Predictive modelling as a tool for Performance Objetives (PO) achievement and Performance Criteria (PC) and Precess/Product Criteria (PcC/PdC) calculation for the mycotoxin hazard

DAIANA GARCIA; ANTONIO J. RAMOS; VICENTE SANCHIS; SONIA MARÍN

Dublin

Congreso; 7º International Conferencia 2011 of Predictive modelling of Food Quality and Safety; 2011

The Food Safety objective (FSO) is the maximum frequency and/or concentration of the hazard in a food at the time of consumption and is preceded by the Performance Objective (PO), which is the maximum frequency and/or concentration of a hazard in a food at a specified step in the food chain before the time of consumption (ICMSF 2002). While Codex considers FSOs only for microbial hazards (the maximum frequency and/or concentration of a microbiological hazard in a food at the time of consumption that provides the appropriate level of protection) (CAC, 2003), in principle, the concept could apply to other types of hazards as well. In practice, FSOs are met through the establishment and implementation of performance and process criteria. In the food chain it is necessary to know the effect of every step and treatment, Performance Criteria (PC), as well as the process parameters, Process Criteria (PrcC) (t, T, pH, aw) which can be applied in any level neither in the final product, Product Criteria (PrdcC) (pH, aw, gaseous atmosphere). PrdcC assure that the hazard level never overtakes safety levels before being cooked or consumed. Maize is a very important cereal for human and animal diet; however, it can be contaminated by mycotoxins. Aspergillus is a mould genus which can contaminate maize and produce mycotoxins. Aspergillus flavus and A. parasiticus can contaminate maize and their by-products and to synthesize aflatoxins, causing damage to human and animal health. Processing of maize to its by products involves a series of steps in which aflatoxin content might either increase or decrease. For the particular case of cornflakes production, 5 key steps were identified regarding aflatoxin hazard, namely, i) maize storage, ii) dry milling, iii) grit storage, iv) cooking, and v) roasting of flakes. For these 5 steps, having in mind that for the particular case of mycotoxins de maximum level as set in the EC Regulation 1881/2006 (FSO) is equal or over the PO (taking into account uncertainty), previous results on predictive modeling were applied in order to either prevent further mycotoxin accumulation (steps i and iii) or to achieve a maximum inactivation (steps iv and v). In the storage cases, in order to prevent mycotoxin production, control of mycotoxigenic mould growth is required. Despite the absence of direct correlation between mould growth and mycotoxins production, prevention of fungal growth effectively conduces to prevention of mycotoxin accumulation. In general, water activity (aw) and temperature are regarded as the main controlling factors determining the potential for mould growth during storage. Given a PC of ?zero increase?, suitable PrcCs were calculated. In the thermal inactivation cases, although aflatoxins are heat stable, several researchers have reported a certain degree of inactivation, eg. 52-94% for the cooking step (Torres, 2001). Those studies were used in order to calculate suitable PCs and PrcCs for the thermal treatments. Conclusion: The role of predictive modelling in microbiological food safety management is widely recognised; the present study demonstrates its usefulness in management and prevention of the mycotoxin hazard.