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An integrated modelling and learning framework for real-time online decision assistance in Swiss agriculture

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Description

We are developing an agricultural risk decision assistant based on a unique model that can assess and visualize reliable weather and seasonal climate forecasts, soil data, and crop growth forecasts. Based on real-time and historical weather, climate, soil and crop data and novel learning algorithms, the system calculates expected weather and climate conditions and crop yields and supports farmers with its real-time and online app in terms of production costs, irrigation management, resources required, etc.