Lihan Huang

Growth kinetics of Escherichia coli O157:H7 in mechanically-tenderized beef.

A kinetic study was conducted to investigate the growth of Escherichia coli O157:H7 in mechanically-tenderized beef meat (MTBM) inoculated and internalized with a cocktail of 5 rifampicin-resistant (Rif(r)) or 3 arbitrarily selected wild-type strains of the bacteria. The storage was conducted at 5, 10, 15, 20, 25, and 37 degrees C. No growth was observed at 5 degrees C and the growth was minimal at 10 degrees C. Above 15 degrees C, a sigmoid trend was observed for all growth curves. Three primary growth models (modified Gompertz, Huang, and Baranyi) were used to fit the growth curves. A new Belehdradek-type secondary model was found more suitable than the traditional Ratkowsky model for describing the temperature dependence of growth rate. The statistical analysis suggested that both bacterial strains and primary growth model affect the determination of growth rates (at alpha=0.05), with Rif(r) strains growing 10-20% slower than the wild-type strains. While there was no significant difference between the growth rates estimated by the modified Gompertz and Baranyi models, and between those of Huang and Baranyi models, the rates estimated from the Gompertz model were significantly higher than those estimated from the Huang model. The temperature dependence of growth rate of E. coli O157:H7 in MTBM was described by both a new Belehdradek-type rate model and the Ratkowsky square-root model. While the theoretical minimum growth temperatures determined by the Ratkowsky square-root model ranged from 1.5 to 4.7 degrees C, more realistic values, varying from 6.64 to 8.76 degrees C, were estimated by the new rate model. For the Baranyi model, the average h(0) value was 2.06+/-0.74 and 2.15+/-1.14 for Rif(r) and wild-type strains of E. coli O157:H7, respectively. For the Huang and modified Gompertz models, the inverse of square-roots of lag phases was found proportional to temperature, making it possible to estimate the lag phase duration from the growth temperature. The results of this work can be used to assess the microbial safety of MTBM during refrigerated and temperature-abused storage conditions.

Mathematical modeling of growth of Salmonella in raw ground beef under isothermal conditions from 10 to 45 °C

The objective of this study was to develop primary and secondary models to describe the growth of Salmonella in raw ground beef. Primary and secondary models can be integrated into a dynamic model that can predict the microbial growth under varying environmental conditions. Growth data of Salmonella at nine different isothermal conditions--10, 15, 20, 25, 28, 32, 35, 42, and 45 degrees C were first fitted into primary models, namely the logistic, modified Gompertz, Baranyi, and Huang models. Performances of these models were evaluated by using various statistical criteria, namely mean square error (MSE), pseudo-R(2), -2 log likelihood, Akaikes and Bayesians information criteria. All the chosen models fitted well to the growth data of Salmonella based on these criteria. The results of statistical analysis showed that there was no significant difference in the performances of the four primary models, suggesting that the models were equally suitable for describing isothermal bacterial growth. The specific growth rates derived from each model was fitted to the Modified Ratkowsky equation, relating the specific growth rate to growth temperatures. It was also observed that the lag phase duration was an inverse function of specific growth rates. These models, if validated, can be used to construct dynamic models to predict potential Salmonella growth in raw ground beef.

Dynamic computer simulation of Clostridium perfringens growth in cooked ground beef

The objective of this study was to develop a computer simulation algorithm to dynamically estimate and predict the growth of Clostridium perfringens in cooked ground beef. The computational algorithm was based on the implicit form of the Gompertz model, the growth kinetics of C. perfringens in cooked ground beef, and the fourth-order Runge-Kutta numerical method. This algorithm was validated using a cocktail of three strains of C. perfringens spores grown under isothermal, square-waved, linear cooling, and exponential cooling temperature profiles. In general, the results of computer simulation matched closely with the experimental data with the absolute errors less than 0.5 log(10) CFU/g. This method may be a useful tool for the food industry, regulatory agencies, distributors, and retailers to predict the effect of temperature abuse on the microbial safety of C. perfringens and other foodborne pathogens in processed meat products.

Factors affecting thermally induced furan formation.

Furan, a potential carcinogen, can be induced by heat from sugars, ascorbic acid, and fatty acids. The objective of this research was to investigate the effect of pH, phosphate, temperature, and heating time on furan formation. Heat-induced furan formation from free sugars, ascorbic acid, and linoleic acid was profoundly affected by pH and the presence of phosphate. In general, the presence of phosphate increased furan formation in solutions of sugars and ascorbic acid. In a linoleic acid emulsion, phosphate increased the formation of furan at pH 6 but not at pH 3. When an ascorbic acid solution was heated, higher amounts of furan were produced at pH 3 than at pH 6 regardless of phosphates presence. However, in linoleic acid emulsion, more furan was produced at pH 6 than at pH 3. The highest amount of furan was formed from the linoleic acid emulsion at pH 6. In fresh apple cider, a product with free sugars as the major components (besides water) and little fatty acids, ascorbic acid, or phosphate, small or very low amounts of furan was formed by heating at 90-120 degrees C for up to 10 min. The results indicated that free sugars may not lead to significant amounts of furan formation under conditions for pasteurization and sterilization. Importantly, this is the first report demonstrating that phosphate (in addition to pH) plays a significant role in thermally induced furan formation.

IPMP 2013 — A comprehensive data analysis tool for predictive microbiology

Predictive microbiology is an area of applied research in food science that uses mathematical models to predict the changes in the population of pathogenic or spoilage microorganisms in foods exposed to complex environmental changes during processing, transportation, distribution, and storage. It finds applications in shelf-life prediction and risk assessments of foods. The objective of this research was to describe the performance of a new user-friendly comprehensive data analysis tool, the Integrated Pathogen Modeling Model (IPMP 2013), recently developed by the USDA Agricultural Research Service. This tool allows users, without detailed programming knowledge, to analyze experimental kinetic data and fit the data to known mathematical models commonly used in predictive microbiology. Data curves previously published in literature were used to test the models in IPMP 2013. The accuracies of the data analysis and models derived from IPMP 2013 were compared in parallel to commercial or open-source statistical packages, such as SAS® or R. Several models were analyzed and compared, including a three-parameter logistic model for growth curves without lag phases, reduced Huang and Baranyi models for growth curves without stationary phases, growth models for complete growth curves (Huang, Baranyi, and re-parameterized Gompertz models), survival models (linear, re-parameterized Gompertz, and Weibull models), and secondary models (Ratkowsky square-root, Huang square-root, Cardinal, and Arrhenius-type models). The comparative analysis suggests that the results from IPMP 2013 were equivalent to those obtained from SAS® or R. This work suggested that the IPMP 2013 could be used as a free alternative to SAS®, R, or other more sophisticated statistical packages for model development in predictive microbiology.

Growth kinetics of Listeria monocytogenes in broth and beef frankfurters--determination of lag phase duration and exponential growth rate under isothermal conditions.

The objective of this study was to develop a new kinetic model to describe the isothermal growth of microorganisms. The new model was tested with Listeria monocytogenes in tryptic soy broth and frankfurters, and compared with 2 commonly used models-Baranyi and modified Gompertz models. Bias factor (BF), accuracy factor (AF), and root mean square errors (RMSE) were used to evaluate the 3 models. Either in broth or in frankfurter samples, there were no significant differences in BF (approximately 1.0) and AF (1.02 to 1.04) among the 3 models. In broth, the mean RMSE of the new model was very close to that of the Baranyi model, but significantly lower than that of the modified Gompertz model. However, in frankfurters, there were no significant differences in the mean RMSE values among the 3 models. These results suggest that these models are equally capable of describing isothermal bacterial growth curves. Almost identical to the Baranyi model in the exponential and stationary phases, the new model has a more identifiable lag phase and also suggests that the bacteria population would increase exponentially until the population approaches to within 1 to 2 logs from the stationary phase. In general, there is no significant difference in the means of the lag phase duration and specific growth rate between the new and Baranyi models, but both are significantly lower than those determined from the modified Gompertz models. The model developed in this study is directly derived from the isothermal growth characteristics and is more accurate in describing the kinetics of bacterial growth in foods.

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.

Thermal inactivation of Escherichia coli O157:H7 in ground beef supplemented with sodium lactate.

A study was conducted to investigate the antimicrobial effect of sodium lactate (NaL) (0, 1.5, 3.0, and 4.5%) on the survival of Escherichia coli O157:H7 in 93% lean ground beef. Samples inoculated with a mixture of four strains of E. coli O157:H7 (10(7) to 10(8) CFU/g) were subjected to immersion heating in a water bath stabilized at 55, 57.5, 60, 62.5, or 65 degrees C. Results of statistical analysis indicated that the heating temperature was the only factor affecting the decimal reduction times (D-values) of E. coli O157:H7 in 93% lean ground beef. The change in temperature required to change the D-value (the z-value) was determined as 7.6 degrees C. The thermal resistance of this organism was neither affected by the addition of NaL nor by the interactions between NaL and temperature. Adding NaL to ground beef to reduce the thermal resistance of E. coli O157:H7 is therefore not recommended.

A new mechanistic growth model for simultaneous determination of lag phase duration and exponential growth rate and a new Bĕlehdrádek-type model for evaluating the effect of temperature on growth rate ☆

A new mechanistic growth model was developed to describe microbial growth under isothermal conditions. The new mathematical model was derived from the basic observation of bacterial growth that may include lag, exponential, and stationary phases. With this model, the lag phase duration and exponential growth rate of a growth curve were simultaneously determined by nonlinear regression. The new model was validated using Listeria monocytogenes and Escherichia coli O157:H7 in broth or meat. Statistical results suggested that both bias factor (B(f)) and accuracy factor (A(f)) of the new model were very close to 1.0. A new Bĕlehdrádek-type rate model and the Ratkowsky square-root model were used to describe the temperature dependence of bacterial growth rate. It was observed that the maximum and minimum temperatures were more accurately estimated by a new Bĕlehdrádek-type rate model. Further, the inverse of square-roots of lag phases was found proportional to temperature, making it possible to estimate the lag phase duration from the growth temperature.

Acids in Combination with Sodium Dodecyl Sulfate Caused Quality Deterioration of Fresh‐Cut Iceberg Lettuce during Storage in Modified Atmosphere Package

Recent studies showed that sodium acid sulfate (SAS) and levulinic acid (LA) in combination with sodium dodecyl sulfate (SDS) was effective in inactivating human pathogens on Romaine lettuce. The present study investigated the effects of LA and SAS in combination with SDS (as compared with citric acid and chlorine) on the inactivation of E. coli O157:H7 and sensory quality of fresh-cut Iceberg lettuce in modified atmosphere packages during storage at 4 °C. Results showed that LA (0.5% to 3%) and SAS (0.25% to 0.75%) with 0.05% SDS caused detrimental effects on visual quality and texture of lettuce. LA- and SAS-treated samples were sensorially unacceptable due to development of sogginess and softening after 7 and 14 d storage. It appears that the combined treatments caused an increase in the respiration rate of fresh-cut lettuce as indicated by higher CO(2) and lower O(2) in modified atmosphere packages. On the positive side, the acid treatments inhibited cut edge browning of lettuce pieces developed during storage. LA (0.5%), SAS (0.25%), and citric acid (approximately 0.25%) in combination with SDS reduced population of E. coli OH157:H7 by 0.41, 0.87, and 0.58 log CFU/g, respectively, while chlorine achieved a reduction of 0.94 log CFU/g without damage to the lettuce. Therefore, compared to chlorine, LA and SAS in combination with SDS have limited commercial value for fresh-cut Iceberg lettuce due to quality deterioration during storage.