Sustainable Agriculture through Artificial Intelligence and Digital Technologies

The aim of the research project 'SAAT' is to demonstrate the technical and economic feasibility of sustainable mixed crops in agriculture. For this purpose, a field planning tool based on explainable AI as well as an AI-controlled sorting robotics module for field crop sorting on autonomous harvesting systems will be developed and the economic efficiency and sustainability of mixed crops compared to monocultures will be measured by means of multidimensional monitoring.

Initial situation

The agricultural sector is one of the largest emitters of greenhouse gases globally, and the common practice of intensive farming and monoculture cultivation are partly responsible for severe species loss through habitat destruction. In addition, climate change requires more climate-resilient cultivation practices in fields. One approach to solving this problem is mixed cropping, for which, however, there is as yet no industrial and thus profitable implementation.

Solution approach

In the 'SAAT' project, solutions are being developed to enable the widespread application of mixed crops. Currently, this is prevented by the technically complex harvest and the insufficiently studied field layout for mixed crops. To develop solutions, partial results are to be achieved in the following steps:

  • Creation of a field planning tool based on explainable AI to determine effective crop-diverse cropping;
  • Measuring profitability and sustainability of mixed crops compared to monocultures using multidimensional monitoring;
  • Creating an AI-controlled sorting robotics module for field crop sorting that can be used in autonomous harvesting systems with mixed crops.

An important aspect of the project is the dissemination of the results to the agricultural industry and the public.

Expected result

As a result, 'SAAT' will identify the potential of mixed cropping through the holistic approach and demonstrate its technical and economic feasibility. The developed technologies as well as identified use cases and databases will serve as a basis for further developments and will demonstrate a sustainable alternative for industrial agriculture.

Benefits for the target group

The results are intended to serve as an incentive and basis for agricultural machinery manufacturers to develop and sell systems suitable for mixed cropping, and to encourage farms to demand and use these systems. If used successfully, higher yields can be achieved in arable farming on more climate-sensitive fields, CO2-intensive fertilizers and pesticides can be saved, and biodiversity as well as soil and water quality can be increased as a result.


  • Machinery and Plant Engineering
  • Research and Development

Topic Area

  • Information Management

Research Focus

  • Informationslogistik

FIR Navigator

  • AI and Data Science
  • JRF Guiding Topic

    • Industry & Environment


    Funding no.
    Project homepage
    Funding information

    Funded by: Federal Ministry for Economic Affairs and Climate Action (BMSK) based on a resolution of the German Bundestag under the funding number 01MN23012B