Robin C. McKellar

Inactivation of microbes using ultrasound: a review.

Alternative methods for pasteurization and sterilization are gaining importance, due to increased consumer demand for new methods of food processing that have a reduced impact on nutritional content and overall food quality. Ultrasound processing or sonication is one of the alternative technologies that has shown promise in the food industry. Sonication alone is not very effective in killing bacteria in food; however, the use of ultrasound coupled with pressure and/or heat is promising. Thermosonic (heat plus sonication), manosonic (pressure plus sonication), and manothermosonic (heat and pressure plus sonication) treatments are likely the best methods to inactivate microbes, as they are more energy-efficient and effective in killing microorganisms. Ultrasonic processing is still in its infancy and requires a great deal of future research in order to develop the technology on an industrial scale, and to more fully elucidate the effect of ultrasound on the properties of foods.

A combined discrete–continuous model describing the lag phase of Listeria monocytogenes☆

Food microbiologists generally use continuous sigmoidal functions such as the empirical Gompertz equation to obtain the kinetic parameters specific growth rate (mu) and lag phase duration (lambda) from bacterial growth curves. This approach yields reliable information on mu; however, values for lambda are difficult to determine accurately due, in part, to our poor understanding of the physiological events taking place during adaptation of cells to new environments. Existing models also assume a homogeneous population of cells, thus there is a need to develop discrete event models which can account for the behavior of individual cells. Time to detection (t(d)) values were determined for Listeria monocytogenes using an automated turbidimetric instrument, and used to calculate mu. Mean individual cell lag times (tL) were calculated as the difference between the observed t(d) and the theoretical value estimated using mu. Variability in tL for individual cells in replicate wells was estimated using serial dilutions. A discrete stochastic model was applied to the individual cells, and combined with a deterministic population-level growth model. This discrete-continuous model incorporating tL and the variability in tL (expressed as standard deviation; S.D.(L)) predicted a reduced variability between wells with increased number of cells per well, in agreement with experimental findings. By combining the discrete adaptation step with a continuous growth function it was possible to generate a model which accurately described the transition from lag to exponential phase. This new model may serve as a useful tool for describing individual cell behavior, and thus increasing our knowledge of events occurring during the lag phase.

A heterogeneous population model for the analysis of bacterial growth kinetics.

A two-compartment, heterogeneous population model (HPM) was derived using the simulation software SB ModelMaker to describe the growth of Listeria monocytogenes in bacteriological media at 5-35 degrees C. The model assumed that, at time t = 0, the inoculum was distributed between two distinct compartments, Non-Growing and Growing, and that growth could be described by four parameters: initial total cell population (N0), final maximum cell population (Nmax), maximum specific growth rate (mu(max)), and initial cell population in the Growing compartment (G0). The model was fitted to the data by optimizing the four parameters, and lag phase duration (lambda) was calculated. The resulting values of mu(max) and lambda were similar to those determined using the modified Gompertz equation. A new parameter, w0, was defined which relates to the proportion of the initial cell population capable of growth, and is a measure of the initial physiological state of the cells. A modified model in which mu(max) was replaced with a temperature function, and w0 replaced G0, was used to predict the effect of temperature on the growth of L. monocytogenes. The results of this study raise questions concerning the current definition of the lag phase.

A probability of growth model for Escherichia coli O157:H7 as a function of temperature, pH, acetic acid, and salt.

Data accumulated on the growth of Escherichia coli O157:H7 in tryptic soy broth (TSB) were used to develop a logistic regression model describing the growth-no growth interface as a function of temperature, pH, salt, sucrose, and acetic acid. A fractional factorial design with five factors was used at the following levels: temperature (10 to 30 degrees C), acetic acid (0 to 4%), salt (0.5 to 16.5%), sucrose (0 to 8%), and pH (3.5 to 6.0). A total of 1,820 treatment combinations were used to create the model, which correctly predicted 1,802 (99%) of the points, with 10 false positives and 8 false negatives. Concordance was 99.9%, discordance was 0.1%, and the maximum rescaled R2 value was 0.927. Acetic acid was the factor having the most influence on the growth-no growth interface; addition of as little as 0.5% resulted in an increase in the observed minimum pH for growth from 4.0 to 5.5. Increasing the salt concentration also had a significant effect on the interface; at all acetic acid concentrations, increasing salt increased the minimum temperature at which growth was observed. Using two literature data sets (26 conditions), the logistic model failed to predict growth in only one case. The results of this study suggest that the logistic regression model can be used to make conservative predictions of the growth-no growth interface of E. coli O157:H7.

Growth and survival of various strains of enterohemorrhagic Escherichia coli in hydrochloric and acetic acid

Nineteen strains of enterohemorrhagic Escherichia coli isolated from humans and foods were examined for their ability to grow and survive at low pH in organic (acetic) and mineral (HCl) acids. Strains were subcultured in tryptic soy broth adjusted to various pH values (3.75 to 4.75 for HCl and 4.75 to 5.75 for acetic acid) and incubated for 72 h at 37 degrees C to determine the minimum growth pH value. Minimum pH values for growth of 4.25 and 5.5 were found for HCl and acetic acid, respectively. Strains were also exposed to pH 2.0 (HCl) and pH 4.0 (acetic acid) for up to 24 h at 37 degrees C to assess their ability to survive. HCl was a more effective inhibitor after 6 h of exposure, whereas acetic acid was more effective after 24 h. Outbreak strains survived acid treatment significantly (P < or = 0.05) better than strains isolated from fermented or high-pH foods or animal or human isolates. Significant (P < or = 0.05) differences among serotypes and between O157:H7 and other serotypes were apparent after 3 or 6 h of exposure to acids.

Development of a dynamic growth-death model for Escherichia coli O157:H7 in minimally processed leafy green vegetables.

Escherichia coli O157:H7, an occasional contaminant of fresh produce, can present a serious health risk in minimally processed leafy green vegetables. A good predictive model is needed for Quantitative Risk Assessment (QRA) purposes, which adequately describes the growth or die-off of this pathogen under variable temperature conditions experienced during processing, storage and shipping. Literature data on behaviour of this pathogen on fresh-cut lettuce and spinach was taken from published graphs by digitization, published tables or from personal communications. A three-phase growth function was fitted to the data from 13 studies, and a square root model for growth rate (μ) as a function of temperature was derived: μ=(0.023*(Temperature-1.20))(2). Variability in the published data was incorporated into the growth model by the use of weighted regression and the 95% prediction limits. A log-linear die-off function was fitted to the data from 13 studies, and the resulting rate constants were fitted to a shifted lognormal distribution (Mean: 0.013; Standard Deviation, 0.010; Shift, 0.001). The combined growth-death model successfully predicted pathogen behaviour under both isothermal and non-isothermal conditions when compared to new published data. By incorporating variability, the resulting model is an improvement over existing ones, and is suitable for QRA applications.

Predictive modelling of Enterobacter sakazakii inactivation in bovine milk during high-temperature short-time pasteurization

Abstract A linear model was derived to describe the thermal inactivation of Enterobacter sakazakii in bovine whole milk in a high-temperature short-time pilot scale pasteurizer. Integrated lethal effect, or pasteurization effect (PE), was obtained by converting times at different temperatures in the various sections of the pasteurizer to the equivalent time at the reference temperature (72°C). PE was then related, by a simple linear function, to the log10 of the % viable counts with a power transformation of the PE values to improve linear fit. R2 values for the three E. sakazakii trials varied from 0.941 to 0.959. Inter-trial variation was incorporated into the model using @RISK™ simulation software, and a comparison between models for E. sakazakii and Listeria monocytogenes revealed that L. monocytogenes was more heat-resistant. Output from simulations confirmed that treatment at 68°C for 16 s can ensure (at the 1st percentile) a 5-log reduction of E. sakazakii.

Predictive modelling of inactivation of Listeria spp. in bovine milk during high-temperature short-time pasteurization

A linear model was derived to describe the thermal inactivation of Listeria innocua in bovine whole milk in a high-temperature short-time pilot scale pasteurizer. Integrated lethal effect, or pasteurization effect (PE), was obtained by converting times at different temperatures in the various sections of the pasteurizer to the equivalent time at the reference temperature (72 degrees C). PE was then related by a simple linear function to the log10 of the % viable counts with a power transformation of the PE values to improve the linear fit. R2 values for the five L. innocua trials varied from 0.728 to 0.974. Validation of this model with Listeria monocytogenes confirmed that L. monocytogenes was more heat sensitive. Inter-trial variation was incorporated into the model using the @RISK simulation software. Output from simulations confirmed that pasteurization at the IDF standard conditions of 72 degrees C for 15 sec can ensure at least an 11-log reduction of L. monocytogenes. The results showed that L. innocua may be used as a model microorganism to assess the thermal inactivation of L. monocytogenes, since its heat resistance is at least equal to or greater than that of the pathogenic species.

Thermal inactivation of Pediococcus sp. in simulated apple cider during high-temperature short-time pasteurization

Prompted by concerns regarding outbreaks of food-borne illness which have occurred due to the consumption of commercial, nonpasteurized fruit juices contaminated with Escherichia coli O157:H7, the US Food and Drug Administration and Canadian Food Inspection Agency are considering several new safety standards to apply to fresh juices, including mandatory pasteurization of all apple cider. In support of these initiatives, a study was conducted to evaluate the pasteurization of simulated cider using a heat-resistant nonpathogenic test bacterium, Pediococcus sp. NRRL B-2354. Thermal inactivation of the Pediococcus sp. was determined using a pilot scale high-temperature short-time (HTST) pasteurizer with a plate heat exchanger. The cumulative lethal effect, or pasteurization effect (PE), was obtained by converting times at different temperatures in the various sections of the pasteurizer to the equivalent time at the reference temperature (72 degrees C). PE was then related by a simple linear function to the log(10) of the percentage of viable counts with a power transformation of the PE values to improve linear fit. r(2) values for the four Pediococcus sp. trials varied from 0.921 to 0.981. Intertrial variation was incorporated into the model using @RISK simulation software. Output from simulations confirmed that treatment at 71 degrees C for 16 s can ensure a 5-log reduction of Pediococcus sp.

Nisin reduces the thermal resistance of Listeria monocytogenes Scott A in liquid whole egg

D-values (decimal reduction times) and z-values (increase in temperature required for a 1-log change in D-value) for Listeria monocytogenes Scott A were determined in liquid whole egg with nisin (0 or 10 microg ml(-1)) and NaCl (0 or 10%) by a submerged glass ampoule procedure. Samples were plated onto nonselective agar at appropriate intervals, and D-values were determined using a modified biphasic logistic equation. Addition of NaCl increased D-values at all temperatures tested. The addition of nisin to unsalted liquid whole egg resulted in a rapid 4-log reduction in viable counts within the first hour. Nisin significantly (P < or = 0.05) decreased D-values at lower (< 58 degrees C) temperatures in both unsalted and salted liquid whole egg but had little effect on the D-values at current minimum U.S. and Canadian pasteurization temperatures (60 degrees C without NaCl; 63 degrees C with NaCl). However, when nisin was added 2 h prior to heat treatment, D-values were significantly (P < or = 0.05) reduced at these temperatures. Inhibitory levels of nisin were detected in the liquid whole egg postpasteurization. Nisin could have a favorable impact on the control of L. monocytogenes in pasteurized liquid egg products.