Monte Carlo Simulation of Disinfection of Bacteria for Food Safety and Security: Non-Linear Approach
A. Argoti1, L. T. Fan1, and S. T. Chou2. (1) Department of Chemical Engineering, Kansas State University, 1005 Durland Hall, Manhattan, KS 66506, (2) Department of Finance and Banking, Kun Shan University, No. 949, Da-Wan Rd., Yung-Kang City, Taiwan
The analysis, modeling, and simulation of disinfection of bacteria, specifically, pathogenic bacteria, in foodstuff should belong to the repertoire of tools for quantitatively assessing strategies for food safety and security. Nevertheless, it is exceedingly difficult, if not impossible, to accurately quantify a population of bacteria throughout disinfection by resorting to any conventional deterministic approach: The bacteria are discrete and mesoscopic in size, thereby exhibiting random, or stochastic, fluctuations in their number concentration, especially at the tail-end of disinfection where their number is minute. Thus, it is indeed appropriate that the disinfection of bacteria in foodstuff be analyzed, modeled, and simulated according to a stochastic paradigm. Such stochastic simulation can be executed by means of the Monte Carlo method, which can deal with models based on linear as well as non-linear rate laws with nearly equal ease. For illustration, the mean, variance, and standard deviation of the number concentration of bacteria during disinfection of foodstuff have been estimated by Monte Carlo simulation. The numerical results are compared with both the analytical solutions and the available experimental data.