Detection of minced lamb and beef fraud using NIR spectroscopy

López Maestresalas, Ainara; Insausti Barrenetxea, Kizkitza; Jarén Ceballos, Carmen; Pérez Roncal, Claudia; Urrutia Vera, Olaia; Beriain Apesteguía, María José; Arazuri Garín, Silvia

Publication:
Detection of minced lamb and beef fraud using NIR spectroscopy

dc.contributor.author	López Maestresalas, Ainara
dc.contributor.author	Insausti Barrenetxea, Kizkitza
dc.contributor.author	Jarén Ceballos, Carmen
dc.contributor.author	Pérez Roncal, Claudia
dc.contributor.author	Urrutia Vera, Olaia
dc.contributor.author	Beriain Apesteguía, María José
dc.contributor.author	Arazuri Garín, Silvia
dc.contributor.department	Ingeniaritza	eu
dc.contributor.department	Agronomia, Bioteknologia eta Elikadura	eu
dc.contributor.department	Institute on Innovation and Sustainable Development in Food Chain - ISFOOD	en
dc.contributor.department	Ingeniería	es_ES
dc.contributor.department	Agronomía, Biotecnología y Alimentación	es_ES
dc.contributor.funder	Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa	es
dc.date.accessioned	2019-06-24T10:04:20Z
dc.date.available	2019-12-06T00:00:11Z
dc.date.issued	2019
dc.description.abstract	The 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.sponsorship	The funding of this work has been covered by the research services of the Universidad Pública de Navarra.	en
dc.embargo.lift	2019-12-06
dc.embargo.terms	2019-12-06
dc.format.extent	48 p.
dc.format.mimetype	application/pdf	en
dc.identifier.doi	10.1016/j.foodcont.2018.12.003
dc.identifier.issn	0956-7135
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/33448
dc.language.iso	eng	en
dc.publisher	Elsevier	en
dc.relation.ispartof	Food Control, Volume 98, April 2019, Pages 465-473	en
dc.relation.publisherversion	https://doi.org/10.1016/j.foodcont.2018.12.003
dc.rights	© 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.	en
dc.rights.accessRights	info:eu-repo/semantics/openAccess	en
dc.rights.accessRights	Acceso abierto / Sarbide irekia	es
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject	Authentication	en
dc.subject	Chemometric techniques	en
dc.subject	Meat fraud	en
dc.subject	Near-infrared spectroscopy	en
dc.subject	PCA	en
dc.subject	PLS-DA	en
dc.title	Detection of minced lamb and beef fraud using NIR spectroscopy	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/acceptedVersion	en
dc.type.version	Versión aceptada / Onetsi den bertsioa	es
dspace.entity.type	Publication
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