Date of this Version
Published in 2005 IEEE International Conference on Granular Computing, Volume 1, pp. 128 - 130. doi: 0.1109/GRC.2005.1547250
Plant diseases, insects, and insect vectored viruses can do extensive damages to host plants and result in severe yield losses. It is reported that overall about 15% of the U.S. crop production is lost annually to infectious crop diseases despite the fact that American agricultural producers are using cutting-edge disease control technology and pesticide products, and adapting newly bred disease-resistant crop cultivars and hybrids. This Nebraska Crop Surveillance Network project has accomplished three objectives. First, it uses advanced computer, database and network technology to automate experimental field data collection, processing and centralization storage processes, thus relieving research staff from tedious and redundant work while also reducing the likelihood of human error during the data collection and transcription processes. Second, it tracks soybean disease infection patterns under different management, environmental and soil conditions during the growing season in Nebraska. Third, it produces an online graphical visualization system based on the near real-time data collected from the experimental field to simulate, monitor and predict soybean disease infection patterns. These graphical representations of patterns are intended to help convey disease infection related concepts and disease control decision-making information to agriculturalists. The online tracking system is designed to help Nebraska farmers to make the right decisions on their daily agricultural practices, such as choosing the right planting date and applying the right pesticide to minimize plant damage and maximize yield potential. We use a Zope web server, a MySQL relational database, and a graphic rendering product, ZGDChart to build this data visualization system which completely automates data gathering and storage processes and enables users to observe a graphical representation of plant disease infection patterns during the growing season in Nebraska under different management and environmental conditions.