By Blake Jackson
University of Missouri Extension specialist Rusty Lee used drone and artificial intelligence technology last growing season to help identify nitrogen deficiency problems in a Montgomery County corn field.
The issue stemmed from a malfunctioning toolbar on a fertilizer applicator, which caused uneven nutrient application across approximately 73 acres.
The producer noticed irregular corn growth when plants reached the V-5 stage. Large sections of pale and weakened corn suggested nitrogen stress, prompting the farmer to seek assistance from MU Extension.
Lee used a drone equipped with multispectral imaging technology to scan the affected fields and detect areas lacking chlorophyll, a key indicator of nitrogen deficiency.
After collecting the images, the data was combined into detailed field maps that identified the most severely affected areas. This allowed the producer to make targeted rescue nitrogen applications instead of treating the entire field.
According to Lee, the approach helped preserve corn yields in areas that otherwise would have suffered significant production losses.
MU Extension research shows that corn can still benefit from nitrogen applications made before tasseling. Areas that did not receive corrective nitrogen treatments produced noticeably lower yields.
Lee said modern precision agriculture tools have improved dramatically in recent years. Farmers can now measure nutrient needs and apply fertilizer at variable rates within the same field, increasing efficiency while reducing unnecessary input costs.
Before drones and AI technology became available, producers often relied on hand-held crop sensors or laboratory testing to evaluate fertilizer needs. Those methods were slower, more labor-intensive and less practical for large farming operations.
The project also connects with broader research at the University of Missouri led by doctoral student Fengkai Tian and associate professor Jianfeng Zhou, whose team is studying digital agriculture technologies that combine artificial intelligence, engineering and plant science to improve crop management and farm profitability.
Recommended Practices for Crop Management:
- Use drones during the V-5 growth stage to identify uneven stands and nutrient stress before damage becomes irreversible.
- Utilize drones with multispectral sensors to map chlorophyll levels, detecting deficiencies invisible to the naked eye.
- Use diagnostic maps to perform site-specific nitrogen applications before the tasseling stage to recover lost yield potential.
- Transition from uniform field treatments to variable-rate applications to reduce input costs and maximize fertilizer efficiency.
- Replace labor-intensive handheld sensors and slow laboratory testing with real-time AI and drone-based field mapping.
Photo Credit: gettyimages-seregalsv
Categories: Missouri, Crops