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dc.contributor.authorMelado-Herreros, Angela-
dc.contributor.authorNieto-Ortega, Sonia-
dc.contributor.authorOlabarrieta, Idoia-
dc.contributor.authorSotelo, Carmen G.-
dc.contributor.authorTeixeira, Barbara-
dc.contributor.authorVelasco, Amaya-
dc.contributor.authorRamilo-Fernandez, Graciela-
dc.contributor.authorMendes, Rogerio-
dc.date.accessioned2023-10-04T10:45:04Z-
dc.date.available2023-10-04T10:45:04Z-
dc.date.issued2022-
dc.identifierWOS:000782277900006-
dc.identifier.issn0260-8774-
dc.identifier.urihttp://dspace.azti.es/handle/24689/1586-
dc.description.abstractBioelectrical impedance analysis (BIA), near-infrared (NIR) spectroscopy and time domain reflectometry (TDR) were compared as non-destructive techniques, coupled with a classifier based on partial least square discriminant analysis (PLS-DA), to assess added water detection in a seafood model: tuna. Three classification models were developed for each technology in unfrozen, thawed and in a combination of both stages to distinguish between added and non-added water samples. Results were acceptable for the unfrozen stage with all the technologies, giving TDR the best performance (accuracy = 0.95; error rate = 0.06). However, results on the model for thawed stage were not satisfactory, due to the behavior of water during the freezing-thawing process in both types of samples (with and without added water). For the combined model, NIR failed in the classification (accuracy = 0.68; error rate = 0.32), BIA gave acceptable results (accuracy = 0.72; error rate = 0.28) and TDR made a good classification (accuracy = 0.87; error rate = 0.12).-
dc.language.isoEnglish-
dc.publisherELSEVIER SCI LTD-
dc.subjectTraceability-
dc.subjectChemometrics-
dc.subjectFish chain-
dc.subjectAdded water-
dc.subjectSmart sensors-
dc.subjectFOOD-SUPPLY CHAINS-
dc.subjectFROZEN-THAWED FISH-
dc.subjectABUSIVE WATER ADDITION-
dc.subjectPROXIMATE COMPOSITION-
dc.subjectFRESH-
dc.subjectDIFFERENTIATION-
dc.subjectQUALITY-
dc.subjectMUSCLE-
dc.subjectOCTOPUS-
dc.subjectPROTEIN-
dc.titleComparison of three rapid non-destructive techniques coupled with a classifier to increase transparency in the seafood value chain: Bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR)-
dc.typeArticle-
dc.identifier.journalJOURNAL OF FOOD ENGINEERING-
dc.format.volume322-
dc.contributor.funderSEATRACES Project - EU Interreg Atlantic Area Programme [EAPA\_87/2016]-
dc.identifier.e-issn1873-5770-
dc.identifier.doi10.1016/j.jfoodeng.2022.110979-
Appears in Publication types:Artículos científicos



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