Root-Associated Bacterial Community Dynamics in Healthy and Diseased Soybeans

Absolute quantitative sequencing data from a study of soybean root rot in Heilongjiang black soil fields. The research analyzed soil chemical properties and bacterial communities across bulk soil, endosphere, rhizoplane, and rhizosphere compartments. Authored by Chunjing Yu and last updated in April 2026, the dataset is 501.2 KB and shared under a CC-BY-4.0 license.

Use Cases

• Compare bacterial community assembly mechanisms based on deterministic processes described in the results.
• Identify key bacterial taxa correlated with soil nutrients based on random forest and correlation analyses mentioned.
• Analyze changes in co-occurrence network complexity based on module hubs and connectors identified in healthy versus diseased groups.
• Assess the impact of root rot on soil chemical properties based on reported changes in SOC, TN, AN, AP, AK, and pH.

Strengths

• Uses absolute quantitative sequencing, which the description states compensates for defects of relative abundance methods.
• Includes measurements for six specific soil chemical properties: pH, SOC, TN, AN, AP, and AK.
• Analysis identifies specific bacterial ASVs (e.g., ASV115, ASV16) and their correlations with environmental factors.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to samples collected only from Heilongjiang black soil fields.

Provenance

Source

figshare

Collection Method

Samples collected from bulk soil, endosphere, rhizoplane, and rhizosphere of soybeans; soil chemistry analyzed and absolute quantitative 16S rRNA sequencing performed.

Freshness

Last updated 2026-04-22 06:32:29; freshness should be verified.

Geography

Black soil fields in Heilongjiang, China.