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Niedersächsisches Ministerium für Ernährung, Landwirtschaft und Verbraucherschutz
Lower Saxony and Hamburg
Calenberger Straße 2
30169 Hannover
Website: External link to the authority
Predictive Plant Production
Due to increasingly dry summers and decreasing water availability, horticultural businesses are increasingly asking for more efficient irrigation. Today, farm irrigation and fertilization is mostly done according to the current situation in the crops. In this context, the weather report, which is adapted to the agricultural sector, is the only useful prediction for irrigation control. Time- and personnel-consuming analyses or measurements are also rarely carried out in practice. The Predictive Plant Production project is basically about an AI to support plant-producing companies in resource-saving plant production. The aim of the project is to research a system that monitors the environmental conditions of these plants in order to determine the necessary cultivation measures. For this purpose, moisture, temperature and salinity are determined in soils or substrates representative for the crop. In addition, local weather data will be collected and AI will be used to learn the individual local conditions of each site. Based on this, predictive models will be trained and irrigation, fertilization and temperature control will be automated.
2025-01-27 09:45:46
Various sensor systems for measuring substrate moisture and salinity were tested and compared with each other. In doing so, their measurement accuracy and the measurement methods used are thoroughly evaluated. Over several measurement seasons, data from sensors were systematically collected and weather stations. This extensive collection of data forms the basis for further analyses and model developments.
The different measuring systems have been calibrated in order to achieve a uniform scale. This enables data evaluation across different devices. A physical model has been developed that can be used under consideration of various environmental parameters enables a precise prediction of the moisture conditions in the substrate. A growth model was created that predicts plant growth depending on solar radiation and irrigation. This model helps to create the optimal conditions for the determine plant growth.
Rural development 2014-2020 for Operational Groups (in the sense of Art 56 of Reg.1305/2013)
OFFIS Institut für Informatik
Escherweg 2
26121 Oldenburg
Phone: 0441/9722185
Email: meyer@offis.de
2021
completed
484,036
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