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Can accelerometer ear tags identify behavioural changes in sheep associated with parturition?

journal contribution
posted on 16.06.2021, 01:14 by Eloise Fogarty, David Swain, GM Cronin, LE Moraes, Mark Trotter
On-animal sensor systems provide an opportunity to monitor ewes during parturition, potentially reducing ewe and lamb mortality risk. This study investigated the capacity of machine learning (ML) behaviour classification to monitor changes in sheep behaviour around the time of lambing using ear-borne accelerometers. Accelerometers were attached to 27 ewes grazing a 4.4 ha paddock. Data were then classified based on three different ethograms: (i) detection of grazing, lying, standing, walking; (ii) detection of active behaviour; and (iii) detection of body posture. Proportion of time devoted to performing each behaviour and activity was then calculated at a daily and hourly scale. Frequency of posture change was also calculated on an hourly scale. Assessment of each metric using a linear mixed-effects model was conducted for the 7 days (day scale) or 12 h (hour scale) before and after lambing. For all physical movements, regardless of the ethogram, there was a change in the days surrounding lambing. This involved either a decrease (grazing, lying, active behaviour) or peak (standing, walking) on the day of parturition, with most values returning to either pre-partum or near-pre-partum levels (all P < 0.001). Hourly changes also occurred for all behaviours (all P < 0.001), the most marked being increased walking behaviour and frequency of posture change. These findings indicate ewes were more restless around the time of parturition. Further application of this research should focus on development of algorithms that can be used to identify onset of lambing and/or time of parturition in pasture-based ewes.

Funding

Category 3 - Industry and Other Research Income

History

Volume

216

Start Page

1

End Page

13

Number of Pages

13

eISSN

1873-2232

ISSN

0378-4320

Location

Netherlands

Publisher

Elsevier

Language

eng

Peer Reviewed

Yes

Open Access

No

Acceptance Date

19/03/2020

External Author Affiliations

The University of Sydney; The Ohio State University, USA

Author Research Institute

Institute for Future Farming Systems

Era Eligible

Yes

Medium

Print-Electronic

Journal

Animal Reproduction Science

Article Number

106345