycota wereA long-term field experiment compared the effects of organic and conventional farming systems on soil microbial diversity. Organic farming increased microbial richness, decreased evenness, and shifted the structure of the soil microbiota compared to conventional systems. These effects were largely due to the use and quality of organic fertilizers, as differences were smaller in conventional systems with integrated fertilization. The plant protection regime had a subordinate impact. Systems without manure had a dispersed, functionally versatile community, while those with organic fertilizer had specific microbial guilds involved in degrading complex organic compounds. High-throughput pyrosequencing revealed specific structural shifts in microbial taxa, offering potential for managing the soil environment by promoting beneficial and suppressing detrimental organisms. The study found that farming systems and crop types significantly influenced bacterial and fungal β-diversity. Bacterial and fungal communities in different farming systems were on average 10% and 13% dissimilar, respectively. Crop type had a stronger effect on fungi than on bacteria. Management effects were accompanied by spatial and temporal variability. The application of FYM (farmyard manure) had the strongest effect on β-diversity, separating data on the first CAP axis with high canonical correlations. Organic versus conventional systems separated data on the second CAP axis. Differences in β-diversity were driven by dissimilarity rather than dispersion in FYM-based systems. Management effects on α-diversity were less robust, but significant shifts were detected. Crop type had no significant effect on α-diversity. FYM-amended soils showed increasing richness and decreasing evenness. CONMIN had the lowest richness and highest evenness, while BIODYN showed the opposite trend. Temporal component significantly influenced most parameters, but the 'time × management' interaction for bacterial richness required cautious interpretation. Soil chemical properties showed the most pronounced differences between the unfertilized system NOFERT and other systems. Soil pH, organic carbon, and total nitrogen were significantly higher in BIODYN. Soil P was higher in CONFYM, and soil Mg was higher in CONMIN. All six chemical parameters were significantly co-correlated, with the strongest correlations between organic carbon and total nitrogen, and between P and K. Taxonomic composition revealed that 1037 bacterial and 592 fungal OTUs were unclassified at the phylum level. The most abundant phyla included Actinobacteria and Acidobacteria, which showed a clear accumulation of management-sensitive OTUs. A bipartite association network showed that 628 significant OTUs were associated with specific farming systems or combinations. These OTUs were broadly distributed across the taxonomic tree, with certain phyla showing clear accumulation of management-sensitive OTUs. Co-correlation networks identified groups where members responded uniformly to specific influences. Networks for Acidobacteria, Actinobacteria, Gemmatimonadetes, and Bacteroidetes had high density, while Basidiomycota and Ascomycota were