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

A dataset of 85 soybean genotypes evaluated under irrigated and rainfed conditions in Stuttgart, Arkansas from 2023 to 2025. It compares visual canopy wilting scores with UAV-derived multispectral vegetation indices and their correlation with grain yield. The data was authored by Popat Shivaji Pawar and shared under a CC-BY-4.0 license.

Use Cases

• Compare the efficacy of UAV-based vegetation indices versus visual wilting scores for predicting soybean yield under drought stress.
• Identify drought-tolerant soybean genotypes based on unsupervised clustering of UAV-derived canopy response data.
• Analyze the correlation between specific vegetation indices (e.g., NDVI, GNDVI) and grain yield retention in rainfed conditions.

Strengths

• Data spans three consecutive growing seasons (2023-2025), allowing for temporal consistency checks.
• Includes yield data for 85 distinct soybean genotypes from multiple U.S. breeding programs.
• Reports specific correlation coefficients (r = 0.22 to 0.45) between UAV indices and yield, providing quantitative validation.

Limitations

• Row count and specific column definitions are unknown, requiring inspection after download.
• The dataset is small (13.7 KB), indicating limited scope or summary-level data rather than raw observations.
• Geographic coverage is limited to a single research location in Stuttgart, Arkansas.

Provenance

Source

figshare, author Popat Shivaji Pawar.

Collection Method

Data collected from field trials comparing irrigated and rainfed soybean plots, using visual scoring and UAV-based multispectral imagery.

Time Range

2023 to 2025

Freshness

Last updated 2026-06-02 05:40:35.

Geography

Stuttgart, Arkansas, United States.