MikroKIez

Microorganisms living in the soil play a key role in soil fertility, plant health and the fixation or release of greenhouse gases and therefore the climate. However, the large-scale recording of the composition of microorganisms in the soil has so far been expensive and requires several complex work steps. The MikroKIez project aims to develop a novel solution that does not require direct measurement in the soil. With the help of satellite and weather data, the microbial diversity in the soil is to be predicted using a model based on artificial intelligence (AI). To create the AI model, available genetic data of the microorganisms will be combined with environmental data (soil data from satellites and weather data from weather stations). AI methods are then applied to create prediction models. Research is carried out to determine which environmental parameters have the greatest predictive power for microbial diversity and how accurate the predictions are.

The first phase of the project focuses on three test areas and produces initial scientific work that enables an effective and rapid entry into a second phase. In addition, the further research concept will be developed in more detail and the application for the second phase will be submitted.

In a possible second phase, the study area will be expanded and the focus will be placed on agricultural land. By monitoring the soil quality on agricultural land, for example, recommendations for action on fertilizer input or for the cultivation of certain crop species can be derived. Another application is the prediction of microbial greenhouse gas emissions, which can improve climate models.