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dc.contributor.authorMasferrer, Gerard
dc.contributor.authorCarreras, Ricard
dc.contributor.authorFont-i-Furnols, Maria
dc.contributor.authorGispert, Marina
dc.contributor.authorMarti-Puig, Pere
dc.contributor.authorSerra, Moises
dc.contributor.otherIndústries Alimentàriesca
dc.date.accessioned2019-04-11T14:26:39Z
dc.date.available2019-06-25T09:42:21Z
dc.date.issued2018-04-13
dc.identifier.citationMasferrer, Gerard, Ricard Carreras, Maria Font-i-Furnols, Marina Gispert, Pere Marti-Puig, and Moises Serra. 2018. "On-Line Ham Grading Using Pattern Recognition Models Based On Available Data In Commercial Pig Slaughterhouses". Meat Science 143: 39-45. Elsevier BV. doi:10.1016/j.meatsci.2018.04.011.ca
dc.identifier.issn0309-1740ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/296
dc.description.abstractThe thickness of the subcutaneous fat in hams is one of the most important factors for the dry-curing process and largely determines its final quality. This parameter is usually measured in slaughterhouses by a manual metrical measure to classify hams. The aim of the present study was to propose an automatic classification method based on data obtained from a carcass automatic classification equipment (AutoFom) and intrinsic data of the pigs (sex, breed, and weight) to simulate the manual classification system. The evaluated classification algorithms were decision tree, support vector machines (SVM), k-nearest neighbour and discriminant analysis. A total of 4000 hams selected by breed and sex were classified as thin (0–10 mm), standard (11–15 mm), semi-fat (16–20 mm) and fat (>20 mm). The most reliable model, with a percentage of success of 73%, was SVM with Gaussian kernel, including all data available. These results suggest that the proposed classification method can be a useful online tool in slaughterhouses to classify hams.ca
dc.format.extent17ca
dc.language.isoengca
dc.publisherElsevierca
dc.relation.ispartofMeat Scienceca
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleOn-line Ham Grading using pattern recognition models based on available data in commercial pig slaughterhousesca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/acceptedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1016/j.meatsci.2018.04.011ca
dc.contributor.groupQualitat i Tecnologia Alimentàriaca


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