Wireless tracking sensors are being used on a herd of dairy cows to monitor their health in new research aimed at helping farmers spot that cows are unwell before symptoms appear. It is hoped that such early detection of illnesses such as lameness and mastitis would result in less suffering for the cows as well as ensuring milk yields.
Dr Jonathan Amory, Principal Lecturer in Animal Behaviour and Welfare at Writtle College and his team are using small sensors attached to cow collars to record the behaviour of the cows. Dr Edd Codling from the University of Essex will then use cutting-edge mathematical techniques to analyse the information in order to develop an early warning system for mastitis and lameness, which have been identified by scientists as the major factors affecting cow welfare. Dr Darren Croft, an expert in social network analysis from the University of Exeter and Dr Nick Bell, a dairy specialist from the Royal Veterinary College complete the BBSRC Cow Tracking research collaboration.
This 39-month joint project is one of eight grants awarded by BBSRC last year to researchers looking at ways of measuring and assessing health in order to improve the welfare of farmed animals.
Findings from the research could have a huge impact on the welfare of the UK's 1.8 million dairy cows as well as increasing productivity, with mastitis and lameness costing the industry in this country around £100M-plus. But it could also have a global implication, helping the huge commercial dairy farms in New Zealand, the US and Canada to monitor their stock.
Dr Amory said: "A sick cow and a well cow behave differently. A sick cow might lie down in different areas of the shed or split itself away from the herd, or use the same areas at different times, or go to eat a bit later. The idea of that is we can quickly identify those cows that are just becoming ill and develop an early warning system.
The battery-powered sensors, produced by Omnisense in Cambridge-will 'talk' to each other every eight seconds over a three-month period using novel network technology that can cope with over 1,000 individuals. Behavioural data from the sensors together with information regarding the health of individual cows will be used to create a predictive model for disease detection.
"Such an early warning system could be applied to all farms, being relatively cheap, particularly the more intensive larger farms where it is harder for farmers to monitor the welfare of the cows themselves," said Dr Amory.
Dr Codling added: "Ideally, we hope the system will highlight any out-of-character behaviour before the symptoms of these diseases start. This early warning will be crucial in identifying which cows are unhealthy so they can be treated earlier and suffer less."
The research started last November and the researchers are initially monitoring an Essex dairy herd of 120 cows before moving onto Devon herds. Results are expected later this year.