By Jamie Martin
A recent University of Florida study reveals how drone technology and artificial intelligence (AI) can support hemp farmers by enhancing crop health and optimizing fertilizer use.
Conducted by researchers at the UF Institute of Food and Agricultural Sciences (UF/IFAS) Tropical Research and Education Center (TREC) in Homestead, the study explored how aerial imaging can help determine the right amount of nitrogen fertilizer for hemp growth and flower production.
This innovative approach has the potential to reduce costs for farmers while promoting environmental sustainability.
“Farmers are looking for ways to assess their crops throughout the year to make informed fertilizer decisions,” said Zack Brym, associate professor of agronomy at UF/IFAS TREC.
By utilizing drones with red and near-infrared (NIR) sensors, researchers could monitor plant health by observing variations in color. “We’ve shown that farmers with access to aerial images using red and near infrared (NIR) detection can spot differences in plant health by their color when scanning their fields,” Brym explained.
This method is especially important in Florida, where frequent fertilizer applications are required due to the rapid movement of nutrients through sandy soils.
“Technology like the use of drone imaging will help determine how much fertilizer might be needed mid-season, promoting more efficient use of resources and supporting sustainable farming practices,” Brym added.
The study focused on a popular floral hemp variety called ‘Wife,’ grown over three years with six different nitrogen levels. Drone flights captured images of the crops one month before harvest, which helped assess plant vigor and health. The ideal nitrogen range for optimal flower yield was found to be between 112 and 168 kilograms per hectare, or roughly 100 to 150 pounds per acre.
Researchers also incorporated AI to analyze canopy reflectance, a measure of how much light bounces off the plants. While the technology was useful, it needed refinement.
“I was eager to see how effective the automated AI would be at identifying hemp canopy,” said Tamara Serrano, a lead author and former agroecology graduate student on Brym’s team. “To my surprise, the process wasn’t as seamless as expected and required manual corrections to address errors in canopy identification.”
Despite challenges, the study confirms drone imaging’s value in guiding fertilizer practices and supporting the growing hemp industry.
Photo Credit: gettyimages-seregalsv
Categories: National