NON-TECHNICAL SUMMARY: Chilling of meat and meat products is critical process for controlling growth of foodborne pathogens. Chilling of meat animal carcasses and/or ready to eat meat products using air chilling is a complex process and is widely used process in the meat industry. Specification and evaluation of rate of temperature decline will be essential in controlling the microbiological hazards such as Escherichia coli O157:H7 and Salmonella spp. to insure food safety. The proposed project will develop mathematical models to accurately describe the chilling temperature profiles of the meat and meat products and integrate them with predictive microbiological models to describe the growth of foodborne pathogens during chilling of meat and meat products. These models can be used to design and develop chilling systems that are intrinsically safe, reducing the burden of foodborne illness in the United States.
OBJECTIVES: The specific objectives of the proposal in brief are: a. Development and validation of mathematical models to describe cold air chilling of meat (beef and pork carcasses) and meat products (roast beef and ham) b. Development and validation of predictive models to describe the growth of foodborne pathogens Escherichia coli O157:H7 and Salmonella spp. during chilling of meat animal carcasses and Clostridium perfringens during chilling of processed meat products. Further, integration and validation of mathematical chilling models and predictive microbiological models will be completed c. Incorporation of the developed programs into the HACCP workshops being conducted by the proposing state extension meat specialists for meat processors
APPROACH: Temperature profiles of carcasses at different locations and different depths of the animal carcasses or meat products will be measured under various chilling conditions. Mathematical models will be developed to describe the meat chilling rates using finite element analysis and computational fluid dynamics. These developed models will be validated in processing establishments using real-life scenarios. Microbial predictive models will be developed using growth kinetics derived from microbial growth experiments at different temperatures. These models will be integrated with the mathematical models describing chilling of meat carcasses and products to generate growth of foodborne pathogens on carcasses or meat products. These models will be validated using industry chilling parameters. Fact sheets, easy-to-use tables, etc. will be generated to assist the processors on the use of the predictive models. In addition, videos describing the use of the models will be developed and distributed to the processors and regulators.
PROGRESS: 2004/09 TO 2009/08
OUTPUTS: The results of the research and outreach program were disseminated through publications, outreach modules (video) and short modules on chilling of meat and poultry carcasses and products. A website has been created and the predictive models were incorporated so the personnel from the industry, regulatory agencies and academia can utilize these models for evaluating the safety of their chilling processes. PARTICIPANTS: Harshavardhan Thippareddi, University of Nebraska Jeyamkondan Subbiah, University of Nebraska Vinod Gumudavelli, University of Nebraska Vijay K. Juneja, USDA Agricultural Research Service Lihan Huang, USDA Agricultural Research Service Harry Marks, USDA Food Safety and Inspection Service TARGET AUDIENCES: The target audiences for the research were the fresh and ready to eat meat and poultry processors, personnel in the regulatory agencies and the academia. The predictive models developed and the website containing the predictive models will assist the food safety personnel in evaluating the microbiological safety of meat chilling processes. PROJECT MODIFICATIONS: Not relevant to this project.
IMPACT: 2004/09 TO 2009/08
The predictive models generated will provide the processors, the regulatory agencies and the academia evaluate the safety of meat chilling processes. The models for C. perfringens, E. coli O157:H7 and Salmonella spp. have already been used by the researchers to evaluate the safety of the process deviations specific to processing operations at various meat processing plant. The incorporation of these models into the website allows the processors to evaluate their current chilling processes and also in case of process deviations. These are valuable tools for the industry as well as the regulatory agencies to evalute the safety of the products produced.
PUBLICATIONS (not previously reported): 2004/09 TO 2009/08
1. Juneja, V. K., H. Marks, and H. Thippareddi, 2009. Predictive model for growth of Clostridium perfringens during cooling of cooked ground chicken. Innov. Food Sci. & Emerg. Technol. 10: 260-266.
2. Juneja, V. K., H. Marks and H. Thippareddi. 2008. Predictive model for growth of Clostridium perfringens during cooling of cooked uncured beef. Food Microbiol. 25: 42-55
3. Juneja, V.K., M.V. Melendres, Huang, L., Gumudavelli, V., Subbiah, J., H. Thippareddi 2007. Modeling the effect of temperature on growth of Salmonella in chicken. Food Microbiology, 24: 328-335
4. Juneja, V. K., Valenzuela Melendres. M., Huang, L., Gumudavelli, V., Subbiah, J., and H. Thippareddi. 2007. Modeling the effect of temperature on growth of Salmonella in chicken. Food Microbiol. 24(4):328-335.
5. Juneja, V. K., L. Huang, H. Thippareddi. 2006. Predictive model for growth of Clostridium perfringens in cooked cured pork. Int J Food Microbiol. 110:85-92.
6. Juneja, V. K., M. V. Melendres, L. Huang, J. Subbiah, and H. Thippareddi. 2009. Mathematical modeling of growth of Salmonella in raw ground beef under isothermal conditions from 10 to 45 C. Int. J. Food Microbiol. 131:106-111.
PROGRESS: 2007/10/01 TO 2008/09/30
OUTPUTS: Growth models based on Baranyi's equations and the logistic function were developed. Using a common approach for constructing dynamic models for predicting Clostridium perfringens growth in ready-to-eat uncured beef during cooling, there was no appreciable difference between the models' predictions when the population of cells was within the lag or exponential phases of growth. The developed models can be used for designing safe cooling processes; however, the discrepancies between predicted and observed growths obtained in this study, together with discrepancies reported in other papers using the same, or similar methodology as used in this paper, point to a possible inadequacy of the derived models. In particular, the appropriateness of the methodology depends on the appropriateness of using estimated growth kinetics obtained from experiments conducted in isothermal environments for determining coefficients of differential equations that are used for predicting growth in constantly changing (dynamic) environments. The coefficients are interpreted as instantaneous specific rates of change that are independent of prior history. However, there is no known scientific reason that would imply the truth of this assumption. Incorporating a different, less restrictive assumption, allowing for a dependency on the prior history of cells for these kinetic parameters, might lead to models that provide more accurate estimates of growth. For example, a cooling scenario of 54.4-27 C in 1.5 h, the average predicted and observed log10 relative growths were 1.1 log10 and 0.66 log10, respectively, a difference of 0.44 log10, whereas, when assuming a particular dependency of history, the predicted value was 0.8 log10. More research is needed to characterize the behavior of growth kinetic parameters relative to prior history in dynamic environments. The models will be incorporated into the website being developed for ready-to-eat meat and poultry processors to use to evaluate the risk of potential pathogen growth during cooling processess. PARTICIPANTS: Not relevant to this project. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Not relevant to this project.
IMPACT: 2007/10/01 TO 2008/09/30
The predictive models developed are more sensitive and accurate and provide the RTE meat and poultry processors a means to evaluate the potential risk of C. perfringens growth in meeat and poultry products during processing and in evaluating the safety of a processing deviation.
PUBLICATIONS: 2007/10/01 TO 2008/09/30
Juneja, V. K., H. Marks and H. Thippareddi. 2008. Predictive model for growth of Clostridium perfringens during cooling of cooked uncured beef. Food Microbiol. 25: 42-55
PROGRESS: 2006/10/01 TO 2007/09/30
OUTPUTS: Dynamic predictive models for the growth of Salmonella in chicken have been developed. Control of C. perfringens spore germination and growth during cooling of cooked, ready to eat turkey and injected pork were developed. PARTICIPANTS: Juneja, V.K., M.V. Melendres, Huang, L., Gumudavelli, V., Velugoti, P. R., Bohra, L. K., Juneja, V. K., L. Rajagopal, V. Juneja and H. Thippareddi. TARGET AUDIENCES: Meat and poultry processors PROJECT MODIFICATIONS: None
IMPACT: 2006/10/01 TO 2007/09/30
The models developed and the safe cooling regimes from the C. perfringens research can be used by the industry to design and develop safe processing conditions and processes for poultry storage and cooling of ready to eat turkey and pork (hams).
PUBLICATIONS: 2006/10/01 TO 2007/09/30
1. Velugoti, P. R., L. Rajagopal, V. Juneja and H. Thippareddi. 2007. Use of calcium, potassium, and sodium lactates to control germination and outgrowth of Clostridium perfringens spores during chilling of injected pork. Food Microbiol. 24(7-8): 687-694.
2. Velugoti, P. R., Bohra, L. K. Juneja, V. K., and H. Thippareddi. 2007. Inhibition of Germination and Outgrowth of Clostridium perfringens Spores by Lactic Acid Salts during Cooling of Injected Turkey J. Food Prot. 70(4): 923-929
3. Juneja, V.K., M.V. Melendres, Huang, L., Gumudavelli, V., Subbiah, J., Thippareddi, H. 2007. Modeling the effect of temperature on growth of Salmonella in chicken. Food Microbiology, 24: 328-335
PROGRESS: 2005/10/01 TO 2006/09/30
The fabrication of a model carcass chilling system (wind tunnel) has been completed. Air velocity, temperature and relative humidity is controllable within the system. The system is ready to evaluate the chilling rate and uniformity of chilling for different meat products under various chilling conditions. An integrated mathematical model of heat transfer and temperature-dependent bacterial growth was developed to validate the safety of cooked hams during air blast chilling. Heat transfer through a cooked ham was mathematically modeled and analyzed with a finite element method. Response of bacteria to temperatures was quantitatively described using predictive microbiology. The cumulative effect of temperature history on the bacterial growth was taken into account in the model.
IMPACT: 2005/10/01 TO 2006/09/30
The integrated model of heat transfer and bacterial growth provided valuable insights into air blast chilling of cooked meats for risk assessment of the final products. The development of integrated validated chilling and microbial growth predictive models can support the decision making process for the food industry, regulatory agencies (USDA-FSIS, etc), and researchers and educators at land grant universities to evaluate the microbiological risk of chilling processes. It can also be used to evaluate adequacies of the refrigeration capabilities and design them to control foodborne pathogens during chilling, thus building food safety into the process.
PUBLICATIONS: 2005/10/01 TO 2006/09/30
1. Wang, L. J., Amezquita, A., Weller, C. L. 2006. A mathematical model for the validation of safe air-blast chilling of cooked hams. Transaction of the ASABE. 49(5):1437-1446.
2. Ryland, K., A. Amezquita, L. Wang and C.L. Weller. 2006. Estimation of heat transfer coefficients of cooked boneless ham. RURALS. http://digitalcommons.unl.edu/rurals/vol1/iss1/
3. Amezquita, A., L. Wang, H. Thippareddi, D. Burson and C.L. Weller. 2006. Temperaturas en Salas de Deshuese y Porcionado de Carne para la Inocuidad Alimentaria , G1573S. University of Nebraska-Lincoln Extension, Lincoln, NE.
4. Wang, L. J. and Sun, D. W. 2005. Heat and Mass Transfer in Thermal Food Processing, Chapter 2, in: Sun, D. W. (editor), Thermal Food Processing: Modeling, Quality Assurance and Innovations. Marcel Dekker, Inc. USA: New York. pp. 33-69.
5. Wang, L. J. and Weller, C. L. 2005. Thermophysical Properties of Frozen Foods, Chapter 5, in: Sun, D. W. (editor), Handbook of Frozen Food Processing and Packaging. Marcel Dekker, Inc. USA: New York. pp. 101-125.
PROGRESS: 2004/10/01 TO 2005/09/30
The project involves development and validation of predictive models for the growth of foodborne pathogens on meat animal carcasses such as beef, swine and poultry. To conduct this research, a self contained Biosafety Level II chamber that can be programmed to several dynamic temperature profiles has been developed. This chamber will allow us to evaluate safety of animal carcass chilling profiles being used by the industry.
IMPACT: 2004/10/01 TO 2005/09/30
The validated predictive models will assist meat processors as well as regulatory agencies evaluate microbiological safety of the chilling rates employed by the industry.
PUBLICATIONS: 2004/10/01 TO 2005/09/30
We expect to publish research in the next year, 2006.
PROGRESS: 2003/10/01 TO 2004/09/30
Research has been started and reports will be generated in a years time.
IMPACT: 2003/10/01 TO 2004/09/30
The predictive models generated will assist meat processors evaluate safety of their meat chilling processes and reduce the risk of foodborne illness.
|Effective start/end date||9/15/04 → 8/31/09|
- U.S. Department of Agriculture: $599,916.00