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dc.contributor.authorO’ Leary, Niall O’
dc.contributor.authorLeso, Lorenzo
dc.contributor.authorBuckley, Frank
dc.contributor.authorKenneally, Jonathon
dc.contributor.authorMcSweeney, Diarmuid
dc.contributor.authorShalloo, Laurence
dc.date.accessioned2020-08-28T14:25:48Z
dc.date.available2020-08-28T14:25:48Z
dc.date.issued2020-06-26
dc.identifier.citationO’ Leary, N.; Leso, L.; Buckley, F.; Kenneally, J.; McSweeney, D.; Shalloo, L. Validation of an Automated Body Condition Scoring System Using 3D Imaging. Agriculture 2020, 10, 246. https://doi.org/10.3390/agriculture10060246en_US
dc.identifier.issn2077-0472
dc.identifier.urihttp://hdl.handle.net/11019/2329
dc.descriptionpeer-revieweden_US
dc.description.abstractBody condition scores (BCS) measure a cow’s fat reserves and is important for management and research. Manual BCS assessment is subjective, time-consuming, and requires trained personnel. The BodyMat F (BMF, Ingenera SA, Cureglia, Switzerland) is an automated body condition scoring system using a 3D sensor to estimate BCS. This study assesses the BMF. One hundred and three Holstein Friesian cows were assessed by the BMF and two assessors throughout a lactation. The BMF output is in the 0–5 scale commonly used in France. We develop and report the first equation to convert these scores to the 1–5 scale used by the assessors in Ireland in this study ((0–5 scale × 0.38) + 1.67 → 1–5 scale). Inter-assessor agreement as measured by Lin’s concordance of correlation was 0.67. BMF agreement with the mean of the two assessors was the same as between assessors (0.67). However, agreement was lower for extreme values, particularly in over-conditioned cows where the BMF underestimated BCS relative to the mean of the two human observers. The BMF outperformed human assessors in terms of reproducibility and thus is likely to be especially useful in research contexts. This is the second independent validation of a commercially marketed body condition scoring system as far as the authors are aware. Comparing the results here with the published evaluation of the other system, we conclude that the BMF performed as well or better.en_US
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.relation.ispartofseriesAgriculture;10
dc.rightsAttribution-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-sa/3.0/us/*
dc.subjectbody condition scoreen_US
dc.subjectcowsen_US
dc.subjectautomateden_US
dc.subjectvalidationen_US
dc.subjectprecision technologyen_US
dc.titleValidation of an Automated Body Condition Scoring System Using 3D Imagingen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/agriculture10060246
dc.identifier.doihttps://doi.org/10.3390/agriculture10060246
dc.contributor.sponsorScience Foundation Irelanden_US
dc.contributor.sponsorDepartment of Agriculture, Food and the Marineen_US
dc.contributor.sponsorGrantNumber13/IA/1977en_US
dc.contributor.sponsorGrantNumber16/RC/3835en_US
dc.source.volume10
dc.source.issue6
dc.source.beginpage246
refterms.dateFOA2020-08-28T14:25:49Z


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