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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Research Project #422155

Research Project: DEVELOPMENT OF PREDICTIVE MICROBIAL MODELS FOR FOOD SAFETY AND THEIR ASSOCIATED USE IN INTERNATIONAL MICROBIAL DATABASES

Location: Residue Chemistry and Predictive Microbiology Research

2015 Annual Report


4. Accomplishments
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.


Review Publications
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.