A few weeks after Yiannis Ampatzidis started working at the University of Florida Institute of Food and Agricultural Sciences (UF/IFAS) in 2017, Hurricane Irma wreaked havoc on Florida citrus groves. Growers needed to count their trees with precision to get crop insurance, but it was a laborious, time-intensive task.
Photo courtesy of UF/IFAS
Ampatzidis, associate professor of agricultural and biological engineering at the Southwest Florida Research and Education Center, said growers came to him seeking “a faster, more accurate and cost-effective way to create tree inventories.”
Manually counting trees is both expensive and error prone. One grower told Ampatzidis it took him 14 months and two full-time employees to complete a tree inventory.
In addition to storm damage, HLB creates gaps in groves because growers remove dead trees, Ampatzidis said. The disease and its consequences have amplified the need for faster, more accurate tree counts.
The tree inventory inefficiency led Ampatzidis and his lab to develop Agroview, artificial intelligence (AI)-based technology that was named a UF Invention of the Year award winner in 2020.
In 2018, Ampatzidis and Victor Partel, then a research assistant in his lab, began developing the cloud-based technology. They initially used drone imagery to create tree inventories. This required combining field research, AI model development and software engineering.
In the field, they collected high-resolution drone images of tree crops, which they analyzed, using novel AI algorithms to measure tree characteristics.
“This approach was transformative,” Ampatzidis said. “It reduced data collection time by up to 90% and significantly cut costs.”
Once the prototype was functional, UF/IFAS researchers worked with growers to test it rigorously. Over time, Agroview evolved beyond tree inventories.
With contributions from research assistants Lucas Costa and Christian Lacerda, Ampatzidis integrated aerial, multispectral imaging and AI algorithms to create fertility and nutrient application maps, enabling precision agriculture practices and optimizing fertilization and harvesting logistics. Scientists also developed yield-prediction models and a technique to enhance images from airplanes and satellites.
One of Agroview’s most impactful applications is performing rapid damage assessments following extreme weather events like hurricanes, Ampatzidis said.
Two crop insurance companies utilize Agroview for inspections, including counting trees, Ampatzidis added.
“Several growers are exploring the use of Agroview for precision crop management, leveraging its capabilities to optimize nutrient application, assess field health and improve overall productivity,” Ampatzidis said. One grower utilized Agroview to rapidly create tree inventory maps and count gaps in a 2,000-acre grove, allowing him to efficiently order and plant new trees.
“The development of Agroview illustrates the journey from identifying a problem to delivering a commercial AI solution,” Ampatzidis said. “What began as a response to manual inefficiencies has grown into a versatile tool that leverages cutting-edge AI to transform agriculture.”
Source: UF/IFAS
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