Listeria monocytogenes: Occurrence in beef and identification of the main contamination points in processing plants

This study aimed to establish the occurrence of Listeria spp., especially L. monocytogenes and its main serotypes, in beef and processing plants. A total of 443 samples were obtained from equipment, installations and products from 11 meat processing establishments from Paraná state, Brazil. All samples were analyzed using USDA methodology for Listeria spp. detection, followed by species identification. The occurrence of Listeria spp. in the samples was 38.1% of which 51.4% were from equipment, 35.4% from installations and 30.2% from products. The identified species were: L. monocytogenes (12.6%), L. innocua (78.4%), L. seeligeri (1.2%), L. welshimeri (7.2%) and L. grayi (0.6%). The identified serotypes of L. monocytogenes were 1/2a and 4b. The results demonstrate the significance of equipment and installations as sources of contamination by Listeria spp. and L. monocytogenes in the processing of beef and meat products.     

Methods to determine the growth domain in a multidimensional environmental space

Data from a database on microbial responses to the food environment (ComBase, see www.combase.cc) were used to study the boundary of growth several pathogens (Aeromonas hydrophila, Escherichia coli, Listeria monocytogenes, Yersinia enterocolitica). Two methods were used to evaluate the growth/no growth interface. The first one is an application of the Minimum Convex Polyhedron (MCP) introduced by Baranyi et al. [Baranyi, J., Ross, T., McMeekin, T., Roberts, T.A., 1996. The effect of parameterisation on the performance of empirical models used in Predictive Microbiology. Food Microbiol. 13, 83–91.]. The second method applies logistic regression to define the boundary of growth. The combination of these two different techniques can be a useful tool to handle the problem of extrapolation of predictive models at the growth limits.     

Design of challenge testing experiments to assess the variability of Listeria monocytogenes growth in foods

The assessment of the evolution of micro-organisms naturally contaminating food must take into account the variability of biological factors, food characteristics and storage conditions. A research project involving eight French laboratories was conducted to quantify the variability of growth parameters of Listeria monocytogenes obtained by challenge testing in five food products. The residual variability corresponded to a coefficient of variation (CV) of approximately 20% for the growth rate (μ_max) and 130% for the parameter K = μ_max × lag. The between-batch and between-manufacturer variability of μ_max was very dependent on the food tested and mean CV of approximately 20 and 35% were observed for these two sources of variability, respectively. The initial physiological state variability led to a CV of 100% for the parameter K. It appeared that repeating a limited number of three challenge tests with three different batches (or manufacturers) and with different initial physiological states seems often necessary and adequate to accurately assess the variability of the behavior of L. monocytogenes in a specific food produced by a given manufacturer (or for a more general food designation).     

Comparison of the hydrophobic grid-membrane filter DNA probe method and the Health Protection Branch standard method for the detection of Listeria monocytogenes in foods

The standard Health Protection Branch (HPB) method for the detection of L. monocytogenes in foods involves lengthy enrichment, selection and biochemical testing, requiring up to 8 days to complete. A hydrophobic grid-membrane filter (HGMF) method employing a digoxigenin-labelled listeriolysin O probe required 5 days to complete, and included an image-analysis system for electronic data acquisition. A total of 200 food samples encompassing 8 high-risk food groups (soft and semi-soft cheeses, packaged raw vegetables, frozen cooked shrimp, ground poultry, ground pork, ground beef, jellied meats, and pâté) were screened for the presence of L. monocytogenes by the two methods. Overall, 32 (16%) and 30 (15%) of the naturally-contaminated food samples tested positive for L. monocytogenes by the HPB and DNA methods, respectively. The DNA probe method was highly specific in discriminating L. monocytogenes from other Listeria spp. present in 50 of the samples tested. Results showed 94% sensitivity and 100% specificity between the two methods. The HGMF DNA probe method is an efficient and reliable alternative to the HPB standard method for detecting L. monocytogenes in foods.     

Predictive model for growth of Clostridium perfringens during cooling of cooked uncured meat and poultry

Comparison of Clostridium perfringens spore germination and outgrowth in cooked uncured products during cooling for different meat species is presented. Cooked, uncured product was inoculated with C. perfringens spores and vacuum packaged. For the isothermal experiments, all samples were incubated in a water bath stabilized at selected temperatures between 10 and 51 °C and sampled periodically. For dynamic experiments, the samples were cooled from 54.4 to 27 °C and subsequently from 27 to 4 °C for different time periods, designated as x and y hours, respectively. The growth models used were based on a model developed by Baranyi and Roberts (1994. A dynamic approach to predicting bacterial growth in food. Int. J. Food Micro. 23, 277-294), which incorporates a constant, referred to as the physiological state constant, q₀. The value of this constant captures the cells’ history before the cooling begins. To estimate specific growth rates, data from isothermal experiments were used, from which a secondary model was developed, based on a form of Ratkowsky’s 4-parameter equation. The estimated growth kinetics associated with pork and chicken were similar, but growth appeared to be slightly greater in beef; for beef, the maximum specific growth rates estimated from the Ratkowsky curve was about 2.7 log₁₀ cfu/h, while for the other two species, chicken and pork, the estimate was about 2.2 log₁₀ cfu/h. Physiological state constants were estimated by minimizing the mean square error of predictions of the log₁₀ of the relative increase versus the corresponding observed quantities for the dynamic experiments: for beef the estimate was 0.007, while those for pork and chicken the estimates were about 0.014 and 0.011, respectively. For a hypothetical 1.5 h cooling from 54 °C to 27° and 5 h to 4 °C, corresponding to USDA-FSIS cooling compliance guidelines, the predicted growth (log₁₀ of the relative increase) for each species was: 1.29 for beef; 1.07 for chicken and 0.95 log₁₀ for pork. However, it was noticed that for pork in particular, the model using the derived q₀ had a tendency to over-predict relative growth when the observed amount of relative growth was small, and under-predict the relative growth when the observed amount of relative growth was large. To provide more fail-safe estimate, rather than using the derived value of q₀, a value of 0.04 is recommended for pork.     

Ultraviolet light and Ultrasound as non-thermal treatments for the inactivation of microorganisms in fresh ready-to-eat foods

The effects of two non thermal disinfection processes, Ultraviolet light (UV 254 nm) and Ultrasound (US) on the inactivation of bacteria and color in two freshly cut produces (lettuce and strawberry) were investigated. The main scope of this work was to study the efficacy of UV and US on the decontamination of inoculated lettuce and strawberries with a cocktail of four bacteria, Escherichia coli, Listeria innocua, Salmonella Enteritidis and Staphylococcus aureus. Treatment of lettuce with UV reduced significantly the population of E. coli, L. innocua, S. Enteritidis and S. aureus by 1.75, 1.27, 1.39 and 1.21 log CFU/g, respectively. Furthermore, more than a 2-log CFU/g reduction of E. coli and S. Enteritidis was achieved with US. In strawberries, UV treatment reduced bacteria only by 1–1.4 log CFU/g. The maximum reductions of microorganisms, observed in strawberries after treatment with US, were 3.04, 2.41, 5.52 and 6.12 log CFU/g for E. coli, S. aureus, S. Enteritidis and L. innocua, respectively. Treatment with UV and US, for time periods (up to 45 min) did not significantly (p > 0.05) change the color of lettuce or strawberry. Treatment with UV and US reduced the numbers of selected inoculated bacteria on lettuce and strawberries, which could be good alternatives to other traditional and commonly used technologies such as chlorine and hydrogen peroxide solutions for fresh produce industry. These results suggest that UV and US might be promising, non-thermal and environmental friendly disinfection technologies for freshly cut produce.     

Survival and growth of Listeria species in a model ready-to-use vegetable product containing raw and cooked ingredients as affected by storage temperature and acidification

Summary The survival and growth of Listeria monocytogenes and L. innocua strains inoculated onto cooked sweet corn and fresh bean sprouts packed individually, and as components of a combination product, were examined at refrigeration and mild abuse temperatures. Growth rates were both temperature and vegetable dependent. Maximal growth rates (1.14 ± 0.1log CFU/day) were identified on cooked sweet corn at 12 °C. The inclusion of cooked sweet corn did not significantly increase ( P > 0.05) the growth rate or final Listeria population density of bean sprouts stored at 8 °C and 12 °C. The sensory quality of bean sprouts was relatively temperature independent for the initial 48 h of storage, but was maximized (4 days shelf life) at 3 °C. Acidification of sweet corn to pH 5, particularly with citric acid, slowed Listeria growth and could be an additional hurdle to supplement temperature in maintaining the safety of minimally processed vegetable combination products.     

Linear and non-linear kinetics in the synthesis and degradation of acrylamide in foods and model systems

Isothermal acrylamide formation in foods and asparagine-glucose model systems has ubiquitous features. On a time scale of about 60 min, at temperatures in the approximate range of 120-160 degrees C, the acrylamide concentration-time curve has a characteristic sigmoid shape whose asymptotic level and steepness increases with temperature while the time that corresponds to the inflection point decreases. In the approximate range of 160-200 degrees C, the curve has a clear peak, whose onset, height, width and degree of asymmetry depend on the system's composition and temperature. The synthesis-degradation of acrylamide in model systems has been recently described by traditional kinetic models. They account for the intermediate stages of the process and the fate of reactants involved at different levels of scrutiny. The resulting models have 2-6 rate constants, accounting for both the generation and elimination of the acrylamide. Their temperature dependence has been assumed to obey the Arrhenius equation, i.e., each step in the reaction was considered as having a fixed energy of activation. A proposed alternative is constructing the concentration curve by superimposing a Fermian decay term on a logistic growth function. The resulting model, which is not unique, has five parameters: a hypothetical uninterrupted generation-level, two steepness parameters; of the concentration climbs and fall and two time characteristics; of the acrylamide synthesis and elimination. According to this model, peak concentration is observed only when the two time constants are comparable. The peak's shape and height are determined by the gap between the two time constants and the relative magnitudes of the two "rate" parameters. The concept can be extended to create models of non-isothermal acrylamide formation. The basic assumption, which is yet to be verified experimentally, is that the momentary rate of the acrylamide synthesis or degradation is the isothermal rate at the momentary temperature, at a time that corresponds to its momentary concentration. The theoretical capabilities of a model of this kind are demonstrated with computer simulations. If the described model is correct, then by controlling temperature history, it is possible to reduce the acrylamide while still accomplishing much of the desirable effects of a heat process.     

Comparison of primary predictive models to study the growth of Listeria monocytogenes at low temperatures in liquid cultures and selection of fastest growing ribotypes in meat and turkey product slurries

This study compared the performance of four primary mathematical models to study the growth kinetics of Listeria monocytogenes ribotypes grown at low temperature so as to identify the best predictive model. The parameters of the best-fitting model were used to select the fastest growing strains with the shortest lag time and greatest growth rate. Nineteen food, human and animal L. monocytogenes isolates with distinct ribotype were grown at 4, 8, and 12 degrees C in tryptic soy broth and slurries prepared from cooked uncured sliced turkey breasts (with or without potassium lactate and sodium diacetate, PL/SD) and cooked cured frankfurters (with or without PL/SD). Separate regressions were performed on semi-logarithm growth curves to fit linear (based on Monod) and non-linear (Gompertz, Baranyi-Roberts, and Logistic) equations and performance of each model was evaluated using an F-test. No significant differences were found in the performance of linear and non-linear models, but the Baranyi model had the best fit for most growth curves. The maximum growth rate (MGR) of Listeria strains increased with the temperature. Similarly MGR was found significantly greater when no antimicrobials were present in the formulation of turkey or frankfurter products. The variability in lag times and MGRs in all media as determined by the Baranyi model was not consistent among strains. No single strain consistently had the fastest growth (shortest lag time, fastest MGR, or shortest time to increase 100-fold), but nine strains were identified as fastest growing strains under most growth conditions. The lack of association between serotype and fastest strain was also observed in the slurry media study. The fastest growing strains resulting from this study can be recommended for future use in L. monocytogenes challenge studies in delicatessen meat and poultry food matrices, so as to develop conservative pathogen growth predictions.     

Dynamic model for predicting growth of Salmonella spp. in ground sterile pork

A predictive model for Salmonella spp. growth in ground pork was developed and validated using kinetic growth data. Salmonella spp. kinetic growth data in ground pork were collected at several isothermal conditions (between 10 and 45 °C) and Baranyi model was fitted to describe the growth at each temperature, separately. The maximum growth rates (μ_max) estimated from the Baranyi model were modeled as a function of temperature using a modified Ratkowsky equation. To estimate bacterial growth under dynamic temperature conditions, the differential form of the Baranyi model, in combination with the modified Ratkowsky equation for rate constants, was solved numerically using fourth order Runge-Kutta method. The dynamic model was validated using five different dynamic temperature profiles (linear cooling, exponential cooling, linear heating, exponential heating, and sinusoidal). Performance measures, root mean squared error, accuracy factor, and bias factor were used to evaluate the model performance, and were observed to be satisfactory. The dynamic model can estimate the growth of Salmonella spp. in pork within a 0.5 log accuracy under both linear and exponential cooling profiles, although the model may overestimate or underestimate at some data points, which were generally < 1 log. Under sinusoidal temperature profiles, the estimates from the dynamic model were also within 0.5 log of the observed values. However, underestimation could occur if the bacteria were exposed to temperatures below the minimum growth temperature of Salmonella spp., since low temperature conditions could alter the cell physiology. To obtain an accurate estimate of Salmonella spp. growth using the models reported in this work, it is suggested that the models be used at temperatures above 7 °C, the minimum growth temperature for Salmonella spp. in pork.     

Survival of Escherichia coli O157:H7 in the processing and post-processing stages of acidophilus yogurt

In this study the survival of Escherichia coli O157:H7 in the production process of acidophilus yogurt was examined and compared with traditional yogurt. Milk was inoculated with different doses of E. coli O157:H7 (10², 10⁴ and 10⁶ CFU mL^?1) and two kinds of yogurt were produced. Samples were taken for pH measurements and bacterial enumeration at 0, 3, 24, 48, and 72 h after inoculation. Escherichia coli O157:H7 was analysed by using a Most Probable Number technique and yogurt starter culture and Lactobacillus  acidophilus were counted by using classical culture methods. Elimination times of E. coli O157:H7 were determined for 10² CFU mL^?1 as 3 h, and for 10⁴ and 10⁶ CFU mL^?1 as 48 h in acidophilus yogurt. Elimination times in traditional yogurt were 48 h for 10² and 10⁴ CFU mL^?1 and 72 h for 10⁶ CFU mL^?1E. coli O157:H7. In conclusion, the elimination time of E. coli O157:H7 in acidophilus yogurt was shorter than in traditional yogurt during the processing and post‐processing stages.     

Prediction of Listeria spp. growth as affected by various levels of chemicals, pH, temperature and storage time in a model broth

The effects of concentration of NaCl (0.5 to 12.5%), methyl paraben (0.0 to 0.2%), sodium propionate (0.3%), sodium benzoate (0.1%), potassium sorbate (0.3%), pH (>5.9) temperature (4 to 30°C), storage time (up to 58 d) and inoculum (>10⁵ to >10⁻² per ml) on the log₁₀ probability percentage of one cell of Listeria spp. to initiate growth in a broth system were evaluated in a factorial design study. At pH 5.96 and temperature ranging from 4 to 30°C the concentrations of sodium propionate, potassium sorbate, and sodium benzoate examined allowed growth of L. monocytogenes with lag phases at 4°C of 18, 27 and 21 days, respectively. For 0.1 and 0.2% methyl paraben growth of all Listeria spp. was initiated at 8°C and 30°C, respectively. At pH 6, concentration of 12% NaCl supported the growth of L. monocytogenes at 8 to 30°C, whereas 12.5% inhibited all Listeria species. Four regression equations were derived relating probability of growth initiation to temperature, concentrations of NaCl and preservatives storage time, and Listeria species specific effects. From these equations, the number of cells needed for growth initiation can be calculated. The impact of this type of quantitative study and its possible application on the development of microbial standards for foods is discussed.     

Development and application of a processing model for the Irish dairy industry

A processing-sector model was developed that simulates (i) milk collection, (ii) standardization, and (iii) product manufacture. The model estimates the product yield, net milk value, and component values of milk based on milk quantity, composition, product portfolio, and product values. Product specifications of cheese, butter, skim and whole milk powders, liquid milk, and casein are met through milk separation followed by reconstitution in appropriate proportions. Excess cream or skim milk are used in other product manufacture. Volume-related costs, including milk collection, standardization, and processing costs, and product-related costs, including processing costs per tonne, packaging, storage, distribution, and marketing, are quantified. Operating costs, incurred irrespective of milk received and processing activities, are included in the model on a fixed-rate basis. The net milk value is estimated as sale value less total costs. The component values of fat and protein were estimated from net milk value using the marginal rate of technical substitution. Two product portfolio scenarios were examined: scenario 1 was representative of the Irish product mix in 2000, in which 27, 39, 13, and 21% of the milk pool was processed into cheese (€3,291.33/t), butter (€2,766.33/t), whole milk powder (€2,453.33/t), and skim milk powder (€2,017.00/t), respectively, and scenario 2 was representative of the 2008 product mix, in which 43, 30, 14, and 13% was processed into cheese, butter, whole milk powder, and skim milk powder, respectively, and sold at the same market prices. Within both scenarios 3 milk compositions were considered, which were representative of (i) typical Irish Holstein-Friesian, (ii) Jersey, and (iii) the New Zealand strain of Holstein-Friesian, each of which had differing milk constituents. The effect each milk composition had on product yield, processing costs, total revenue, component values of milk, and the net value of milk was examined. The value per liter of milk in scenario 1 was 24.8, 30.8, and 27.4 cents for Irish Holstein-Friesian, Jersey, and New Zealand strain of Holstein-Friesian milk, respectively. In scenario 2 the value per liter of milk was 26.1, 32.6, and 28.9 cents for Irish Holstein-Friesian, Jersey, and New Zealand strain of Holstein-Friesian milk, respectively.     

A review of kinetic models for inactivating microorganisms and enzymes by pulsed electric field processing

As a non-thermal technology, pulsed electric field (PEF) treatment can be utilized in food processing and bioengineering for the inactivation of microorganisms and quality-degrading enzymes, as well as the retention of health-related compounds and the extension of shelf-life. Development of kinetic models that fit the degree of microbial inactivation and the loss of food quality is important to improve the efficiency of PEF treatment. The current review aims to provide an overview of the kinetic models used by PEF for microbial inactivation in liquid foods. Kinetics modeling for the destruction of microorganisms, inactivation of enzymes, retention of health-related compounds, and extension of shelf-life are discussed. Additionally, the fitting accuracy of several models, as well as issues that need further investigation, are discussed to promote further understanding and the deployment of PEF technology.     

Modeling the growth rate and lag time of different strains of Salmonella enterica and Listeria monocytogenes in ready-to-eat lettuce

The growth parameters (growth rate, μ and lag time, λ) of three different strains each of Salmonella enterica and Listeria monocytogenes in minimally processed lettuce (MPL) and their changes as a function of temperature were modeled. MPL were packed under modified atmosphere (5% O₂, 15% CO₂ and 80% N₂), stored at 7–30 °C and samples collected at different time intervals were enumerated for S. enterica and L. monocytogenes. Growth curves and equations describing the relationship between μ and λ as a function of temperature were constructed using the DMFit Excel add-in and through linear regression, respectively. The predicted growth parameters for the pathogens observed in this study were compared to ComBase, Pathogen modeling program (PMP) and data from the literature. High R² values (0.97 and 0.93) were observed for average growth curves of different strains of pathogens grown on MPL. Secondary models of μ and λ for both pathogens followed a linear trend with high R² values (>0.90). Root mean square error (RMSE) showed that the models obtained are accurate and suitable for modeling the growth of S. enterica and L. monocytogenes in MP lettuce. The current study provides growth models for these foodborne pathogens that can be used in microbial risk assessment.     

Effects of heat-processing regime, pH, water activity and their interactions on the behaviour of Listeria monocytogenes in ground pork. Modelling the boundary of the growth/no-growth areas as a function of pH, water activity and temperature

The influence of four heat‐processing regimes and a storage phase on the behaviour of Listeria monocytogenes in ground pork was studied. The effects of pH and water activity (a_w) were also tested. During the heat process phase, a_w, the heat‐processing regime and its interactions with pH or a_w, had a significant effect on the behaviour of L. monocytogenes. During the storage phase, all parameters tested and their interactions had significant effects. Nevertheless, the area in which the growth of L. monocytogenes was observed at the end of the experiment was not influenced by the heat‐processing regime tested. On the contrary, pH, a_w and their interactions had significant effects on Listeria behaviour. The boundary of the growth area delimited by environmental conditions where growth was higher than 1.0 Log CFU g^?1 from those where growth was lower than this limit was correctly predicted by Augustin's model.     

Validation of a model for growth of Lactococcus lactis and Listeria innocua in a structured gel system: effect of monopotassium phosphate

The effect of monopotassium phosphate (KH(2)PO(4)) on the chemical environment and on growth of Listeria innocua and Lactococcus lactis in coculture were investigated in a liquid and in a gelled microbiological medium at 12 degrees C and an initial pH of 6.2. As expected, addition of KH(2)PO(4) to both the liquid and gelled media resulted in an increase in buffering capacity. This effect on buffering capacity changed the profiles of lactic acid dissociation and pH evolution. At all gelatin concentrations studied, addition of KH(2)PO(4) increased the growth rate and the stationary cell concentration of L. lactis. In addition, the growth rate of L. innocua slightly increased but, in contrast, the stationary cell concentration remained unchanged. A new class of predictive models developed previously in our research team to quantify the effect of food model gel structure on microbial growth [Antwi, M., Bernaerts, K., Van Impe, J. F., Geeraerd, A. H., 2007. Modelling the combined effect of food model system and lactic acid on L. innocua and L. lactis growth in mono- and coculture. International Journal of Food Microbiology 120, 71-84] was applied. Our analysis indicate that KH(2)PO(4) influenced the parameters of the chemical and microbiological subprocesses of the model. Nonetheless, the growth model satisfactorily predicted the stationary cell concentration when (i) the undissociated lactic acid concentrations at which L. innocua and L. lactis growth cease were chosen as previously reported, and (ii) all other parameters of the chemical and microbiological subprocesses were computed for each medium. This confirms that the undissociated lactic acid concentrations at which growth ceases is a unique property of a bacterium and does not, within our case study, depend on growth medium. The study indicates that microbial growth depends on the interplay between the individual food components which affect the physicochemical properties of the food, such as the buffering capacity. Towards future research, it can be concluded that mathematical models which embody the effect of buffering capacity are needed for accurate predictions of microbial growth in food systems.     

A stochastic interspecific competition model to predict the behaviour of <Emphasis Type="Italic">Listeria monocytogenes</Emphasis> in the fermentation process of a traditional Sicilian salami

The present article discusses the use of modified Lotka–Volterra equations in order to stochastically simulate the behaviour of Listeria monocytogenes and lactic acid bacteria (LAB) during the fermentation period (168 h) of a typical Sicilian salami. For this purpose, the differential equation system is set considering temperature (T), pH, water activity (aw) as stochastic variables. Each of them is governed by dynamics that involve a deterministic linear decrease as a function of the time t and an “additive noise” term which instantaneously mimics the fluctuations of T, pH and aw. The choice of a suitable parameter accounting for the interaction of LAB on L. monocytogenes as well as the introduction of appropriate noise levels allows to match the observed data, both for the mean growth curves and for the probability distribution of L. monocytogenes concentration at 168 h.     

Preparation and validation of a growth model for Bacillus cereus: the effects of temperature, pH, sodium chloride and carbon dioxide

The growth responses of a vegetative inoculum of Bacillus cereus as influenced by varying conditions of temperature, pH value and sodium chloride concentration (% w/v) and carbon dioxide concentration (% v/v) were determined in laboratory medium. Growth curves in concentrations of NaCl in the range 0.5–10.5% (w/v), pH values in the range 4.5–7.0, CO₂ concentrations in the range 10–80% (v/v) and storage temperatures from 10 °C to 30 °C were fitted using the regime of Baranyi et al. (1993). A response surface model was prepared and predictions of doubling time, growth rate, lag time and time to 1000-fold increase could be obtained for any set of conditions within the matrix studied. This model is included in Food MicroModel Version 1. Predicted doubling times from the model were compared to observed doubling times in the literature and the model was found to give realistic estimates of doubling time for a range of foods including milk, meat and poultry and carbohydrate-based products.     

Effect of water activity on the inactivation kinetics of Escherichia coli O157:H7 by electron beam in ground beef, chicken breast meat, and trout fillets

Water activity (a_w) of ground beef, chicken breast meat, and trout fillets was modified to intermediate (a_w 0.98–0.99) and lowest (a_w 0.94–0.96) levels. The meat samples with modified and unaltered (native, a_w 1.00) a_w were inoculated with Escherichia coli O157:H7 and subjected to electron beam (e‐beam). Survivor curves were plotted and the D₁₀‐values were calculated. The D₁₀‐values ranged from 0.22 kGy for trout at native a_w to 0.33 kGy for beef at intermediate, and chicken and trout at lowest a_w. Regardless of the species, a_w reduction increased E. coli resistance to e‐beam, suggesting that even small depletion of unbound water from food increases survival. The difference of the D₁₀‐values between the samples at intermediate and lowest a_w was insignificant. E‐beam could be used before a_w‐reducing techniques are applied to food products. However, this would require stringent microbial control following e‐beam processing. The ‘tailing’ of survivors was observed for some samples with reduced a_w.