The rabbit production sector in Europe is undergoing a profound transformation, driven by evolving animal welfare standards and increasing economic and environmental constraints. In this context, precision livestock farming (PLF) technologies have been proposed as tools to support monitoring and decision-making, although their applicability under commercial conditions remains uncertain. This review adopts a need-driven approach to assess whether existing and emerging PLF technologies can effectively address key challenges in rabbit production such as on-farm efficiency, animal welfare and health monitoring even beyond the on-farm production stage. For each issue, relevant indicators were identified and linked to available technologies, which were evaluated in terms of precision and technological readiness (TRL). On-farm applications mainly focus on environmental monitoring and feed management. While Internet of things (IoT)-based sensors enable continuous assessment of microclimatic conditions, their ability to capture animal-level variability remains limited. Feeding technologies range from cage-level computer vision systems to individual Radio Frequency Identification (RFID)-based feeders and robotic solutions, showing increasing precision but also greater complexity and reduced applicability. Beyond the farm, monitoring during transport remains largely unexplored, with welfare outcomes assessed retrospectively at slaughter (e.g. death on arrival). In contrast, the slaughter stage offers concrete opportunities for PLF implementation, particularly through computer vision systems to assess stunning effectiveness and the use of iceberg indicators for on-farm welfare, such as body condition score and lesions. Although widely applied in other species, these advanced technologies have not yet been translated to rabbit production. Overall, current PLF technologies reveal a clear trade-off between measurement precision and practical feasibility, highlighting the need for scalable and decision-oriented solutions.
De las necesidades a la tecnología en la cunicultura de precisión
Bordignon F.;Xiccato G.;Trocino A.
2026
Abstract
The rabbit production sector in Europe is undergoing a profound transformation, driven by evolving animal welfare standards and increasing economic and environmental constraints. In this context, precision livestock farming (PLF) technologies have been proposed as tools to support monitoring and decision-making, although their applicability under commercial conditions remains uncertain. This review adopts a need-driven approach to assess whether existing and emerging PLF technologies can effectively address key challenges in rabbit production such as on-farm efficiency, animal welfare and health monitoring even beyond the on-farm production stage. For each issue, relevant indicators were identified and linked to available technologies, which were evaluated in terms of precision and technological readiness (TRL). On-farm applications mainly focus on environmental monitoring and feed management. While Internet of things (IoT)-based sensors enable continuous assessment of microclimatic conditions, their ability to capture animal-level variability remains limited. Feeding technologies range from cage-level computer vision systems to individual Radio Frequency Identification (RFID)-based feeders and robotic solutions, showing increasing precision but also greater complexity and reduced applicability. Beyond the farm, monitoring during transport remains largely unexplored, with welfare outcomes assessed retrospectively at slaughter (e.g. death on arrival). In contrast, the slaughter stage offers concrete opportunities for PLF implementation, particularly through computer vision systems to assess stunning effectiveness and the use of iceberg indicators for on-farm welfare, such as body condition score and lesions. Although widely applied in other species, these advanced technologies have not yet been translated to rabbit production. Overall, current PLF technologies reveal a clear trade-off between measurement precision and practical feasibility, highlighting the need for scalable and decision-oriented solutions.
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