Automated monitoring of Dairy Cattle for Pre-Clinical Ketosis and other conditions

This project is a feasibility study to establish if the RoboScientific VOC (Volatile Organic Compound) sensing system can be used to monitor the breath of individual dairy cattle in the milking parlour to give early warning of disease and other conditions. This system monitors the VOC "fingerprint" of the breath and compares it with other fingerprints held in a memory library. Initially the system will be trial tested to detect sub-clinical ketosis which has a major economic impact upon farmers. Sub Clinical Ketosis (SCK) needs to be detected more efficiently and accurately by Dairy Farmers to reduce their economic losses. It currently goes largely unseen and accurate blood tests are expensive and undertaken infrequently. SCK affects both the Dairy and the Beef industry and impacts upon productivity and profitability. Its incidence has been cited to be as high as 60% in some literature. Based upon a cost per head from Esslemont, BVCA, of £560; a potential cost to the UK herd of over £1.5bn a year. The incidence of SCK varies internationally, with key European and North American markets experiencing rates of between 20-40%. In the USA, with a dairy herd of 18m this translates to potential losses of over $12bn annually. The EU herd is even larger at 28m. The system would be extended to monitor for other diseases and conditions (including individual beast methane output levels) and developed into a fully automatic system for incorporation into robotic milking systems.