PhenoRob CP5.2 - New Field Arrangements

One approach to enhancing agricultural sustainability is through spatial and temporal crop diversification, which is becoming more promising with advances in agricultural machinery. At the patchCROP experiment (https://comm.zalf.de/sites/patchcrop/SitePages/Homepage.aspx) two diversified crop rotations have been implemented according to the soil conditions in the field.

 The objective of this joint effort within the PhenoRob Cluster of Excellence between the Crop Science Department of the University of Bonn and Forschungszentrum Jülich, is to use proximal soil sensing to derive model compatible soil information and therefore enable agroecosystem models to capture the within field heterogeneity of crop and ecosystem services at the experimental site.

 Soil plays a pivotal role in nurturing plant growth and significantly impacts agricultural productivity. Near-surface geophysical methods have emerged as powerful tools for achieving high-resolution soil characterization. Among these methods, Electromagnetic Induction (EMI) stands out as a widely employed near-surface geophysical and proximal sensing technique. EMI provides insights into soil attributes such as texture, layering, moisture content, and compaction. Our project will investigate and map the sub-surface soil structure on a field scale. Additionally, we aim to delineate distinct agricultural management zones within the patchCROP experimental site. To accomplish this, we will integrate EMI data, high-resolution satellite imagery, and historical yield data using (machine learning) clustering algorithms.

 The SIMPLACE modelling framework has been used to calibrate and validate an agroecosystem model using crop growth and management data, that was collected at the patchCROP experiment. This model can now serve as a tool to better understand and design diversified cropping systems and evaluate them regarding the provision of ecosystems services. Furthermore an intensive soil sampling campaign was conducted to gain insights into the soil heterogeneity at the experimental site, since these impact the water holding capacity of the soil and consequently crop growth dynamics. We also aim to use the model as a tool to design and evaluate spatially adapted management in terms of crop rotation and crop management in respect to the diverse soil characteristics. Therefore, an additional analysis regarding the model's ability to simulate soil water dynamics has been carried out, which showed that the model is able to capture the seasonal water dynamics of the diversified cropping system under heterogeneous soil conditions. In the next steps a combination of agroecosystem models and soil zones derived from proximally sensed soil data will be used to optimize diversified cropping systems based on nutrient and residue management for the provision and regulation of ecosystem services under current and future climate conditions.

Crop Sience Department:
Prof. Dr. Frank Ewert
Dr. Thomas Gaiser
Dr. Ixchel M. Hernandez-Ochoa (Postdoc)
Anna Engels (PhD student)

 Forschungszentrum Jülich:
Prof. Dr. Sander Huisman
Salar Saaed