2012 Annual Report
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.
Studies examining the survival of Listeria monocytogenes on cooked ham surface-treated with lactic acid were completed. Experiments on the growth of acid-stressed L. monocytogenes on cooked ham and growth behaviors of L. monocytogenes in simulated smoked salmon and meat salad containing potassium sorbate are in progress. Also, experiments to determine the germination and outgrowth of Clostridium perfringens spores during cooling of cooked pork products were completed and a predictive model based on the product composition factors is being developed.
Experiments were conducted to determine the effect of pH (4.5 – 8.5), water activity (0.95 – 0.99), and incubation temperature (7 – 46C) on the growth kinetics of a three-strain mixture of Escherichia coli O104:H4 in broth. Mathematical models to predict generation times, lag phase durations, and maximum population densities with pH, water activity and temperature as controlling factors are being developed.
Research was conducted to investigate the growth behaviors of non-O157 Shiga toxin-producing E. coli (STEC) in ground beef and spinach leaves, Salmonella and L. monocytogenes in processed liquid eggs, Cronobacter sakazakii in reconstituted powdered infant formula, L. monocytogenes in fresh-cut cantaloupe, and E. coli O104 in mung bean sprouts. Growth curves of these foodborne pathogens in various food matrixes were or will be used to develop mathematical models that predict the bacterial growth under different temperature conditions. New models and algorithms were developed. Research was also conducted to develop a simplified computer model to simulate the heating process during open-flame grilling of non-intact-beef steaks. A finite element method was used to analyze the heat transfer process and simulate the temperature distribution within the steaks during open flame grilling. This computer model can be used to evaluate the effectiveness of a cooking process on survival of E. coli O157:H7 in non-intact-beef steaks, and develop more effective grilling methods to ensure elimination of E. coli O157:H7.
4. Thermal death time model for Salmonella in chicken. Adequate cooking time and temperature ensures safety against pathogens in ready-to-eat foods while minimizing quality losses. ARS reseachers at Wyndmoor, Pennsylvania, defined the heat treatment required to achieve a specified lethality for starvation-stressed Salmonella in ground chicken supplemented with natural antimicrobials, cinnamaldehyde and carvacrol. The thermal death predictive model for the pathogen, which can predict the D-values for any combinations of the factors that are within the range of those tested, was developed. Using this model for Salmonella, food processors can design thermal processes for the production of a safe chicken product with extended shelf life. 5. Modeling heat resistance of Listeria monocytogenes in ground beef. Adequate heat treatment destroys L. monocytogenes and is the most effective means to guard against the potential hazards in cooked meat products. Due to public health concerns associated with high salt levels in the diet, consumers these days are increasingly demanding processed meats with reduced salt levels. ARS researchers at Wyndmoor, Pennsylvania, defined reduced heat treatment required to achieve a specified lethality for L. monocytogenes in beef supplemented with salt and apple polyphenols (antioxidants). The predictive model will assist processors to develop beef products with reduced salt and apple polyphenols. 6. Predictive model for Listeria monocytogenes in ready-to-eat (RTE) meat. Consumption of contaminated ready-to-eat meat may cause bacterial foodborne illnesses. ARS researchers at Wyndmoor, Pennsylvania, developed models to describe the growth of L. monocytogenes on cooked ham surface-treated with lactic acid. These models will help the manufacturers to select a suitable lactic acid treatment to improve the safety of their food products. 7. Proper means for cooling of cooked beef. Inadequate rate and extent of cooling is a major food safety problem. ARS researchers at Wyndmoor, Pennsylvania, determined the germination and outgrowth of Clostridium perfringens spores during cooling of cooked beef products. A predictive model for growth of C. perfringens during cooling of cooked beef products based on the product composition factors was developed. Also, growth of the pathogen was quantified in ten commercially prepared acidified beef, pork, and poultry products. The growth data/predictive model on the safe cooling rate of meat will provide the food industry means to assure that cooked products remain pathogen-free.
Velugoti, P.R., Bohra, L.K., Juneja, V.K., Huang, L., Subbiah, J., Wessling, A.L., Thippareddi, H. 2010. Dynamic model for predicting growth of salmonella spp. in ground sterile pork. Food Microbiology. 28:796-803.
Hwang, C., Sheen, S., Juneja, V.K. 2011. Effects of lactate on the growth of Listeria monocytogenes, Escherichia coli 0157:H7 and Salmonella SPP., in cooked ham at refrigeration and abuse temperatures. Food and Nutrition Sciences. 2(5):464-470.
Huang, L., Hwang, C., Phillips, J.G. 2011. Evaluating the effect of temperature on microbial growth rate - the Ratkowsky and a Belehrádek type models. Journal of Food Science. 76(8):547-557.
Huang, L., Hwang, C., Phillips, J.G. 2011. Effect of temperature on microbial growth rate - thermodynamic analysis, the arrhenius and eyring-polanyi connection. Journal of Food Science. 76:553-560.
Juneja, V.K., Huang, L., Yan, X. 2011. Thermal inactivation of foodborne pathogens and the USDA pathogen modeling program. Journal of Thermal Analysis. 106(1):191-198.
Juneja, V.K., Yadav, A.S., Hwang, C., Sheen, S., Mukhopadhyay, S., Friedman, M. 2012. Kinetics of thermal destruction of Salmonella in ground chicken by containing trans-cinnamaldehyde and carvacrol. Journal of Food Protection. 75(2):289-296.
Huang, L., Hwang, C. 2012. In-package pasteurization of ready-to-eat meat and poultry product. In: Kerry, J.P., editor. In Advances in meat, poultry and seafood packaging. Philadelphia, PA: Woodhead Publishing Ltd. 313:320.
Huang, L. 2012. A simplified method for numerical simulation of gas grilling of non-intact beef steaks to elimate Escherichia coli O157:H7. Journal of Food Engineering. 113:380-388.
Gunes Altuntas, E., Kocan, D., Cosansu, S., Ayhan, K., Juneja, V.K., Materon, L. 2012. Determination of antibiotic resistance pattern and bacteriocin sensitivity of Listeria monocytogenes strains isolated from different foods in turkey. Food and Nutrition Sciences. 3:363-368.
Singh, A.A., Korasapati, N.R., Juneja, V.K., Subbiah, J., Fronging, G., Thippareddi, H. 2011. Dynamic predictive model for the growth of salmonella spp. in liquid whole egg. Journal of Food Science. 76(3)225-232.