Automated Mesoscale Pest Risk Forecast Maps for Agricultural Production and Potential Plant Biosecurity threats
Horticultural Crops Research
2011 Annual Report
1a.Objectives (from AD-416)
Incorporate real-time weather data into disease forecasting models for diseases of grapevines, forage grass, and hops.
1b.Approach (from AD-416)
In conjunction with cooperation growers, virtual weather data and weather maps received will be evaluated for running disease forecasting models in the Willamette Valley. Actual weather data will be collected from automated weather stations installed at three field sites for each crop. Weather data to be used include temperature, daily rainfall, and leaf wetness. Virtual and actual weather data will be collected and compared. Documents reimbursable with OSU (AFRI). Log 39772.
The purpose of this project is to develop, implement and support new methods of modeling and visualizing plant pest and pathogen threats. Technologies being developed include new terrain-sensitive ways to estimate point-based and gridded hourly weather data needed as inputs for disease risk models, improved weather forecasts that provide greater skill in disease prediction, and new ways to visualize disease risk using real-time risk maps and animations. A stepwise, end-user-feedback driven, systems approach to developing these tools is being use to quickly learn from any missteps and allow integration of multiple sources of technology. To date, we have found that information technologies are progressing for the three types of weather data streaming into the spatial modeling system: near real-time (PRISM Group), real-time (IPPC), and forecast (Fox Weather, LLC).