Predictive model to describe the combined effect of pH and NaCl on apparent heat resistance of Bacillus stearothermophilus

Impact of shoulders on the calculus of heat sterilization treatments with different bacterial spores

To date, heat is still the most used technology in food preservation. The calculus of heat treatments is usually based on Bigelow observations i.e. treatment time is an exponential function of the heat treatment temperature. However, a number of researchers have reported deviations from linearity in heat inactivation curves that caused errors in the calculus. This research was designed to evaluate the variability of shoulder length among different sporulated species, the impact of treatment temperature on these shoulders and the relationship between the traditional D_T value and shoulder length. The heat inactivation kinetics of five bacterial spores of importance for the food industry was evaluated. B. weihenstephanensis and B. cereus did not show shoulders and D_T values calculated ranged from 0.99 to 0.23 and from 1.33 to 0.56 respectively at temperatures from 100 to 102.5 °C. On the other side B. subtilis, B. licheniformis and G. stearothermophilus showed shoulders of 1.75-0.42, 1.92-0.43 and 3.22-0.78 and D_T values of 1.52-0.32, 2.12-0.59 and 2.22-0.48 respectively in the range of temperatures tested. From the results obtained it was concluded that the presence and magnitude of shoulders depended on the bacterial spore species, the longest being those on the bacterial spores which showed greatest heat resistance. It has also been proved that shoulder lengths vary with treatment temperature in the same proportion of traditional D_T values, with the relationship Sl/D_T being constant. Thus, an equation which included the constant Sl/D_T was proposed.

Contamination pathways of spore-forming bacteria in a vegetable cannery

Spoilage of low-acid canned food during prolonged storage at high temperatures is caused by heat resistant thermophilic spores of strict or facultative bacteria. Here, we performed a bacterial survey over two consecutive years on the processing line of a French company manufacturing canned mixed green peas and carrots. In total, 341 samples were collected, including raw vegetables, green peas and carrots at different steps of processing, cover brine, and process environment samples. Thermophilic and highly-heat-resistant thermophilic spores growing anaerobically were counted. During vegetable preparation, anaerobic spore counts were significantly decreased, and tended to remain unchanged further downstream in the process. Large variation of spore levels in products immediately before the sterilization process could be explained by occasionally high spore levels on surfaces and in debris of vegetable combined with long residence times in conditions suitable for growth and sporulation. Vegetable processing was also associated with an increase in the prevalence of highly-heat-resistant species, probably due to cross-contamination of peas via blanching water. Geobacillus stearothermophilus M13-PCR genotypic profiling on 112 isolates determined 23 profile-types and confirmed process-driven cross-contamination. Taken together, these findings clarify the scheme of contamination pathway by thermophilic spore-forming bacteria in a vegetable cannery.

Modeling the recovery of heat-treated Bacillus licheniformis Ad978 and Bacillus weihenstephanensis KBAB4 spores at suboptimal temperature and pH using growth limits

The apparent heat resistance of spores of Bacillus weihenstephanensis and Bacillus licheniformis was measured and expressed as the time to first decimal reduction (δ value) at a given recovery temperature and pH. Spores of B. weihenstephanensis were produced at 30°C and 12°C, and spores of B. licheniformis were produced at 45°C and 20°C. B. weihenstephanensis spores were then heat treated at 85°C, 90°C, and 95°C, and B. licheniformis spores were heat treated at 95°C, 100°C, and 105°C. Heat-treated spores were grown on nutrient agar at a range of temperatures (4°C to 40°C for B. weihenstephanensis and 15°C to 60°C for B. licheniformis) or a range of pHs (between pH 4.5 and pH 9.5 for both strains). The recovery temperature had a slight effect on the apparent heat resistance, except very near recovery boundaries. In contrast, a decrease in the recovery pH had a progressive impact on apparent heat resistance. A model describing the heat resistance and the ability to recover according to the sporulation temperature, temperature of treatment, and recovery temperature and pH was proposed. This model derived from secondary mathematical models for growth prediction. Previously published cardinal temperature and pH values were used as input parameters. The fitting of the model with apparent heat resistance data obtained for a wide range of spore treatment and recovery conditions was highly satisfactory.

A meta-analysis accounting for sources of variability to estimate heat resistance reference parameters of bacteria using hierarchical Bayesian modeling: Estimation of D at 121.1 °C and pH 7, zT and zpH of Geobacillus stearothermophilus

Predicting microbial survival requires reference parameters for each micro-organism of concern. When data are abundant and publicly available, a meta-analysis is a useful approach for assessment of these parameters, which can be performed with hierarchical Bayesian modeling. Geobacillus stearothermophilus is a major agent of microbial spoilage of canned foods and is therefore a persistent problem in the food industry. The thermal inactivation parameters of G. stearothermophilus (D(ref), i.e.the decimal reduction time D at the reference temperature 121.1°C and pH 7.0, z(T) and z(pH)) were estimated from a large set of 430 D values mainly collected from scientific literature. Between-study variability hypotheses on the inactivation parameters D(ref), z(T) and z(pH) were explored, using three different hierarchical Bayesian models. Parameter estimations were made using Bayesian inference and the models were compared with a graphical and a Bayesian criterion. Results show the necessity to account for random effects associated with between-study variability. Assuming variability on D(ref), z(T) and z(pH), the resulting distributions for D(ref), z(T) and z(pH) led to a mean of 3.3 min for D(ref) (95% Credible Interval CI=[0.8; 9.6]), to a mean of 9.1°C for z(T) (CI=[5.4; 13.1]) and to a mean of 4.3 pH units for z(pH) (CI=[2.9; 6.3]), in the range pH 3 to pH 7.5. Results are also given separating variability and uncertainty in these distributions, as well as adjusted parametric distributions to facilitate further use of these results in aqueous canned foods such as canned vegetables.

Application of artificial neural networks to describe the combined effect of pH and NaCl on the heat resistance of Bacillus stearothermophilus

A model for prediction of bacterial spore inactivation was developed. The influence of temperature, pH and NaCl on the heat resistance of Bacillus stearothermophilus spores was described using low-complexity, black box models based on artificial neural networks. Literature data were used to build and train the neural network, and new experimental data were used to evaluate it. The neural network models gave better predictions than the classical quadratic response surface model in all the experiments tried. When the neural networks were evaluated using new experimental data, also good predictions were obtained, providing fail-safe predictions of D values in all cases. The weights and biases values of neurons of the neural network that gave the best results are presented, so the reader can use the model for their own purposes. The use of this non-linear modelling technique makes it possible to describe more accurately interacting effects of environmental factors when compared with classical predictive microbial models.

Thermal inactivation of the frozen thawed traditional meat starter culture, Pediococcus pentosaceus, in a meat model system

The equation, y((t))=y((0))e(kt), was fitted (R=0.9281, 0.9220 and 0.9117, respectively) to thermal inactivation data (55, 60 and 65°C) of the traditional meat starter culture Pediococcus pentosaceus (10(7)cfu/ml) in a meat model system. The population reduction constant ('k') increased (about 2.5- and 3-fold) with an increase in the treatment temperature (from 55 to 60°C and from 60 to 65°C, respectively). The Q(10) (55-65°C) for 'k' was 7.63. Thermal treatments of 19.1, 9.0 and 3.1min (55, 60 and 65°C, respectively) reduced the population of P. pentosaceus by 2.0 logs. The value of 'k' and the duration of the thermal treatment played an important role in the extent of the inactivation of the culture. The "zero inactivation" temperature (T(0)) for P. pentosaceus was 49.9°C. About 5 logs of the culture would be destroyed at 63 and 68°C within about 15.5 and 6.5min, respectively.

Validation of a polynomial regression model: the thermal inactivation of Bacillus subtilis spores in milk

AIMS

The predicted survival of Bacillus subtilis 168 spores from a polynomial regression equation was validated in milk.

METHODS AND RESULTS

Bias factor suggested as an index of model performance was used to validate the polynomial model predictions in ultrahigh temperature (UHT) treated and sterilized whole and skim milk. Model predictions were fail safe, predicting higher D-values (decimal reduction times) in buffer than actually noted in milk.

CONCLUSIONS

The D-values for spores were lower in milk as compared with those predicted in potassium phosphate buffer contrary to the popular expectation of better spore survival in complex food systems. The Bias factor, a quantitative measure of the model performance, indicated that on average the model predictions exceed the observations by 40% in the case of whole milk and by 60% in the case of skim milk.

SIGNIFICANCE AND IMPACT OF THE STUDY

The present work is an attempt to ascertain the extent of reliability that one can safely place in polynomial model predictions, without compromising on the safety or palatability of foods where it is eventually intended to be applied. The work has also highlighted the differences in the thermal inactivation pattern of spores in buffer and in milk with a possible influence of the various constituents of milk. The work will assist the dairy industry to better design thermal processes to ensure longer shelf life of dairy foods.

Modelling the combined effects of pH, temperature and sodium chloride stresses on the thermal inactivation of Bacillus subtilis spores in a buffer system

AIMS

The inactivation of Bacillus subtilis 168 spores subjected to the combined stress of pH, temperature and sodium chloride in a buffer system was modelled.

METHODS AND RESULTS

Bacillus subtilis 168 spore suspension in 50 mmol l-1 potassium phosphate buffer was heated in an open system using a block heater. A second order polynomial equation was used to describe the relationship between pH, temperature, sodium chloride concentration and the logarithm of the decimal reduction time (D-value) of the spores. Response surface graphs were constructed to predict the inactivation within the experimental domain. The data obtained were also compared with those reported for B. subtilis in different media and foods included in a large reference-based database of thermal inactivation (ThermoKill Database, TKDB R9100), which was constructed in the laboratory.

CONCLUSIONS

All the variables studied seemed to have a significant effect on the inactivation of B. subtilis 168 spores in potassium phosphate buffer. The coefficient of determination, r2, and an analysis of the residuals from the model indicated the adequacy of the model to predict the inactivation of B. subtilis spores within the range of the experimental variables studied.

SIGNIFICANCE AND IMPACT OF THE STUDY

The findings of this study will enable a better understanding of the inactivation of B. subtilis spores under the influence of the studied environmental variables. The model can be used by food industries to assess and monitor the shelf life of food products in the event of a chance contamination by B. subtilis spores.

Heat inactivation data for Mycobacterium avium subsp. paratuberculosis: implications for interpretation

AIMS

We discuss several factors that are critical for heat inactivation experiments and which should be taken into account for future research.

METHODS AND RESULTS

On the basis of examples from the literature we discuss critical factors influencing the calculated heat inactivation of Mycobacterium avium subsp. paratuberculosis (MAP). Furthermore, using a modelling approach, we show that tailing of the inactivation curve of MAP is caused by the presence of cell clumps and not by a more heat-resistant cell fraction.

CONCLUSIONS

The experimental conditions of the MAP heat inactivation studies of different research groups vary significantly and lead to considerable differences in results and conclusions. Therefore, a more consensual approach should be employed in future studies. In addition, our model on clumping of MAP can be used to predict the decimal reduction of MAP during heat treatment and to study the effect of clumping on other lethal effects.

SIGNIFICANCE AND IMPACT OF THE STUDY

We discuss several factors that should be carefully considered in heat resistance experiments. This is essential for a thorough interpretation of results from experiments and should be given proper attention in future experiments and publications on this topic.