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IoT

Pest and Disease Advisory

Pest and Disease advisory an online decision-support system for farmers, promotes sustainable farming and optimizes farm operations. It does this by combining global data with local field data. The app also provides reliable forecasts of fungal disease pressure. This allows for more efficient spraying programs, resulting in reduced fungicides, labor and environmental costs. Advisory  can access the forecasted risks of downy mildew, powdery mildew and botrytis on individualized dashboards that contain user-friendly maps, tables and graphs at field level.

Next to weather variability, the occurrence of pests and diseases in crops is one of the main reasons for yield loss. Atmospheric conditions are the major driver for the development and spread of crop pests and diseases. When conditions are humid, diseases can easily develop, while the direction of migratory pests is among other things controlled by wind direction and rainfall patterns. Weather Impact forecasts if future weather conditions are suitable for the development of pest and disease.

When future atmospheric conditions are combined with land-use of crop stage data, for example from weather data, these forecasts can be further specified and converted into risk areas. This enables us to not only provide a probability for future outbreaks, but also identify the regions that are most at risk.

Scientific disease risk models are used to determine whether the weather conditions are favorable for an infection of fungal diseases. Advanced weather forecasts serve as input for these models to calculate the infection risk for the coming days

Benefits

Optimize your farm management, discover the benefits of using the Pest and Disease Advisory:

• Reliable forecasting up to five days ahead to optimize preventative farm  operations

• Best weather data available (Open Weather) to make reliable estimations

• Best fungal disease models available

• Zero-tolerance approach to disease pressures

• Reduce spraying costs up to 40%

• Save the environment

• Save human health

• Optimize logistical planning

• Optimize farm  management practices: depending on risk level

• User-friendly with easy to understand colour-coded graphs and models

• Information and knowledge are stored and transferable

• Low maintenance and minimal data input

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