Lameness is recognised as the primary animal welfare issue in dairy farming. Nationally, 25% of dairy cows are lame at any one time. Although it has multiple causes, the key factor in most herds is endemic diseases, such as digital dermatitis, sole ulcers, and white line disease. Early detection and prompt intervention is critical to effective control and treatment of lameness, which costs farmers in excess of £300 per case. Many hoof lesions, especially relating to digital dermatitis, are visible prior to lameness developing but can be difficult to see in practice and require specialist training to diagnose.
The Hoofcount footbath was developed and introduced to the UK market in 2012. Designed with simplicity in mind, it now has a sustained reputation in the UK as the Market leader in Effective and Reliable Footbathing.
The UWE academic team collaborating on the Hoofcount project is led by Dr Wenhao Zhang of the Centre for Machine Vision. Wenhao’s team are working on developing and integrating machine vision technology and AI software for hoof disease detection. Their aim is to realise algorithms, able to capture, filter, and analyse hoof images several times daily in a non-invasive way, to detect hoof issues in the earliest stages and to monitor for changes. Experiments and tests are being conducted in several UK dairy farms.
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