Abstract
Purpose All food safety management standards require effective control measures of food safety hazards in order to ensure that food is safe at the time of human consumption. Furthermore, ISO 22000:2005 requires a logical approach to be carried out for the selection and categorization of the control measures according to the level of effect on identified food safety hazards. The purpose of this paper is to describe the COntrol MEasures CATegorization (COMECAT) method for the categorization of control measures in food safety management systems (FSMS) in order to assist organizations to prioritize and deploy their efforts and limited resources mainly to control significant hazards. Design/methodology/approach A thorough clarification of the characteristics of the different control measures used in FSMS has been achieved based on the definitions and the descriptions given by the different food safety standards such as the ISO 22000, the IFS and the BRC standards. The basic approaches for the determination of control measures found in literature and web pages have been examined and the proposed methodology has been implemented in feta cheese production in order to evaluate its applicability. Findings A decision tree model has been proposed as the most suitable approach for the categorization of control measures in FSMS. The implementation of the proposed COMECAT method in feta cheese production revealed its applicability. The method was able to identify the different risk level of food hazards and prioritize and deploy the organization’s efforts and limited resources for their management accordingly. Originality/value In the literature, there is a lack of justified methodologies for the categorization of control measures in FSMS. Most of the approaches concern attempts of private companies operating in the food industry or business consultancies and which can be found in their web pages. This paper describes a well-justified model for the categorization of control measures which is easy to implement and which results in more robust decisions.
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