AI-powered app can detect poison ivy

Poison ivy ranks among the most medically problematic plants. Up to 50 million people worldwide suffer annually from rashes caused by contact with the plant, a climbing, woody vine native to the United States, Canada, Mexico, Bermuda, the Western Bahamas and several areas in Asia.

It’s found on farms, in woods, landscapes, fields, hiking trails and other open spaces. So, if you go to those places, you’re susceptible to irritation caused by poison ivy, which can lead to reactions that require medical attention. Worse, most people don’t know poison ivy when they see it.

To find poison ivy before it finds you, University of Florida scientists published a new study in which they use artificial intelligence to confirm that an app can identify poison ivy.

Nathan Boyd. Courtesy, UF/IFAS photography.

Nathan Boyd, a professor of horticultural sciences at the UF/IFAS Gulf Coast Research and Education Center near Tampa, led the research. Renato Herrig, a post-doctoral researcher in Boyd’s lab, designed the app.

“We were the first to do this, and it was designed as a tool for hikers or others working outdoors,” Boyd said. “The app uses a camera to identify in real-time if poison ivy is present and provides you with a measure of certainty for the detection. It also functions even if you don’t have connectivity to the internet.”

The next step is to make the app commercially available, and there’s no timetable for that yet, Boyd said.

For the study, researchers collected thousands of images of poison ivy from five locations: Alderman’s Ford Conservation Park and Hillsborough River State Park, both in Florida; Eufala National Wildlife Refuge  in Alabama; York River State Park in Virgina and Fall Creek Falls State Park in Tennessee.

They labeled images, and in each image, scientists put boxes around the leaves and stems of the plant. The boxed images were critical because poison ivy has a unique leaf arrangement and shape. Scientists use those characteristics to identify the plant.

They then ran the images through AI programs and taught a computer to recognize which plants are poison ivy. They also included images of plants that are not poison ivy or plants that look like poison ivy to be certain the computer learns to distinguish them.

“We believe that by integrating an object-detection algorithm, public health and plant science, our research can encourage and support further investigations to understand poison ivy distribution and minimize health concerns,” Boyd said. In their future work UF/IFAS researchers hope to expand the use of the app to identify more noxious plants.


The mission of the University of Florida Institute of Food and Agricultural Sciences (UF/IFAS) is to develop knowledge relevant to agricultural, human and natural resources and to make that knowledge available to sustain and enhance the quality of human life. With more than a dozen research facilities, 67 county Extension offices, and award-winning students and faculty in the UF College of Agricultural and Life Sciences, UF/IFAS brings science-based solutions to the state’s agricultural and natural resources industries, and all Florida residents.  |  @UF_IFAS

About AI at UF

The University of Florida is making artificial intelligence the centerpiece of a major, long-term initiative that combines world-class research infrastructure, cutting-edge research and a transformational approach to curriculum. UF is committed to building the nation’s first AI University by offering artificial intelligence courses to all students in its 16 colleges through our AI Across the Curriculum program. Our faculty and students can analyze vast amounts of data that can impact our country’s biggest challenges with HiPerGator, the most powerful, university-owned supercomputer in the nation.



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Posted: January 23, 2024

Category: UF/IFAS
Tags: Algorithm, App, Artificial Intelligence, Detection, Gulf Coast Research And Education Center, Horticultural Sciences, Nathan Boyd, Poison Ivy, Precision-ag, Renato Herrig

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