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ISCF WAVE 1 AGRI TECH: Early Detection of Lameness in Dairy Cows through Multi-format Data Synthesis
Reference
BB/R021538/1
Principal Investigator / Supervisor
Professor Martin Green
Co-Investigators /
Co-Supervisors
Dr Christopher Hudson
,
Professor Jonathan Huxley
Institution
University of Nottingham
Department
School of Veterinary Medicine and Sci
Funding type
Research
Value (£)
191,465
Status
Completed
Type
Research Grant
Start date
03/01/2018
End date
31/03/2019
Duration
15 months
Abstract
Lameness in dairy cattle is increasingly recognised as a growing and significant economic and welfare problem in dairy nations around the world. Lameness remains at unacceptably high levels amongst the UK's 1.8 million dairy cattle; recent work suggests that approximately one in three cows are identifiably lame on any given day. Research has indicated that very early detection and treatment of lameness substantially reduces the prevalence of lameness which leads to increased milk production as well as enhanced cow welfare. Very early detection of lameness is difficult and technologies to identify the pre-clinical stages of disease would dramatically advance this area. The aim of this research is to synthesis data from multiple sources, including state-of-the-art thermography, activity/location monitoring and rumination sensors, to accurately predict pre-clinical onset of lameness in dairy cows such that early stage interventions are possible.
Summary
Lameness in dairy cattle is increasingly recognised as a growing and significant economic and welfare problem in dairy nations around the world. Lameness remains at unacceptably high levels amongst the UK's 1.8 million dairy cattle; recent work suggests that approximately one in three cows are identifiably lame on any given day. Research has indicated that very early detection and treatment of lameness substantially reduces the prevalence of lameness which leads to increased milk production as well as enhanced cow welfare. Very early detection of lameness is difficult and technologies to identify the pre-clinical stages of disease would dramatically advance this area. The aim of this research is to synthesis data from multiple sources, including state-of-the-art thermography, activity/location monitoring and rumination sensors, to accurately predict pre-clinical onset of lameness in dairy cows such that early stage interventions are possible.
Impact Summary
Possible results of this research include: A method to identify lameness at the pre-clinical or very early onset stage that can be used to enhance treatment outcomes, reduce herd prevalence of disease and reduce recurrence of lameness throughout a cow's life. Main beneficiaries of the research will be: 1. Farmers 2. Veterinary surgeons and farm advisors 3. The dairy industry 4. Consumers 5. UK PLC How will they benefit? 1. Farmers - through improved lameness control leading to significant financial savings and working conditions 2. Veterinary surgeons and farm advisors - through being able to use an improved approach to lameness control 3.The dairy industry - through improved sustainability, welfare and image by reducing lameness 4. Consumers - through consuming a product associated with improved cow welfare and with improved farming sustainability 5. UK PLC - through improved efficiency of dairy farming and economic returns from selling the technological advancement
Committee
Not funded via Committee
Research Topics
Animal Health, Animal Welfare
Research Priority
X – Research Priority information not available
Research Initiative
Industrial Strategy Challenge Fund Wave 1 - Agri Tech (ISCF AT) [2017]
Funding Scheme
X – not Funded via a specific Funding Scheme
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