Development of Predictive Models for the Growth of Escherichia coli O157:H7 on Cabbage in Korea

Modeling the Growth of Salmonella on Sliced Cucumbers as a Function of Temperature and Relative Humidity

ABSTRACT

Recent multistate outbreaks of salmonellosis linked to fresh cucumbers underscore the importance of understanding Salmonella behavior on cucumbers under different storage conditions. No validated models that describe the impact of environmental factors on the growth of Salmonella on sliced cucumbers currently exist. This study developed mathematical models to predict the growth of Salmonella on sliced cucumbers at different temperature and relative humidity (RH) conditions. Sliced cucumbers were inoculated with a four-strain cocktail of Salmonella and placed in desiccators containing a saturated salt solution to create controlled RH environments (∼15, 50, and 100% RH) at 7, 14, and 21°C for up to 120 h. Predictive models were developed by using the Baranyi and Roberts equation as a primary model, and estimated kinetic parameters were fitted into a square root (or Ratkowsky) equation for secondary models. The maximum growth rates for Salmonella on sliced cucumbers depended on temperature but not RH. The square root model for Salmonella growth was √μ= 0.0297 × (T - 6.5185), with a high R2 value (0.98). The models in this study will be useful for future microbial risk assessments and predictions of Salmonella behavior in the cucumbers to manage the risk of Salmonella on sliced cucumbers.

HIGHLIGHTS

Modeling the survival of Salmonella on whole cucumbers as a function of temperature and relative humidity

Recent multistate outbreaks of salmonellosis associated with fresh cucumbers underscore the importance of understanding Salmonella behavior on cucumbers under different conditions. This study developed mathematical models to predict the survival of four-strain cocktail of Salmonella on whole cucumbers at different temperature and relative humidity (RH) conditions. The strains were Salmonella Newport H1275 and Stanley H0558 (sprout outbreaks), Montevideo G4639 (tomato outbreak), and Saintpaul 02-517-1 (cantaloupe outbreak). Inoculated cucumbers were placed in desiccators containing saturated salt solution to create controlled RH environments (~15, 50, 100% RH) at 7, 14, and 21 °C, and enumerated at time intervals ranging from 0 to 240 h. Predictive models were developed using Baranyi and Roberts equation as a primary model and estimated kinetic parameters were fitted into a polynomial equation for secondary models. Reduced model polynomial equations which describe the maximum death rate and the log reduction of Salmonella on whole cucumber as a function of temperature and RH had high R² values (>0.95). Validation results verified the performance and reliability of the predictive models. The models in this study will be useful for future microbial risk assessments and predictions of Salmonella behavior in the cucumbers to manage the risk of Salmonella on whole cucumbers.

Prediction of Escherichia coli O157:H7, Salmonella , and Listeria monocytogenes Growth in Leafy Greens without Temperature Control

A recent study by the Centers for Disease Control and Prevention reported that between 1998 and 2008, leafy greens outbreaks accounted for 22.3% of foodborne outbreaks in the United States. Several studies on the growth of bacteria at different temperatures have been conducted; however, there is a need for the prediction of bacterial growth when leafy greens are transported without temperature control. Food products, when taken out of refrigeration, undergo a temperature change, with the rate of temperature change being proportional to the difference in the temperature of food and its surroundings. The objective of this study was to estimate the growth of Escherichia coli O157:H7, Salmonella enterica , and L. monocytogenes in leafy greens during transportation from retail to home at ambient temperatures ranging from 10 to 40°C for up to 10 h. Experiments were conducted to monitor the temperature increase in fresh spinach taken from refrigeration temperature to ambient temperature. The growth of pathogens was predicted using these changing temperature profiles with the three-phase linear model as a primary model and the square root model as the secondary model. The levels of E. coli O157:H7, S. enterica , and L. monocytogenes increased by 3.12, 2.43, and 3.42 log CFU at 40°C for the 10-h period, respectively, when no lag phase was assumed. If leafy greens are not kept out of refrigeration for more than 3 h, when the air temperature is 40°C or more, pathogen growth should be less than 1 log CFU. These results would assist in developing recommendations for food transportation without refrigeration.

Estimating Occupational Illness, Injury, and Mortality in Food Production in the United States: A Farm-to-Table Analysis

OBJECTIVES

The study provides a novel model and more comprehensive estimates of the burden of occupational morbidity and mortality in food-related industries, using a farm-to-table approach.

METHODS

The authors analyzed 2008 to 2010 US Bureau of Labor Statistics data for private industries in the different stages of the farm-to-table model (production, processing, distribution and storage, and retail and preparation).

RESULTS

The morbidity rate for food system industries was significantly higher than the morbidity rate for nonfood system industries (rate ratio = 1.62; 95% confidence interval = 1.30 to 2.01). Furthermore, the occupational mortality rate for food system industries was significantly higher than the national nonfood occupational mortality rate (rate ratio = 9.51; 95% confidence interval = 2.47 to 36.58).

CONCLUSIONS

This is the first use of the farm-to-table model to assess occupational morbidity and mortality, and these findings highlighting specific workplace hazards across food system industries.

Development of Predictive Models for the Growth Kinetics of Listeria monocytogenes on Fresh Pork under Different Storage Temperatures

This study was conducted to develop a predictive model to estimate the growth of Listeria monocytogenes on fresh pork during storage at constant temperatures (5, 10, 15, 20, 25, 30, and 35°C). The Baranyi model was fitted to growth data (log CFU per gram) to calculate the specific growth rate (SGR) and lag time (LT) with a high coefficient of determination (R(2) > 0.98). As expected, SGR increased with a decline in LT with rising temperatures in all samples. Secondary models were then developed to describe the variation of SGR and LT as a function of temperature. Subsequently, the developed models were validated with additional independent growth data collected at 7, 17, 27, and 37°C and from published reports using proportion of relative errors and proportion of standard error of prediction. The proportion of relative errors of the SGR and LT models developed herein were 0.79 and 0.18, respectively. In addition, the standard error of prediction values of the SGR and LT of L. monocytogenes ranged from 25.7 to 33.1% and from 44.92 to 58.44%, respectively. These results suggest that the model developed in this study was capable of predicting the growth of L. monocytogenes under various isothermal conditions.

Risk factors for Escherichia coli O157 shedding and super-shedding by dairy heifers at pasture

We undertook a longitudinal study within a cohort of 52 dairy heifers maintained under constant management systems and sampled weekly to investigate a comprehensive range of risk factors which may influence shedding or super-shedding of E. coli O157 (detected by direct faecal culture and immunomagnetic separation). E. coli O157 was detected from 416/933 (44.6%) samples (faeces and recto-anal mucosal swabs) and 32 (3.4%) samples enumerated at >10000 c.f.u./g. Weekly point prevalence ranged from 9.4% to 94.3%. Higher temperature (P < 0.001), rainfall (P = 0.02), relative humidity (P < 0.001), pasture growth (P = 0.013) and body score (P = 0.029) were positively associated with increased shedding. Higher rainfall (P < 0.001), hide contamination (P = 0.002) and increased faecal consistency (P = 0.023) were positively associated with super-shedding. Increased solar exposure had a negative effect on both shedding and super-shedding within bivariate analyses but in the final multivariate model for shedding demonstrated a positive effect (P = 0.017). Results suggest that environmental factors are important in E. coli O157 shedding in cattle.

Growth of Escherichia coli O157:H7 and Listeria monocytogenes in packaged fresh-cut romaine mix at fluctuating temperatures during commercial transport, retail storage, and display

Temperature abuse during commercial transport and retail sale of leafy greens negatively impacts both microbial safety and product quality. Consequently, the effect of fluctuating temperatures on Escherichia coli O157:H7 and Listeria monocytogenes growth in commercially-bagged salad greens was assessed during transport, retail storage, and display. Over a 16-month period, a series of time-temperature profiles for bagged salads were obtained from five transportation routes covering four geographic regions (432 profiles), as well as during retail storage (4,867 profiles) and display (3,799 profiles). Five different time-temperature profiles collected during 2 to 3 days of transport, 1 and 3 days of retail storage, and 3 days of retail display were then duplicated in a programmable incubator to assess E. coli O157:H7 and L. monocytogenes growth in commercial bags of romaine lettuce mix. Microbial growth predictions using the Koseki-Isobe and McKellar-Delaquis models were validated by comparing the root mean square error (RMSE), bias, and the acceptable prediction zone between the laboratory growth data and model predictions. Monte Carlo simulations were performed to calculate the probability distribution of microbial growth from 8,122,127,472 scenarios during transport, cold room storage, and retail display. Using inoculated bags of retail salad, E. coli O157:H7 and L. monocytogenes populations increased a maximum of 3.1 and 3.0 log CFU/g at retail storage. Both models yielded acceptable RMSEs and biases within the acceptable prediction zone for E. coli O157:H7. Based on the simulation, both pathogens generally increased <2 log CFU/g during transport, storage, and display. However, retail storage duration can significantly impact pathogen growth. This large-scale U.S. study-the first using commercial time/temperature profiles to assess the microbial risk of leafy greens-should be useful in filling some of the data gaps in current risk assessments for leafy greens.