Lamb meat tenderness prediction using neural networks and sensitivity analysis

Bibliographic Details
Main Author: Cortez, Paulo
Publication Date: 2005
Other Authors: Portelinha, Manuel, Rodrigues, Sandra, Cadavez, Vasco, Teixeira, Alfredo
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/4289
Summary: The 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.
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spelling Lamb meat tenderness prediction using neural networks and sensitivity analysisRegressionMultilayer perceptronsMultiple regressionMeat qualityEnsemblesData miningScience & TechnologyThe 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.EUROSIS-ETIUniversidade do MinhoCortez, PauloPortelinha, ManuelRodrigues, SandraCadavez, VascoTeixeira, Alfredo2005-102005-10-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/4289engTEIXEIRA. J. Feliz; BRITO, A., ed. lit. – “ESM’2005 : proceedings of the European Simulation Multiconference, Oporto, Portugal, 2005. [S.l.]: Eurosis, [2005]. ISBN 90-77381-22-8. p. 177-181.90-77381-22-8info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:16:20Zoai:repositorium.sdum.uminho.pt:1822/4289Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:21:12.386508Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Lamb meat tenderness prediction using neural networks and sensitivity analysis
title Lamb meat tenderness prediction using neural networks and sensitivity analysis
spellingShingle Lamb meat tenderness prediction using neural networks and sensitivity analysis
Cortez, Paulo
Regression
Multilayer perceptrons
Multiple regression
Meat quality
Ensembles
Data mining
Science & Technology
title_short Lamb meat tenderness prediction using neural networks and sensitivity analysis
title_full Lamb meat tenderness prediction using neural networks and sensitivity analysis
title_fullStr Lamb meat tenderness prediction using neural networks and sensitivity analysis
title_full_unstemmed Lamb meat tenderness prediction using neural networks and sensitivity analysis
title_sort Lamb meat tenderness prediction using neural networks and sensitivity analysis
author Cortez, Paulo
author_facet Cortez, Paulo
Portelinha, Manuel
Rodrigues, Sandra
Cadavez, Vasco
Teixeira, Alfredo
author_role author
author2 Portelinha, Manuel
Rodrigues, Sandra
Cadavez, Vasco
Teixeira, Alfredo
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Cortez, Paulo
Portelinha, Manuel
Rodrigues, Sandra
Cadavez, Vasco
Teixeira, Alfredo
dc.subject.por.fl_str_mv Regression
Multilayer perceptrons
Multiple regression
Meat quality
Ensembles
Data mining
Science & Technology
topic Regression
Multilayer perceptrons
Multiple regression
Meat quality
Ensembles
Data mining
Science & Technology
description The 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.
publishDate 2005
dc.date.none.fl_str_mv 2005-10
2005-10-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/4289
url http://hdl.handle.net/1822/4289
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv TEIXEIRA. J. Feliz; BRITO, A., ed. lit. – “ESM’2005 : proceedings of the European Simulation Multiconference, Oporto, Portugal, 2005. [S.l.]: Eurosis, [2005]. ISBN 90-77381-22-8. p. 177-181.
90-77381-22-8
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EUROSIS-ETI
publisher.none.fl_str_mv EUROSIS-ETI
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833595894736355328

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