Regulatory\nStructures all around the world have been mainly set up to achieve the\nobjective of ensuring the safety of food and protection of consumer interests.\nBoth these objectives require that regulators should analyze the data on\nvarious food safety and regulatory aspects throughout the chain of Food,\nincluding estimating dietary exposure for carrying out scientific risk\nassessments. <\/p>\n\n\n\n
Keeping\nin mind the considerable diversity in the food products being used up, regions\nin which they consumed the population groups involved, etc., it becomes\nvirtually impossible to track the information on an individual product basis. Apart\nfrom the absolute volume of data, the problem is complexed by the use of\nmultiple languages and regional variations. The preparation of such data on Food\nrequires a proper structure and a detailed description of foods. Even data of a\nkind class can be a basis of error if they are derived from foods that are not visibly\ndefined. Further, it isn’t easy to exchange data on foods due to its complexity\nor to understand and compare various parameters such as status of nutrition,\nconsumption patterns, etc. for different regions, states or individuals,\nwithout a clear description of foods in databases. <\/p>\n\n\n\n
To analyze the relevant data, regulators have used the categorization approach, where groups of similar products are bashed together as one category. The category is used as the basic unit for capturing information\/data and driving conclusion making in regulatory framework. <\/p>\n\n\n\n