MarblingPredictor: A software to analyze the quality of dry-cured ham slices

Dry-cured ham is a traditional Mediterranean meat product consumed throughout the world. This product is very variable in terms of composition and consumer's acceptability is influenced by different factors, among others, visual intramuscular fat and its distribution across the slice, also know...

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Detalles Bibliográficos
Autores: Cernadas, Eva, Fernández-Delgado, Manuel, Sirsat, Manisha, Fulladosa, Elena, Muñoz, Israel
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Institut de Recerca i Tecnologia Agroalimentàries (IRTA)
Repositorio:IRTA Pubpro. Open Digital Archive
OAI Identifier:oai:repositori.irta.cat:20.500.12327/3478
Acceso en línea:http://hdl.handle.net/20.500.12327/3478
https://doi.org/10.1016/j.meatsci.2024.109713
Access Level:acceso abierto
Palabra clave:663/664
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spelling MarblingPredictor: A software to analyze the quality of dry-cured ham slicesCernadas, EvaFernández-Delgado, ManuelSirsat, ManishaFulladosa, ElenaMuñoz, Israel663/664Dry-cured ham is a traditional Mediterranean meat product consumed throughout the world. This product is very variable in terms of composition and consumer's acceptability is influenced by different factors, among others, visual intramuscular fat and its distribution across the slice, also known as marbling. On-line inter and intramuscular fat evaluation and marbling assessment is of interest for classification purposes at the industry. Currently, this assessment can only be performed by visual inspection and traditional sensory panels. The current work presents the software MarblingPredictor, which predicts the marbling score of the three most representative ham muscles from square regions of interest automatically extracted from a ham slice. It also estimates the rate of subcutaneous and intermuscular fat content in the ham slice. Using MarblingPredictor, the mean absolute error between the true and predicted marbling scores was 0.53, very similar to the error of sensory panellist, which is 0.50. The correlation between the computer and sensory scores is 0.68, which means a moderate to good recognition. This result underscores the relevance of this tool for its application in the ham industry for quality control and categorization purposes. As part of this work, we also present the dataset HamMarbling of annotated ham slices used to train and test the software with the marbling scores provided by the panellists. The MarblingPredictor software and images are available from https://citius.usc.es/transferencia/software/marblingpredictor for Windows- and Linux-based systems for research purposes.This work has received financial support from the Xunta de Galicia (Centro singular de investigación de Galicia, accreditation 2020–2023) and the European Union (European Regional Development Fund—ERDF), Project ED431G-2019/04. IRTA's contribution was also funded by the CCLabel project (RTI-2018- 096883-R-C41) and the CERCA programme from Generalitat de Catalunya.info:eu-repo/semantics/publishedVersionElsevierIndústries AlimentàriesQualitat i Tecnologia Alimentària202420242024info:eu-repo/semantics/article10application/pdfhttp://hdl.handle.net/20.500.12327/3478https://doi.org/10.1016/j.meatsci.2024.109713reponame:IRTA Pubpro. Open Digital Archiveinstname:Institut de Recerca i Tecnologia Agroalimentàries (IRTA)InglésMeat ScienceMICIU/Programa Estatal de I+D+I orientada a los retos de la Sociedad/RTI2018-096883-R-C41/ES/SISTEMAS DE CARACTERIZACION Y COMUNICACION DE LA CALIDAD Y LA COMPOSICION NUTRICIONAL DE LOS ALIMENTOS PARA LOS CONSUMIDORES Y LA INDUSTRIA ALIMENTARIA/FEDER/ / /EU/ /Attribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:repositori.irta.cat:20.500.12327/34782026-06-16T08:51:17Z
dc.title.none.fl_str_mv MarblingPredictor: A software to analyze the quality of dry-cured ham slices
title MarblingPredictor: A software to analyze the quality of dry-cured ham slices
spellingShingle MarblingPredictor: A software to analyze the quality of dry-cured ham slices
Cernadas, Eva
663/664
title_short MarblingPredictor: A software to analyze the quality of dry-cured ham slices
title_full MarblingPredictor: A software to analyze the quality of dry-cured ham slices
title_fullStr MarblingPredictor: A software to analyze the quality of dry-cured ham slices
title_full_unstemmed MarblingPredictor: A software to analyze the quality of dry-cured ham slices
title_sort MarblingPredictor: A software to analyze the quality of dry-cured ham slices
dc.creator.none.fl_str_mv Cernadas, Eva
Fernández-Delgado, Manuel
Sirsat, Manisha
Fulladosa, Elena
Muñoz, Israel
author Cernadas, Eva
author_facet Cernadas, Eva
Fernández-Delgado, Manuel
Sirsat, Manisha
Fulladosa, Elena
Muñoz, Israel
author_role author
author2 Fernández-Delgado, Manuel
Sirsat, Manisha
Fulladosa, Elena
Muñoz, Israel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Indústries Alimentàries
Qualitat i Tecnologia Alimentària
dc.subject.none.fl_str_mv 663/664
topic 663/664
description Dry-cured ham is a traditional Mediterranean meat product consumed throughout the world. This product is very variable in terms of composition and consumer's acceptability is influenced by different factors, among others, visual intramuscular fat and its distribution across the slice, also known as marbling. On-line inter and intramuscular fat evaluation and marbling assessment is of interest for classification purposes at the industry. Currently, this assessment can only be performed by visual inspection and traditional sensory panels. The current work presents the software MarblingPredictor, which predicts the marbling score of the three most representative ham muscles from square regions of interest automatically extracted from a ham slice. It also estimates the rate of subcutaneous and intermuscular fat content in the ham slice. Using MarblingPredictor, the mean absolute error between the true and predicted marbling scores was 0.53, very similar to the error of sensory panellist, which is 0.50. The correlation between the computer and sensory scores is 0.68, which means a moderate to good recognition. This result underscores the relevance of this tool for its application in the ham industry for quality control and categorization purposes. As part of this work, we also present the dataset HamMarbling of annotated ham slices used to train and test the software with the marbling scores provided by the panellists. The MarblingPredictor software and images are available from https://citius.usc.es/transferencia/software/marblingpredictor for Windows- and Linux-based systems for research purposes.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12327/3478
https://doi.org/10.1016/j.meatsci.2024.109713
url http://hdl.handle.net/20.500.12327/3478
https://doi.org/10.1016/j.meatsci.2024.109713
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Meat Science
MICIU/Programa Estatal de I+D+I orientada a los retos de la Sociedad/RTI2018-096883-R-C41/ES/SISTEMAS DE CARACTERIZACION Y COMUNICACION DE LA CALIDAD Y LA COMPOSICION NUTRICIONAL DE LOS ALIMENTOS PARA LOS CONSUMIDORES Y LA INDUSTRIA ALIMENTARIA/
FEDER/ / /EU/ /
dc.rights.none.fl_str_mv Attribution-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 10
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:IRTA Pubpro. Open Digital Archive
instname:Institut de Recerca i Tecnologia Agroalimentàries (IRTA)
instname_str Institut de Recerca i Tecnologia Agroalimentàries (IRTA)
reponame_str IRTA Pubpro. Open Digital Archive
collection IRTA Pubpro. Open Digital Archive
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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