Details of Award
NERC Reference : NE/P008011/1
Novel animal-mounted sensor technology to improve efficiency and sustainability
Grant Award
- Principal Investigator:
- Professor C Duthie, SRUC, Research
- Co-Investigator:
- Professor M Mitchell, SRUC, Learning
- Co-Investigator:
- Professor EA Codling, University of Essex, Mathematical Sciences
- Co-Investigator:
- Dr JR Amory, Anglia Ruskin University, Faculty of Science and Engineering
- Co-Investigator:
- Dr Z Barker, University of Reading, Sch of Agriculture Policy and Dev
- Science Area:
- Atmospheric
- Terrestrial
- Overall Classification:
- Unknown
- ENRIs:
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Animal behaviour
- Maternal behaviour
- Multi-sensory processing
- Animal behaviour
- Instrumentation Eng. & Dev.
- Physical Biosensors
- Instrumentation Eng. & Dev.
- Physical Biosensors
- Intelligent Measurement Sys.
- Smart Sensors
- Abstract:
- In the UK, the average herd size and animal to stockman ratio is increasing within the beef and dairy sectors, thus the time devoted to monitoring of individual animals is reducing. In order to optimise the production efficiency of the UK livestock sector, there is a requirement for the development and use of cost-effective animal monitoring solutions to inform on the health and productive status of individual animals. Dystocia is a considerable problem within beef and dairy systems causing the cow considerable pain. Prevalences of up to 22.6% in dairy cattle and 6% in beef cattle have been reported, with as many as 51% or dairy calvings and 34% of beef calvings requiring some level of assistance. The costs associated with mild and severe cases of dystocia in the dairy herds have been estimated as between #110 and #400 due to milk loss, increased days open, increased numbers of services, premature culling of loss of cows and lost calves. Timely intervention on difficult calving's can significantly reduce calf mortality, uterine infections post-partum and calving to conception interval compared with unassisted calving . Thus the development of methods to automatically predict calving onset and identify problematic calvings is important to facilitate timely and appropriate interventions. A number of physiological and behavioural changes occur around calving which offer opportunities for the prediction of calving onset. Despite the possibility of using ability of hormonal changes as indicators to be used for prediction of calving, the variable accuracy of these, figures and need for invasive nature of blood sampling to detect changes in hormones limits its usefulness as a method of automatic dystocia prediction. Reductions in body temperature occur on the day of calving compared with 2-3 days before calving but high variations in temperature change between individual animals and possible impacts of pyrexia limit the predictive power of temperature alone. The non-invasive nature of behavioural observations and the availability of a number of sensors on the market or near to market designed to monitor different elements of cattle behaviour provides opportunities for translation of current behavioural and technology validation research into a multi-sensor platform for the prediction of calving onset and calving difficulties. Lying and standing behaviour, eating and rumination patterns, social behaviour and tail raising events are known to change during the 24 hours prior to calving This study will assist in translating a range of behavioural research and technical knowledge into a potential early warning system for calving and dystocia. It will assess a number of technologies on the market or near-to-market for related and other uses (e.g. detection of oestrus) for their capabilities in the detection of calving and dystocia. The use of combined technologies is likely to result in increased accuracy of decision making algorithms and will therefore provide added value to the end user. The availability of early detection and alerts for parturition/dystocia will enable farmers to intervene in a timely manner to prevent the losses associated with dystocia, thus optimising the economic and production efficiency of their business. The prevention of pain and suffering for both the dam and calf aligns clearly with the BBSRC animal welfare strategies. The development of appropriate early warning systems is key to maximising the sustainability of UK and global agriculture.
- NERC Reference:
- NE/P008011/1
- Grant Stage:
- Completed
- Scheme:
- Innovation
- Grant Status:
- Closed
- Programme:
- Innovation - SARIC
This grant award has a total value of £202,100
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DI - T&S |
|---|---|---|---|---|---|
| £21,663 | £34,834 | £5,276 | £53,776 | £81,561 | £4,989 |
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