Jorquera-Chavez, M, Fuentes, S, Dunshea, FR orcid.org/0000-0003-3998-1240 et al. (5 more authors) (2021) Using imagery and computer vision as remote monitoring methods for early detection of respiratory disease in pigs. Computers and Electronics in Agriculture, 187. 106283. ISSN 0168-1699
Abstract
Respiratory diseases in pigs impact the wellbeing of animals and increase the cost of production. One of the most appropriate approaches to minimizing these negative effects is the early detection of ill animals. The use of cameras coupled with computer-based techniques could assist the early detection of physiological changes in pigs when they are beginning to become ill and prior to exhibiting clinical signs. This study consisted of two experiments that aimed to (a) evaluate the use of computer-based techniques over RGB (red, green, and blue) and thermal infrared imagery to measure heart rate and respiration rate of pigs, and (b) to investigate whether eye-temperature, heart rate and respiration rate assessed remotely could be used to identify early signs of respiratory diseases in free-moving, and group-housed growing pigs in a commercial piggery. In the first experiment, the remotely-obtained heart rate and respiration rate were compared with the measures obtained with standard methods, showing positive correlations (r = 0.61 – 0.66; p < 0.05). In the second experiment, pigs were recorded by overhead cameras and the remotely-obtained physiological measures were analysed to identify whether physiological changes could be detected in sick pigs before clinical signs were observed. The changes in eye-temperature and heart rate remotely obtained showed clear differences between sick and healthy pigs two days before clinical signs were detected. While significant changes in respiration rate occurred the day before clinical signs of illness were identified. The results of the present study indicate the possible use of computer vision technique for constant animal monitoring and rapid detection of physiological changes related to illness in commercial pigs. Further research is recommended to continue the development, automatization, and commercial practicality of this novel technology.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier B.V. All rights reserved. This is an author produced version of an article, published in Computers and Electronics in Agriculture. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Animal monitoring; Non-invasive methods; Contactless monitoring; Animal health; Physiological indicators |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Jul 2021 10:22 |
Last Modified: | 05 May 2023 13:23 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.compag.2021.106283 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:176254 |
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