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dc.contributor.authorBuller, H
dc.contributor.authorBlokhuis, H
dc.contributor.authorLokhorst, K
dc.contributor.authorSilberberg, M
dc.contributor.authorVeissier, I
dc.date.accessioned2020-10-15T09:52:27Z
dc.date.issued2020-10-01
dc.description.abstractAlthough there now exists a wide range of policies, instruments and regulations, in Europe and increasingly beyond, to improve and safeguard the welfare of farmed animals, there remain persistent and significant welfare issues in virtually all types of animal production systems ranging from high prevalence of lameness to limited possibilities to express natural behaviours. Protocols and indicators, such as those provided by Welfare Quality, mean that animal welfare can nowadays be regularly measured and surveyed at the farm level. However, the digital revolution in agriculture opens possibilities to quantify animal welfare using multiple sensors and data analytics. This allows daily monitoring of animal welfare at the group and individual animal level, for example, by measuring changes in behaviour patterns or physiological parameters. The present paper explores the potential for developing innovations in digital technologies to improve the management of animal welfare at the farm, during transport or at slaughter. We conclude that the innovations in Precision Livestock Farming (PLF) offer significant opportunities for a more holistic, evidence-based approach to the monitoring and surveillance of farmed animal welfare. To date, the emphasis in much PLF technologies has been on animal health and productivity. This paper argues that this emphasis should not come to define welfare. What is now needed is a coming together of industry, scientists, food chain actors, policy-makers and NGOs to develop and use the promise of PLF for the creative and effective improvement of farmed animal welfare.en_GB
dc.identifier.citationVol. 10 (10), article 1779en_GB
dc.identifier.doi10.3390/ani10101779
dc.identifier.urihttp://hdl.handle.net/10871/123249
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectanimal welfareen_GB
dc.subjectprecision livestock farmingen_GB
dc.subjectwelfare managementen_GB
dc.subjectwelfare monitoringen_GB
dc.subjectwelfare assuranceen_GB
dc.titleAnimal Welfare Management in a Digital Worlden_GB
dc.typeArticleen_GB
dc.date.available2020-10-15T09:52:27Z
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this recorden_GB
dc.identifier.eissn2076-2615
dc.identifier.journalAnimalsen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-09-24
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-10-01
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-10-15T09:50:34Z
refterms.versionFCDVoR
refterms.dateFOA2020-10-15T09:52:33Z
refterms.panelCen_GB


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).