1a. Objectives (from AD-416):
1. Develop predictive models that quantify growth kinetics and/or survival behavior of high priority pathogens (including but not limited to Shiga-toxin producing Escherichia coli, Listeria monocytogenes, Salmonella spp., Clostridium perfringens, and Staphylococcus aureus) in foods or food systems. This includes development of predictive models that quantify growth and/or inactivation kinetics of pathogens in food systems during heating and cooling. 1A: Pathogen Behavior in RTE Foods, Liquid Egg Products, and Produce - Measure and model pathogen growth in RTE foods, liquid egg products, and pre-packaged produce as a function of intrinsic and extrinsic factors, pathogen strain and physiological state, and natural background microflora. 1B: Thermal Inactivation Studies - Define combinations of intrinsic and extrinsic factors that delineate minimum heat treatments for pathogen lethality. 1C: Time-Temperature Conditions for Cooling Cooked Meat - Evaluate excessive time in cooling of heated meat and poultry products supplemented with additives to determine if the product remains safe. 2. Develop methods for application in predictive microbiology that are allied to Objective 1. For example: computer simulation of bacterial growth and inactivation under dynamic conditions, and simulation of the growth, inactivation and survival of foodborne pathogens in the presence of competing background flora. 3. Extend technology transfer through the expansion and continued maintenance of the Pathogen Modeling Program (PMP) and the Predictive Microbiology Information Portal (PMIP). Develop a computational framework to make the PMP compatible with Combase, and continue to support the development of ComBase with our associated partners (the Institute of Food Research [IFR] and the University of Tasmania [UTAS]) as an international data resource.
1b. Approach (from AD-416):
Pathogen growth in RTE foods, liquid egg products, and pre-packaged produce as a function of intrinsic and extrinsic food factors, and pathogen strain and physiological state will be determined. Also, combinations of intrinsic and extrinsic factors that delineate minimum heat treatments for pathogen lethality as well as safe rate and extent of cooling of heated meat and poultry supplemented with additives will be determined. Both static and dynamic temperature models will be developed. Developed models will be validated against data sets not used in model development and data set obtained from ComBase and published literatures. The underlying mathematics of each predictive model will be implemented in the ARS Pathogen Modeling Program. Raw data will be added to ComBase. The project will also collaborate with the IFR and the UTAS to further develop the Combase on improving its interface, functionality, and compatibility with PMP.
3. Progress Report:
Within this fiscal year, research was conducted to generate predictive models that quantify growth kinetics and/or survival behavior of high priority pathogens and develop methods for application in predictive microbiology. Research was conducted to evaluate the growth of S. aureus in semi-dry meat (pepperoni) and L. monocytogenes in a simulated cooked pork product and raw salmon roe. The growth studies of S. aureus and L. monocytogenes were conducted under dynamic conditions. The growth of L. monocytogenes in salmon roe was conducted under isothermal conditions to develop dynamic models. Research was also conducted to simulate the dynamic growth of C. perfringens in cooked poultry. Studies were conducted to determine the growth rates of Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. in five varieties of fresh-cut vegetables at refrigerated and abuse temperatures. Results may be used to predict the growth of each pathogen in fresh-cut produce during distribution and storage and determine the relative risk of each vegetable variety. Studies were conducted to determine the survival of Salmonella spp. in egg white and egg yolk with or without the addition of salt or sugar (5 and 10%) treated with mild heat treatments (50-62 degree C) and the subsequent survival under abuse temperatures. Results may be used to determine heat processing for liquid egg products to ensure product safety. Studies were completed for evaluating the effects of chlorine, water activity, acid, and starvation stresses on the growth behavior and cytotoxcity of Shiga toxin-producing Escherichia coli (STEC) in ground beef and spinach. Results will be used in controlling the pathogen and providing an adequate degree of protection against STEC in ground beef and spinach. Since inadequate cooking time and temperature is a significant factor that may lead to foodborne illness, a study on the effect of pomegranate-extracted ellagic acid on the reduced heat resistance of E. coli O157:H7 in ground chicken as completed. The thermal death predictive model developed for the pathogen will assist meat processors to design lethality treatments in order to achieve specific reductions of E. coli O157:H7 in ground chicken. Study as completed for the inactivation of Salmonella spp. in ground beef jerky, as a function of temperature, pH, potassium sorbate, and final water activity. A predictive model developed may be used to effectively design drying processes for beef jerky under low humidity conditions and thereby, ensuring an adequate degree of protection against risks associated with Salmonella spp.
1. USDA IPMP-Dynamic Prediction software for growth of Clostridium perfringens during cooling. C. perfringens grows rapidly in many products regulated by the USDA FSIS. The pathogen can produce a toxin that causes acute abdominal pain and diarrhea in consumers who ingest cooked meat products that are not properly cooled during manufacturing. ARS researchers at Wyndmoor, Pennsylvania, developed a new computer simulation software package – the USDA IPMP-Dynamic Prediction that can accurately predict the growth of C. perfringens in cooked beef under dynamic conditions. The USDA IPMP-Dynamic Prediction also calculates the probabilities of greater than 1 log and 2 logs in relative growth of C. perfringens in the products. This new software can be used by the food industry and regulatory agencies to conduct process risk analysis of growth of C. perfringens in uncured cooked meats during cooling, and can significantly enhance risk-based management of foodborne illnesses caused by C. perfringens. This software can be downloaded from http://www.ars.usda.gov/Main/docs.htm?docid=25312.
2. One-Step kinetic analysis and predictive model development. Mathematical modeling is frequently used to predict the growth and survival of microorganisms undergoing complex environmental changes, and is an important tool for conducting quantitative risk assessment of foodborne pathogens. Accurate estimation of kinetic parameters is essential to provide microbial growth and survival. ARS researchers at Wyndmoor, Pennsylvania have developed a one-step approach to accurately estimate kinetic parameters by directly constructing predictive models that minimize the global errors. This new approach can significantly improve the accuracy of data analysis and model development. A new software package – IPMP –Global Fit has been developed and offered as a free tool to scientists and risk modelers around the world and can be downloaded from http://www.ars.usda.gov/Main/docs.htm?docid=25355.
3. Growth rates of foodborne pathogens in vegetables. The growth rates of L. monocytogenes, E. coli O157:H7, and Salmonella spp. in lettuce, green pepper, carrot, celery, and broccoli were determined by ARS researchers at Wyndmoor, Pennsylvania. L. monocytogenes was identified to be more of a pathogen of concern than E. coli O157:H7 and Salmonella spp. and carrot was less supportive to the growth of the pathogens among the vegetable varieties. The results indicate that processing controls for fresh-cut produce be focused on preventing the contamination of L. monocytogenes and preventing its growth with proper temperature control.
4. Destruction of Salmonella spp. in liquid egg products. The inactivation rates of Salmonella spp. in egg white (50-53 degree C) and egg yolk (55-62 degree C) with or without salt or sugar (5 and 10%) were determined by ARS researchers at Wyndmoor, Pennsylvania. Salmonella spp. in egg white was more susceptible to heat treatment than in egg yolk. The addition of salt or sugar in liquid egg reduced the inactivation rates of Salmonella spp. After heat treatments, Salmonella spp. was able to grow in egg yolk, but not in egg white, during the subsequent storage at abuse temperature (15 degree C). The results provide information regarding the heat treatment for using in liquid egg processing.
5. Control of Shiga toxin-producing E. coli (STEC) in ground beef and spinach. After exposure to chlorine, low water activity, acid, and starvation stresses, ARS researchers found that the growth behaviors of STEC were different at 8 degree C, but not at 12 and 16 degree C, in ground beef or spinach. The exposure to sub-lethal stresses may also render STEC strains more cytotoxic. The results indicate that control measures should be implemented to avoid the presence of stressed (STEC) in food processing environments and their contamination in meat and produce.
6. Modeling heat resistance of E. coli O157:H7 in beef. Adequate heat treatment destroys E. coli 0157:H7, is the most effective means to guard against the potential hazards and in cooked meat products. Sodium consumption in the American diet is a major public health issue due to its association with hypertension and damaged blood vessels. Consumers these days are increasingly demanding reduced salt in meat products. ARS researchers at Wyndmoor, Pennsylvania defined the heat treatment required to achieve a specific lethality for E. coli O157:H7 in beef supplemented with sodium chloride and sodium pyrophosphate. The predictive model developed can assist food processors to design appropriate thermal processes for the production of beef products without adversely affecting the quality of the product.
7. Performance of Clostridium perfringens cooling models evaluated. After meat products have been cooked to achieve desired lethality for vegetative foodborne pathogens, the heat resistant spores of C. perfringens can germinate and grow in a nutrient rich environment without bacterial competition. FSIS (Food Safety and Inspection Service) regulations require establishments to use models that predict C. perfringens growth to document process compliance. ARS researchers at Wyndmoor, Pennsylvania, compared several models and found that with the exception of the PMP 7.0 broth model, the other three cooling models, i.e., PMIP, the Smith-Schaffner, and the ComBase Perfringens Predictor, are useful and reliable tools for food processors and regulatory agencies for evaluating the safety of cooked/heat-treated, uncured meat and poultry products involved in cooling deviations or developing customized cooling schedules.
Juneja, V.K., Garcia-Davila, J., Lopez-Romero, J., Pena-Ramos, E., Camou, J., Valenzuela-Melendres, M. 2014. Modeling the effects of temperature, sodium chloride and green tea and their interactions on the thermal inactivation of Listeria monocytogenes in turkey. Journal of Food Protection. 77(10):1696-1702.
Fang, T., Huang, L., Liu, L., Mei, F., Chen, J. 2015. Mathematical modeling of growth Salmonella and spoilage microorganisms in raw oysters. Food Control. DOI: 10.1016/j.foodcont.2014.12.036.
Li, C., Huang, L., Hwang, C., Chen, J. 2015. Growth of Listeria monocytogenes in Salmon Roe - a kinetic analysis. Food Control. DOI:10.1016/j.foodcont.2015.06.016.
Juneja, V.K., Cadavez, V., Gonzales-Barron, U., Mukhopadhyay, S. 2014. Modelling the effect of pH, sodium chloride and sodium pyrophosphate on the thermal resistance of Escherichia coli O157:H7 in ground beef. Food Research International. 69:289-304.
Gunduz, G.T., Juneja, V.K., Pazira, F. 2015. Application of ultraviolet-C light on oranges for the inactivation of postharvest wound pathogens. Food Control. DOI: 10.1016/j.foodcont.2015.04.003.
Hwang, C., Juneja, V.K., Huang, L. 2015. Effect of acidified sorbate solutions on the lag phase durations and growth rates of Listeria monocytogenes on meat surfaces. Journal of Food Protection. 78(6):1154-1160.
Huang, L. 2015. Direct construction of predictive models for describing growth Salmonella enteritidis in liquid eggs – a one-step approach. Food Control. DOI: 10.1016j.foodcont.2015.03.051.
Huang, L. 2014. Dynamic determination of kinetic parameters and computer simulation of growth of Clostridium perfringens in cooked beef. International Journal of Food Microbiology. DOI: 10.1016/j.ifoodmicro.2014.11.025.