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The use of non-thermal methods for food preservation is due to consumer demands for microbiological safe products, without changes in the sensory and nutritional qualities of the product. High hydrostatic pressure (HHP) has emerged as an alternative to traditional thermal processing methods for foods. Listeria monocytogenes CECT 5672 was treated under HHPs (350, 400 and 450 MPa) for 3, 16 and 23 min. The effects of pH (5, 6 and 7) and sodium chloride concentration (0, 0.5 and 1.0) of the recovery medium were studied on L. monocytogenes . The kinetic parameters were estimated by the method described by Metris, George, and Baranyi (2006) . From results obtained, histograms of the lag phase were generated and distributions were fitted. The duration of the lag phase of HHP damaged cells increased with the application of additional stresses. Histograms showed a shift to longer lag phases and an increase in variability with high stress levels in the recovery medium. Using a primary model together with Monte Carlo simulation, predictions of time to growth (100 cfu/g) of L. monocytogenes were established and they were compared with deterministic predictions. It was evidenced that deterministic predictions do not give a good indication of the probability of a certain level of growth.

The quantitative measurements of the growth of Salmonella can be traced back to the 1950s, when the Copenhagen School studied its cell cycle. Although predictive food microbiology has only been recognised as a discipline in its own right since the 1980s, the first predictive models on Salmonella, specifically on its thermal inactivation, were published in the 1960s. Today this is the foodborne pathogen for which the most D-values can be found in the literature. Being of concern in meat, growth models were developed mainly in poultry, other meats, egg products and culture media. With the advent of the internet, predictive modelling has become more advanced in terms of organising, analysing and visualising large amounts of data, and it has also become easier to disseminate the resultant predictive software packages. We anticipate that computational developments will generate further improvements, including complex scenario analysis, probabilistic and dynamic models.

The aim of the present study was to characterize the thermal inactivation of Alicyclobacillus acidoterrestris spores under isothermal and non-isothermal conditions simulating industrial heating processes applied to tangerine vesicles. A microbiological time temperature integrator (TTI) suitable for estimating the severity of thermal processes applied to acid foods was also developed. The heat resistance of A. acidoterrestris was characterized by D105 °C = 0.63 min and z = 10.8 °C in tangerine juice, showing linear survival curves, without shoulders and tails. Under non-isothermal conditions, the use of isothermal data allowed for an accurate prediction of the inactivation. The spores were included in alginate TTIs and they were used to estimate the severity of thermal treatments applied both in a thermoresistometer Mastia and in a food pilot plant scale system, which allows fast heating of the product to 93 °C and then a short holding time (2 min). In the thermoresistometer, tangerine juice was used as heating medium. In the food pilot plant scale system, thermal treatments were applied in batch to unpackaged tangerine vesicles. In both equipments, the TTIs accurately predicted the lethality of the thermal treatments applied. The percent coefficients of variation for survivor counting in TTIs showed that distribution of heat is homogeneous both in the thermoresistometer and in the reactor, being lower than 10% in all cases. The logistic and normal distributions were found to be the best for fitting the different survivor datasets.

Bacillus weihenstephanensis is a psychrotolerant bacterium belonging to the Bacillus cereus group. Some strains may be cytotoxic although they have not been described as food-poisoning agents so far. The objective of this work is to model the effects of temperature and a w downshifts on the lag time of B. weihenstephanensis and the dependence of μ max on the growth conditions (temperature and a w ). Effects of temperature downshifts were studied on 30 experimental conditions (shifts magnitude ranging from 2 to 20 °C, temperature after shift from 10 to 20 °C and a w ranging from 0.977 to 0.997). Osmotic shifts were studied for 13 conditions (shift magnitude ranging from 0.008 to 0.020 units of a w , temperature from 10 to 30 °C, a w after shift from 0.977 to 0.997). Experimental results show that temperature downshifts were able to induce considerable lag times (up to 20 days) when occurring near the growth limits. At lower temperatures, osmotic shifts had also a significant effect. Validation experiments in food subjected to changing conditions of temperature showed that the model provided valid predictions in diluted creamed pasta but overestimated bacterial growth in carrot soup (fail safe predictions).

8 pages, 2 tables, 4 figures.-- Online Ahead of Print: October 8, 2010.-- This is a copy of an article published in the Foodborne Pathogens and Disease © 2011 [copyright Mary Ann Liebert, Inc.]; Foodborne Pathogens and Disease is available online at: http://www.liebertonline.com., Stochastic models are useful for estimating the risk of foodborne illness and they can be integrated, besides other sources of variability, into microbial risk assessment. A stochastic approach to evaluate growth of two strains of Listeria monocytogenes influenced by different factors affecting microbial growth (pH and storage temperature) was performed. An individual-based approach of growth through optical density measurements was used. From results obtained, histograms of the lag phase were generated and distributions were fitted. Histograms presented increased variation when the factors applied were suboptimal for L. monocytogenes and they were combined. The extreme value distribution was ranked as the best one in most cases, whereas normal was the poorest fitting distribution. To evaluate the influence of pH and storage temperature on L. monocytogenes CECT 5672 in real food, commercial samples of courgette and carrot soup were inoculated with this pathogen. It was able to grow in both soups at storage temperatures from 4°C to 20°C. Using the distributions adjusted, predictions of time to growth (102 cfu/g) of L. monocytogenes were established by Monte Carlo simulation and they were compared with deterministic predictions and observations in foods., Dr. Marina Muñoz thanks Fundación CAJAMURCIA for awarding her a fellowship. This project was funded by Ministerio de Educación y Ciencia Español (ref. AGL 2006-13320-C03-02=ALI)

The dynamic model for the growth of a bacterial population described by Baranyi and Roberts (J. Baranyi and T. A. Roberts, Int. J. Food Microbiol. 23: 277-294, 1994) was applied to model the lag period and exponential growth of L isteria monocytogenes under conditions of fluctuating temperature and water activity (a w ) values. To model the duration of the lag phase, the dependence of the parameter h 0 , which quantifies the amount of work done during the lag period, on the previous and current environmental conditions was determined experimentally. This parameter depended not only on the magnitude of the change between the previous and current environmental conditions but also on the current growth conditions. In an exponentially growing population, any change in the environment requiring a certain amount of work to adapt to the new conditions initiated a lag period that lasted until that work was finished. Observations for several scenarios in which exponential growth was halted by a sudden change in the temperature and/or a w were in good agreement with predictions. When a population already in a lag period was subjected to environmental fluctuations, the system was reset with a new lag phase. The work to be done during the new lag phase was estimated to be the workload due to the environmental change plus the unfinished workload from the uncompleted previous lag phase.