Analysing the behaviour of dairy cows

Analysing the behaviour of dairy cows

Understanding the behaviour of housed dairy cows has the potential to detect changes in behaviour indicative of illness, and optimise farm management regimes. This research uses data collected on a housed commercial dairy herd throughout 2014, via a wireless local positioning system.

Firstly, we investigate the structure and consistency of the proximity interaction network, determining herd-level networks from sustained proximity interactions (pairs of cows continuously within three metres for 60 s or longer). We assessed for social differentiation, temporal stability and the influence of individual attributes including lameness.

Secondly, we analyse the potential influence of heat stress, using the temperature-humidity index (THI), on the clustering behaviour of the herd. As a part of this, we analyse relationships between THI and range size (core and full), inter-cow distance (the distance between each dyad) and nearest neighbour distance (the distance of the closest cow). We found the networks to be highly connected and temporally unstable, with significant preferential assortment, and no social assortment by individual attributes.

Furthermore, it appears that the herd is maladaptively increasing clustering behaviour, in response to increasing THI, above a 20 °C threshold. Our research demonstrates the potential benefits of automated tracking technology to monitor proximity interactions of individuals, as well as clustering responses to heat stress, within commercially relevant groups of livestock.

Speaker

Kareemah Chopra, University of Essex

How to attend

If not a member of the Dept. Mathematical Science at the University of Essex, you can register your interest in attending the seminar and request the Zoom’s meeting password by emailing Dr Osama Mahmoud (o.mahmoud@essex.ac.uk).