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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Bibliographic Details
Authors: López Maestresalas, Ainara, Insausti Barrenetxea, Kizkitza, Jarén Ceballos, Carmen, Pérez Roncal, Claudia, Urrutia Vera, Olaia, Beriain Apesteguía, María José, Arazuri Garín, Silvia
Format: article
Status:Versión aceptada para publicación
Publication Date:2019
Country:España
Institution:Universidad Pública de Navarra
Repository:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/33448
Online Access:https://hdl.handle.net/2454/33448
Access Level:Open access
Keyword:Authentication
Chemometric techniques
Meat fraud
Near-infrared spectroscopy
PCA
PLS-DA
Description
Summary: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.