There have been reported many mathematical models for thermal inactivation of microorganisms in food. The basic models are an inactivation-technology model using D value and a chemical reaction model using a first order reaction. The former model is easy to handle, but hard to express non-linear survivor curves. The latter has a potential to describe non-linear curves. There are also empirical models to describe sigmoidal survivor curves of microorganisms during the heating period. Recently the interests of food scientists have focused on predictive microbiology models. Two expert software programs, Food Micromodel and Pathogen Modeling Program, are now available. During the heating process of a food product, the temperature of it changes. The temperature history of a food product is necessary for estimation of thermal inactivation of contaminants in it. F value may not directly indicate the magnitude of thermal death, but it can be a measure of thermal inactivation for a heating process. Also, a simple simulation of thermal inactivation of a pathogen contaminating a hamburger pate on a heated plate was performed using the heat conduction equation. A systematic model for thermal inactivation of microorganisms in food products that predicts the optimized thermal process of the products will further need to food industry.
The desorption processes of β-lactogloblin fouled on a stainless steel surface during caustic and enzymatic cleanings were analyzed using the model in which the free energy of activation for the rate constant of the first-order kinetics was assumed to obey a Gaussian distribution. The model well expressed both processes. This would indicate that the β-lactogloblin molecules exist in various states and interact with the surface in various strengths corresponding to the states. The rate constant corresponding to the mean value of the free energy of activation was greater at the higher detergent concentrations for both the caustic and enzymatic cleanings.
The cost and the carbon dioxide emission in microfiltration (MF) of soy sauce sediment with Agitated Disk Membrane Module (AD Module) were estimated in this note, using the results in the actual soy sauce production line. The cost and the carbon dioxide emission of soy sauce sediment filtration process largely depended upon the operation conditions of AD Module and the concentration ratio of batch filtration. Both more than the agitator revolution of 300rpm and more than 5 times concentration ratio were required economical and environmental friendly MF. This estimation method would be one of the effective tools to adopt new processes of food industry.
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