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dc.creatorLópez-Maestresalas, Ainaraes_ES
dc.creatorInsausti Barrenetxea, Kizkitzaes_ES
dc.creatorJarén Ceballos, Carmenes_ES
dc.creatorPérez Roncal, Claudiaes_ES
dc.creatorUrrutia Vera, Olaiaes_ES
dc.creatorBeriain Apesteguía, María Josées_ES
dc.creatorArazuri Garín, Silviaes_ES
dc.date.accessioned2019-06-24T10:04:20Z
dc.date.available2019-12-06T00:00:11Z
dc.date.issued2019
dc.identifier.issn0956-7135
dc.identifier.urihttps://hdl.handle.net/2454/33448
dc.description.abstractThe aim of this work was to investigate the feasibility of near-infrared spectroscopy (NIRS), combined with chemometric techniques, to detect fraud in minced lamb and beef mixed with other types of meats. For this, 40 samples of pure lamb and 30 samples of pure beef along with 160 samples of mixed lamb and 156 samples of mixed beef at different levels: 1-2-5-10% (w/w) were prepared and analyzed. Spectral data were pre-processed using different techniques and explored by a Principal Component Analysis (PCA) to find out differences among pure and mixed samples. Moreover, a PLS-DA was carried out for each type of meat mixture. Classification results between 78.95 and 100% were achieved for the validation sets. Better rates of classification were obtained for samples mixed with pork meat, meat of Lidia breed cattle and foal meat than for samples mixed with chicken in both lamb and beef. Additionally, the obtained results showed that this technology could be used for detection of minced beef fraud with meat of Lidia breed cattle and foal in a percentage equal or higher than 2 and 1%, respectively. Therefore, this study shows the potential of NIRS combined with PLS-DA to detect fraud in minced lamb and beef.en
dc.description.sponsorshipThe funding of this work has been covered by the research services of the Universidad Pública de Navarra.en
dc.format.extent48 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofFood Control, Volume 98, April 2019, Pages 465-473en
dc.rights© 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAuthenticationen
dc.subjectChemometric techniquesen
dc.subjectMeat frauden
dc.subjectNear-infrared spectroscopyen
dc.subjectPCAen
dc.subjectPLS-DAen
dc.titleDetection of minced lamb and beef fraud using NIR spectroscopyen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa. ISFOOD - Institute for Innovation and Sustainable Development in Food Chaines_ES
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Ingenieríaes_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Ingeniaritza Sailaeu
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Agronomía, Biotecnología y Alimentaciónes_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Agronomia, Bioteknologia eta Elikadura Sailaeu
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.embargo.terms2019-12-06
dc.identifier.doi10.1016/j.foodcont.2018.12.003
dc.relation.publisherversionhttps://doi.org/10.1016/j.foodcont.2018.12.003
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.type.versionVersión aceptada / Onetsi den bertsioaes
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoaes


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© 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.
Except where otherwise noted, this item's license is described as © 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.