Agriculture of Data (AgData) (AgData)
PartnerAgriculture of Data (AgData)
AgData is a large endeavour with a variety of partners bringing together in particular research funders and research providers. Digital technologies and data are integral to the future of agriculture. AgData will enhance the use of data for developing data-based solutions, methodologies, and indicators to improve climate adaptation and resilience of agriculture as well as to minimise the undesired impact of agriculture on the climate, environmental quality, ecosystem services.
AgData has focus on integrating data from different sources including EO, environmental, agricultural and other relevant data in the combination with data technologies (including AI). The partnership will build on results of existing (ongoing or finished) initiatives and projects. AgData will explore the potential for achieving synergies with programmes, projects and activities on digital and data technologies in member states and between EU and its member states and associated countries. At the EU level AgData will explore synergies with relevant topics / projects, partnerships, missions particularly in Cluster 6 and Cluster 4 of the Horizon Europe Programme as well as with the Digital Europe Programme, the EU Space Programme and the Common Agricultura Policy.
Via its unique concept of Use Cases (UCs), the AgData partnership will deploy a broad variety of activities in all relevant branches of agriculture based on modern digital-technologies and data sources. The UCs will all be based on the Strategic Research and Innovation Agenda (SRIA). Besides the UCs AgData will also implement joint calls for transnational proposals resulting in financial support to third parties (FSTP).
- EC contribution:
- EUR 27k
- Start:
- 2025-10-01
- End:
- 2032-09-30
- Status:
- SIGNED
- Scheme:
- HORIZON-COFUND
- Call:
- HORIZON-CL6-2024-GOVERNANCE-02
artificial intelligencedata scienceclimatic change mitigationclimate change adaptation
View on CORDIS (DOI 10.3030/101197332)
Doctoral Training in Ruminant Microbiome Science:Developing Evidence-Based Interventions for Sustainable Food Production and Climate Change Mitigation (Rumen-Innovate)
associatedpartnerRUMEN-INNOVATE will establish a pioneering Marie Skłodowska-Curie Doctoral Network that advances sustainable ruminant agriculture through microbiome-based innovations. Building on extensive existing datasets, this network will train the next generation of scientists to revolutionise direct-fed microbial applications and sustainable ruminant production.
The programme operates through three integrated pillars: Discovery & Prediction using machine learning and multi-omics to identify key microbiome-host interactions; Validation & Mechanistic Understanding through controlled studies and synthetic microbial community design; and Translation & Implementation developing real-world diagnostic tools, delivery systems, and on-farm technologies.
RUMEN-INNOVATE will train doctoral candidates across European institutions with industry partnerships spanning nutrition companies, dairy, and meat sectors. Researchers will gain expertise in computational biology, experimental validation, and commercial application—creating versatile scientists capable of bridging laboratory discovery with agricultural implementation.
The network addresses critical global challenges: feeding a growing population sustainably, reducing greenhouse gas emissions from livestock, and developing alternatives to antibiotics in animal agriculture. By advancing microbiome-based solutions, RUMEN-INNOVATE will deliver innovations that enhance animal health, improve production efficiency, and support environmental sustainability.
Through international, interdisciplinary, and intersectoral collaboration, the network will produce breakthrough technologies, highly skilled researchers, and direct pathways for microbiomics innovations to reach farmers and consumers, positioning Europe as the global leader in ruminant microbiome science.
- EC contribution:
- EUR 0
- Start:
- 2027-03-01
- End:
- 2031-02-28
- Status:
- SIGNED
- Scheme:
- HORIZON-TMA-MSCA-DN
- Call:
- HORIZON-MSCA-2025-DN-01
microbiomesproduction economicsanimal husbandryclimatic changesmachine learning
View on CORDIS (DOI 10.3030/101311612)