Combined applications of organic bran Fertilizer, biochar and microbial inoculants control tobacco soil-borne diseases by recruiting beneficial rhizosphere microbes and enhancing soil quality

This dataset supports the research article titled "Combined Applications of Organic Bran Fertilizer, Biochar, and Microbial Inoculants Control Tobacco Soil-Borne Diseases by Recruiting Beneficial Rhizosphere Microbes and Enhancing Soil Quality". It systematically compiles multi-dimensional experimental data related to tobacco soil-borne disease management, including the following core components:

1. Soil-borne disease occurrence data: Statistics on incidence rate, disease index, and control efficacy of tobacco Ralstonia solanacearum (bacterial wilt), Phytophthora nicotianae (black shank), and root rot at seedling, rosette, and maturity stages, covering different amendment combination treatments and control groups;

2. Microbial community data: Raw and analyzed high-throughput sequencing data of rhizosphere microbes, including taxonomic annotation tables, species abundance matrices, and α/β diversity indices (e.g., Shannon, Simpson, and PCoA results) for Operational Taxonomic Units (OTUs) and Amplicon Sequence Variants (ASVs), as well as relative abundance data of key beneficial microbes (e.g., Bacillus, Pseudomonas, Trichoderma);

3. Functional prediction and pathway analysis data: KEGG pathway annotation results based on OTU/ASV data, including KEGG Orthology (KO) classification of functional genes, metabolic pathway enrichment analysis data (e.g., carbon metabolism, nitrogen metabolism, and disease defense-related pathways), and predicted abundances of microbial functional groups;

4. Soil enzyme activity data: Determined values of soil enzyme activities related to soil nutrient transformation and disease control (e.g., urease, sucrase, catalase, polyphenol oxidase, phosphatase), including dynamic monitoring data before and after amendment application;

5. Structural Equation Model (SEM) data: Raw variable data required for SEM construction (including disease severity, microbial community diversity, soil physicochemical properties, enzyme activities, and amendment application parameters), model fitting indices (e.g., χ²/df, RMSEA, GFI), and output results such as path coefficients and variance explanation rates.

All data were derived from field and pot experiments with three biological replicates, and their reliability was verified through statistical tests including one-way ANOVA and correlation analysis. This dataset provides comprehensive data support for deciphering the microbial mechanisms and soil ecological effects of combined amendment application in controlling tobacco soil-borne diseases.