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Pierluigi Acutis
Istituto Zooprofilattico Sperimentale del Piemonte Liguria e Valle d’Aosta
Computer Science & IT Electrical & Electronics Engineering

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DNA Pool Analysis-based Forgery-Detection of Dairy Products Francesco Rossi; Paola Modesto; Cristina Biolatti; Alfredo Benso; Stefano Di Carlo; Gianfranco Politano; Pierluigi Acutis
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1513.051 KB) | DOI: 10.11591/ijece.v8i5.pp3913-3922

Abstract

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.
Co-Authors Alfredo Benso Cristina Biolatti Francesco Rossi Gianfranco Politano Paola Modesto Stefano Di Carlo