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Safety Assessment of Functional Foods

  • Bobbie Bradford
Living reference work entry

Abstract

The safety assessment of functional foods follows the same paradigm established for conventional foods consisting of an assessment of the intrinsic hazards associated with the food/food ingredient combined with knowledge about the expected exposure that will occur. Addressing safety concerns on single components is relatively straightforward. However, functional foods can be whole foods and/or may consist of multiple components with increasing complexity (Fig. 1) which results in a different strategy often being required depending on the type of food/food ingredient. Traditionally whole foods have been considered safe because no evidence has accumulated on adverse effects and/or any intrinsic hazards have been addressed by adequate processing/preparation techniques. For example, red kidney beans need to be soaked and boiled at high temperatures to ensure destruction of phytohemagglutinin associated with gastrointestinal adverse effects (http://www.fda.gov/Food/FoodborneIllnessContaminants/CausesOfIllnessBadBugBook/ucm071092.htm). However, if these whole foods are exotic compared with the region where they are now to be marketed, then it was recognized that there needed to be governance and guidance in how to determine the safety of such food. These now fall into the category of novel foods which are legislated for in Canada, Australia and New Zealand, and Europe, all of which require a premarket assessment. Detailed information on the origin, production, composition, nutritional characteristics, and prior exposure to the novel food is required (Edwards 2005). The European Novel Foods legislation in May 1997 (http://ec.europa.eu/food/food/biotechnology/novelfood/initiatives_en.htm) established the need for determining safety of exotic fruits and vegetables introduced to Europe after this date.

Keywords

Quantitative Structure Activity Relationship Safety Assessment Plant Sterol European Food Safety Authority Quantitative Structure Activity Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.UnileverMilton KeynesUK

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