Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/31002
Title: A Pilot Study Using Accelerometers to Characterise the Licking Behaviour of Penned Cattle at a Mineral Block Supplement
Contributor(s): Simanungkalit, Gamaliel  (author); Barwick, Jamie  (author)orcid ; Cowley, Frances  (author)orcid ; Dobos, Robin  (author)orcid ; Hegarty, Roger  (author)
Publication Date: 2021-04-17
Open Access: Yes
DOI: 10.3390/ani11041153
Handle Link: https://hdl.handle.net/1959.11/31002
Abstract: Identifying the licking behaviour in beef cattle may provide a means to measure time spent licking for estimating individual block supplement intake. This study aimed to determine the effectiveness of tri-axial accelerometers deployed in a neck-collar and an ear-tag, to characterise the licking behaviour of beef cattle in individual pens. Four, 2-year-old Angus steers weighing 368 ± 9.3 kg (mean ± SD) were used in a 14-day study. Four machine learning (ML) algorithms (decision trees [DT], random forest [RF], support vector machine [SVM] and k-nearest neighbour [kNN]) were employed to develop behaviour classification models using three different ethograms: (1) licking vs. eating vs. standing vs. lying; (2) licking vs. eating vs. inactive; and (3) licking vs. non-licking. Activities were video-recorded from 1000 to 1600 h daily when access to supplement was provided. The RF algorithm exhibited a superior performance in all ethograms across the two deployment modes with an overall accuracy ranging from 88% to 98%. The neck-collar accelerometers had a better performance than the ear-tag accelerometers across all ethograms with sensitivity and positive predictive value (PPV) ranging from 95% to 99% and 91% to 96%, respectively. Overall, the tri-axial accelerometer was capable of identifying licking behaviour of beef cattle in a controlled environment. Further research is required to test the model under actual grazing conditions.
Publication Type: Journal Article
Source of Publication: Animals, 11(4), p. 1-16
Publisher: MDPI AG
Place of Publication: Switzerland
ISSN: 2076-2615
Fields of Research (FoR) 2020: 300303 Animal nutrition
Socio-Economic Objective (SEO) 2020: 100401 Beef cattle
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science
School of Science and Technology

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