Periodic Reporting for period 1 - OrganicYieldsUP (Improving yields in organic cropping systems)
Berichtszeitraum: 2024-02-01 bis 2025-07-31
With the European Green Deal, the Farm-to-Fork and Biodiversity Strategy, the EU aims to achieve the target of at least 25% of the EU’s agricultural land under organic farming by 2030. This means tripling the current organic farm area with estimated 700.000 farmers expected to enter the organic sector. One of the obstacles hindering conversion to organic farming is the lower yields per hectare grown under organic conditions as compared with those produced under conventional farming. Therefore, improving organic yields is a key challenge of the organic sector, which however needs to be achieved on the basis of the principles of organic farming. Against this background, the overall aim of the project is to contribute to a sustainable increase in yields in organic cropping systems through a comprehensive and structured compilation and evaluation of existing knowledge, devising sustainable impact strategies relevant to stakeholders and policy. The project will set up an European-wide network of testing, experimentation and demonstration sites from 11 regions / countries, representing a wide range of pedo-climatic and structural conditions. It will connect actors from science and practice to jointly reflect on organic yield increase strategies. It will draw recommendations for the future research agenda and development of EU policies relevant for organic production. The outcomes of the project will be widely available and disseminated to actors within and beyond the organic community.
During the first reporting period, the consortium laid the foundations for data-driven innovation in organic crop production. A central project database was co-created, tested, and finalised, ensuring consistent integration of diverse datasets and reflecting the specific practices of organic farming. By July 2025, 45 datasets (51 Zenodo entries) covering a wide range of pedo-climatic conditions were collected, harmonised, and quality-checked. In parallel, a systematic review of 751 publications resulted in harmonised data from 69 high-quality studies, which has been publicly archived. Together, these resources now form a robust basis for on-site and cross-site analysis and future modelling work. Data analysis protocols were established to guide agronomic, economic, and environmental analyses. Currently, the LPJml model is being adapted to the specificities of organic farming, with special focus on crop rotation and weed management.
In parallel, a preparatory work on 44 lighthouse farms is well underway, with 35 already described and 8 field visits completed. These farms and key local actors will serve as basis for the establishment of living labs for testing innovative practices to improve organic yields across EU regions. Stakeholder integration is advancing through workshops, interviews, and the development of a methodological roadmap combining local engagement, cross-regional visits, modelling, and expert workshops. A toolbox is also being prepared and will be provided to on-site partners to achieve results that will support scaling of strategies across Europe.
Overall, the consortium has successfully delivered the database, datasets and protocols, while initiating lighthouse farm and stakeholder engagement activities.
In parallel, a preparatory work on 44 lighthouse farms is well underway, with 35 already described and 8 field visits completed. These farms and key local actors will serve as basis for the establishment of living labs for testing innovative practices to improve organic yields across EU regions. Stakeholder integration is advancing through workshops, interviews, and the development of a methodological roadmap combining local engagement, cross-regional visits, modelling, and expert workshops. A toolbox is also being prepared and will be provided to on-site partners to achieve results that will support scaling of strategies across Europe.
Overall, the consortium has successfully delivered the database, datasets and protocols, while initiating lighthouse farm and stakeholder engagement activities.
A key result of the OrganicYieldsUP project is the development of a database (OYUP database) designed to address the complexity of organic farming systems and their yields. Data on organic yields have often been fragmented, inconsistent in scope, or lacking contextual information. The OYUP database is a harmonised, flexible, and tested structure that enables analysis of yield performance in organic systems across Europe.
The novelty of the OYUP database lies in its ability to integrate heterogeneous data sources (experimental stations, on-farm trials, monitoring networks, and published studies) within a common framework. Existing datasets are often restricted to single crops, specific regions, or particular experimental designs. In contrast, the OYUP structure is designed to handle multiple levels of resolution (from plot to farm scale), accommodate different trial designs, and embed relevant contextual variables such as weather, soil type, and management history. This integration of technical and contextual dimensions is a step beyond current practice, where such factors are rarely combined in a comparable way.
The development process has been based on participatory and iterative design. Researchers from 11 countries and multi-disciplinary backgrounds collaboratively defined a minimum dataset, ensuring comparability while leaving room for flexibility. The use of lookup tables based on recognised international standards (AGROVOC, ICASA, EPPO), adapted to reflect organic realities, adds to the long-term interoperability of the resource. Guidelines and supporting materials ensure consistency in data entry across partners, something often missing in multi-partner data initiatives.
Beyond its technical features, the OYUP database constitutes an enabling resource for research and practice. By making it possible to link crop yields with contextual drivers and management practices, it opens new opportunities to:
• Identify why and under which conditions yields vary.
• Compare performance across systems and regions in a harmonised manner.
• Provide an evidence base for recommendations to farmers, advisors, and policymakers.
• Reveal knowledge gaps and generate new research questions.
This resource provides a foundation for more robust and evidence-based insights into organic yields than has previously been possible.
The novelty of the OYUP database lies in its ability to integrate heterogeneous data sources (experimental stations, on-farm trials, monitoring networks, and published studies) within a common framework. Existing datasets are often restricted to single crops, specific regions, or particular experimental designs. In contrast, the OYUP structure is designed to handle multiple levels of resolution (from plot to farm scale), accommodate different trial designs, and embed relevant contextual variables such as weather, soil type, and management history. This integration of technical and contextual dimensions is a step beyond current practice, where such factors are rarely combined in a comparable way.
The development process has been based on participatory and iterative design. Researchers from 11 countries and multi-disciplinary backgrounds collaboratively defined a minimum dataset, ensuring comparability while leaving room for flexibility. The use of lookup tables based on recognised international standards (AGROVOC, ICASA, EPPO), adapted to reflect organic realities, adds to the long-term interoperability of the resource. Guidelines and supporting materials ensure consistency in data entry across partners, something often missing in multi-partner data initiatives.
Beyond its technical features, the OYUP database constitutes an enabling resource for research and practice. By making it possible to link crop yields with contextual drivers and management practices, it opens new opportunities to:
• Identify why and under which conditions yields vary.
• Compare performance across systems and regions in a harmonised manner.
• Provide an evidence base for recommendations to farmers, advisors, and policymakers.
• Reveal knowledge gaps and generate new research questions.
This resource provides a foundation for more robust and evidence-based insights into organic yields than has previously been possible.