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https://hdl.handle.net/2440/133892
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Type: | Journal article |
Title: | What are sheep doing? Tri‐axial accelerometer sensor data identify the diel activity pattern of ewe lambs on pasture |
Author: | Ikurior, S.J. Marquetoux, N. Leu, S.T. Corner‐thomas, R.A. Scott, I. Pomroy, W.E. |
Citation: | Sensors, 2021; 21(20):6816-1-6816-16 |
Publisher: | MDPI AG |
Issue Date: | 2021 |
ISSN: | 1424-8220 1424-8220 |
Statement of Responsibility: | Seer J. Ikurior, Nelly Marquetoux, Stephan T. Leu, Rene A. Corner-Thomas, Ian Scott and William E. Pomroy |
Abstract: | Monitoring activity patterns of animals offers the opportunity to assess individual health and welfare in support of precision livestock farming. The purpose of this study was to use a triaxial accelerometer sensor to determine the diel activity of sheep on pasture. Six Perendale ewe lambs, each fitted with a neck collar mounting a triaxial accelerometer, were filmed during targeted periods of sheep activities: grazing, lying, walking, and standing. The corresponding acceleration data were fitted using a Random Forest algorithm to classify activity (=classifier). This classifier was then applied to accelerometer data from an additional 10 ewe lambs to determine their activity budgets. Each of these was fitted with a neck collar mounting an accelerometer as well as two additional accelerometers placed on a head halter and a body harness over the shoulders of the animal. These were monitored continuously for three days. A classification accuracy of 89.6% was achieved for the grazing, walking and resting activities (i.e., a new class combining lying and standing activity). Triaxial accelerometer data showed that sheep spent 64% (95% CI 55% to 74%) of daylight time grazing, with grazing at night reduced to 14% (95% CI 8% to 20%). Similar activity budgets were achieved from the halter mounted sensors, but not those on a body harness. These results are consistent with previous studies directly observing daily activity of pasture-based sheep and can be applied in a variety of contexts to investigate animal health and welfare metrics e.g., to better understand the impact that young sheep can suffer when carrying even modest burdens of parasitic nematodes. |
Keywords: | Sheep; diel activity; classification algorithm; tri-axial accelerometers; health monitoring |
Rights: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
DOI: | 10.3390/s21206816 |
Grant ID: | http://purl.org/au-research/grants/arc/DE170101132 |
Published version: | http://dx.doi.org/10.3390/s21206816 |
Appears in Collections: | Animal and Veterinary Sciences publications |
Files in This Item:
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hdl_133892.pdf | Published version | 2.22 MB | Adobe PDF | View/Open |
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