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

dc.contributor.affiliationUniversidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS)
dc.contributor.authorCernadas García, Eva
dc.contributor.authorFernández Delgado, Manuel
dc.contributor.authorSirsat, Manisha
dc.contributor.authorFulladosa, Elena
dc.contributor.authorMuñoz, Israel
dc.date.accessioned2025-03-03T08:34:23Z
dc.date.available2025-03-03T08:34:23Z
dc.date.issued2024-11-28
dc.description.abstractDry-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.
dc.description.peerreviewedSI
dc.description.sponsorshipThis 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.
dc.identifier.citationCernadas, E., Fernández-Delgado, M., Sirsat, M., Fulladosa, E., Muñoz, I. (2024). MarblingPredictor: A software to analyze the quality of dry-cured ham slices. "Meat Science", vol. 221
dc.identifier.doi10.1016/j.meatsci.2024.109713
dc.identifier.issn0309-1740
dc.identifier.urihttps://hdl.handle.net/10347/39986
dc.journal.titleMeat Science
dc.language.isoeng
dc.publisherElsevier
dc.relation.publisherversionhttps://doi.org/10.1016/j.meatsci.2024.109713
dc.rights© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the Attribution-NonCommercial 4.0 International licence
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectDry-cured ham
dc.subjectIntramuscular fat
dc.subjectMarbling
dc.subjectSupport vector regression
dc.subjectTexture analysis
dc.subjectImage segmentation
dc.subjectSubcutaneous fat
dc.subject.classification3309 Tecnología de los alimentos
dc.titleMarblingPredictor: A software to analyze the quality of dry-cured ham slices
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number221
dspace.entity.typePublication
relation.isAuthorOfPublication5b9d06b8-f9ab-4a8c-8105-38af29bd0562
relation.isAuthorOfPublicationfe860f28-b531-4cad-859e-a38536a615ea
relation.isAuthorOfPublication.latestForDiscovery5b9d06b8-f9ab-4a8c-8105-38af29bd0562

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