Veterinary medicine and science · 2026
Precision Livestock Farming Technologies for Sheep Welfare in Extensive Systems: A Comprehensive Review.
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Souf Ikram Ben, Darej Cyrine, Najjar Amel, M'Hamdi Naceur
Аннотация
BACKGROUND: Ensuring animal welfare in extensive sheep production systems remains challenging due to large grazing areas, limited human supervision and the difficulty of detecting early signs of health or behavioural problems. Precision Livestock Farming (PLF) technologies have emerged as promising tools to enhance monitoring and welfare assessment in such environments.
OBJECTIVE: This review examines recent advances in PLF technologies and their potential contribution to improving sheep welfare in extensive farming systems.
METHODS: A synthesis of more than 35 peer-reviewed studies was conducted, focusing on the use of wearable sensors, computer vision, artificial intelligence and environmental monitoring technologies for behavioural and physiological assessment in sheep.
RESULTS: The reviewed literature indicates that wearable devices, including accelerometers and Global Positioning System (GPS) collars, can achieve up to 85% accuracy in detecting lameness and over 97% accuracy in identifying stress-related physiological changes. Integration of remote sensing tools, drones and ground-based sensors also improves monitoring of grazing patterns, social behaviour and environmental conditions. However, adoption remains limited due to economic costs, technical constraints and limited farmer awareness.
CONCLUSIONS: Advances in cost-effective sensors, standardized welfare indicators and participatory technology design may facilitate wider adoption of PLF tools, supporting improved animal welfare, productivity and sustainability in extensive sheep production systems.
OBJECTIVE: This review examines recent advances in PLF technologies and their potential contribution to improving sheep welfare in extensive farming systems.
METHODS: A synthesis of more than 35 peer-reviewed studies was conducted, focusing on the use of wearable sensors, computer vision, artificial intelligence and environmental monitoring technologies for behavioural and physiological assessment in sheep.
RESULTS: The reviewed literature indicates that wearable devices, including accelerometers and Global Positioning System (GPS) collars, can achieve up to 85% accuracy in detecting lameness and over 97% accuracy in identifying stress-related physiological changes. Integration of remote sensing tools, drones and ground-based sensors also improves monitoring of grazing patterns, social behaviour and environmental conditions. However, adoption remains limited due to economic costs, technical constraints and limited farmer awareness.
CONCLUSIONS: Advances in cost-effective sensors, standardized welfare indicators and participatory technology design may facilitate wider adoption of PLF tools, supporting improved animal welfare, productivity and sustainability in extensive sheep production systems.