This study analysed the usefulness of near infrared spectroscopy (NIRS), combined with volatile compound (VOC) and fatty acid (FA) analyses, for the authentication of the unique Italian Valle d'Aosta Arnad Protected Designation of Origin (PDO) lard. Ensuring the authenticity of high value meat products remains an emerging topic within the food sector. This study validated a FA, VOC and NIRS model for use in the authentication of Arnad PDO lard. The model showed a high potential rate to recognize patterns in lard samples. In particular the sensitivity and specificity calibration values were both 100%, and cross-validation models were performed using FAs and VOCs separately. The NIRS model obtained sensitivity and specificity values of 98.2% in the calibration data set, and 94.4% in the cross-validation step. This analytical approach may represent an effective tool to prevent food fraud, which is crucial for meat derived products with a high commercial value.
Authentication of Italian PDO lard using NIR spectroscopy, volatile profile and fatty acid composition combined with chemometrics / L. Chiesa, S. Panseri, S. Bonacci, A. Procopio, A. Zecconi, F. Arioli, F.J. Cuevas, J.M. Moreno-Rojas. - In: FOOD CHEMISTRY. - ISSN 0308-8146. - 212(2016), pp. 296-304.
Authentication of Italian PDO lard using NIR spectroscopy, volatile profile and fatty acid composition combined with chemometrics
L. ChiesaPrimo
;S. Panseri
;A. Zecconi;F. Arioli;
2016
Abstract
This study analysed the usefulness of near infrared spectroscopy (NIRS), combined with volatile compound (VOC) and fatty acid (FA) analyses, for the authentication of the unique Italian Valle d'Aosta Arnad Protected Designation of Origin (PDO) lard. Ensuring the authenticity of high value meat products remains an emerging topic within the food sector. This study validated a FA, VOC and NIRS model for use in the authentication of Arnad PDO lard. The model showed a high potential rate to recognize patterns in lard samples. In particular the sensitivity and specificity calibration values were both 100%, and cross-validation models were performed using FAs and VOCs separately. The NIRS model obtained sensitivity and specificity values of 98.2% in the calibration data set, and 94.4% in the cross-validation step. This analytical approach may represent an effective tool to prevent food fraud, which is crucial for meat derived products with a high commercial value.File | Dimensione | Formato | |
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