Aims: To design and build a thermoresistometer, named Mastia, which could perform isothermal and nonisothermal experiments. Methods and Results: In order to evaluate the thermoresistometer, the heat resistance of Escherichia coli vegetative cells and Alicyclobacillus acidoterrestris spores was explored. Isothermal heat resistance of E. coli was characterized by D60� C =0 AE38 min and z= 4AE7� C in pH 7 buffer. When the vegetative cells were exposed to nonisothermal conditions, their heat resistance was largely increased at slow heating and fast cooling rates. Isothermal heat resistance of A. acidoterrestris was characterized by D95� C =7 AE4 min and z= 9AE5� C in orange juice. Under nonisothermal conditions, inactivation was reasonably well predicted from isothermal data. Conclusions: The thermoresistometer Mastia is a very suitable instrument to get heat resistance data of micro-organisms under isothermal and nonisothermal treatments. Significance and Impact of the Study: The thermoresistometer Mastia can be a helpful tool for food processors in order to estimate the level of safety of the treatments they apply.

https://sfamjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2672.2009.04236.x

Nonisothermal heat resistance determinations with the thermoresistometer Mastia.

Modeling includes two distinct parts, the forward problem and the inverse problem. The forward problem—computing y(t) given known parameters— has received much attention, especially with the explosion of commercial simulation software. What is rarely made clear is that the forward results can be no better than the accuracy of the parameters. Therefore, the inverse problem—estimation of parameters given measured y(t)—is at least as important as the forward problem. However, in the food science literature there has been little attention paid to the accuracy of parameters. The purpose of this article is to summarize the state of the art of parameter estimation in food science, to review some of the common food science models used for parameter estimation (for microbial inactivation and growth, thermal properties, and kinetics), and to suggest a generic method to standardize parameter estimation, thereby making research results more useful. Scaled sensitivity coefficients are introduced and shown to be important in parameter identifiability. Sequential estimation and optimal experimental design are also reviewed as powerful parameter estimation methods that are beginning to be used in the food science literature.

Parameter estimation in food science.

Degradation of nutraceuticals in low- and intermediate-moisture foods heated at high temperature (>100 ◦ C) is difficult to model because of the nonisothermal condition. Isothermal experiments above 100 ◦ Ca re difficult to design because they require high pressure and small sample size in sealed containers. Therefore, a non- isothermal method was developed to estimate the thermal degradation kinetic parameter of nutraceuticals and de- termine the confidence intervals for the parameters and the predicted Y (concentration). Grape pomace at 42% moisture content (wb) was heated in sealed 202 × 214 steel cans in a steam retort at 126.7 ◦ Cf or> 30 min. Can cen- tertemperaturewasmeasuredbythermocoupleandpredictedusingComsolsoftware.Thermalconductivity(k)and specificheat(Cp)wereestimatedasquadraticfunctionsoftemperatureusingComsolandnonlinearregression.The kandCp functionswere thenusedtopredicttemperatureinsidethegrapepomaceduringretorting.Similarheating experiments were run at different time-temperature treatments from 8 to 25 min for kinetic parameter estimation. Anthocyanin concentration in the grape pomace was measured using HPLC. Degradation rate constant (k110◦C )a nd activationenergy(Ea)wereestimatedusingnonlinearregression.Thethermophysicalpropertiesestimatesat100 ◦ C were k = 0.501 W/m ◦ C, Cp = 3600 J/kg and the kinetic parameters were k110◦C = 0.0607/min and Ea = 65.32 kJ/mol. The 95% confidence intervals for the parameters and the confidence bands and prediction bands for anthocyanin retention were plotted. These methods are useful for thermal processing design for nutraceutical products.

Confidence intervals for modeling anthocyanin retention in grape pomace during nonisothermal heating.

Effect of heat activation and inactivation conditions on germination and thermal resistance parameters of Bacillus cereus spores.

Nonlinear regression technique to estimate kinetic parameters and confidence intervals in unsteady-state conduction-heated foods

The purpose of this work was to develop a means for determining product and process specific thermal kinetic parameters of constituents in foods that do not heat uniformly. The concept of the method of Paired Equivalent Isothermal Exposures (PEIE) was developed for such products. The ability of the PEIE to define Arrhenius parameters from simulated retort experiments was demonstrated. The PEIE was applied to survival data from retort experiments of canned pea puree inoculated with Bacillus stearothermophilus spores (NCA 1518). Mean activation energy and reaction rate constant (at 121.1°C) of the spores in retort processed canned pea puree were E a = 250 (± 15) kJ/mol and k 121.1°C = 0.26 (0.23 < k 121.1°C < 0.30) min -1 , respectively.

Kinetic parameter estimation in conduction heating foods subjected to dynamic thermal treatments.

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Kinetic parameter estimation in conduction heating foods subjected to dynamic thermal treatments.