As a crop scientist with a high level of understanding of systemic relationships in agroecological systems, I have devoted myself to interdisciplinary research in the fields of sustainable crop science, soil science, modeling, climate change protection and adaption, and novel digital tools. My research interests include:
- Development and testing of innovative diverse (organic) cropping systems (e.g. identify promising partners and field designs in intercropping)
- Quantification of ecosystem (dis)services including yield and greenhouse gases (measurements and observations)
- Model-based improvement of the understanding of (Gx)G×E×M interactions (focus: water, N, roots) in cropping systems
- Identification of promising crop traits and field designs for future climates
- Short- and long-term soil organic carbon, soil water and nutrient dynamics
- Simulation of the water dynamics from the soil through the soil, root, shoot and stomata into the atmosphere using agro-ecosystem models.
- Roots: field observations and modelling root growth with focus on the effect of nutrient deficiency and/or drought stress on root growth
- Digital Farming / Development and application of AI tools in agriculture (e.g. detecting pollinators in images and videos), digital twin development
After studying agricultural sciences at the Technical University of Munich and completing my doctorate on crop modelling and irrigation at the Chair of Hydrology at the Technical University of Dresden, I have been a PostDoc at the Institute of Crop Sciences and Resource Conservation, Crop Sciences Group, University of Bonn since 2016. Since May 2020, I am research group leader at the Chair of Crop Science as part of the PhenoRob cluster of excellence (DFG). The research group entitled “Optimizing crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models” strengthens PhenoRob especially at the interface of crop modeling, ecology, crop and soil science. I actively participate in the PhenoRob cluster of excellence in four out of six core projects. My research within PhenoRob includes 1) data analytics, simulation of sensor signals (sEIT), and process-based forecasting of root and crop growth, soil dynamics and impacts of potential interventions, 2) robot-based selective weeding for improved biodiversity, 3) optimization of crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models (my research group), 4) phenotyping over scales combining destructive on-site measurements such as root and shoot obervations with UAV-based cameras, and 5) non-destructive diagnosis of nutrient deficiencies using deep learning algorithms. Before leading the research group I worked as a PostDoc at the same Chair in the BMBF funded project “Soil3 – Sustainable Subsoil Management” which aims to explore how and to which degree the subsoil can be managed to secure or even increase plant yields by improving the overall nutrient and water use efficiency of crops.
Current projects:
1. DFG Excellence cluster PhenoRob https://www.phenorob.de/
- Junior Research Group leader in Core Project CP5: New Field Arrangements (group title: “Optimizing crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models”)
Crop mixtures offer multiple advantages over traditional sole crops, including production of greater yield on a given piece of land, complementary resource use in time and space among different species; reduction of production risk due to complementarity; improved weed suppression; increased N availability for the subsequent crop due to legumes; decreased nitrate leaching by non-legume cover crops; improved soil fertility, soil organic matter content, and carbon sequestration; increased biodiversity, and maintainance and regeneration of ecosystem services. The numerous processes and mechanisms involved in crop mixtures highlight the need to deal with their complexity by combining concepts from diverse disciplines (agronomy, physiology and ecology) and demand for further information on crop species combination, arrangements and proportion as factors that affect mixtures. Crop simulation models are widely recognized as useful tools that examine cause and effect relationships in crop production. Although existing models can simulate interactions, the degree of precision is questionable because of the general poor understanding of system dynamics within mixed cropping systems. The overall objectives of the Research Group are to i) obtain data using classical and new methods and technologies to gain insights into interactions and mechanisms in crop mixtures, ii) develop new and advanced crop models for crop mixtures, iii) determine optimal field arrangements (e.g. species combination, arrangements and proportion) and management (e.g. sowing, fertilization, harvest) in mixtures for a sustainable and climate-resilient crop production by combining highly monitored experiments and models.
PhenoRob video on maize-based intercropping providing pollinator fodder: link
- Core Project CP3: Putting the Soil-Root Zone into Sustainable Crop Production using Sensor Data and Analytics Algorithm
The accurate quantification of soil-root zone processes for application within yield and efficiency analysis is important to increase crop sustainability while conserving global resources. CP3 will address the task of measuring soil-root zones of crops in the field and in controlled environment rhizotron systems with minimally or non-invasive bespoke sensors and robotics. Sensor data will be ground-truthed at sub-millimeter to meter scales, and aligned with above ground sensor and yield component data and analyses in collaboration with CP1 and CP2. The state-of-the-art root-soil zone models will be used initially to support experimental design and interpretation; however, because these models have limited scope with complex phenomena and 4D data, they will be superseded by novel learning and pattern recognition algorithms from DATA. Using an iterative process of supplying sensor and ground-truthed data to analytics, this project aims to assemble the tools to collect and apply soil-root zone data to crop yield predictions and optimize resource inputs on farms in real time.
2. BonaRes (BMBF) project Soil3 (“Sustainable Subsoil Management “) https://www.soil3.de/
We presume that nutrient and water uptake from the subsoil can be elevated at given or even increased crop yields when there are attractive options for the plants to invest into subsoil roots, like low physical resistance for roots, hot spots of high microbially facilitated nutrient supply in the subsoil, as well as plant available subsoil water under conditions of seasonal drought stress in the surface soil. I developed process-based model routines to describe the observed impacts of different subsoil management options (tillage, subsoil amendments, rotations with deep rooting precrops) on plant water and nutrient uptake and on yield at field scale. I will be one of the PIs of this project in the next phase which presumably starts in October 2021.
3. DiARNIKA – Diversified arable farming for risk mitigation and sustainable climate adaptation
In addition to rising temperatures, the problematic consequences of climate change for arable farming include the increasing frequency of extreme weather events such as dry and hot spells. Sustainable adaptation of plant production to the consequences of climate change can be achieved by minimising risks through targeted diversification of the cultivation system. The aim of the DIARNIKA project is to evaluate and optimise approaches to diversification with regard to climate adaptation.
The focus is on analysing two approaches: The first approach – crop diversity – involves the cultivation of several crop species on a farm that respond to weather extremes in a complementary way in order to minimise cultivation risks with regard to unpredictable extreme events. The second approach is spatial diversification within fields through mixed cropping systems, in particular mixed cropping in strips with the possibility of staggered cultivation. This strip cropping offers outstanding potential to further develop the already well-established advantages of mixed crops, to solve technical problems in crop management and to make them more usable in practice in the context of climate change adaptation. DIARNIKA aims to quantify the potential for adaptation to climate change in order to optimise suitable climate change adaptation measures for conventional and organic practice. The aim is to promote implementation in practice as well as a deeper understanding of the processes. The overarching objectives are (a) high (yield) stability and low cultivation risk in the face of highly fluctuating and changing weather conditions; and (b) agronomic feasibility of the measures.
Details and images see also https://www.aol.uni-bonn.de/de/forschung/diarnika
4. BLE project smartMaN2agement (“Standortdifferenzierte Modellierung der N-Dynamiken zur Verringerung der gasförmigen N-Emissionen und weiterer N-Verluste im Pflanzenbau”). Duration: 2023-2026
The focus of the presented project is on the reduction of N2O and NH3 emissions as well as N leaching through predictable, informed and site-adapted management in crop production. The long-term experiments selected for sampling and informing the modelling cover the most important management measures crop rotation incl. catch crops, tillage incl. mulching of crops that have high amounts of N, as well as mineral and a wide range of organic fertilisation measures. The consistent focus of the project on modelling, using the extensive data sets already available from the long-term trials for the validation of the models, ensures that the ambitious goal of a model-based and thus comprehensive evaluation is achieved. Furthermore, within the project period, well-founded statements on the influences of the different farming systems, crop rotations, soil tillage and fertilisation events adapted to the respective location and the respective farming
system are to be derived from this evaluation, regionalised to the federal territory and processed for agricultural practice and consulting.
5. EU project IntercropValueES (duration: 2022-2026) https://intercropvalues.eu/
The goal of IntercropValueES is to exploit the benefits of intercropping to design productive, diversified, resilient, profitable and environmentally friendly agro-
ecological cropping systems less dependent on external inputs than current systems and acceptable to farmers and actors in the agri-food chain. This goal includes analysing the conditions needed to increase yield and economic performance, but also soil health and ecosystem services (ES), as indicators of the value of intercropping. IntercropValueES will then develop a detailed analysis of lock-ins and levers at the value chain level in order to identify credible solutions that can be adopted by farmers and actors of the value chain. The project will implement a participative and multi-actor approach to overcome such barriers and lock-ins identified by the key actors of the local value-chain by providing multiple services of intercropping. IntercropValueES aims to exploit the benefits of intercropping to design and manage productive, diversified, resilient, profitable, environmentally friendly cropping systems acceptable to farmers and actors in the agri-food chain. As a multi-disciplinary and multi-actor project, it brings together scientists and local actors representing the food value chain. It includes 27 participants from 15 countries (3 continents) from a wide diversity of organizations and stakeholders.
Video on field trial: https://intercropvalues.eu/news/germany-first-field-season-ends-in-campus-klein-altendorf/
IntercropVALUES video on trial of UniBonn: https://youtube.com/watch?v=FXyo5lK15Vc&si=-epL-FkYnAVEz9vt
6. BLE project MIKODU (“Fruchtfolgen für optimierte Nutzung der Bodenressourcen: Mischanbau allorhizer und homorhizer Arten zur komplementären Durchwurzelung des Ober- und Unterbodens “), ended in Oct 2024