Soybean UAV Phenotyping and Yield Data for Drought Tolerance Evaluation, 2023-2025

Popat Shivaji Pawar's dataset compares UAV-based multispectral phenotyping against visual canopy wilting scores for evaluating soybean drought tolerance and yield retention. The data covers 85 genotypes from breeding programs in Arkansas, Missouri, Kansas, and North Carolina, tested under irrigated and rainfed conditions in Stuttgart, Arkansas from 2023 to 2025. UAV-derived vegetation indices showed significant correlations with yield, while visual scores showed weak associations.

Use Cases

• Comparing the efficacy of UAV-derived vegetation indices versus visual canopy wilting scores for predicting soybean yield under drought stress.
• Clustering soybean genotypes into distinct canopy stress response groups based on multispectral indices like ARI, CIG, and NDVI.
• Analyzing the year-to-year consistency of drought tolerance phenotypes and their relationship with grain yield retention.
• Training models to identify high-yielding genotypes under rainfed conditions using objective, quantitative remote sensing data.

Strengths

• Data spans three consecutive growing seasons (2023 to 2025), allowing for temporal consistency checks.
• Includes 85 soybean genotypes from multiple U.S. breeding programs, providing genetic diversity.
• UAV-derived indices showed significant correlations with yield (r = 0.22 to 0.45), providing a quantitative basis for analysis.
• Dataset is openly licensed under CC-BY-4.0, facilitating reuse and sharing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is geographically limited to a single test location in Stuttgart, Arkansas.

Provenance

Source

Popat Shivaji Pawar via figshare.

Collection Method

Field experiment evaluating soybean genotypes under irrigated and rainfed conditions, using UAV-based multispectral imagery and visual canopy wilting scores.

Time Range

2023 to 2025

Freshness

Last updated 2026-06-02 05:40:34; freshness should be verified.

Geography

Stuttgart, Arkansas, United States