Using Bio-logging to Improve Sheep Health and Performance

The UK sheep industry has more than 16M breeding sheep and contributes an estimated £465.9M p.a to the UK economy. Health problems cost the industry millions of pounds and cause significant welfare issues. Two major interlinked challenges constrain the industry and threaten future food security: i) a need to improve animal health and welfare; and ii) pressure to improve production.

Current breeding programmes in sheep generally focus on easily measured production measures such as carcass traits. There is mounting evidence that behavioural traits such as temperament, maternal care, aggression and prosocial behaviour can jointly predict both production (e.g. growth rates) and health (e.g. immune function). To date, however, the practical difficulties of measuring behaviour in commercial flocks means that the genetic basis of behavioural traits remains largely unknown. There is an urgent need for the development of new methods to monitor sheep behaviour and to quantify the relationships between behaviour, health and production.

In partnership with Activinsights, a UK-based manufacturer of devices for the measurement of behaviour, this project will use animal-borne sensors and machine learning to develop new methods to automatically classify sheep behaviour and health. We will use accelerometers to automatically track behaviour (e.g. grazing, walking), GPS devices to determine where the behaviour occurs and proximity tags to record patterns of social contact. We will combine these multiple streams of bio-logging data with direct observations of animal health and production (e.g. growth and pregnancy rates) in a single event-based data platform. Using this data platform we will use machine learning to digitally measure health and behavioural traits. The research will be done in collaboration with Centurion, a group of Poll Dorset breeders with over 25 years of production data on thousands of sheep. Working with this pedigree breed group will allow us to determine the genetic basis of variation in functional traits and predict the performance of genotypes under different farm management conditions.

This project is central to the 'Agriculture and Food Security' and 'Bioscience for Health' BBSRC research priorities and is directly aligned with a number of the BBSRC priorities. It will take a data-driven approach and by working with national and international partners will develop new measures of animal health and behaviour to improve the welfare of managed animals. By collaboratively working with the end-users of the research this project promises to sustainably enhance agricultural production.