Location: Water Management and Systems Research
Project Number: 3012-13210-001-022-N
Project Type: Non-Funded Cooperative Agreement
Start Date: Jul 1, 2025
End Date: Jun 30, 2030
Objective:
Will develop a robust, AI-enabled remote sensing framework for detecting and analyzing drought stress in corn, supporting precision irrigation strategies and generating high-throughput phenotypic data to advance breeding for drought tolerance.
Approach:
Data will be collected from ARS research farms, the Limited Irrigation Research Farm (LIRF) in Greeley, CO. The CSU cooperator will provide unmanned aerial-based hyperspectral and LiDAR systems. Aerial images will be collected bi-weekly with these systems from two irrigation experimental fields. These data will be used to characterize drought stress in corn across different spatial and temporal resolutions, plant growth and physiological traits, including leaf area index, plant height, water content, yield and evapotranspiration; and evaluate how irrigation regimes and planting density affect corn development.