Remote Sensing Shows Promise for Vegetable Growers
Initial research focused on management of white mold disease in snap beans, one of the most difficult diseases to manage.
Large acreage vegetable fields lend themselves readily to remote sensing technologies. Çornell Vegetable Processing Vegetable Specialist Julie Kikkert and Cornell University Vegetable Pathologist, Sarah Pethybridge have continued a three-year partnership with scientists from the Rochester Institute of Technology (RIT) Center for Imaging Sciences.
Initial investigations, funded by a grant from the USDA CARE Program have focused on management of white mold disease in snap beans, one of the most difficult diseases to manage. The project focuses on risk modeling and detection of crop flowering.
When favorable environmental conditions exist, spores of the fungus infect bean flowers and the infection later spreads to the pods making them unmarketable. So far, the project has narrowed down the useful spectral wavelengths, which will make the technology more affordable to the industry. Additionally, the technology has been highly accurate at detecting flowering in snap beans, critical knowledge for the timing of fungicide sprays.
In 2018, the group has expanded their work to table beets, where imaging of crop emergence and growth is being correlated with beet root quality and yield. This project was initially funded by Love Beets USA. The group was also recently funded by a large NSF grant to RIT (subcontract to Cornell) and will provide student training, as well as focus on disease risk modeling, harvest scheduling, and yield modeling. The project is also supported by advisory team members from Seneca Foods, Farm Fresh First, Love Beets, Agrinetix, Harris Corporation, and Headwall Photonics.