Phenet - Methods for advanced plant phenotyping and environmental typing services of the European research infrastructures
Challenges for mixed cultures
The acceptance of mixed crops in arable farming remains low in Europe, despite numerous experimental studies demonstrating the advantages of mixed crops compared to pure crops, including higher land and nitrogen utilisation efficiency and more robust plant health. In order to further develop mixed crops in science and practice, more targeted research is required that goes beyond simple system comparisons between mixed crops and pure seeds. To this end, bioecological mechanisms and the practical design elements of mixed cropping systems are systematically analysed on the basis of existing empirical findings and theories.
Contribution to the research infrastructure for agroecology
As part of the EU-funded PHENET project, we aim to take research into mixed cropping to a new level. Phenet is a project that aims to develop new tools and methods as a research infrastructure to support an agroecological transition in Europe. We are developing mixed cropping as a use case within this broader perspective.
Project objectives
The research objectives are:
1.Systematic review of the state of experimental research on mixed cropping for arable crops to identify gaps in knowledge. The focus is on:
(a) Experimental design (sowing densities, spatial arrangement, sowing timing, varieties) and management (fertilisation, crop protection) of mixed crops to support practical optimisation of cropping systems.
b) Recording different experimental methods and the way in which studies explicitly link experimental design to hypotheses and ecological theories (inter- and intraspecific competition or compensation mechanisms) in order to test or extend them.
c) Identification of research gaps, methodological pitfalls and best practices.
2. Provision of metadata on mixed culture experiments as research infrastructure for science.
3. Utilising digital technologies such as remote sensing and machine learning for mixed cropping research.
4. Utilising data sets from multiple experiments to derive broader conclusions for agricultural practice and understanding of basic mechanisms for mixed cropping.
Applied mix of methods
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Systematic review of the experimental literature
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Expert interviews on the use of farmers' contextual knowledge for the optimisation of mixed crops
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Remote sensing and machine learning
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Statistical analysis of existing experimental data
Project partners
Wopke van der Werf, Wageningen University & Research, Department of Plant Sciences, Centre for Crop Systems Analysis, Bornsesteeg 48, 6708PE WAGENINGEN
Roland Pieruschka, Forschungszentrum Jülich GmbH, Institut für Bio- und Geowissenschaften (IBG), Pflanzenwissenschaften (IBG-2), Wilhelm-Johnen-Straße, 52428 Jülich
| Acronym: | PHENET |
| Duration: | |
| Funding code: | 101094587 |
| Funding: |
This project has received funding from the European Union's Horizon Europe research and innovation programme under grant agreement No 101094587. |
| Project website: |