Sorghum-Soybean Intercropping Semiochemical Data for Japanese Beetle Management

Chemical analysis data investigating a semiochemical-based mechanism for managing Popillia japonica (Japanese beetle) through sorghum-soybean intercropping. The dataset was created by Nicole B. Kucherov and includes plant extracts analyzed via GC-MS, with samples collected from field plots in Kansas in 2025. The dataset is 45.4 KB in size and is available in R and CSV formats under a CC0-1.0 license.

Use Cases

• Modeling the effect of intercropping on pest attraction based on volatile organic compound (VOC) profiles.
• Comparing semiochemical emissions from monocropped versus intercropped soybean plants.
• Identifying potential repellent or attractant compounds for Popillia japonica from sorghum and soybean extracts.

Strengths

• Data is derived from controlled field experiments with specific planting dates (May 13, 2025) and sample collection dates (August 5, 2025).
• Chemical analysis was performed using standardized GC-MS methodology with an internal standard.
• Dataset is openly available under a permissive CC0-1.0 license.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (45.4 KB), indicating limited scope.

Provenance

Source

figshare

Collection Method

Field collection of insects and plants, followed by solvent extraction and GC-MS analysis.

Time Range

2025 (specifically July-August for insect collection, May and August for planting and sampling).

Freshness

Last updated 2026-05-01 16:30:55; freshness should be verified.

Geography

Riley and Pottawatomie Counties, Kansas, USA; specifically Kansas State University's North Farm fields.