Digital silage
AI-based intelligent silage management for early detection of bottlenecks due to weather extremes and increasing resource efficiency in the ensiling and utilization of whole plants
Brief description
The aim of this project is to introduce automated and AI-based controlling for forage production. In addition to the losses in forage production, the daily feed ranges and quality parameters such as silage density and feed rate are recorded and processed completely automatically for the first time. Together with feed analysis and ration calculation, all data on forage production is collected digitally.
The relevant key figures and balances for farms are collected and the parameters are made intuitively usable via an interactive front end on the farmer's end device. In the second step, the collected data is evaluated for the farms and points for improving efficiency are developed. In the following year, these points will be implemented on the farms in a targeted manner and adapted to the usage requirements. Together with the farms, an automated controlling system for forage production will be introduced, which will make it possible to react to undesirable developments in real time.
The aim is to increase the efficiency of silage management by 5% and eliminate avoidable losses. A 5% increase in resource efficiency in relation to the total area under cultivation in Schleswig-Holstein would mean that 8150 ha of maize cultivation area and 16,950 ha of grassland would be freed up for alternative forms of use by avoiding losses while maintaining the same level of production. Operating resources such as diesel, fertilizer and pesticides would also be saved to a considerable extent. These measures actively contribute to achieving climate neutrality in agriculture by 2045.
