Food integrity and food safety have received much attention in recent years due to the dramatic increasing number of food frauds. In this article we focus on the problem of dairy products traceability. In particular, we propose an automatic forgery detection system able to detect frauds in milk and cheese. We investigate the use of Short Tandem Repeats analysis data, processed by a Covariance Matrix Adaptation Evolution Strategy algorithm in order to evaluate a traceability score between the products and their producer, and to highlight possible adulterations and inconsistencies. To demonstrate the usability of the proposed heuristic algorithm in a real setup, we also present the results collected from two real Italian farms.
DNA Pool Analysis-based Forgery-Detection of Dairy Products / Rossi, F.; Modesto, P.; Biolatti, C.; Benso, A.; Di Carlo, S.; Politano, G.; Acutis, P. L.. - In: INTERNATIONAL JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING. - ISSN 2088-8708. - STAMPA. - 8:5(2018), pp. 3913-3922. [10.11591/ijece.v8i6]
|Titolo:||DNA Pool Analysis-based Forgery-Detection of Dairy Products|
|Data di pubblicazione:||2018|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.11591/ijece.v8i6|
|Appare nelle tipologie:||1.1 Articolo in rivista|