Application of non-invasive monitoring technology in intensive sheep farming: A review
Under the intensive sheep farming model, traditional monitoring and management methods face issues such as outdated equipment and low efficiency, which cannot fully meet the requirements for refined and intelligent management in breeding. This paper reviews the application of non-invasive monitoring...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375525004460 |
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| Summary: | Under the intensive sheep farming model, traditional monitoring and management methods face issues such as outdated equipment and low efficiency, which cannot fully meet the requirements for refined and intelligent management in breeding. This paper reviews the application of non-invasive monitoring technology in intensive sheep farms, analyzing the differences and application scenarios between contact and non-contact sensors. The results show that contact sensors have advantages such as relatively precise, continuous, and accurate monitoring of individual animals with minimal stress responses during use. However, they also have drawbacks, including wear and tear caused by stress and high equipment maintenance costs. Non-contact sensors, on the other hand, offer advantages such as scalability for group use, high accuracy, non-interference with sheep behavior, and no disruption of flock habits. Non-invasive monitoring technology demonstrates good accuracy and applicability in individual identification, behavior analysis, body measurement parameters, and physiological indicators. In the future, through in-depth integration of multidisciplinary and multi-field approaches and deep learning of multiple algorithms, non-invasive monitoring technology is expected to develop towards low cost and intelligence, providing a comprehensive solution for smart animal husbandry. |
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| ISSN: | 2772-3755 |