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Lamb meat tenderness prediction using neural networks and sensitivity analysis

2005Conference paper Open access
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dc.contributor.authorCortez, Paulo
dc.contributor.authorPortelinha, Manuel
dc.contributor.authorRodrigues, Sandra
dc.contributor.authorCadavez, Vasco
dc.contributor.authorTeixeira, Alfredo
dc.date.accessioned2008-09-17T08:41:00Z
dc.date.available2008-09-17T08:41:00Z
dc.date.issued2005
dc.description.abstractThe assessment of quality is a key factor for the meat industry, where the aim is to fulfill the consumer’s needs. In particular, tenderness is considered the most important characteristic affecting consumer perception of taste. In this paper, a Neural Network Ensemble, with feature selection based on a Sensitivity Analysis procedure, is proposed to predict lamb meat tenderness. This difficult real-world problem is defined in terms of two regression tasks, by using instrumental measurements and a sensory panel. In both cases, the proposed solution outperformed other neural approaches and the Multiple Regression method.en
dc.identifier.citationCortez, P.; Portelinha, M.; Rodrigues, Sandra; Cadavez, Vasco; Teixeira, Alfredo (2005). Lamb meat tenderness prediction using neural networks and sensitivity analysis. In Proceedings of the 19 th European Simulation Multiconference - ESM'2005. Porto. p. 177-181en
dc.identifier.urihttp://hdl.handle.net/10198/865
dc.language.isoengen
dc.publisherEurosisen
dc.subjectRegressionen
dc.subjectMultilayer perceptronsen
dc.subjectMultiple regressionen
dc.subjectMeat qualityen
dc.subjectEnsemblesen
dc.subjectData miningen
dc.titleLamb meat tenderness prediction using neural networks and sensitivity analysisen
dc.typeconference paper
dspace.entity.typePublication
person.familyNamePortelinha
person.familyNameRodrigues
person.familyNameCadavez
person.familyNameTeixeira
person.givenNameManuel
person.givenNameSandra
person.givenNameVasco
person.givenNameAlfredo
person.identifierR-000-HDG
person.identifier958487
person.identifier.ciencia-id7610-3BAB-B4C1
person.identifier.ciencia-id651F-D964-32E1
person.identifier.ciencia-id441B-01AB-A12E
person.identifier.ciencia-id2A1A-FF0C-185B
person.identifier.orcid0000-0003-3301-1729
person.identifier.orcid0000-0002-3077-7414
person.identifier.orcid0000-0003-4607-4796
person.identifier.ridC-6486-2008
person.identifier.ridA-3958-2010
person.identifier.ridG-4118-2011
person.identifier.scopus-author-id14048942500
person.identifier.scopus-author-id9039121900
person.identifier.scopus-author-id56195849200
rcaap.rightsopenAccess
rcaap.typeconferenceObjecten
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relation.isAuthorOfPublication.latestForDiscovery684ab6a0-e3ea-4b6e-9874-d20d71e2a3f5

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