Costing the farming industry around £80m every year, lameness is the biggest health and welfare issue on sheep farms today. Early identification and treatment is key in reducing lameness levels but there are no validated commercial tools for automatically detecting the condition. Instead, farmers and vets rely on visual inspection of each flock’s movement – a subjective, labour intensive method that can’t produce the accurate results they really need.
As a prey species, sheep often mask signs of mild lameness when they feel threatened – including in the presence of an observing farmer. In fact, previous research conducted by our team showed that only 20% of farmers detected lameness in its early stages, clearly highlighting the need for an appropriate, effective tool or protocol for identifying it in the field.
Within the Ruminant Population Health Research Group, we’re developing:
We’re working closely with our industry partners to make this happen. This includes drawing on Intel’s cutting-edge hardware and software engineering, as well as their novel methods for data transmission. We’re also using machine learning tools in collaboration with Hewlett Packard Enterprise to develop the project’s algorithms.
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School of Veterinary Medicine and ScienceUniversity of NottinghamSutton Bonington Campus Leicestershire, LE12 5RD