A dynamic risk assessment approach based on stochastic hybrid system: Application to microbial hazards in food processing

Abstract

In food processing, it is essential to guarantee the safety of microbial hazards. Microorganisms exist, transit and continuously grow along the food processing with hybrid evolutionary characteristics and uncertainties. Thus, a particular risk assessment is essential to effectively predict and evaluate the risk of microbial hazards in food processing. For such a purpose, we propose a comprehensive dynamic risk assessment approach based on a stochastic hybrid system (SHS). First, we formulate a dynamic evolution of microorganisms in food processing according to the SHS model. Second, we employ a Monte Carlo simulation to obtain the probability density functions of process characteristic information for microorganisms during processing. Additionally, we design a novel risk indicator of “hazard degree” to quantify the potential risks of microorganisms based on this process information. Finally, we present a case study of wheat flour processing to estimate the risk of mixed mildew on the basis of the SHS approach. Experimental results show that the proposed approach is feasible in modeling the hybrid evolution and handling uncertainties in predictions of microbial hazards. This study should prove to be a valuable reference to ensure food safety for risk management and decision-making departments.