Researchers at the University of Missouri (Mizzou) have demonstrated that drones equipped with multispectral cameras and AI can assess the health of corn crops more efficiently than traditional handheld methods. By estimating chlorophyll content—a key indicator of nitrogen needs—this approach enables more precise fertilizer application, potentially reducing costs and environmental impact.
The project, led by doctoral student Fengkai Tian in the lab of Associate Professor Jianfeng Zhou, combined drone imagery capturing near-infrared and red-edge wavelengths with soil data. Machine learning models then predicted chlorophyll levels across entire fields with high accuracy. The work was published in Smart Agricultural Technology in collaboration with the USDA Agricultural Research Service.
“Nitrogen application has been one of the biggest challenges facing corn farmers,” Zhou said in an August 2025 Mizzou release. “We want to help farmers increase their yields while using fewer chemicals that can impact the environment. Precision agriculture can help apply nitrogen at the right time, in the right place, in the right amount.”
Mizzou’s work joins a growing body of research using drones and AI for precision agriculture:
The convergence of drone technology and AI-driven analytics is proving valuable not just for nitrogen-intensive crops like corn, but also for soybeans, wheat, and disease-prone specialty crops. Studies show it can:
With agriculture under pressure to balance productivity and sustainability, these innovations are positioning drones and AI as essential tools in next-generation crop management.
