Development and validation of primary, secondary, and tertiary models for growth of Salmonella Typhimurium on sterile chicken

Models are used in the food industry to predict pathogen growth and to help assess food safety. However, criteria are needed to determine whether models provide acceptable predictions. In the current study, primary, secondary, and tertiary models for growth of Salmonella Typhimurium (10(4.8) CFU/g) on sterile chicken were developed and validated. Kinetic data obtained at 10 to 40 degrees C were fit to a primary model to determine initial density (N0), lag time (lambda), maximum specific growth rate (micromax), and maximum population density (Nmax). Secondary models for N0, lambda, micromax, and Nmax as a function of temperature were developed and combined with the primary model to create a tertiary model that predicted pathogen density (N) at times and temperatures used and not used in model development. Performance of models was evaluated using the acceptable prediction zone method in which experimental error associated with growth parameter determinations was used to set criteria for acceptable model performance. Models were evaluated against dependent and independent (validation) data. Models with 70% prediction or relative errors (RE) in an acceptable prediction zone from -0.3 to 0.15 for micromax, -0.6 to 0.3 for lambda, and -0.8 to 0.4 for N, N0, and Nmax were classified as acceptable. All secondary models had acceptable goodness of fit and were validated against independent (interpolation) data. Percent RE in the acceptable prediction zone for the tertiary model was 90.7 for dependent data and 97.5 for independent (interpolation) data. Although the tertiary model was validated for interpolation, an unacceptable %RE of 2.5 was obtained for independent (extrapolation) data obtained with a lower N0 (10(0.8) CFU/g). The tertiary model provided overly fail-dangerous predictions of N from a lower N0. Because Salmonella concentrations on chicken are closer to 10(0.8) than 10(4.8) CFU/g, the tertiary model should not be used to help assess chicken safety.     

Effects of Lactic Acid on the Growth Characteristics of Listeria monocytogenes on Cooked Ham Surfaces

The surfaces of ready-to-eat meats are susceptible to postprocessing contamination by Listeria monocytogenes. This study examined and modeled the growth characteristics of L. monocytogenes on cooked ham treated with lactic acid solutions (LA). Cooked ham was inoculated with L. monocytogenes (ca. 10(3) CFU/g), immersed in 0, 0.5, 0.75, 1.0, 1.25, 1.5, and 2.0% LA for 30 min, vacuum packaged, and stored at 4, 8, 12, and 16°C. LA immersion resulted in <0.7 log CFU/g immediate reduction of L. monocytogenes on ham surfaces, indicating the immersion alone was not sufficient for reducing L. monocytogenes. During storage, no growth of L. monocytogenes occurred on ham treated with 1.5% LA at 4 and 8°C and with 2% LA at all storage temperatures. LA treatments extended the lag-phase duration (LPD) of L. monocytogenes and reduced the growth rate (GR) from 0.21 log CFU/day in untreated ham to 0.13 to 0.06 log CFU/day on ham treated with 0.5 to 1.25% LA at 4°C, whereas the GR was reduced from 0.57 log CFU/day to 0.40 to 0.12 log CFU/day at 8°C. A significant extension of the LPD and reduction of the GR of L. monocytogenes occurred on ham treated with >1.25% LA. The LPD and GR as a function of LA concentration and storage temperature can be satisfactorily described by a polynomial or expanded square-root model. Results from this study indicate that immersion treatments with >1.5% LA for 30 min may be used to control the growth of L. monocytogenes on cooked meat, and the models would be useful for selecting LA immersion treatments for meat products to achieve desired product safety.     

Modeling the growth of Listeria monocytogenes in pasteurized white asparagus

Growth of Listeria monocytogenes in pasteurized white asparagus was monitored at different storage temperatures (4, 10, 20, and 30 degrees C). Among the main microbial kinetic parameters, growth rate (mu) per hour was calculated at each temperature using the Baranyi-Roberts model. L. monocytogenes was able to grow at all temperatures, although at 4 degrees C only a slight increment of the microbial population was observed (approximately 1 log CFU/g) after 300 h of storage. Subsequently, two different secondary modeling approaches were proposed to study the relationship between mu and storage temperature: the Arrhenius and Ratkowsky models. Although both models properly described the data observed, smaller values of root mean square error (RMSE) and standard error of prediction (SEP) were obtained with the Ratkowsky model, providing a better goodness of fit (Ratkowsky model: RMSE = 0.010, SEP = 21.23%; Arrhenius model: RMSE = 0.026, SEP = 54.37%). The maximum population density (MPD) was calculated at each temperature studied. A clear dependence between MPD and temperature was found; lower temperatures produced lower values of MPD. This finding confirmed the Jameson effect, indicating that multiple hurdles in the food-processing chain plus lower temperatures reduced L. monocytogenes growth. Predicting the growth of L. monocytogenes along the food chain will help to reduce microbial risks associated with consumption of pasteurized white asparagus.     

Modeling the Growth Characteristics of Listeria monocytogenes and Native Microflora in Smoked Salmon

ABSTRACT:  Smoked salmon contaminated with Listeria monocytogenes has been implicated in foodborne listeriosis. The objectives of this study were to model the growth characteristics and examine the growth relationship of L. monocytogenes and native microflora in smoked salmon. Smoked salmon samples with a native microflora count of 2.9 log₁₀ CFU/g were inoculated with a 6-strain mixture of L. monocytogenes to levels of log₁₀ 1.6 and log₁₀ 2.8 CFU/g, and stored at 4, 8, 12, and 16 °C. Growth characteristics (lag phase duration [LPD, h], growth rate [GR, log₁₀ CFU/h], and maximum population density [MPD, log₁₀ CFU/g]) of L. monocytogenes and native microflora were determined. At 4 to 16 °C, the LPD, GR, and MPD were 254 to 35 h, 0.0109 to 0.0538 log₁₀ CFU/h, and 4.9 to 6.9 log₁₀ CFU/g for L. monocytogenes , respectively, and were 257 to 29 h, 0.0102 to 0.0565 log₁₀ CFU/h, and 8.5 to 8.8 log₁₀ CFU/g for native microflora. The growth characteristics of L. monocytogenes or the native microflora were not significantly different ( P > 0.05), regardless the initial levels of L. monocytogenes . Mathematical equations were developed to describe the LPD, GR, and MPD of L. monocytogenes and native microflora as a function of storage temperature. The growth relationship between L. monocytogenes and native microflora was modeled and showed that the LPD and GR of L. monocytogenes were similar to those of native microflora. These models can be used to estimate the growth characteristics of L. monocytogenes in smoked salmon, and thereby enhance the microbiological safety of the product.     

Development of a Predictive Model for Spoilage of Cooked Cured Meat Products and Its Validation Under Constant and Dynamic Temperature Storage Conditions

ABSTRACT:  In the present study, the spoilage flora of a sliced cooked cured meat product was studied to determine the specific spoilage organism (SSO). The physicochemical changes of the product during its storage in a temperature range of 0 to 12 °C were also studied. Among the primary models used to model the temperature effect on SSO growth, the modified Gompertz described better the experimental data than modified logistic and Baranyi. The derived growth kinetic parameters, such as maximum specific growth rate (μ_max) and lag phase duration (LPD), were modeled by using the square root and Arrhenius equation (secondary models). The latter described better the data of μ_max and LPD; therefore, this model was chosen for correlating temperature with kinetic parameters. The selection of the best model (primary or secondary) was based on some statistical indices (the root mean square error of residuals of the model, the coefficient of multiple determination, the F -test, the goodness of fit, the bias, and accuracy factor). The validation of the developed model was carried out under constant and dynamic temperature storage conditions. To validate its usefulness to similar products, another sliced cooked cured meat product stored under constant temperature conditions was also used. The log shelf life model was used for shelf life predictions based on the evident (visual defects) or the incipient spoilage (attainment of a certain spoilage level by SSO and/or chemical spoilage index). The possibility for shelf life predictions constitutes a valuable information source for the quality assurance systems of meat industries.     

Effect of salt, smoke compound, and storage temperature on the growth of Listeria monocytogenes in simulated smoked salmon

Smoked salmon can be contaminated with Listeria monocytogenes. It is important to identify the factors that are capable of controlling the growth of L. monocytogenes in smoked salmon so that control measures can be developed. The objective of this study was to determine the effect of salt, a smoke compound, storage temperature, and their interactions on L. monocytogenes in simulated smoked salmon. A six-strain mixture of L. monocytogenes (10(2) to 10(3) CFU/g) was inoculated into minced, cooked salmon containing 0 to 10% NaCl and 0 to 0.4% liquid smoke (0 to 34 ppm of phenol), and the samples were stored at temperatures from 0 to 25 degrees C. Lag-phase duration (LPD; hour), growth rate (GR; log CFU per hour), and maximum population density (MPD; log CFU per gram) of L. monocytogenes in salmon, as affected by the concentrations of salt and phenol, storage temperature, and their interactions, were analyzed. Results showed that L. monocytogenes was able to grow in salmon containing the concentrations of salt and phenol commonly found in smoked salmon at the prevailing storage temperatures. The growth of L. monocytogenes was affected significantly (P < 0.05) by salt, phenol, storage temperature, and their interactions. As expected, higher concentrations of salt or lower storage temperatures extended the LPD and reduced the GR. Higher concentrations of phenol extended the LPD of L. monocytogenes, particularly at lower storage temperatures. However, its effect on reducing the GR of L. monocytogenes was observed only at higher salt concentrations (>6%) at refrigerated and mild abuse temperatures (< 10 degrees C). The MPD, which generally reached 7 to 8 log CFU/g in salmon that supported L. monocytogenes growth, was not affected by the salt, phenol, and storage temperature. Two models were developed to describe the LPD and GR of L. monocytogenes in salmon containing 0 to 8% salt, 0 to 34 ppm of phenol, and storage temperatures of 4 to 25 degrees C. The data and models obtained from this study would be useful for estimating the behavior of L. monocytogenes in smoked salmon.     

Modeling and predicting the simultaneous growth of Listeria monocytogenes and natural flora in minced tuna

The growth kinetics of Listeria monocytogenes and natural flora (NF) in minced tuna from 2 to 30 °C were examined, and a simultaneous growth model was developed. The inhibiting effect of the NF on the growth of L. monocytogenes was examined by inoculating different levels of NF isolated from the minced tuna. The kinetic data were fitted to the Baranyi model and estimated the growth parameters such as specific growth rate (μ(max)), maximum population density (N(max)), and lag time. The temperature and inoculated NF dependency on the μ(max) of L. monocytogenes and NF were described by modified Ratkowsky's square-root model. As the initial NF level increased, the slopes of the square-root models were decreased for both L. monocytogenes and NF. The N(max) of L. monocytogenes was described as a function of temperature and inoculated NF level. Simultaneous growth prediction of L. monocytogenes and NF under constant temperature conditions was examined by using the differential equations based on the Baranyi model with the effect of interspecies competition substituted into the developed μ(max) and N(max) models. The root mean square errors between the model prediction and the observation for L. monocytogenes and NF were 0.42 and 0.34, respectively. Predictive simulation under fluctuating temperature conditions also demonstrated a high accuracy of simultaneous prediction for both L. monocytogenes and NF, representing the root mean square errors of 0.19 and 0.34, respectively. These results illustrate that the developed model permits accurate estimation of the behavior of L. monocytogenes in minced tuna under real temperature history until consumption.     

Validation of a tertiary model for predicting variation of Salmonella typhimurium DT104 (ATCC 700408) growth from a low initial density on ground chicken breast meat with a competitive microflora

Growth of a multiple antibiotic-resistant strain (ATCC 700408) of Salmonella Typhimurium definitive phage type 104 (DT104) from a low initial density (10(0.6) most probable number [MPN] or CFU/g) on ground chicken breast meat with a competitive microflora was investigated and modeled as a function of time and temperature (10 to 40 degrees C). MPN and viable counts (CFU) on a selective medium with four antibiotics enumerated the pathogen. Data from five replicate challenge studies per temperature were combined and fit to a primary model to determine maximum specific growth rate (micro), maximum population density (Nmax), and the 95% prediction interval (PI). Nonlinear regression was used to obtain secondary models as a function of temperature for micro, Nmax, and PI, which ranged from 0.04 to 0.4 h(-1), 1.6 to 9.4 log MPN or CFU/g, and 1.4 to 2.4 log MPN or CFU/g, respectively. Secondary models were combined with the primary model to create a tertiary model for predicting variation (95% PI) of pathogen growth among batches of ground chicken breast meat with a competitive microflora. The criterion for acceptable model performance was that 90% of observed MPN or CFU data had to be in the 95% PI predicted by the tertiary model. For data (n=344) used in model development, 93% of observed MPN and CFU data were in the 95% PI predicted by the tertiary model, whereas for data (n=236) not used in model development but collected using the same methods, 94% of observed MPN and CFU data were in the 95% PI predicted by the tertiary model. Thus, the tertiary model was successfully verified against dependent data and validated against independent data for predicting variation of Salmonella Typhimurium DT104 growth among batches of ground chicken breast meat with a competitive microflora and from a low initial density.     

The influence of mayonnaise pH and storage temperature on the growth of Listeria monocytogenes in seafood salad

Seafood salad has been identified as a ready-to-eat food with a relatively high incidence of contamination by Listeria monocytogenes; however, little is known about the behavior of this pathogen in seafood salad as a function of product pH and storage temperature. To produce data towards the development of a predictive growth model, a 6-strain cocktail of L. monocytogenes was inoculated onto the surface of a shrimp-crabmeat product, mixed with mayonnaise that was previously adjusted with NaOH to pH 3.7, 4.0, 4.4, 4.7 or 5.1, and then stored at 4 degrees , 8 degrees or 12 degrees C under both aerobic and vacuum conditions. At each storage temperature, L. monocytogenes was able to grow in the seafood salad under both aerobic and vacuum conditions. The slowest growth of L. monocytogenes was observed in seafood salad with a mayonnaise pH of 3.7 and a storage temperature of 4 degrees C under vacuum condition. In salad with the same mayonnaise pH, the growth rate (GR, log10 cfu/h) of L. monocytogenes increased as a function of storage temperature. At the same storage temperature, the lag phase duration (LPD, h) of L. monocytogenes decreased as mayonnaise pH increased. At the same mayonnaise pH and temperature, LPD of L. monocytogenes was greater under aerobic than under vacuum conditions. Regression analyses indicated that mayonnaise pH is the main effector on the LPD of L. monocytogenes in seafood salad, and storage temperature was the main effector on the GR. Secondary models that describe LPD and GR of L. monocytogenes in seafood salad as a function of mayonnaise pH and storage temperature were produced.     

Temperature effect on Listeria monocytogenes growth in the event of contamination of cooked pork products

The aim of this study was to describe the effect of temperature on the growth of Listeria monocytogenes in the event of postprocess contamination of packaged pork meats. This study was carried out in two steps. In the first step, the effect of temperature on L. monocytogenes growth rates was determined in duplicates at 13 temperatures between 2 and 43 degrees C by turbidimetric methods and adjusted by a quantitative secondary model. Then, seven sets of growth kinetics were collected by challenge testing in white pudding and roulade, both cooked pork products prepared according to an industrial process and stored at suboptimal temperatures ranging from 2 to 20 degrees C. In the second step, objectives were to (i) collect direct information on the temperature effect of L. monocytogenes on the two pork products, (ii) compare the two products regarding L. monocytogenes exposure, and (iii) compare results given by modeling (step i) with results obtained independently and then evaluate the model application domain. Each kinetic was built with at least 10 experimental data and two replicates. Comparison between L. monocytogenes behavior at 4 degrees C on white pudding and roulade indicated that both meat products were affected by food safety problems. Indeed, after contamination and storage for 10 days at 4 degrees C, the bacterial population increased by 2 log CFU/g in both products. Comparison between growth kinetic simulations and experimental data obtained separately gave satisfactory conclusions; the difference between observed and predicted bacterial population values was always less than 1 log CFU/g and a bias factor of 1.18 when growth rates were compared. These results applied to L. monocytogenes contamination of white pudding or roulade can now be used either in the management of optimal process and distribution networks or in risk assessment (exposure assessment).     

Modelling the effect of temperature, carbon dioxide, water activity and pH on growth and histamine formation by Morganella psychrotolerans

A mathematical model was developed to predict growth and histamine formation by Morganella psychrotolerans depending on temperature (0-20 degrees C), atmosphere (0-100% CO2), NaCl (0.0-6.0%) and pH (5.4-6.5). Data from experiments with both sterile tuna meat and Luria Bertani broth was used to develop the mathematical growth and histamine formation model. The expanded Logistic model with a growth dampening parameter (m) of 0.7 was used as primary growth model. A primary model for histamine formation during storage was obtained by combining the expanded Logistic growth model with a yield factor (YHis/CFU). 120 maximum specific growth rate (micromax)-values were generated for M. psychrotolerans and used to model the combined effect of the studied environmental parameters. A simple cardinal parameter type secondary model was used to model the effect of the four parameters on micro(max). The maximum population density (log Nmax) was correlated with log (YHis/CFU) and a simple constrained polynomial (quadratic) secondary model was developed for the effect of the environmental conditions on these model parameters. The developed model describes the effect of initial cell concentrations, storage conditions and product characteristics on histamine formation. This is a significant progress compared to previously available models for the effect of storage temperature only.     

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, and 1.162, and 1.267, 1.281, and 1.756 from Growth Predictor and Sym'Previus, respectively.     

Modeling the lag phase and growth rate of Listeria monocytogenes in ground ham containing sodium lactate and sodium diacetate at various storage temperatures

ABSTRACT:  Refrigerated ready-to-eat (RTE) meats contaminated with Listeria monocytogenes were implicated in several listeriosis outbreaks. Lactate and diacetate have been shown to control L. monocytogenes in RTE meats. The objective of this study was to examine and model the effect of lactate (1.0% to 4.2%) and diacetate (0.05% to 0.2%) in ground ham on the lag phase duration (LPD, h) and growth rate (GR, log CFU/h) of L. monocytogenes at a range of temperatures (0 to 45 °C). A 6-strain mixture of L. monocytogenes was inoculated into ground ham containing lactate and diacetate, and stored at various temperatures. The LPD and GR of L. monocytogenes in ham as affected by lactate, diacetate, and storage temperature were analyzed and accurately represented with mathematical equations. Resulting LPD and GR equations for storage temperatures within the range of 0 to 36 °C significantly represented the experimental data with a regression coefficient of 0.97 and 0.96, respectively. Significant factors ( P < 0.05) that affected the LPD were temperature, lactate, diacetate, and the interactions of all three, whereas only temperature and the interactions between temperature and lactate and diacetate had a significant effect on GR. At suboptimal growth temperatures (≤12 °C) the increase of lactate and diacetate concentrations, individually or in combination, extended the LPD. The effect of higher concentrations of both additives on reducing the GR was observed only at temperatures that were more suitable for growth of L. monocytogenes , that is, 15 to 35 °C. These data may be used to assist in determining concentrations of lactate and diacetate in cooked ham products to control the growth of L. monocytogenes over a wide range of temperatures during manufacturing, distribution, and storage.     

Effect of sub-lethal heating and growth temperature on expression of the ribosomal RNA rrnB P(2) promoter during the lag phase of Pseudomonas fluorescens

Current models for the lag phase of food-borne pathogens are limited by our poor understanding of the physiological changes taking place as bacterial cells prepare for exponential growth. In a previous paper in this series, a strain of Pseudomonas fluorescens containing the Tn7-luxCDABE gene cassette regulated by the rRNA promoter rrnB P(2) was used to measure the influence of starvation on the lag phase duration (LPD(OD)) and growth rate (R(OD)). rrnB P(2) promoter activity increased exponentially during the lag phase, and was characterized by lag (LPD(Exp)) and rate (R(Exp)) parameters. In the present study, this work was expanded to include the influence of growth temperature (10 to 30 degrees C) and exposure to sub-lethal heating at 47 degrees C. With these additional datasets, the LPD(Exp) was often more pronounced than had been noted with starvation, so the original exponential association model (EXP) was compared to logistic and Gompertz (GOM) models. Based on root mean square error, the GOM model gave the better fit for some of the sub-lethal heating and growth temperature datasets; however, the EXP model was assessed as best overall. Increased growth temperature and decreased time of sub-lethal heating produced significant decreases in LPD(OD) and LPD(Exp) and increases in R(OD) and R(Exp). The results suggest that different stressors have differential effects on gene expression and subsequent growth.     

Development and validation of a dynamic growth model for Listeria monocytogenes in fluid whole milk

Listeria monocytogenes, a psychrotrophic microorganism, has been the cause of several food-borne illness outbreaks, including those traced back to pasteurized fluid milk and milk products. This microorganism is especially important because it can grow at storage temperatures recommended for milk (< or =7 degrees C). Growth of L. monocytogenes in fluid milk depends to a large extent on the varying temperatures it is exposed to in the postpasteurization phase, i.e., during in-plant storage, transportation, and storage at retail stores. Growth data for L. monocytogenes in sterilized whole milk were collected at 4, 6, 8, 10, 15, 20, 25, 30, and 35 degrees C. Specific growth rate and maximum population density were calculated at each temperature using these data. The data for growth rates versus temperature were fitted to the Zwietering square root model. This equation was used to develop a dynamic growth model (i.e., the Baranyi dynamic growth model or BDGM) for L. monocytogenes based on a system of equations which had an intrinsic parameter for simulating the lag phase. Results from validation of the BDGM for a rapidly fluctuating temperature profile showed that although the exponential growth phase of the culture under dynamic temperature conditions was modeled accurately, the lag phase duration was overestimated. For an alpha0 (initial physiological state parameter) value of 0.137, which corresponded to the mean temperature of 15 degrees C, the population densities were underpredicted, although the experimental data fell within the narrow band calculated for extreme values of alpha0. The maximum relative error between the experimental data and the curve based on an average alpha0 value was 10.42%, and the root mean square error was 0.28 log CFU/ml.     

Impact of the population of spoilage microflora on the growth of Listeria monocytogenes on frankfurters

Approximately 100 CFU/cm2 of a five-strain mixture of Listeria monocytogenes was coinoculated onto frankfurters with three different concentrations (10(2), 10(4), and 106 CFU/cm2) of an undefined spoilage microflora derived from commercial frankfurters. The frankfurters were vacuum packaged and stored at 10 degrees C for up to 48 days. The populations of L. monocytogenes, aerobic mesophilic bacteria, lactic acid bacteria, and Enterobacteriaceae were determined at various time intervals during storage. After 14 days, the population of L. monocytogenes was highest when grown with a spoilage microflora population of 10(2) CFU/cm2, and this trend continued until 48 days. Throughout the entire storage period, the populations of L. monocytogenes at any concentration of inoculated spoilage microflora rarely differed by more than 0.5 log CFU/cm2, and the maximum observed difference as 1.1 log CFU/cm2 at 40 days. The growth rate of L. monocytogenes was approximately the same at all concentrations of the inoculated spoilage microflora. These results suggest that the concentration of spoilage microflora present on the original processed meat may have a slight impact on the growth of L. monocytogenes in the package.     

Effect of selected generally recognized as safe preservative sprays on growth of Listeria monocytogenes on chicken luncheon meat

The ability of selected generally recognized as safe (GRAS) chemical preservatives to reduce populations or inhibit growth of Listeria monocytogenes on chicken luncheon meat was evaluated. Slices of luncheon meat were treated by evenly spraying onto their surfaces 0.2 ml of a solution of one of four preservatives (sodium benzoate, sodium propionate, potassium sorbate, and sodium diacetate) at one of three different concentrations (15, 20, or 25% [wt/vol]). Each slice was then surface inoculated with a five-strain mixture of 10(5) CFU of L. monocytogenes per ml, held at 4, 13, or 22 degrees C, and assayed for L. monocytogenes immediately after inoculation and at 3, 7, 10, and 14 days of storage. Initial reductions of L. monocytogenes populations ranged from 0.78 to 1.32 log10 CFU g(-1) at day 0 for sodium benzoate- or sodium diacetate-treated meat, whereas reductions for the sodium propionate or potassium sorbate treatments were only 0.14 to 0.36 log10 CFU g(-1). After 14 days of storage at 4 degrees C, L. monocytogenes populations on all treated slices were 1.5 to 3 log10 CFU g(-1) less than on the untreated slices. At 13 degrees C and after 14 days of storage, L. monocytogenes populations were 3.5 and 5.2 log10 CFU g(-1) less on luncheon meat slices treated with 25% sodium benzoate or 25% sodium diacetate, respectively, and ca. 2 log10 CFU g(-1) less when treated with 25% sodium propionate or 25% potassium sorbate than on untreated control slices. Only sodium diacetate was highly inhibitory to L. monocytogenes on meat slices held at 22 degrees C for 7 days or longer. Untreated luncheon meat held at 22 degrees C was visibly spoiled within 10 days, whereas there was no evidence of visible spoilage on any treated luncheon meat at 14 days of storage.     

生鲜猪肉中单增李斯特菌动态生长预测与数值模拟

构建生鲜猪肉中单增李斯特菌的动态生长预测模型。猪肉样品接种由3 株单增李斯特菌制备的混合菌液,并置于3 组波动温度（1～45 ℃）条件下培养,采用一步法对获得的生长数据进行分析,构建并比较由初级模型（Baranyi或Two-compartment模型）与二级模型（Cardinal模型）集成的组合模型。结果表明,Baranyi-Cardinal和Two-compartment-Cardinal模型均适合用于描述猪肉中单增李斯特菌的生长,由两者估计的猪肉样品中单增李斯特菌最低、最适、最高生长温度分别为0.94、38.37、45.36 ℃和1.03、37.96、45.58 ℃,最适生长速率分别为0.891 h－1和0.858 h－1,最大生长浓度分别为9.07（lg（CFU/g））和9.09（lg（CFU/g））;通过另设的4 组动态生长实验和3 组等温（4、20、37 ℃）生长实验对模型进行验证,分析表明,模型可以准确预测动态及等温条件下的单增李斯特菌的生长,预测曲线的均方根误差介于0.13～0.48 （lg（CFU/g））,残差服从均值为－0.02 （lg（CFU/g））、标准差为0.29（lg（CFU/g））的正态分布。最后,基于构建的模型开展生鲜猪肉家庭冰箱冷藏过程中单增李斯特菌的生长数值模拟,以证明模型潜在的应用性。本研究结果可用于猪肉中单增李斯特菌的生长预测及风险评估。     

The effect of micro-architectural structure of cabbage substratum and or background bacterial flora on the growth of Listeria monocytogenes

The effect of micro-architectural structure of cabbage (Brassica oleracea var. capitata L.) substratum and or background bacterial flora on the growth of Listeria monocytogenes as a function of incubation temperature was investigated. A cocktail mixture of Pseudomonas fluorescens, Pantoea agglomerans and Lactobacillus plantarum was constituted to a population density of approximately 5 log CFU/ml in order to pseudo-simulate background bacterial flora of fresh-cut cabbage. This mixture was co-inoculated with L. monocytogenes (approximately 3 log CFU/ml) on fresh-cut cabbage or in autoclaved cabbage juice followed by incubation at different temperatures (4-30 degrees C). Data on growth of L. monocytogenes were fitted to the primary growth model of Baranyi in order to generate the growth kinetic parameters of the pathogen. During storage, microbial ecology was dominated by P. fluorescens and L. plantarum at refrigeration and abuse temperature, respectively. At all temperatures investigated, lag duration (lambda, h), maximum specific growth rate (micro(max), h(-1)) and maximum population density (MPD, log CFU/ml) of L. monocytogenes were only affected by medium micro-architectural structure, except at 4 degrees C where it had no effect on the micro(max) of the pathogen. Comparison of observed values of micro(max) with those obtained from the Pathogen Modelling Program (PMP), showed that PMP overestimated the growth rate of L. monocytogenes on fresh-cut cabbage and in cabbage juice, respectively. Temperature dependency of micro(max) of L. monocytogenes, according to the models of Ratkowsky and Arrhenius, showed linearity for temperature range of 4-15 degrees C, discontinuities and linearity again for temperature range of 20-30 degrees C. The results of this experiment have shown that the constituted background bacterial flora had no effect on the growth of L. monocytogenes and that micro-architectural structure of the vegetable was the primary factor that limited the applicability of PMP model for predicting the growth of L. monocytogenes on fresh-cut cabbage. A major limitation of this study however is that nutrient profile of the autoclaved cabbage juice may be different from that of the raw juice thus compromising realistic comparison of the behaviour of L. monocytogenes as affected by micro-architectural structure.     

Predicting pathogen growth during short-term temperature abuse of raw pork, beef, and poultry products: use of an isothermal-based predictive tool

A computer-based tool (available at: www.wisc.edu/foodsafety/meatresearch) was developed for predicting pathogen growth in raw pork, beef, and poultry meat. The tool, THERM (temperature history evaluation for raw meats), predicts the growth of pathogens in pork and beef (Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus) and on poultry (Salmonella serovars and S. aureus) during short-term temperature abuse. The model was developed as follows: 25-g samples of raw ground pork, beef, and turkey were inoculated with a five-strain cocktail of the target pathogen(s) and held at isothermal temperatures from 10 to 43.3 degrees C. Log CFU per sample data were obtained for each pathogen and used to determine lag-phase duration (LPD) and growth rate (GR) by DMFit software. The LPD and GR were used to develop the THERM predictive tool, into which chronological time and temperature data for raw meat processing and storage are entered. The THERM tool then predicts a delta log CFU value for the desired pathogen-product combination. The accuracy of THERM was tested in 20 different inoculation experiments that involved multiple products (coarse-ground beef, skinless chicken breast meat, turkey scapula meat, and ground turkey) and temperature-abuse scenarios. With the time-temperature data from each experiment, THERM accurately predicted the pathogen growth and no growth (with growth defined as delta log CFU > 0.3) in 67, 85, and 95% of the experiments with E. coli 0157:H7, Salmonella serovars, and S. aureus, respectively, and yielded fail-safe predictions in the remaining experiments. We conclude that THERM is a useful tool for qualitatively predicting pathogen behavior (growth and no growth) in raw meats. Potential applications include evaluating process deviations and critical limits under the HACCP (hazard analysis critical control point) system.