3-D stochastic modeling approach in thermal inactivation: estimation of thermal survival kinetics of Escherichia coli O157:H7 in a hamburger after exposure to desiccation stress.

Desiccation tolerance of pathogenic bacteria is one strategy for survival in harsh environments, which has been studied extensively. However, the subsequent survival behavior of desiccation-stressed bacterial pathogens has not been clarified in detail. Herein, we demonstrated that the effect of desiccation stress on the thermotolerance of Escherichia coli O157:H7 in ground beef was limited, and its thermotolerance did not increase. E. coli O157:H7 was inoculated into a ground beef hamburger after exposure to desiccation stress. We combined a bacterial inactivation model with a heat transfer model to predict the survival kinetics of desiccation-stressed E. coli O157:H7 in a hamburger. The survival models were developed using the Weibull model for two-dimensional pouched thin beef patties (ca. 1 mm), ignoring the temperature gradient in the sample, and a three-dimensional thick beef patty (ca. 10 mm), considering the temperature gradient in the sample. The two-dimensional (2-D) and three-dimensional (3-D) models were subjected to stochastic variations of the estimated Weibull parameters obtained from 1,000 replicated bootstrapping based on isothermal experimental observations as uncertainties. Furthermore, the 3-D model incorporated temperature gradients in the sample calculated using the finite element method. The accuracies of both models were validated via experimental observations under non-isothermal conditions using 100 predictive simulations. The root mean squared errors in the log survival ratio of the 2-D and 3-D models for 100 simulations were 0.25-0.53 and 0.32-2.08, respectively, regardless of the desiccation stress duration (24 or 72 h). The developed approach will be useful for setting appropriate process control measures and quantitatively assessing food safety levels.IMPORTANCEAcquisition of desiccation stress tolerance in bacterial pathogens might increase thermotolerance as well and increase the risk of foodborne illnesses. If a desiccation-stressed pathogen enters a kneaded food product via cross-contamination from a food-contact surface and/or utensils, proper estimation of the internal temperature changes in the kneaded food during thermal processing is indispensable for predicting the survival kinetics of desiccation-stressed bacterial cells. Various survival kinetics prediction models that consider the uncertainty or variability of pathogenic bacteria during thermal processing have been developed. Furthermore, heat transfer processes in solid food can be estimated using finite element method software. The present study demonstrated that combining a heat transfer model with a bacterial inactivation model can predict the survival kinetics of desiccation-stressed bacteria in a ground meat sample, corresponding to the temperature gradient in a solid sample during thermal processing. Combining both modeling procedures would enable the estimation of appropriate bacterial survival kinetics in solid food.

Characterization of the microbiota and chemical properties of pork loins during dry aging.

Dry aging (DA) allows for the storage of meat without packaging at 0 to 3°C for several weeks. It enhances the production of pleasant flavors, tenderness, and juiciness in meat. Due to the long storage period and roles of indigenous microbiota in the maturation of several meat products, the microbiota of DA meat is of interest in terms of microbial contributions and food hygiene but has not yet been characterized in detail. This study identified the microbiota of pork loins during DA using culturing and culture-independent meta-16S rRNA gene sequencing and elucidated its characteristics. The amounts of free amino acids and profiles of aroma-active compounds were also monitored by high-performance liquid chromatography and gas chromatography, respectively. The meta-16S rRNA gene sequencing revealed that Pseudomonas spp. generally dominated the microbiota throughout DA; however, the culturing analysis showed marked changes in the species composition during DA. Acinetobacter spp. were the second most dominant bacteria before DA in the culture-independent analysis but became a minor population during DA. The cell numbers of yeasts showed an increased tendency during DA, and Debaryomyces hansenii was the only microorganism isolated from all meat samples throughout DA. Well-known foodborne pathogens were not observed in two microbiota analyses. The amounts of free amino acids were increased by DA, and the number of aroma-active compounds and their flavor dilution values markedly changed during DA. Most microbial isolates showed positive reactions with proteolytic and lipolytic activities, suggesting their contribution to tenderness and aroma production in DA meats.

Rapid Inverse Method to Measure Thermal Diffusivity of Low-Moisture Foods.

Thermal diffusivity is an important transport property needed in modeling and computations of transient heat transfer in basic food processing operations. In addition, the prediction of nutritional and microbial changes occurring in food during thermal processing requires knowledge of thermal diffusivity of foods. The objectives of this study were to develop a new nonisothermal and nonlinear determination method of thermal diffusivity and to measure the thermal diffusivity of low-moisture foods using that new method. Thermal diffusivities of 5 kinds of low-moisture foods (almond meal, corn meal, wheat flour, chocolate fudge, and peanut butter) were estimated using an inverse technique. Samples were canned and heated at the surface in a water bath at about 70 °C. The 1-dimensional transient heat conduction problem for radial coordinates was solved with a finite-difference model. The thermal diffusivity of each of the 5 samples was determined by the ordinary least squares and sequential estimation methods, respectively. Predicted and observed temperature matched well, with maximum residuals of 0.9 °C. The thermal diffusivity values of the samples ranged from 9.8 × 10-8 to 1.3 × 10-7 m2 /s. The advantages of this method are that the device and the estimation method are simple, inexpensive, rapid, and can handle large spatial temperature gradients, such as those experienced during heating of low-moisture foods. The results obtained in this study will be useful in the design of equipment and in calculations for the thermal processing of low-moisture foods.