Application of accelerometers to record drinking behaviour of beef cattle
Lauren R. Williams A D , Greg J. Bishop-Hurley B , Angela E. Anderson C and Dave L. Swain A
+ Author Affiliations
- Author Affiliations
A CQUniversity, School of Medical and Applied Sciences, Ibis Avenue, North Rockhampton, Qld 4701, Australia.
B Commonwealth Scientific and Industrial Research Organisation (CSIRO), 306 Carmody Road, St Lucia, Qld 4067, Australia.
C Department of Agriculture and Fisheries, 9–15 Langton Street, Garbutt, Qld 4814, Australia.
D Corresponding author. Email: l.r.williams@cqu.edu.au
Animal Production Science 59(1) 122-132 https://doi.org/10.1071/AN17052
Submitted: 30 January 2017 Accepted: 17 August 2017 Published: 11 December 2017
Abstract
Accelerometers have been used to record many cattle postures and behaviours including standing, lying, walking, grazing and ruminating but not cattle drinking behaviour. This study explores whether neck-mounted triaxial accelerometers can identify drinking and whether head-neck position and activity can be used to record drinking. Over three consecutive days, data were collected from 12 yearling Brahman cattle each fitted with a collar containing an accelerometer. Each day the cattle were herded into a small yard containing a water trough and allowed 5 min to drink. Drinking, standing (head up), walking and standing (head down) were recorded. Examination of the accelerometer data showed that drinking events were characterised by a unique signature compared with the other behaviours. A linear mixed-effects model identified two variables that reflected differences in head-neck position and activity between drinking and the other behaviours: mean of the z- (front-to-back) axis and variance of the x- (vertical) axis (P < 0.05). Threshold values, derived from Kernel density plots, were applied to classify drinking from the other behaviours using these two variables. The method accurately classified drinking from standing (head up) with 100% accuracy, from walking with 92% accuracy and from standing (head down) with 79% accuracy. The study shows that accelerometers have the potential to record cattle drinking behaviour. Further development of a classification method for drinking is required to allow accelerometer-derived data to be used to improve our understanding of cattle drinking behaviour and ensure that their water intake needs are met.
Additional keywords: biotechnology, drinking water, grazing.
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