Proceedings
Year
| Filter results3 paper(s) found. |
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1. Citrus Greening Disease Detection Using Airborne Multispectral And Hyperspectral ImagingCitrus greening disease (Huanglongbing or HLB) has become a major catastrophic disease in Florida’s $9 billion citrus industry since 2005, and continued to be spread to other parts of the U.S. There is no known cure for this disease. As of October 2009, citrus trees in 2,702 different sections (square mile) in 34 counties were infected in Florida. A set of hyperspectral imageries were used to develop disease detection algorithms using image-derived spectral library, the mixture tu... W. Lee, A. Kumar, R. Ehsani, C. Yang, L.G. Albrigo, |
2. Development Of Ground-based Sensor System For Automated Agricultural Vehicle To Detect Diseases In Citrus PlantationsAn integrated USDA-funded project involving Carnegie Mellon University, University of Florida, Cornell University and John Deere is ongoing, to develop an autonomous tractors for sustainable specialty crop farming. The research teams have come together to develop an automated system for detecting plant stress, estimating yields, and reducing chemical usage through precision spraying for specialty crops. The goals of the automation process are to reduce the tractor-related labor costs, r... S. Sankaran, R. Ehsani, A. Mishra, C. Dima |
3. HLB Detection Using Hyperspectral RadiometryThe need for sustainable agriculture requires the adoption of low input, long-term and cost-effective strategies to overcome the adverse impact of disease and nutritional deficiencies on citrus groves. In this context, early detection of diseased trees has become an important topic in the citrus industry. Multiple factors make field assessment of disease conditions a challenging task: the non-specific nature of many symptoms, the possibility of having localized affections in only certain area... J. Gonzalez-mora, C. Vallespi gonzalez, R. Ehsani, C.S. Dima, G. Duhachek |