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 analyze dairy products for which one of the crucial issues is traditional cheese traceability. In this paper we propose a computer- assisted molecular traceability system able to certify a traditional dairy product. We investigate the use of short tandem repeat analysis data processed by a Covariance Matrix Adaptation Evolution Strategy algo- rithm in order to predict the traceability between dairy products and the corresponding producer and to highlight possible adulterations and/or inconsistencies. Preliminary results collected from two farms are pre- sented in this study to show the capability of the proposed algorithm in a real setup.
Computer-Assisted Molecular Traceability for Dairy Farming Products / Rossi, Francesco; Modesto, Paola; DI CARLO, Stefano; Politano, GIANFRANCO MICHELE MARIA; Savino, Alessandro; Acutis, Pier Luigi; Benso, Alfredo. - ELETTRONICO. - (2016), pp. 1-11. (Intervento presentato al convegno INTERNATIONAL WORK-CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (IWBBIO 2016) tenutosi a Granada, ES nel 20-22 April, 2016).
Computer-Assisted Molecular Traceability for Dairy Farming Products
ROSSI, FRANCESCO;DI CARLO, STEFANO;POLITANO, GIANFRANCO MICHELE MARIA;SAVINO, ALESSANDRO;BENSO, ALFREDO
2016
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 analyze dairy products for which one of the crucial issues is traditional cheese traceability. In this paper we propose a computer- assisted molecular traceability system able to certify a traditional dairy product. We investigate the use of short tandem repeat analysis data processed by a Covariance Matrix Adaptation Evolution Strategy algo- rithm in order to predict the traceability between dairy products and the corresponding producer and to highlight possible adulterations and/or inconsistencies. Preliminary results collected from two farms are pre- sented in this study to show the capability of the proposed algorithm in a real setup.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2649757
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