The effect of lameness on lying behaviour of zero grazed Holstein dairy cattle

Use of novel sensors combining local positioning and acceleration to measure feeding behavior differences associated with lameness in dairy cattle

“…Lame cows are slower to respond to food being made available (Blackie et al, 2011;Yunta et al, 2012) and feed faster, although for a reduced overall duration per day (González, 2008;Palmer et al, 2012;Norring et al, 2014). Lameness in dairy cows is also associated with changes in lying behavior, although these results are more equivocal (increased lying: Singh et al, 1993;Galindo and Broom, 2002;Blackie et al, 2011; no difference: Ito et al, 2010;Yunta et al, 2012;decreased lying: Cook et al, 2008). Therefore, automated monitoring of individual cow behaviors may potentially offer the opportunity for the early detection of lameness.…”

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

“…Although this feature was not used in this study, it may be possible to combine accelerometer data with spatial location data to more accurately determine real-time behaviour and behavioural changes as part of an automated detection system for dairy cow health and welfare status within a Precision Livestock Farming approach. The behaviours investigated in this study (lying, standing and feeding) have been suggested as indicators of health and welfare in dairy cows [27][28][29][30]. Using a neck-mounted sensor, we are able to include feeding behaviour in the repertoire of behaviours, something that is not usually possible in studies that use leg-mounted sensors.…”

“…3 and 4). Such measures can provide relevant information about the behaviour and behavioural changes of cattle over time and can potentially be used as indirect indicators of the health and welfare of dairy cows as part of a Precision Livestock Farming approach [27][28][29][30].…”

“…Analysis of behaviour and behavioural changes has been suggested as a potential way to indirectly monitor health and welfare of dairy cows [27][28][29][30], and several automated systems have been proposed to identify different biologically important behaviours [8,9]. In this study, we have developed a simple decision-tree classification algorithm that uses tri-axial accelerometer data from a neckmounted sensor to accurately classify biologically relevant behaviours such as lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision) and feeding (98.78 % sensitivity, 93.10 % precision).…”

“…Medrano-Galarza et al [29] observed behavioural changes in lying behaviour and at milking times for cows with mild clinical mastitis. Blackie et al [30] found significantly longer lying down and significantly shorter standing times for lame cows. Hence, by monitoring behaviour in real-time and observing changes in lying, standing and feeding, it may be possible to detect some of the most common diseases in cattle.…”