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DNA Pool Analysis-based Forgery-Detection of Dairy Products

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 5 (2018)

DOI
10.11591/ijece.v8i5.pp3913-3922
ISSN
2088-8708, 2088-8708
Published
2018-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

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.

Collaboration network of the authors

7 authors · 21 co-authorship links · 6 across different organisations

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  • Politecnico di Torino
  • Istituto Zooprofilattico Sperimentale del Piemonte Liguria e Valle d'Aosta
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>DNA Pool Analysis-based Forgery-Detection of Dairy Products</dc:title><dc:creator>Rossi, Francesco</dc:creator><dc:creator>Modesto, Paola</dc:creator><dc:creator>Biolatti, Cristina</dc:creator><dc:creator>Benso, Alfredo</dc:creator><dc:creator>Di Carlo, Stefano</dc:creator><dc:creator>Politano, Gianfranco</dc:creator><dc:creator>Acutis, Pierluigi</dc:creator><dc:description>&lt;jats:p&gt;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.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2018-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v8i5.pp3913-3922</dc:identifier><dc:identifier>10.11591/ijece.v8i5.pp3913-3922</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 5 (2018); 3913</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/10512/10732</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>