Machine counts early dropped citrus
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.
In addition, the researchers said, growers could use the data to detect where citrus greening is most prevalent in their groves. Growers could then implement management practices, such as fertilization programs and irrigation schedules, to fight greening and other diseases, and minimize the fruit drop. All of that would help cut costs and increase profits.
Currently, fruit drop data are collected by sampling random areas within a specific area and manually counting dropped fruit, which is costly and time consuming.
Other researchers have developed imaging machines but had problems with the color resolution in their images, depending on the time of day pictures were taken. Like Monet paintings of the same subject created at different times of the day, colors can vary greatly depending on the light.
Lee and the UF/IFAS team created an outdoor imaging system with two cameras that deliver the three basic color components -- red, green and blue -- to obtain accurate color images. They were equipped with microprocessors and had special “charge-coupled device” sensors, which turn light into electrons for greater resolution. They were also designed with the conditions of citrus groves in mind: dusty and humid with high temperatures and low-hanging branches. Finally, a global positioning system receiver was attached.
For more information:
Kimberly Moore Wilmoth
University of Florida
Tel: +1 352-294-3302
Email: k.moore.wilmoth@ufl.edu