The changes in microbial flora and sensory characteristics of fresh ground meat (beef and pork) with pH values ranging from 5.34 to 6.13 were monitored at different isothermal storage temperatures (0 to 20°C) under aerobic conditions. At all conditions tested, pseudomonads were the predominant bacteria, followed by Brochothrix thermosphacta , while the other members of the microbial association (e.g., lactic acid bacteria and Enterobacteriaceae ) remained at lower levels. The results from microbiological and sensory analysis showed that changes in pseudomonad populations followed closely sensory changes during storage and could be used as a good index for spoilage of aerobically stored ground meat. The kinetic parameters (maximum specific growth rate [μ _max ] and the duration of lag phase [λ]) of the spoilage bacteria were modeled by using a modified Arrhenius equation for the combined effect of temperature and pH. Meat pH affected growth of all spoilage bacteria except that of lactic acid bacteria. The “adaptation work,” characterized by the product of μ _max and λ(μ _max × λ) was found to be unaffected by temperature for all tested bacteria but was affected by pH for pseudomonads and B. thermosphacta . For the latter bacteria, a negative linear correlation between ln(μ _max × λ) and meat pH was observed. The developed models were further validated under dynamic temperature conditions using different fluctuating temperatures. Graphical comparison between predicted and observed growth and the examination of the relative errors of predictions showed that the model predicted satisfactorily growth under dynamic conditions. Predicted shelf life based on pseudomonads growth was slightly shorter than shelf life observed by sensory analysis with a mean difference of 13.1%. The present study provides a “ready-to-use,” well-validated model for predicting spoilage of aerobically stored ground meat. The use of the model by the meat industry can lead to effective management systems for the optimization of meat quality.

A survey on the time-temperature conditions of pasteurized milk in Greece during transportation to retail, retail storage, and domestic storage and handling was performed. The data derived from the survey were described with appropriate probability distributions and introduced into a growth model of Listeria monocytogenes in pasteurized milk which was appropriately modified for taking into account strain variability. Based on the above components, a probabilistic model was applied to evaluate the growth of L. monocytogenes during the chill chain of pasteurized milk using a Monte Carlo simulation. The model predicted that, in 44.8% of the milk cartons released in the market, the pathogen will grow until the time of consumption. For these products the estimated mean total growth of L. monocytogenes during transportation, retail storage, and domestic storage was 0.93 log CFU, with 95th and 99th percentiles of 2.68 and 4.01 log CFU, respectively. Although based on EU regulation 2073/2005 pasteurized milk produced in Greece belongs to the category of products that do not allow the growth of L. monocytogenes due to a shelf life (defined by law) of 5 days, the above results show that this shelf life limit cannot prevent L. monocytogenes from growing under the current chill chain conditions. The predicted percentage of milk cartons—initially contaminated with 1 cell/1-liter carton—in which the pathogen exceeds the safety criterion of 100 cells/ml at the time of consumption was 0.14%. The probabilistic model was used for an importance analysis of the chill chain factors, using rank order correlation, while selected intervention and shelf life increase scenarios were evaluated. The results showed that simple interventions, such as excluding the door shelf from the domestic storage of pasteurized milk, can effectively reduce the growth of the pathogen. The door shelf was found to be the warmest position in domestic refrigerators, and it was most frequently used by the consumers for domestic storage of pasteurized milk. Furthermore, the model predicted that a combination of this intervention with a decrease of the mean temperature of domestic refrigerators by 2°C may allow an extension of pasteurized milk shelf life from 5 to 7 days without affecting the current consumer exposure to L. monocytogenes .

Conventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells of Salmonella enterica serotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time (λ) and maximum specific growth rate (μ _max ) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size ( N ₀ ). For bacterial populations with N ₀ of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations.

A time/temperature indicator (TTI) system based on the growth and metabolic activity of a Lactobacillus sakei strain was developed for monitoring food quality throughout the chilled-food chain. In the designed system, an irreversible color change of a chemical chromatic indicator (from red to yellow) progressively occurs due to the pH decline that results from microbial growth and metabolism in a selected medium. The relation of the TTI response (color change) to the growth and metabolic activity (glucose consumption, lactic acid production, pH decrease) of L. sakei was studied. In addition, the temperature dependence of the TTI kinetics was investigated isothermally in the range of 0 to 16°C and modeled with a system of differential equations. At all temperatures tested, the pH and color changes of the TTI system followed closely the growth of L. sakei , with the endpoint (the time at which a distinct visual color change to the final yellow was observed) of the TTI coinciding with a population level of 10 ⁷ to 10 ⁸ CFU/ml. The endpoint decreased from 27 days at 0°C to 2.5 days at 16°C, yielding an activation energy of 97.7 kJ/mol, which was very close to the activation energy of the L. sakei growth rate in the TTI substrate (103.2 kJ/mol). Furthermore, experiments conducted on the effect of the inoculum level showed a negative linear relationship between the level of L. sakei inoculated in the system medium and the endpoint of the TTI. For example, the endpoint at 8°C ranged from 6 to 2 days for inoculum levels of 10 ¹ and 10 ⁶ CFU/ml, respectively. This relationship allows the easy adjustment of the TTI endpoint at a certain temperature according to the shelf life of the food product of concern by using an appropriate inoculum level of L. sakei . The microbial TTI prototype developed in the present study could be used as an effective tool for monitoring shelf life during the distribution and storage of food products that are spoiled primarily by lactic acid bacteria or other bacteria exhibiting similar kinetic responses and spoilage potentials. Apart from the low cost, the main advantage of the proposed TTI is that its response closely matches the loss of the quality of a food product by simulating the microbial spoilage process in particular environments.