Risk-Off Method: Improving Data Quality Generated by Chemical Risk Analysis of Milk

Walter Coelho Pereira de Magalhães Junior (Embrapa Dairy Cattle, Brazil & Federal University of São Carlos, Brazil), Marcelo Bonnet (Embrapa Dairy Cattle, Brazil), Leandro Diamantino Feijó (Ministry of Agriculture, Livestock and Supply, Brazil) and Marilde Terezinha Prado Santos (Federal University of São Carlos, Brazil)
Copyright: © 2012 |Pages: 64
EISBN13: 9781466603509|DOI: 10.4018/978-1-61350-314-0.ch003
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Abstract

Here the Risk-Off Method is presented as a contribution to improve the quality of data and information using milk chemical safety as a model, as overseen by the National Plan for Control of Residues and Contaminants (PNCRC) of the Brazilian Ministry of Agriculture, Livestock and Supply (MAPA). In particular, Small and Medium Enterprises (SMEs), which notably lack internal expertise, could benefit from the Risk-Off method, given that SMEs worldwide contribute significant amounts of food to meet global needs. This study develops an innovative tool to help countries provide robust and transparent chemical safety guarantees for their food products. Creating a flexible base platform to appropriately pre-classify results generated by laboratory testing of food samples, the method pre-processes data undergoing the process of Knowledge Discovery in Databases – KDD, producing systemic intelligence deriving from effective, proactive assessment and management of chemical safety risks in foods, a complex issue of increasingly global concern.
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