Lameness Detection in Dairy Cows: Part 2. Use of Sensors to Automatically Register Changes in Locomotion or Behavior
Identifieur interne : 000064 ( Pmc/Curation ); précédent : 000063; suivant : 000065Lameness Detection in Dairy Cows: Part 2. Use of Sensors to Automatically Register Changes in Locomotion or Behavior
Auteurs : Annelies Van Nuffel ; Ingrid Zwertvaegher ; Stephanie Van Weyenberg ; Matti Pastell ; Vivi M. Thorup [France] ; Claudia Bahr ; Bart Sonck [Belgique] ; Wouter SaeysSource :
- Animals : an Open Access Journal from MDPI [ 2076-2615 ] ; 2015.
Abstract
As lame cows produce less milk and tendto have other health problems, finding and treating lame cows is very importantfor farmers. Sensors that measure behaviors associated with lameness in cowscan help by alerting the farmer of those cows in need of treatment. This reviewgives an overview of sensors for automated lameness detection and discussessome practical considerations for investigating and applying such systems inpractice.
Despite the research on opportunities toautomatically measure lameness in cattle, lameness detection systems are notwidely available commercially and are only used on a few dairy farms. However, farmers need to be aware of the lame cows in their herds in order treat themproperly and in a timely fashion. Many papers have focused on the automatedmeasurement of gait or behavioral cow characteristics related to lameness. Inorder for such automated measurements to be used in a detection system, algorithms to distinguish between non-lame and mildly or severely lame cowsneed to be developed and validated. Few studies have reached this latter stageof the development process. Also, comparison between the different approachesis impeded by the wide range of practical settings used to measure the gait or behavioralcharacteristic (e.g., measurements during normal farming routine or duringexperiments; cows guided or walking at their own speed) and by the differentdefinitions of lame cows. In the majority of the publications, mildly lame cowsare included in the non-lame cow group, which limits the possibility of alsodetecting early lameness cases. In this review, studies that used sensortechnology to measure changes in gait or behavior of cows related to lamenessare discussed together with practical considerations when conducting lamenessresearch. In addition, other prerequisites for any lameness detection system onfarms (e.g., need for early detection, real-time measurements) are discussed.
Url:
DOI: 10.3390/ani5030388
PubMed: 26479390
PubMed Central: 4598710
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Lameness Detection in Dairy Cows: Part 2. Use of Sensors to Automatically Register Changes in Locomotion or Behavior</title>
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(I.Z);<email>stephanie.vanweyenberg@ilvo.vlaanderen.be</email>
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<author><name sortKey="Zwertvaegher, Ingrid" sort="Zwertvaegher, Ingrid" uniqKey="Zwertvaegher I" first="Ingrid" last="Zwertvaegher">Ingrid Zwertvaegher</name>
<affiliation><nlm:aff id="af1-animals-05-00388">Technology and Food Science Unit, Precision Livestock Farming, Institute for Agricultural and Fisheries Research (ILVO), Burgemeester van Gansberghelaan 115 bus 1, 9820 Merelbeke, Belgium; E-Mails:<email>ingrid.zwertvaegher@ilvo.vlaanderen.be</email>
(I.Z);<email>stephanie.vanweyenberg@ilvo.vlaanderen.be</email>
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(I.Z);<email>stephanie.vanweyenberg@ilvo.vlaanderen.be</email>
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<author><name sortKey="Pastell, Matti" sort="Pastell, Matti" uniqKey="Pastell M" first="Matti" last="Pastell">Matti Pastell</name>
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<author><name sortKey="Bahr, Claudia" sort="Bahr, Claudia" uniqKey="Bahr C" first="Claudia" last="Bahr">Claudia Bahr</name>
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<author><name sortKey="Sonck, Bart" sort="Sonck, Bart" uniqKey="Sonck B" first="Bart" last="Sonck">Bart Sonck</name>
<affiliation><nlm:aff id="af6-animals-05-00388">Animal Sciences Unit, Institute for Agricultural and Fisheries Research (ILVO), Scheldeweg 68, 9090 Melle, Belgium; E-Mail:<email>bart.sonck@ilvo.vlaanderen.be</email>
</nlm:aff>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="af7-animals-05-00388">Department of Biosystems Engineering, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, 9000 Gent, Belgium</nlm:aff>
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<wicri:regionArea>Department of Biosystems Engineering, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, 9000 Gent</wicri:regionArea>
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<author><name sortKey="Saeys, Wouter" sort="Saeys, Wouter" uniqKey="Saeys W" first="Wouter" last="Saeys">Wouter Saeys</name>
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<series><title level="j">Animals : an Open Access Journal from MDPI</title>
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<front><div type="abstract" xml:lang="en"><sec><title>Simple Summary</title>
<p>As lame cows produce less milk and tendto have other health problems, finding and treating lame cows is very importantfor farmers. Sensors that measure behaviors associated with lameness in cowscan help by alerting the farmer of those cows in need of treatment. This reviewgives an overview of sensors for automated lameness detection and discussessome practical considerations for investigating and applying such systems inpractice.</p>
</sec>
<sec><title>Abstract</title>
<p>Despite the research on opportunities toautomatically measure lameness in cattle, lameness detection systems are notwidely available commercially and are only used on a few dairy farms. However, farmers need to be aware of the lame cows in their herds in order treat themproperly and in a timely fashion. Many papers have focused on the automatedmeasurement of gait or behavioral cow characteristics related to lameness. Inorder for such automated measurements to be used in a detection system, algorithms to distinguish between non-lame and mildly or severely lame cowsneed to be developed and validated. Few studies have reached this latter stageof the development process. Also, comparison between the different approachesis impeded by the wide range of practical settings used to measure the gait or behavioralcharacteristic (e.g., measurements during normal farming routine or duringexperiments; cows guided or walking at their own speed) and by the differentdefinitions of lame cows. In the majority of the publications, mildly lame cowsare included in the non-lame cow group, which limits the possibility of alsodetecting early lameness cases. In this review, studies that used sensortechnology to measure changes in gait or behavior of cows related to lamenessare discussed together with practical considerations when conducting lamenessresearch. In addition, other prerequisites for any lameness detection system onfarms (e.g., need for early detection, real-time measurements) are discussed.</p>
</sec>
</div>
</front>
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</TEI>
<pmc article-type="review-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Animals (Basel)</journal-id>
<journal-id journal-id-type="iso-abbrev">Animals (Basel)</journal-id>
<journal-id journal-id-type="publisher-id">animals</journal-id>
<journal-title-group><journal-title>Animals : an Open Access Journal from MDPI</journal-title>
</journal-title-group>
<issn pub-type="epub">2076-2615</issn>
<publisher><publisher-name>MDPI</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">26479390</article-id>
<article-id pub-id-type="pmc">4598710</article-id>
<article-id pub-id-type="doi">10.3390/ani5030388</article-id>
<article-id pub-id-type="publisher-id">animals-05-00388</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Review</subject>
</subj-group>
</article-categories>
<title-group><article-title>Lameness Detection in Dairy Cows: Part 2. Use of Sensors to Automatically Register Changes in Locomotion or Behavior</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Van Nuffel</surname>
<given-names>Annelies</given-names>
</name>
<xref ref-type="aff" rid="af1-animals-05-00388">1</xref>
<xref rid="c1-animals-05-00388" ref-type="corresp">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zwertvaegher</surname>
<given-names>Ingrid</given-names>
</name>
<xref ref-type="aff" rid="af1-animals-05-00388">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Van Weyenberg</surname>
<given-names>Stephanie</given-names>
</name>
<xref ref-type="aff" rid="af1-animals-05-00388">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Pastell</surname>
<given-names>Matti</given-names>
</name>
<xref ref-type="aff" rid="af2-animals-05-00388">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Thorup</surname>
<given-names>Vivi M.</given-names>
</name>
<xref ref-type="aff" rid="af3-animals-05-00388">3</xref>
<xref ref-type="aff" rid="af4-animals-05-00388">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Bahr</surname>
<given-names>Claudia</given-names>
</name>
<xref ref-type="aff" rid="af5-animals-05-00388">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Sonck</surname>
<given-names>Bart</given-names>
</name>
<xref ref-type="aff" rid="af6-animals-05-00388">6</xref>
<xref ref-type="aff" rid="af7-animals-05-00388">7</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Saeys</surname>
<given-names>Wouter</given-names>
</name>
<xref ref-type="aff" rid="af8-animals-05-00388">8</xref>
</contrib>
</contrib-group>
<contrib-group><contrib contrib-type="editor"><name><surname>Huxley</surname>
<given-names>Jon</given-names>
</name>
<role>Academic Editor</role>
</contrib>
</contrib-group>
<aff id="af1-animals-05-00388"><label>1</label>
Technology and Food Science Unit, Precision Livestock Farming, Institute for Agricultural and Fisheries Research (ILVO), Burgemeester van Gansberghelaan 115 bus 1, 9820 Merelbeke, Belgium; E-Mails:<email>ingrid.zwertvaegher@ilvo.vlaanderen.be</email>
(I.Z);<email>stephanie.vanweyenberg@ilvo.vlaanderen.be</email>
(S.V.W.)</aff>
<aff id="af2-animals-05-00388"><label>2</label>
Natural Resources Institute Finland (Luke), Green Technology, Koetilantie 5, 00790 Helsinki, Finland; E-Mail:<email>matti.pastell@luke.fi</email>
</aff>
<aff id="af3-animals-05-00388"><label>3</label>
INRA, UMR 791 Systemic Modelling of Ruminant Nutrition, 16 rue Claude Bernard, 75231 Paris cedex 05, France</aff>
<aff id="af4-animals-05-00388"><label>4</label>
AgroParisTech, UMR 791 Systemic Modelling of Ruminant Nutrition, 16 rue Claude Bernard, 75231 Paris cedex 05, France; E-Mail:<email>vivi.thorup@agroparistech.fr</email>
</aff>
<aff id="af5-animals-05-00388"><label>5</label>
Division Measure, Model and Manage BioResponses, Department of Biosystems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30 bus 2456, 3001 Heverlee, Belgium; E-Mail:<email>Claudia.bahr@biw.kuleuven.be</email>
</aff>
<aff id="af6-animals-05-00388"><label>6</label>
Animal Sciences Unit, Institute for Agricultural and Fisheries Research (ILVO), Scheldeweg 68, 9090 Melle, Belgium; E-Mail:<email>bart.sonck@ilvo.vlaanderen.be</email>
</aff>
<aff id="af7-animals-05-00388"><label>7</label>
Department of Biosystems Engineering, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, 9000 Gent, Belgium</aff>
<aff id="af8-animals-05-00388"><label>8</label>
Division Mechatronics, Biostatistics and Sensors (MeBioS), Department of Biosystems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30 bus 2456, 3001 Heverlee, Belgium; E-Mail:<email>wouter.saeys@biw.kuleuven.be</email>
</aff>
<author-notes><corresp id="c1-animals-05-00388"><label>*</label>
Author to whom correspondence should be addressed; E-Mail: <email>annelies.vannuffel@ilvo.vlaanderen.be</email>
.</corresp>
</author-notes>
<pub-date pub-type="epub"><day>28</day>
<month>8</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="collection"><month>9</month>
<year>2015</year>
</pub-date>
<volume>5</volume>
<issue>3</issue>
<fpage>861</fpage>
<lpage>885</lpage>
<history><date date-type="received"><day>29</day>
<month>5</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>23</day>
<month>7</month>
<year>2015</year>
</date>
</history>
<permissions><copyright-statement>© 2015 by the authors; licensee MDPI, Basel, Switzerland.</copyright-statement>
<copyright-year>2015</copyright-year>
<license><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
).</license-p>
</license>
</permissions>
<abstract><sec><title>Simple Summary</title>
<p>As lame cows produce less milk and tendto have other health problems, finding and treating lame cows is very importantfor farmers. Sensors that measure behaviors associated with lameness in cowscan help by alerting the farmer of those cows in need of treatment. This reviewgives an overview of sensors for automated lameness detection and discussessome practical considerations for investigating and applying such systems inpractice.</p>
</sec>
<sec><title>Abstract</title>
<p>Despite the research on opportunities toautomatically measure lameness in cattle, lameness detection systems are notwidely available commercially and are only used on a few dairy farms. However, farmers need to be aware of the lame cows in their herds in order treat themproperly and in a timely fashion. Many papers have focused on the automatedmeasurement of gait or behavioral cow characteristics related to lameness. Inorder for such automated measurements to be used in a detection system, algorithms to distinguish between non-lame and mildly or severely lame cowsneed to be developed and validated. Few studies have reached this latter stageof the development process. Also, comparison between the different approachesis impeded by the wide range of practical settings used to measure the gait or behavioralcharacteristic (e.g., measurements during normal farming routine or duringexperiments; cows guided or walking at their own speed) and by the differentdefinitions of lame cows. In the majority of the publications, mildly lame cowsare included in the non-lame cow group, which limits the possibility of alsodetecting early lameness cases. In this review, studies that used sensortechnology to measure changes in gait or behavior of cows related to lamenessare discussed together with practical considerations when conducting lamenessresearch. In addition, other prerequisites for any lameness detection system onfarms (e.g., need for early detection, real-time measurements) are discussed.</p>
</sec>
</abstract>
<kwd-group><kwd>Lameness</kwd>
<kwd>early detection</kwd>
<kwd>on-farm</kwd>
<kwd>dairy cattle</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
</record>
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