University of Florida

Precision Agriculture Laboratory News

Graduate Student award at 14th ICPA

June 29, 2018
Hao Gan, a PhD student at the Precision Agriculture Lab received the ISPA (International Society of Precision Agriculture) "Outstanding Graduate Student Award" at the 14th ICPA (International Conference on Precision Agricultue), Montreal Canada.
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UF President Kent Fuchs visited the Precision Agriculture Lab

January 19, 2018
UF president Kent Fuchs (right) visited Precision Agriculture Laboratory on January 19th, 2018.
Dr. Lee (middle) was introducing the current research in our lab to President Fuchs. Conveyer experiment President Fuchs and the department head Dr. Dorota Haman were with the Precision Agriculture lab members. From the left to the right are Dr. Haman, Dr. Lee, Chenglin Wang, Arumugam Kalaikannan, President Fuchs, Wansoo Kim, Yang Chen, Hao Gan and Thiago Onofre. Conveyer experiment

An Autonomous Citrus Yield Mapping System

Oct 12th, 2017
Video by Hao Gan

PhD Graduation, 2017

August 21, 2017
A PhD candidate, Daeun "Dana" Choi, from the Precision Agriculture Lab graduated on August 4th, 2017. She is now an assistant professor at the ABE department in Penn State University. Congradulations to Dr. Daeun "Dana" Choi.
Dr. Lee was hooding Dr. Choi during the commencement. Conveyer experiment Dr. Lee and Dr. Choi were in front of one of the UF landmarks, the Bull Gator Statue. Conveyer experiment

Precision Agriculture Lab members went to the 2017 FL ASABE meeting

June 28, 2017
Dr. Wonsuk "Daniel" Lee and PhD student Hao Gan from the Precision Agriculture Lab went to the 2017 Florida section ASABE conference.
Dr. Lee and Hao were in the award dinner on June 23rd, after Hao winning the 2nd place in the Graduate Stuendt Presentation Competition Conveyer experiment Dr. Lee and ABE graduate students were having breakfast with ASABE president Maynard Herron during the FL ASABE. From the left to the right are Thiago Onofre, Hao Gan, Maynard Herron, Joe Sagues and Dr. Daniel Lee. Conveyer experiment

Precision Agriculture Lab developed a postharvest inspection system

March 15, 2017
To enable precision agriculture technology in Florida’s citrus industry, a machine vision system was developed to identify common citrus production problems such as Huanglongbing (HLB), rust mite and wind scar. Objectives of this research were 1) to develop a simultaneous image acquisition system using multiple cameras on a customized conveyor that rotates citrus fruit to allow the imaging hardware to acquire the entire fruit surfaces, 2) to develop a machine vision algorithm with a deep learning technique utilizing a convolutional neural network to accurately inspect the visual characteristics of fruit surface and distinguish HLB-infected citrus from fruit with other common defects and 3) to simulate real-time video processing utilizing a GPU for faster image processing. A real-time video processing with the state-of-the-art deep learning algorithm was developed and tested using uncompressed RGB video streams recorded from the developed hardware. Accuracy of various defect detection by the deep convolutional neural network was 100, 89.7, 94.7, and 88.9 percent for healthy, HLB, rust mite and wind scar classes, respectively. The system can be used in citrus packing houses or developed on a portable conveyor that identifies the severity of the diseases in particular locations and enables site-specific crop management in the field.
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Precision Agriculture Lab Published a patent about a Method for Huanglongbing (HLB) Detection

December 23, 2015
Dr. Wonsuk “Daniel” Lee (the director of the Precision Agriculture Laboratory) and Dr. Alireza Pourreza (PostDoc) in colaboration with Dr. Eran Raveh (Agricultural Research Organization ARO, Bet Dagan, Israel), and Dr. Reza Ehsani (Citrus Research and Education Center, UF) published a patent on their Method for Huanglongbing (HLB) Detection. More information...
Citrus Greening Detection sensor

Precision Agriculture Lab researchers develop machine to count dropped citrus, identify problem areas in groves

August 12, 2015
University of Florida researchers Wonsuk “Daniel” Lee, Daeun "Dana" Choi, Reza Ehsani and Fritz Roka devised a “machine vision system” to count citrus fruit that has dropped early. The device is suitable for various conditions in citrus groves, including addressing problems of variable lighting, giving accurate estimates of dropped fruit counts and providing exact locations of trees with greater fruit drop, indicating a problem area...Full Story
Read more about this invention on The Washington Times, , Brazil Business Today, , noodles, ,, , Agri Marketing, , Southeast AG NET, , and Growing Florida. Citrus Greening Detection sensor

Citrus Greening (HLB) detection sensor

February 25th, 2015
Video by Alireza Pourreza

UF IFAS News released an article about the citrus greening detection sensor that was developed at the precision agriculture laboratory, UF.

January 28, 2015
While a commercially available cure for crop-killing citrus greening remains elusive, University of Florida researchers have developed a tool to help growers combat the insidious disease: an efficient, inexpensive and easy-to-use sensor that can quickly detect whether a tree has been infected. That early warning could give growers enough lead time to destroy plagued trees and save the rest...Full Story
Read more about this invention on Fresh Fruit Portal, Morning AgClips , Growing produce , Florida Research Consortium , and The World News. Citrus Greening Detection sensor

PhD Graduation, 2014

December, 2014
Three PhD candidates, Alireza Pourreza, Mahmoud Agha, and Mazin Saber, from the Precision Agriculture Lab graduated in December, 2014.
From left to right are Alireza Pourreza, Mahmoud Agha, Mazin Saber and their advisor Dr. Daniel Lee. Conveyer experiment