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UC 95 — OCH

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Key Information
Title
RRes One Crop Health
Acronym
OCH
Coordinator
Rothamsted Research (United Kingdom)Research Institute
Duration
24 months
Budget
Not shown at your access level. Hidden
Maturity
Committed
Source
In Proposal
Use Case Summit Pitch
Health, Pests, Diseases & Protection
Sectors
Arable crop
Data Types
Machine sensor dataEarth observation dataFarm Management Information Systems (FMIS) data
SRIA Activities

3.1.4 Applications of AI techniques

  • 3.1.4.6 Digital twins of farms & environments
  • 3.1.4.7 Strengthen AI uptake; trust in AI

3.2.2 Farm modelling systems

  • 3.2.2.1 Take stock of existing modelling approaches
  • 3.2.2.2 Novel forecasting & prediction methodologies
  • 3.2.2.3 Whole-farm & landscape environmental impact
  • 3.2.2.4 Farm modelling for optimal practice
  • 3.2.2.5 Farm modelling for agri-environmental measures

3.2.4 Data-based solutions for addressing environmental challenges

  • 3.2.4.4 Areas for biodiversity & pollinator conservation
  • 3.2.4.5 Continuous soil & water sensor monitoring
Themes
Crop production & monitoring
Partners (1)
  • Rothamsted ResearchP1
    Coordinator

    United KingdomResearch Institute

#OrganisationCountryType
P1Rothamsted ResearchCoordinatorUnited KingdomResearch Institute

Introduction OCH is a 6 year, bilateral project funded by the novo-Nordisk foundation to facilitate the transition to more sustainable crop protection systems that reduce inputs of synthetic pesticides. The philosophy of the project is that the future of crop protection does not lie in a single domain: biotechnology, new digital technology or agroecology but will require the synthesis of all available tools within a resilient cropping system. The project is testing ecological, biotechnological and digital approaches at multiple scales: 1) parallel networks of commercial farms in Denmark and the UK, 2) living lab study farms and 3) plot scale, long-term systems experiments. Finally, a cohort of 12 PhD students are being supported by the project studying a range of crop protection topics. Methodologies • Monitoring of pest, weed disease pressure across 50 winter wheat and 50 oilseed rape fields in the UK and Denmark. • Testing of digital tools for detecting and monitoring pests, weeds, diseases and beneficial invertebrates. • Long-term experiments monitoring multiple system states in contrasting cropping systems. Output • Georeferenced data on pest, weed and disease incidence at the intra- and inter-field scale and in contrasting regions with associated management data. • Data on impact of alternative management interventions on pest, weed, disease and beneficial invertebrate populations and diversity. • Output from digital monitoring tools (including camera traps and eDNA spore traps). Impact What I can offer: Initially, we have lots of crop images with matched ground truth data on pest, weed and disease incidence What I need: We currently lack resources for image analysis and there are possibilities for exploring earth observation data.

Source: Annual AgData Use Case Summit 2026 booklet.

Test and experimental facilities (TEF research) data
Models & Macro data
  • 3.2.4.6 Robots/UGV + IoT for pest & weed detection