Developments in automated systems for monitoring livestock health: lameness

Publication date: 27/06/2022
Extent: 42 pages

Contributions by: Zoe E. Barker, University of Reading, UK; Nick J. Bell, University of Nottingham, UK; Jonathan R. Amory, Writtle University College, UK; and Edward A. Codling, University of Essex, UK

Chapter synopsis: Lameness is a key issue for commercially managed livestock species such as dairy cattle. Lameness can lead to significant economic impacts for farmers and to ongoing health and welfare problems for animals. However, lameness detection remains a difficult and time-consuming task and there is a need for reliable automated methods to support farmers, especially where herd sizes are large. In this chapter we provide an overview of lameness and its impacts on animal health and behaviour, with a particular focus on dairy cows. We review existing methods for manual and automated detection of lameness, including approaches that detect changes and abnormalities in the gait or stance of the animal, and methods that directly or indirectly detect changes in individual and social behaviour. We highlight approaches that use automated technology such as video, accelerometers and spatial positioning systems, and discuss methods to analyse trends and signals in these data.

DOI: 10.19103/AS.2021.0090.10