Challenges and opportunities for precision livestock farming applications in the rabbit production sector

Tomás Norton

https://orcid.org/0000-0002-0161-3189

Belgium

KU Leuven image/svg+xml

Department of Biosystems, Division of Animal and Human Health Engineering, Faculty of Bioscience Engineering, KU Leuven

María Cambra-López

https://orcid.org/0000-0001-6130-9392

Spain

Universitat Politècnica de València image/svg+xml

Institute of Animal Science and Technology, Universitat Politècnica de Valencia

|

Accepted: 2025-04-07

|

Published: 2025-06-30

DOI: https://doi.org/10.4995/wrs.2025.22701
Funding Data

Downloads

Keywords:

rabbit farming, precision livestock farming, remote sensing, animal monitoring

Supporting agencies:

This publication is part of the FREE-RAB project (PID2022-143036OB-I00) Tailor-made feeding strategies and precision livestock farming technology for cage-free rabbit farming, funded by MICIU/AEI /10.13039/501100011033FREE-RAB project (PID2022-143036OB-I00) Tailor-made feeding strategies and precision livestock farming technology for cage-free rabbit farming, funded by MICIU/AEI /10.13039/501100011033

Abstract:

Precision livestock farming (PLF) is an established field in many livestock sectors. However, when it comes to rabbit production, it is still emerging. Nevertheless, we believe that the rapid advancements in sensor technologies, data analytics and automation we are witnessing can bring significant and transformative opportunities to the rabbit farming industry. Within this context, this paper explores the potential use of PLF for the rabbit sector. We start by briefly reviewing the current state of the art of PLF applications in other livestock sectors, such as dairy and pig farming, focusing on remote sensing solutions. Then we outline how different technologies can potentially be adapted for rabbit production. Recent rabbit research studies that implement PLF-like technology are then reviewed. We finalise by discussing the challenges of implementing PLF in rabbit farming, including the need for tailored solutions that consider rabbits’ specific behavioural and physiological characteristics. When considering the future impact of PLF, early disease detection probably offers the highest potential for rabbit production. Being able to automatically detect early signs of digestive disorders around weaning, particularly in large group-housed growing rabbits where disease spread is a concern, would represent a significant step forward. Additionally, PLF tools can enhance rabbit breeding and genetic programmes by providing detailed and accurate individual phenotypic data. Data can be then used to better define animal management practices that promote positive experiences and affective states, reducing negative social interactions. Besides, precision feeding models could contribute to enhancing feed efficiency for both growing and reproductive rabbits, reducing the negative environmental impact of feeding. To this end, camera monitoring, sound analysis, electronic feeders, accelerometers and other biometric and physiological monitoring technologies can be utilised. The integration of PLF technologies promises to support farmers in meeting the increasingly stringent welfare regulations across the European Union, ultimately enhancing the sustainability and profitability of rabbit production systems. Further research is needed to address the challenges that remain in developing and validating reliable algorithms so that sensors can be used more effectively in diverse rabbit farm conditions.

Show more Show less

References:

Adedeji O.J., Abayomi-Alli A., Arogundade O., Abayomi-Alli O., Omoyiola B.O. 2023. Deep transfer learning for classification of rabbit behaviour using publicly available datasets. In: First International Conference on the Advancements of Artificial Intelligence in African Context (AAIAC), Arusha, Tanzania, United Republic 2023, 1-10. https://doi.org/10.1109/AAIAC60008.2023.1046547

Adell E., Calvet S., Torres A.G., Cambra-López M. 2012. Particulate matter concentrations and emissions in rabbit farms. World Rabbit Sci., 20: 1-11. https://doi.org/10.4995/wrs.2012.1035

Agea I., García M.L., Argente M.J. 2021. Preliminary study of body temperature emissivity in rabbits selected for litter size residual variability. Agriculture, 11: 604. https://doi.org/10.3390/agriculture11070604

Bäuerl C., Collado M.C., Zuniga M., Blas E., Pérez Martínez G. 2014. Changes in cecal microbiota and mucosal gene expression revealed new aspects of epizootic rabbit enteropathy. PLoS ONE, 9: e105707. https://doi.org/10.1371/journal.pone.0105707

Birolo M., Trocino A., Zuffellato A., Xiccato G. 2019. Time-based feed restriction and group size in growing rabbits: effects on health status and growth performance. Ital. J. Anim. Sci.,18: 79. https://doi.org/10.1080/1828051X.2018.1532329

Briefer E.F., Sypherd C.C.R., Linhart P., Leliveld L.M., Padilla de La Torre M., Read E.R., Guérin C., Deiss V., Monestier C., Rasmussen J.H., Špinka M. 2022. Classification of pig calls produced from birth to slaughter according to their emotional valence and context of production. Sci. Rep., 12: 3409. https://doi.org/10.1038/s41598-022-07174-8

Calvet S., Cambra-López M., Estellés F., Torres A.G. 2011. Characterization of the indoor environment and gas emissions in rabbit farms. World Rabbit Sci., 19: 49-61. https://doi.org/10.4995/wrs.2011.802

Cambra-López M., Aarnink A.J., Zhao Y., Calvet S., Torres A.G. 2010. Airborne particulate matter from livestock production systems: a review of an air pollution problem. Environ. Pollut., 158: 1-17. https://doi.org/10.1016/j.envpol.2009.07.011

Cambra-López M., Blas E., Marín-García P., Zemzmi J., Ródenas L., Martínez-Paredes E., López M.C., Ramón-Moragues A., Zhao Y., Remus A., Pascual J.J. 2023. Cómo puede contribuir la ganadería de precisión a la transición hacia el alojamiento sin jaulas de la cunicultura. In: XX Jornadas sobre Producción Animal de AIDA, AIDA-ITEA, 269.

Cambra-López M., Ramón-Moragues A., Blas E., Marín-García P., Pascual J.J. 2024. Opportunities for precision livestock farming applications in cage-free farming. In Proc.: European Precision Livestock Farming Conference 2024. Bolonia, Italy.

Carpentier L., Vranken E., Berckmans D., Paeshuyse J., Norton T. 2019. Development of sound-based poultry health monitoring tool for automated sneeze detection. Computers and electronics in agriculture, 162: 573-581. https://doi.org/10.1016/j.compag.2019.05.013

Chen Y., Niimi M., Zhang L., Tang X., Lu J., Fan J. 2023. A simple telemetry sensor system for monitoring body temperature in rabbits-A brief report. Animals 13: 1677. https://doi.org/10.3390/ani13101677

Chen C., Zhu W. and Norton T. 2021. Behaviour recognition of pigs and cattle: Journey from computer vision to deep learning. Comput. Electron. Agric., 187: 106255. https://doi.org/10.1016/j.compag.2021.106255

CIWF, Compassion in world farming. 2020. End the cage age. Why the EU must stop caging farm animals. “End the Cage Age”. Accessible at https://www.ciwf.org.uk/

Duan E.Z., Wang L.J., Wang H.Y., Hao H.Y., Li R.L. 2022. Remaining feed weight estimation model for health monitoring of meat rabbits based on deep convolutional neural network. Int. J. Agric. Biol. Eng., 15: 233-240. https://doi.org/10.25165/j.ijabe.20221501.6797

EFSA AHAW Panel (EFSA Panel on animal health and welfare), 2020. Saxmose Nielsen S., Alvarez J., Bicout D.J., Calistri P., Depner K., Drewe J.A., Garin-Bastuji B., Gonzales Rojas J.L., Gortázar Schmidt C., Michel V., Miranda Chueca M.A., Roberts H.C., Sihvonen L.H., Spoolder H., Stahl K., Velarde Calvo A., Viltrop A., Buijs S., Edwards S., Candiani D., Mosbach-Schulz O., Van der Stede Y., Winckler C. Scientific Opinion on the health and welfare of rabbits farmed in different production systems. EFSA 4: 96 pp.

European Commission. 2017. Directorate-General for Health and Food Safety, Commercial rabbit farming in the European Union - Overview report, Publications Office, 2017. Accessible at https://data.europa.eu/doi/10.2772/62174

European Commission. 2021. Communication from the Commission on the European Citizens’ Initiative (ECI) “End the Cage Age”. C(2021)4747. Directorate-General for Health and Food Safety, European Commission.

Exadaktylos V., Silva M., Aerts J.M., Taylor C.J., Berckmans D. 2008. Real-time recognition of sick pig cough sounds. Comput. Electron. Agric., 63: 207-214. https://doi.org/10.1016/j.compag.2008.02.010

García M., Gunia M., Argente M. 2021. Genetic factors of functional traits. World Rabbit Sci., 29: 207-220. https://doi.org/10.4995/wrs.2021.13320

Gidenne T., Fortun-Lamothe L., Huang Y., Savietto D. 2024. Pastured rabbit systems and organic certification: European union regulations and technical and economic performance in France. World Rabbit Sci., 32: 83-97. https://doi.org/10.4995/wrs.2024.20894

Giersberg F.M., Kemper N., Fels M. 2015. Planimetric measurement of floor space covered by fattening rabbits and breeding does in different body positions and weight classes. Livest. Sci., 177: 142-150. https://doi.org/10.1016/j.livsci.2015.04.010

Huneau-Salaün A., Bougeard S., Balaine L., Eono F., Le Bouquin S., Chauvin C. 2015. Husbandry factors and health conditions influencing the productivity of French rabbit farms. World Rabbit Sci., 23: 27-37. https://doi.org/10.4995/wrs.2015.3076

Ipek N., Van Damme L.G.W., Tuyttens F.A.M., Verwaeren J. 2023. Quantifying agonistic interactions between group-housed animals to derive social hierarchies using computer vision: a case study with commercially group-housed rabbits. Sci. Rep., 13: 14138. https://doi.org/10.1038/s41598-023-41104-6

Jaén-Téllez J.A., Sánchez-Guerrero M.J., Valera M., González-Redondo P. 2021. Influence of stress assessed through infrared thermography and environmental parameters on the performance of fattening rabbits. Animals, 11: 1747. https://doi.org/10.3390/ani11061747

Latham A.D.M., Nugent G., Warburton B. 2012. Evaluation of camera traps for monitoring European rabbits before and after control operations in Otago, New Zealand. Wildl. Res., 39: 621-628. https://doi.org/10.1071/WR12050

Licois D., Wyers M., Coudert P. 2005. Epizootic Rabbit Enteropathy: experimental transmission and clinical characterization. Vet. Res., 36: 601-613. https://doi.org/10.1051/vetres:2005021

Liu D., He D., Norton T. 2020. Automatic estimation of dairy cattle body condition score from depth image using ensemble model. Biosyst. Eng., 194: 16-27. https://doi.org/10.1016/j.biosystemseng.2020.03.011

Liu D., Parmiggiani A., Psota E., Fitzgerald R. and Norton T. 2023. Where’s your head at? Detecting the orientation and position of pigs with rotated bounding boxes. Comput. Electron. Agric., 212: 108099. https://doi.org/10.1016/j.compag.2023.108099

Machado L.C., Martínez-Paredes E., Cervera C. 2019. Performance of rabbit does housed in collective pens and individual cages. World Rabbit Sci., 27: 227-235. https://doi.org/10.4995/wrs.2019.11540

Machado L.C., Simões J. 2024. Rabbit farming: industrial, small-scale, and organic housing systems. In: Simões J., Monteiro J.M. (eds) Veterinary care of farm rabbits. Springer, Cham. https://doi.org/10.1007/978-3-031-44542-2_5

Matics Z., Cullere M., Dalle Zotte A., Szendrő K., Szendrő Z., Odermatt M., Atkári T., Radnai I., Nagy I., Gerencsér Z. 2019. Effect of cage and pen housing on the live performance, carcase, and meat quality traits of growing rabbits. Ital. J. Anim. Sci., 18: 441-449. https://doi.org/10.1080/1828051X.2018.1532329

Martínez-Paredes E., Nicodemus N., Pascual J.J., García J. 2022. Challenges in rabbit doe feeding, including the young doe. World Rabbit Sci., 30: 13-34. https://doi.org/10.4995/wrs.2022.15562

Monclús R., Rödel H.G. 2008. Different forms of vigilance in response to the presence of predators and conspecifics in a group-living mammal, the European Rabbit. Ethology, 114: 287-297. https://doi.org/10.1111/j.1439-0310.2007.01463.x

Nan J.I., Yanling Y.I.N., Weizheng S.H.E.N., Shengli K.O.U., Baisheng D.A.I., Guowei W.A.N.G. 2022. Pig sound analysis: a measure of welfare. Smart Agric., 4: 19.

Negretti P., Bianconi G., Finzi A. 2007. Visual image analysis to estimate morphological and weight measurements in rabbits. World Rabbit Sci., 15: 37-41. https://doi.org/10.4995/wrs.2007.606

Parmiggiani A., Liu D., Psota E., Fitzgerald R., Norton T. 2023. Don’t get lost in the crowd: Graph convolutional network for online animal tracking in dense groups. Comput. Electron. Agric., 212: 108038. https://doi.org/10.1016/j.compag.2023.108038

Pérez-Fuentes S., Muñoz-Silvestre A., Moreno-Grua E., Martínez-Paredes E., Viana D., Selva L., Villagrá A., Sanz-Tejero C., Pascual J.J., Cervera C., Corpa J.M. 2020. Effect of different housing systems (single and group penning) on the health and welfare of commercial female rabbits. Animal, 14: 1270-1277. https://doi.org/10.1017/S1751731119003379

Piles M., Mora M., Kyriazakis I., Tusell L., Pascual M., Sánchez J.P. 2024. Novel phenotypes of feeding and social behaviour and their relationship with individual rabbit growth and feed efficiency. Animal, 18: 101090. https://doi.org/10.1016/j.animal.2024.101090

Pomar C., Remus A. 2019. Precision pig feeding: a breakthrough toward sustainability. Animal Front., 9: 52-59. https://doi.org/10.1093/af/vfz006

Psiroukis V., Malounas I., Mylonas N., Grivakis K.E., Fountas S., Hadjigeorgiou I. 2021. Monitoring of free-range rabbits using aerial thermal imaging. Smart Agric. Technol., 1100002. https://doi.org/10.1016/j.atech.2021.100002

Rosell J.M., de la Fuente L.F. 2009. Culling and mortality in breeding rabbits. Prev. Vet. Med., 88: 120-127. https://doi.org/10.1016/j.prevetmed.2008.08.003

Rosell J.M., de la Fuente L.F. 2016. Causes of mortality in breeding rabbits. Prev. Vet. Med., 127: 56-63. https://doi.org/10.1016/j.prevetmed.2016.03.014

Rosell J.M., de la Fuente L.F., Badiola J.I., Perez de Rozas A., Fernández de Luco D., Arnal M.C., Casal J. X.M., Pinto de Carvalho A. 2023. Respiratory disorders of farmed rabbits: occurrence and risk factors. World Rabbit Sci., 31: 147-161. https://doi.org/10.4995/wrs.2023.18280

Sánchez J.P., Muñoz I., González O., Pascual M., Perucho O., Alsina P., Piles M. 2022. A computer vision system for individual tracking of group housed rabbits. In Proc.: 12th World Congress on Genetics Applied to Livestock Production (WCGALP) Wageningen, The Netherlands, 610-613. https://doi.org/10.3920/978-90-8686-940-4_140

Sánchez J.P., Muñoz J., Chetrit R., Pascual M., Piles M. 2024. Method: eFeederRab: A new electronic feeder to measure individual feed intake−related traits on growing rabbits raised in collective cages. Animal - Open Space, 3: 100074 https://doi.org/10.1016/j.anopes.2024.100074

Savietto D., Fillon V., Temple-Boyer A., Derbez F., Aymard P., Pujol S., Rodríguez A., Borne S., Simon S., Grillot M., Lhoste E., Dufils A., Drusch S. 2023. Design of a functional organic agroforestry system associating rabbits and apple trees. Animal-Open Space, 2: 100051. https://doi.org/10.1016/j.anopes.2023.100051

Schofield C.P., Marchant J.A., White R.P., Brandl N., Wilson M. 1999. Monitoring pig growth using a prototype imaging system. J. Agric. Eng. Res., 72: 205-210. https://doi.org/10.1006/jaer.1998.0365

Studd E.K., Boudreau M.R., Majchrzak Y.N., Menzies A.K., Peers M.J.L., Seguin J.L., Lavergne S.G., Boonstra R., Murray D.L., Boutin S., Humphries M.M. 2019. Use of acceleration and acoustics to classify behavior, generate time budgets, and evaluate responses to moonlight in free-ranging snowshoe hares. Front. Ecol. Evol., 7: 154. https://doi.org/10.3389/fevo.2019.00154

Szendrő, Zs., Dalle Zotte A. 2011. Effect of housing conditions on production and behaviour of growing meat rabbits: A review. Livest. Sci., 137: 296-303. https://doi.org/10.1016/j.livsci.2010.11.012

Trocino A., Xiccato G. 2006. Animal welfare in reared rabbits: a review with emphasis on housing systems. World Rabbit Sci., 14: 77-93. https://doi.org/10.4995/wrs.2006.553

Verga M., Luzi F., Carenzi C. 2007. Effects of husbandry and management systems on physiology and behaviour of farmed and laboratory rabbits. Hormones Behav., 52: 122-129. https://doi.org/10.1016/j.yhbeh.2007.03.024

Show more Show less