Endpoints Method to Predict Microbial Survival, Nutrients Degradation, and Quality Loss at High and Ultra High Temperatures

Abstract

The traditional methods to predict and assess the safety of a sterilization or pasteurization process are based on kinetic models whose parameters are extracted from the experimental isothermal survival curves of the targeted organism or spore, preferably determined in the actual food. The temperatures encountered in ultra high temperature (UHT) and other high temperature short time (HTST) thermal preservation processes can reach 120–160 °C. Since substantial inactivation occurs during the come-up time, creating meaningful isothermal conditions for a very short time at such temperatures is not a feasible option. Extrapolation from lower temperatures or long exposures in the order of several minutes is also not a satisfactory solution. The same is true for the study of the accompanying chemical reactions’ kinetics, be they the degradation of nutrients, notably vitamins or pigments, and the formation of undesirable compounds, such as the various Maillard reaction’s products. These predicaments can be avoided by using the endpoints method, which eliminates the need to follow the inactivation/reaction at high temperatures. When using this method, the targeted organism’s or spore’s counts, or the concentrations of the chemical species of interest, are only determined before and after the process’s completion, i.e., after the end of the cooling stage. At that time, one can assume that the microbial inactivation has ceased, and the chemical reactions slowed down to insignificance. Depending on the type of kinetic model and number of its parameters, the experiment is repeated 3–4 times, each having a carefully monitored different temperature history (profile). The final count or concentration is then converted into a survival or concentration ratio and used to calculate the kinetic parameters. This is done by solving 2 or 3 simultaneous equations numerically, each being itself the numerical solution of the underlying differential rate equation, which corresponds to the particular temperature history of the process. Each temperature-time relationship can be described either algebraically or as an Interpolating Function obtained from the corresponding digitized record. To validate the method and the developed kinetic model, one compares one or more final count or concentration ratios predicted with the model with experimental data not used in the model’s parameters calculation. Software to do the calculations is now available on the Internet as freely downloadable interactive Mathematica® programs including their codes.