Detection of minced lamb and beef fraud using NIR spectroscopy

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 l...

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Autores: López Maestresalas, Ainara, Insausti Barrenetxea, Kizkitza, Jarén Ceballos, Carmen, Pérez Roncal, Claudia, Urrutia Vera, Olaia, Beriain Apesteguía, María José, Arazuri Garín, Silvia
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/33448
Acceso en línea:https://hdl.handle.net/2454/33448
Access Level:acceso abierto
Palabra clave:Authentication
Chemometric techniques
Meat fraud
Near-infrared spectroscopy
PCA
PLS-DA
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spelling Detection of minced lamb and beef fraud using NIR spectroscopyLópez Maestresalas, AinaraInsausti Barrenetxea, KizkitzaJarén Ceballos, CarmenPérez Roncal, ClaudiaUrrutia Vera, OlaiaBeriain Apesteguía, María JoséArazuri Garín, SilviaAuthenticationChemometric techniquesMeat fraudNear-infrared spectroscopyPCAPLS-DAThe 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.The funding of this work has been covered by the research services of the Universidad Pública de Navarra.ElsevierIngeniaritzaAgronomia, Bioteknologia eta ElikaduraInstitute on Innovation and Sustainable Development in Food Chain - ISFOODIngenieríaAgronomía, Biotecnología y AlimentaciónUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2454/33448reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarrainstname:Universidad Pública de NavarraInglés© 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:academica-e.unavarra.es:2454/334482026-06-17T12:41:47Z
dc.title.none.fl_str_mv Detection of minced lamb and beef fraud using NIR spectroscopy
title Detection of minced lamb and beef fraud using NIR spectroscopy
spellingShingle Detection of minced lamb and beef fraud using NIR spectroscopy
López Maestresalas, Ainara
Authentication
Chemometric techniques
Meat fraud
Near-infrared spectroscopy
PCA
PLS-DA
title_short Detection of minced lamb and beef fraud using NIR spectroscopy
title_full Detection of minced lamb and beef fraud using NIR spectroscopy
title_fullStr Detection of minced lamb and beef fraud using NIR spectroscopy
title_full_unstemmed Detection of minced lamb and beef fraud using NIR spectroscopy
title_sort Detection of minced lamb and beef fraud using NIR spectroscopy
dc.creator.none.fl_str_mv López Maestresalas, Ainara
Insausti Barrenetxea, Kizkitza
Jarén Ceballos, Carmen
Pérez Roncal, Claudia
Urrutia Vera, Olaia
Beriain Apesteguía, María José
Arazuri Garín, Silvia
author López Maestresalas, Ainara
author_facet López Maestresalas, Ainara
Insausti Barrenetxea, Kizkitza
Jarén Ceballos, Carmen
Pérez Roncal, Claudia
Urrutia Vera, Olaia
Beriain Apesteguía, María José
Arazuri Garín, Silvia
author_role author
author2 Insausti Barrenetxea, Kizkitza
Jarén Ceballos, Carmen
Pérez Roncal, Claudia
Urrutia Vera, Olaia
Beriain Apesteguía, María José
Arazuri Garín, Silvia
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Ingeniaritza
Agronomia, Bioteknologia eta Elikadura
Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Ingeniería
Agronomía, Biotecnología y Alimentación
Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
dc.subject.none.fl_str_mv Authentication
Chemometric techniques
Meat fraud
Near-infrared spectroscopy
PCA
PLS-DA
topic Authentication
Chemometric techniques
Meat fraud
Near-infrared spectroscopy
PCA
PLS-DA
description 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.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2454/33448
url https://hdl.handle.net/2454/33448
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv © 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.
https://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv © 2018 Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname:Universidad Pública de Navarra
instname_str Universidad Pública de Navarra
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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