Pest and Weather Modeling Tools
- Degree-Day and Prediction Tools
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Disease Risk and Alert Maps
- Boxwood Blight (also available as Apple iOS and Android apps)
- Fire Blight
- Tomato Black Mold
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Tomato-Potato Smith Late Blight
- Pest-specific and Crop-Specific Tools
Program Goals
Weather and climate are important drivers of agricultural production, and particularly of pest and disease activity. USPEST.ORG has evolved over the last 20 years into a multi-crop and multi-pest modeling platform.
The growth and development of plants and invertebrates is influenced by surrounding temperature and moisture levels. This development is often researched and published to create practical decision support models for growers and other agricultural pest management decision makers. For example, the first flight of pests such as the codling moth and filbert moth (key pests of apples and hazelnuts, respectively) can be predicted using well-researched patterns and models. The risk of infection from multiple crop diseases such as late blight in potato, and powdery mildew in grapes and hops, can also be forecasted using these models.
These models benefit from multiple types of weather forecasts, and are driven by hourly and daily weather data. With these models, growers and other agricultural decision makers can better assess their past, current, and future situation to bring more precision to their pest management activities, and reduce unnecessary treatments.
The USPEST.ORG website is national in scope, and is particularly important for underserved regions--crops, areas, or pests that may not be well represented by a state-level decision support system. Through regional and national funding sources, we have been able to add value to simple crop and pest models by developing numerous model interfaces, forecasts, and model visualization tools, with added quality assurance. We also provide support and modeling tools to protect agricultural commodities from many invasive pest species.
The overall goal of this program is to continue to build and streamline these decision support tools for usage all agricultural commodities in the US, as a key component of Integrated Pest Management (IPM).