Antibiotic Resistance Influences Growth Rates and Cross-Tolerance to Lactic Acid in Escherichia coli O157:H7 H1730.

Escherichia coli O157:H7-contaminated beef has been implicated in numerous foodborne outbreaks. Contamination occurs despite the use of antimicrobial interventions such as lactic acid (LA). In addition, resistance to antibiotics such as ampicillin and streptomycin among isolates has been frequently reported. The influence of antibiotic resistance (ABR) on growth rates and cross-tolerance of lettuce isolate E. coli O157:H7 H1730 to LA was evaluated. Antibiotic-resistant strain variants were generated by conferring resistance to either ampicillin (ampC) or streptomycin (strepC) or both ampicillin and streptomycin (ampC strepC) through incremental exposure to the antibiotics. Ampicillin resistance was also conferred by plasmid transformation to generate the ampP and ampP strepC strains. The minimum inhibitory concentration of LA on all the strains evaluated was 0.375% v/v. The lag phase duration of all strains except E. coli O157:H7 ampP strepC increased with increasing concentration of LA. The ampP strepC and ampC strains were most tolerant to 5% LA with declines in the cell population of 2.86 and 2.56 log CFU/mL, respectively (p < 0.05). The ampP strepC strain was the most tolerant when evaluated by the live/dead viability assay. The addition of the efflux pump inhibitor, carbonyl cyanide m-chlorophenylhydrazone, with 2.5% LA resulted in a significant increase in sensitivity in the no resistance (NR) wild-type and ampC strains, resulting in 6.62 and 6.65 log CFU/mL reduction, respectively, while the highly tolerant ampP strepC strain had a 2.90 log CFU/mL decrease. Tolerance to LA was significantly influenced by both the ABR profile of the strain and LA concentration. The results from this study indicate that E. coli O157:H7 strains with certain ABR profiles might be more tolerant to LA.

A predictive growth model for Clostridium botulinum during cooling of cooked uncured ground beef.

A dynamic model to predict the germination and outgrowth of Clostridium botulinum spores in cooked ground beef was presented. Raw ground beef was inoculated with a ten-strain C. botulinum spore cocktail to achieve approximately 2 log spores/g. The inoculated ground beef was vacuum packaged, cooked to 71 °C to heat shock the spores, cooled to below 10 °C, and incubated isothermally at temperatures from 10 to 46 °C. C. botulinum growth was quantified and fitted into the primary Baranyi Model. Secondary models were fitted to maximum specific growth rate and lag phase duration using Modified Ratkowsky equation (R2 0.96) and hyperbolic function (R2 0.94), respectively. Similar experiments were also performed under non-isothermal (cooling) conditions. Acceptable zone prediction (APZ) analysis was conducted on growth data collected over 3 linear cooling regimes from the current study. The model performance (prediction errors) for all 22 validation data points collected in the current work were within the APZ limits (-1.0 to +0.5 log CFU/g). Additionally, two other growth data sets of C. botulinum reported in the literature were also subjected to the APZ analysis. In these validations, 20/22 and 10/14 predictions fell within the APZ limits. The model presented in this work can be employed to predict C. botulinum spore germination and growth in cooked uncured beef under non-isothermal conditions. The beef industry processors and food service organizations can utilize this predictive microbial model for cooling deviations and temperature abused situations and in developing customized process schedules for cooked, uncured beef products.

Dynamic predictive model for growth of Salmonella spp. in scrambled egg mix.

Liquid egg products can be contaminated with Salmonella spp. during processing. A dynamic model for the growth of Salmonella spp. in scrambled egg mix - high solids (SEM) was developed and validated. SEM was prepared and inoculated with ca. 2 log CFU/mL of a five serovar Salmonella spp. cocktail. Salmonella spp. growth data at isothermal temperatures (10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47 °C) in SEM were collected. Baranyi model was used (primary model) to fit growth data and the maximum growth rate and lag phase duration for each temperature were determined. A secondary model was developed with maximum growth rate as a function of temperature. The model performance measures, root mean squared error (RMSE, 0.09) and pseudo-R2 (1.00) indicated good fit for both primary and secondary models. A dynamic model was developed by integrating the primary and secondary models and validated using two sinusoidal temperature profiles, 5-15 °C (low temperature) for 480 h and 10-40 °C (high temperature) for 48 h. The RMSE values for the sinusoidal low and high temperature profiles were 0.47 and 0.42 log CFU/mL, respectively. The model can be used to predict Salmonella spp. growth in case of temperature abuse during liquid egg processing.

Effects of spore purity on the wet heat resistance of Clostridium perfringens, Bacillus cereus and Bacillus subtilis spores.

Heat resistance of spores of Clostridium perfringens 8238 (Hobbs Serotype 2), Bacillus cereus NCTC 11143 (4810/72), and Bacillus subtilis PS533, an isogenic derivative of strain PS832 (a 168 strain) was determined in ground beef at 95 °C. Spore purification was by centrifugation and washing with sterile distilled water (dH2O), followed by sonication and then Histodenz centrifugation for B. subtilis and C. perfringens, and centrifugation and washing with sterile dH2O followed by Histodenz centrifugation for B. cereus. Bags containing inoculated beef samples were submerged in a temperature-controlled water bath and held at 95 °C for predetermined lengths of time. Surviving spore populations were enumerated by plating on mannitol egg yolk polymyxin agar (MYP) agar plates for B. cereus and B. subtilis, and on tryptose-sulfite-cycloserine agar (TSC) agar plates for C. perfringens. Survivor curves were fitted to linear, linear with tail, and Weibull models using the USDA Integrated Pathogen Modeling Program (IPMP) 2013 software. The Weibull model provided a relatively better fit to the data since the root mean square error (RMSE), mean square error (MSE), sum of squared errors (SSE), and Akaike information criterion (AIC) values were lower than the values obtained using the linear or the linear with tail models. Additionally, the Weibull model accurately predicted the observed D-values at 95 °C for the three spore-formers since the accuracy factor (Af) values ranged from 1.03 to 1.08 and the bias factor (Bf) values were either 1.00 or 1.01. Times at 95 °C to achieve a 3-log reduction decreased from 206 min for C. perfringens spores purified with water washes alone to 191 min with water washes followed by sonication and Histodenz centrifugation, from 7.9 min for B. cereus spores purified with water washes alone to 1.4 min with water washes followed by Histodenz centrifugation, and from 20.6 min for B. subtilis spores purified with water washes alone to 6.7 min for water washes followed by sonication and Histodenz centrifugation. Thermal-death-time values reported in this study will assist food processors to design thermal processes to guard against bacterial spores in cooked foods. In addition, clearly spore purity is an additional factor in spore wet heat resistance, although the cause of this effect is not clear.

Effect of meat ingredients (sodium nitrite and erythorbate) and processing (vacuum storage and packaging atmosphere) on germination and outgrowth of Clostridium perfringens spores in ham during abusive cooling.

The effect of nitrite and erythorbate on Clostridium perfringens spore germination and outgrowth in ham during abusive cooling (15 h) was evaluated. Ham was formulated with ground pork, NaNO2 (0, 50, 100, 150 or 200 ppm) and sodium erythorbate (0 or 547 ppm). Ten grams of meat (stored at 5 °C for 3 or 24 h after preparation) were transferred to a vacuum bag and inoculated with a three-strain C. perfringens spore cocktail to obtain an inoculum of ca. 2.5 log spores/g. The bags were vacuum-sealed, and the meat was heat treated (75 °C, 20 min) and cooled within 15 h from 54.4 to 7.2 °C. Residual nitrite was determined before and after heat treatment using ion chromatography with colorimetric detection. Cooling of ham (control) stored for 3 and 24 h, resulted in C. perfringens population increases of 1.46 and 4.20 log CFU/g, respectively. For samples that contained low NaNO2 concentrations and were stored for 3 h, C. perfringens populations of 5.22 and 2.83 log CFU/g were observed with or without sodium erythorbate, respectively. Residual nitrite was stable (p > 0.05) for both storage times. Meat processing ingredients (sodium nitrite and sodium erythorbate) and their concentrations, and storage time subsequent to preparation of meat (oxygen content) affect C. perfringens spore germination and outgrowth during abusive cooling of ham.

Ready-to-Eat Egg Products Formulated with Nisin and Organic Acids to Control Listeria monocytogenes.

Formulating ready-to-eat (RTE) products with growth inhibitors minimizes the risk of listeriosis. In part I, RTE egg products formulated with 6.25 ppm nisin were evaluated to control Listeria monocytogenes. Individual experimental units were surface inoculated with 2.5-log CFU/g of L. monocytogenes, packaged in pouches with a headspace gas of 20:80 CO2:NO2, and stored at 4.4°C for 8 weeks. Formulations with finished product pH of 6.29 ± 0.07 limited growth to <2-log for 4 weeks. Products at pH values of 7.42 ± 0.12 and 7.84 ± 0.11 were not different (p > 0.05) from the control without nisin at pH 7.34 ± 0.13, all supported 4-log growth by 4 weeks. In part II, a nisin bioassay test was performed to evaluate the stability of nisin in eggs as affected by the product pH (6.00 ± 0.03, 7.00 ± 0.00, 7.50 ± 0.03, and 8.00 ± 0.02) and cooking to an internal temperature of 73.9 or 85°C for 90 s. The nisin activity loss increased as the product pH or the cooking temperature increased (p < 0.05). Part III evaluated the effectiveness of 6.25 ppm nisin in combination with either an acetate-based antimicrobial used at 1.0% (w/w) in egg formulation (A1.0), propionate at 0.3% (P0.3), acetate-diacetate at 1.0% (AD1.0), acetate-diacetate at 0.6% (AD0.6), and lactate at 2.0% (L2.0) as a positive control. These formulations had a finished product pH, moisture, and salt contents of 5.97 ± 0.21, 72.4 ± 0.9%, and 0.67 ± 0.05%, respectively. L. monocytogenes did not grow in formulations A1.0 and AD1.0, whereas L2.0 and P0.3 supported 2-log growth by weeks 6 and 15, respectively and AD0.6 supported <1-log growth over 20 weeks at 4.4°C. Evaluation of uninoculated control units in parts I and III showed no changes (p > 0.05) in the CO2 and O2 headspace gas composition, generally no detection or growth of background microbes, and no changes (p > 0.05) in the pH of the formulations during storage, all assuring absence of uncontrolled interferences for the growth of L. monocytogenes.

Predictive modeling of thermal inactivation of non-O157 Shiga toxin-producing Escherichia coli in ground beef with varying fat contents.

A mathematical model to predict the thermal inactivation of non-O157 Shiga toxin-producing Escherichia coli (STEC) in ground beef was developed, with temperature and fat content of ground beef as controlling factors. Survival curves for a cocktail of non-O157 STEC strains in ground beef at four temperatures (55, 60, 65, and 68 °C) and six fat levels (5, 10, 15, 20, 25, and 30%) were generated. Nine primary models-log-linear, log-linear with tail, biphasic, sigmoidal, four-factor sigmoidal, Baranyi, Weibull, mixed Weibull, and Gompertz-were tested for fitting the survival curves. Primary modeling analysis showed the Weibull model had the highest accuracy factor and Akaike's weight, making it the best-fitting model. The parameters of the Weibull model were estimated using a nonlinear mixed, and response surface modeling was used to develop a second-order polynomial regression to estimate the impact of fat in ground beef and cooking temperature on the heat resistance of non-O157 STEC strains. The secondary model was successfully validated by comparing predicted lethality (log10 CFU/g) with the observed values for ground beef containing 10 and 27% fat at 58 and 62 °C. Process lethality obtained from experimental data was within the prediction interval of the predictive model. The developed model will assist the food industry in estimating the appropriate time and temperature required for cooking ground beef to provide adequate protection against STEC contaminants.

Effect of Disulfide Bonds on the Thermal Stability of Pediocin: In-silico Screening Using Molecular Dynamics Simulation.

The thermal stability properties of pediocin at 310, 313, 323, 333, 343, and 348 K (37, 40, 50, 60, 70, and 75°C, respectively) are reported in this study. A theoretical approach, such as the molecular dynamics method, was used to analyze the structure. Molecular dynamics simulation confirms the stability of molecules with Cys. Furthermore, this study reveals that Cys residues play an essential role in structure stability at high temperatures. To understand the structural basis for the stability of pediocin, a detailed in-silico analysis using molecular dynamics simulations to explore the thermal stability profiles of the compounds was conducted. This study shows that thermal effects fundamentally alter the functionally crucial secondary structure of pediocin. However, as previously reported, pediocin's activity was strictly conserved due to the disulfide bond between Cys residues. These findings reveal, for the first time, the dominant factor behind the thermodynamic stability of pediocin.

Optimizing the Effects of Nisin and NaCl to Thermal Inactivate Listeria monocytogenes in Ground Beef with Chipotle Sauce During Sous-vide Processing.

Mild cooking thermal treatments, like sous-vide, can compromise ground meat entrees such as meatballs with chipotle sauce, especially when salt levels are reduced during its preparation. Listeria monocytogenes is a thermoresistant pathogen that can be in ready-to-eat food. On the other hand, nisin, due to its thermal stability, can be a good alternative to aid on the thermal inactivation of L. monocytogenes and ensure meat safety. The objective was to optimize the amount of nisin and salt concentrations to thermally inactivate L. monocytogenes during the sous-vide cooking of ground beef marinated in chipotle sauce, and to generate a predictive model. A four-strain cocktail was prepared and inoculated in ground beef in combination (3:2) with chipotle sauce added with nisin (0-150 IU) and salt (0-2%). After that, meat samples were sous-vide cooked at different temperatures, nisin, and salt concentrations, established by a central composite design. Depending on the levels of these factors, D-values ranged from 49.71 to 0.27 min. A predictive model (p < 0.05) was obtained by response surface, which described that D-values variation was explained by the linear effects of the three factors, the interaction between nisin and temperature, and the quadratic effects of salt and temperature. It was also observed that nisin presented a bactericidal effect while salt presented a protective effect during the thermal inactivation of L. monocytogenes. Adding 120 IU of nisin and 0.4% of salt to the meat product at 63°C temperature can help to ensure food safety by making L. monocytogenes cells more sensitive to the lethal effect of heat. The model developed in this study can be used by food processors for planning and designing effective levels of salt and nisin to thermally inactivate L. monocytogenes in ground beef products marinated with chipotle sauce to ensure their safety.

Modeling the Fate of Listeria monocytogenes and Salmonella enterica on Fresh Whole and Chopped Wood Ear and Enoki Mushrooms.

Two recent foodborne illness outbreaks linked to specialty mushrooms have occurred in the United States, both representing novel pathogen-commodity pairings. Listeria monocytogenes and Salmonella enterica were linked to enoki and wood ear mushrooms, respectively. The aim of this study was therefore to examine the survival of both L. monocytogenes and S. enterica on raw whole and chopped enoki and wood ear mushrooms during storage at different temperatures. Fresh mushrooms were either left whole or chopped and subsequently inoculated with a cocktail of either S. enterica or rifampicin-resistant L. monocytogenes, resulting in an initial inoculation level of 3 log CFU/g. Mushroom samples were stored at 5, 10, or 25°C for up to 7 d. During storage, the population levels of S. enterica or L. monocytogenes on the mushrooms were enumerated. The primary Baranyi model was used to estimate the growth rates of both pathogens and the secondary Ratkowsky square root model was used to model the relationship between growth rates and temperature. Both L. monocytogenes and S. enterica survived on both mushroom types and preparations at all temperatures. No proliferation of either pathogen was observed on mushrooms stored at 5°C. At 10°C, moderate growth was observed for both pathogens on enoki mushrooms and for L. monocytogenes on wood ear mushrooms; no growth was observed for S. enterica on wood ear mushrooms. At 25°C, both pathogens proliferated on both mushroom types with growth rates ranging from 0.43 to 3.27 log CFU/g/d, resulting in 1 log CFU/g increases in only 0.31 d (7.44 h) to 2.32 d. Secondary models were generated for L. monocytogenes on whole wood ear mushrooms and S. enterica on whole enoki mushrooms with goodness-of-fit parameters of r2 = 0.9855/RMSE = 0.0479 and r2 = 0.9882/RMSE = 0.1417, respectively. Results from this study can aid in understanding the dynamics of L. monocytogenes and S. enterica on two types of specialty mushrooms.

Advances in multi-omics based quantitative microbial risk assessment in the dairy sector: A semi-systematic review.

With the increasing consumption of packaged and ready-to-eat food products, the risk of foodborne illness has drastically increased and so has the dire need for proper management. The conventional Microbial Risk Assessment (MRA) investigations require prior knowledge of process flow, exposure, and hazard assessment throughout the supply chain. These data are often generated using conventional microbiological approaches based either on shelf-life studies or specific spoilage organisms (SSOs), frequently overlooking crucial information such as antimicrobial resistance (AMR), biofilm formation, virulence factors and other physiological variations coupled with bio-chemical characteristics of food matrix. Additionally, the microbial risks in food are diverse and heterogenous, that might be an outcome of growth and activity of multiple microbial populations rather than a single species contamination. The uncertainty on the microbial source, time as well as point of entry into the food supply chain poses a constraint to the efficiency of preventive approaches and conventional MRA. In the last few decades, significant breakthroughs in molecular methods and continuously progressing bioinformatics tools have opened up a new horizon for risk analysis-based approaches in food safety. Real time polymerase chain reaction (qPCR) and kit-based assays provide better accuracy and precision with shorter processing time. Despite these improvements, the effect of complex food matrix on growth environment and recovery of pathogen is a persistent problem for risk assessors. The dairy industry is highly impacted by spoilage and pathogenic microorganisms. Therefore, this review discusses the evolution and recent advances in MRAmethodologies equipped with predictive interventions and "multi-omics" approach for robust MRA specifically targeting dairy products. It also highlights the limiting gap area and the opportunity for improvement in this field to ensure precision food safety.

Effect of Citral on the Thermal Inactivation of Escherichia coli O104:H4 in Ground Beef.

ABSTRACT: The objective of the present study was to analyze the combined effect of heat treatment (55 to 62.5°C) and citral (0 to 3%) on the heat resistance of Escherichia coli O104:H4 inoculated into ground beef. Inoculated meat packages were immersed in a circulating water bath stabilized at 55, 57.5, 60, or 62.5°C for various times. The surviving microbial cells were counted after culture on tryptic soy agar. A factorial design (4 × 4) was used to analyze the effects and interaction of heat treatment and citral. Heat and citral promoted E. coli O104:H4 thermal inactivation, suggesting a synergistic effect. At 55°C, the incorporation of citral at 1, 2, and 3% decreased D-values (control = 42.75 min) by 85, 89, and 91%, respectively (P < 0.05). A citral concentration-dependent effect (P < 0.05) also was noted at other evaluated temperatures. These findings could be of value to the food industry for designing a safe thermal process for inactivating E. coli O104:H4 in ground beef under similar thermal inactivation conditions.

Modeling the impact of chlorine on the behavior of Listeria monocytogenes on ready-to-eat meats.

Listeria monocytogenes (Lm) continues to pose a food safety hazard in ready-to-eat (RTE) meats due to potential cross-contamination. Chlorine is commonly used to sanitize processing equipment and utensils. However, Lm may survive the treatment and then contaminate food products. The objective of this study was to characterize the behavior of chlorine-exposed Lm on RTE ham during refrigerated storage. A two strain cocktail of Lm serotype 4b was pre-treated with chlorine (0, 25, and 50 ppm) for one hour, and then inoculated onto the surface of RTE ham to obtain an inoculum of about 3.0 log CFU/g. The inoculated ham samples were stored at 4, 8, and 16 °C, and Lm was enumerated periodically during the storage. The growth characteristics (lag time and growth rate) of Lm were estimated using the DMFit software. The results indicated that Lm growth was suppressed by the chlorine treatment. At 4 °C, the lag time of Lm with no (0 ppm) chlorine exposure (4.2 days) was shorter than those exposed to 25 ppm (5.4 days) and 50 ppm (6.8 days). The lag time decreased with the increase of temperature, e.g., at 25 ppm, the lag times were 5.2, 3.8 and 2.6 days for 4, 8 and 16 °C, respectively, and increased with the increase of chlorine concentration, e.g., at 16 °C, the lag times were 1.2, 2.6 and 4.0 days for 0, 25 and 50 ppm, respectively. However, growth rate increased with the increase of temperature and decreased with the increase of chlorine concentration. The lag time and growth rate as a function of chlorine concentration and temperature can be described using a modified Ratkowsky model and a modified Zwietering model, respectively. The results showed that the growth of Lm on RTE ham was delayed by pre-exposure to chlorine (at ≤ 50 ppm). The predictive models developed will contribute to microbial risk assessments of RTE meats.

Effects and interactions of sodium lactate, sodium diacetate, and pediocin on the thermal inactivation of starved Listeria monocytogenes on bologna.

The effects and interactions of temperature (56.3-60 °C), sodium lactate (SL; 0-4.8%), sodium diacetate (SDA; 0-2.5%), and pediocin (0-10,000 AU) on starved Listeria monocytogenes (10(7) CFU/g) on bologna were investigated. Bologna slices containing SL and SDA in the formulation were dipped in pediocin, surface inoculated, and treated at various temperatures using combinations of parameters determined by central composite design. D-values were calculated. The observed D-values ranged from 2.8 min at 60 °C to 24.61 min at 56.3 °C. Injury ranged from 9.1 to 76% under various conditions. The observed D-values were analyzed using second order response surface regression for temperature, SL, SDA, and pediocin, and a predictive model was developed. Predicted D-values were calculated and ranged from 3.7 to 19 min for various combinations of parameters. Temperature alone reduced the predicted D-values from 33.96 min at 56.3 °C to 11.51 min at 60 °C. Addition of SL showed a protective effect. Other combination treatments either reduced or increased D-values depending on temperature. The combination of SL and SDA was effective at lower temperatures, however, higher levels of SDA at higher temperatures made the organism more heat resistant. Pediocin (up to 5000 AU) with increasing temperature and SDA reduced D-values. Depending on temperature and concentration, the interactions between various additives can affect thermal inactivation of L. monocytogenes on bologna. Starvation rendered L. monocytogenes more susceptible to heat and additives.

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, q(0). 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 log(10) cfu/h, while for the other two species, chicken and pork, the estimate was about 2.2 log(10) cfu/h. Physiological state constants were estimated by minimizing the mean square error of predictions of the log(10) 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 1.5h cooling from 54°C to 27° and 5h to 4°C, corresponding to USDA-FSIS cooling compliance guidelines, the predicted growth (log(10) of the relative increase) for each species was: 1.29 for beef; 1.07 for chicken and 0.95 log(10) for pork. However, it was noticed that for pork in particular, the model using the derived q(0) 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 q(0), a value of 0.04 is recommended for pork.

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.

Predictive model for growth of Clostridium perfringens during cooling of cooked pork supplemented with sodium chloride and sodium pyrophosphate.

A dynamic model was developed to predict growth of Clostridium perfringens in cooked ground pork supplemented with salt (0-3% wt/wt) and sodium pyrophosphate (0-0.3% wt/wt) under varying temperatures. C. perfringens (NCTC 8238, NCTC 8239, and NCTC 10240) spores were heat shocked, cooled, and inoculated into ground pork. Isothermal bacterial growth was quantified with variable salt and phosphate concentrations at temperatures ranging from 15 to 51 °C. The primary Baranyi model was fitted to all C. perfringens growth profiles and gave a satisfactory fit (R2 ≥ 0.85). A quadratic polynomial secondary model was developed (P < 0.0001) to predict the maximum specific growth rate as a function of temperature, salt, and phosphate concentrations (R2 = 0.93). A dynamic model was developed and validated using growth data retrieved from 7 published studies. Thirty three out of 44 predictions were within the acceptable prediction zone (-0.5 ≤ prediction error ≤ 1.0). The developed predictive model can be used to minimize the risk of C. perfringens in pork products supplemented with additives during cooling.

Predictive model for growth of Clostridium botulinum from spores during cooling of cooked ground chicken.

Cooking temperature of poultry meat is typically inadequate to inactivate the heat resistant spores of Clostridium botulinum. The purpose of this study is to develop a predictive model for C. botulinum during cooling of cooked ground chicken. Cooked chicken was inoculated with a cocktail of five strains of proteolytic C. botulinum type A and five strains of proteolytic C. botulinum type B to yield a final spore concentration of approximately 2 log CFU/g. The growth of C. botulinum was determined at constant temperatures from 10 to 46 °C. Dynamic temperature experiments were performed with continued cooling from 54.4 to 4.4 °C or 7.2 °C in mono- or bi-phasic cooling profiles, respectively. The Baranyi primary model was used to fit growth data and the modified Ratkowsky secondary model was used to fit growth rates with respect to temperature. The primary models fitted the growth data well (R2 values ranging from 0.811 to 0.988). The R2 and root mean square error (RMSE) of the modified Ratkowsky secondary model were 0.95 and 0.06, respectively. Out of 11 prediction error values calculated in this study, ten were within the limit of acceptable prediction zone (-1.0 to 0.5), indicating a good fit of the model. The predictive model will assist institutional food service operations in determining the safety of cooked ground chicken subjected to different cooling periods.

Review of antimicrobial and antioxidative activities of chitosans in food.

Interest in chitosan, a biodegradable, nontoxic, non-antigenic, and biocompatible biopolymer isolated from shellfish, arises from the fact that chitosans are reported to exhibit numerous health-related beneficial effects, including strong antimicrobial and antioxidative activities in foods. The extraordinary interest in the chemistry and application in agriculture, horticulture, environmental science, industry, microbiology, and medicine is attested by about 17,000 citations on this subject in the Scopus database. A special need exists to develop a better understanding of the role of chitosans in ameliorating foodborne illness. To contribute to this effort, this overview surveys and interprets our present knowledge of the chemistry and antimicrobial activities of chitosan in solution, as powders, and in edible films and coating against foodborne pathogens, spoilage bacteria, and pathogenic viruses and fungi in several food categories. These include produce, fruit juices, eggs and dairy, cereal, meat, and seafood products. Also covered are antimicrobial activities of chemically modified and nanochitosans, therapeutic properties, and possible mechanisms of the antimicrobial, antioxidative, and metal chelating effects. Further research is suggested in each of these categories. The widely scattered data on the multifaceted aspects of chitosan microbiology, summarized in the text and in 10 tables and 8 representative figures, suggest that low-molecular-weight chitosans at a pH below 6.0 presents optimal conditions for achieving desirable antimicrobial and antioxidative-preservative effects in liquid and solid foods. We are very hopeful that the described findings will be a valuable record and resource for further progress to improve microbial food safety and food quality.