Progress 10/01/03 to 09/30/06
Outputs
The microbiological safety of food products is important to consumers around the globe. Although first-order models have been used to describe microbial inactivation during cooking, both linear and non-linear survival curves have been reported. In this project, we a) examined the inactivation behavior of Salmonella spp., Listeria monocytogenes and Escherichia coli O157:H7 in ground turkey breast, turkey thigh, pork shoulder and beef when exposed to isothermal and non-isothermal cooking temperatures, b) evaluated the ability of the Weibull distribution to predict pathogen inactivation under non-isothermal conditions, c) evaluated pathogen inactivation in ground meat patties exposed to industry style cooking conditions, and d) investigated the ability of a fluorescent protein complex, R-phycoerythrin (PE), to serve as a marker to indicate pathogen destruction during processing. Ground pork, turkey breast, turkey thigh and beef were inoculated with pathogens and cooked
isothermally (50-72C) and non-isothermally (54, 60 and 66C at a rate of 5 and 10C/min) to determine reduction in counts. Surviving pathogens were enumerated at intervals throughout each cooking process. Isothermal survival curves were described by the both the Weibull distribution and its simplified linear form (n=1), log S=-bt, to determine pathogen characteristics. Predicted and experimental values were compared to determine the relationship between isothermal and non-isothermal data and verify fitness of the Weibull model. Non-linearity was observed when experimental and predicted isothermal survival curves of Salmonella spp. in turkey breast, turkey thigh and pork were graphed. The Weibull distribution described Salmonella inactivation better than its simplified linear form at temperatures of 58C and above. The n values were greater than one (1.2-2.0) for most curves. A linear model better predicted isothermal inactivation of Salmonella spp. and E. coli in ground beef at 58C and
above. A strong positive correlation was found between cooking temperature, lethality, and pathogen destruction in the ground meat patties. A weaker correlation was observed between R-PE fluorescence and pathogen inactivation. Experiments in ground turkey, pork and beef patties indicated that recommended safe harbor temperatures and hold times are insufficient to meet lethality performance standards for Salmonella inactivation published in Title 9 Code of Federal Regulations.
Impacts
Successful completion of this study will yield a computer model that can be used to compare the effect of different nonisothermal temperature histories on microbial destruction. Processors could use these models to determine the efficacy of any new/modified thermal process. A better understanding of microbial lethality and better process control will ultimately lead to a safer food supply, fewer illnesses and deaths, and reduce economic losses to the food industry.
Publications
- Head, K.L. 2006. Traditional and non-linear predictive modeling of Salmonella spp. inactivation in ground pork and turkey during isothermal and non-isothermal cooking conditions. M.S. Thesis, University of Idaho, Moscow. 85 pp.
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Progress 01/01/05 to 12/31/05
Outputs
It is important to understand the thermal inactivation kinetics of pathogens when designing safe cooking processes for meat products. Although first-order models are usually used to describe microbial inactivation during cooking, both linear and non-linear survival curves have been reported. Our objective was to evaluate the ability of the Weibull distribution to predict the inactivation of Salmonella spp. in ground beef, turkey and pork cooked under non-isothermal conditions. Ground turkey thigh (5.09% fat, pH 6.45), turkey breast (0.47% fat, pH 6.04) and pork (17.04% fat, pH 6.36) were inoculated with an 8 strain cocktail of Salmonella spp. The meat was cooked isothermally at 50, 54, 58, 62 and 66C, while non-isothermal cooking trials were performed at two heating rates (5 or 10C/min) to 54, 60 and 66C. Surviving Salmonella were enumerated at intervals throughout each cooking process. Isothermal survival curves were described by the Weibull distribution, Log S (t) =
-b (T) tn(T), and its simplified form as a linear equation (n=1), log S=-bt. Parameter estimates (b and n) were found under isothermal cooking conditions. The model was validated under isothermal and nonisothermal conditions by making comparisons to the experimental data. The nonisothermal predictions were made using b and n values predicted from isothermal data. Non-linearity was observed when experimental and predicted isothermal survival curves of Salmonella spp. in the 3 ground meats were graphed. The average absolute difference was obtained for both the Weibull predictive curve and the linear model to determine which demonstrated a tighter fit to the observed isothermal data. The Weibull distribution described pathogen inactivation better than its simplified linear form at temperatures of 58C and above. The n values were greater than one (1.2-2.0) for most curves. The temperature dependence of b values was supported by previous studies. There was good agreement between
experimental and predicted non-isothermal survival curves, although the model over-predicted the destruction of Salmonella spp. in turkey thigh and pork at 54C for both heating rates. Mathematical models that take into account the potential for non-linear survival curves may more accurately predict microbial inactivation and prevent undercooking. In future work, we will investigate the use of other fundamental engineering models to describe microbial lethality.
Impacts
Successful completion of this study will yield a computer model that can be used to compare the effect of different nonisothermal temperature histories on microbial destruction. Processors could use these models to determine the efficacy of any new/modified thermal process. A better understanding of microbial lethality and better process control will ultimately lead to a safer food supply, fewer illnesses and deaths, and reduce economic losses to the food industry.
Publications
- Smith, D.M., Head, K.L., Hendrix, K.M., and Takhar (Singh), P.P. 2005. Predictive modeling of Salmonella spp. inactivation in ground turkey and pork during cooking. Abstract 89F-32. Abstracts of the Institute of Food Technologists Annual Meeting, New Orleans, LA, July 17-20, 2005.
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Progress 01/01/04 to 12/31/04
Outputs
Replicated isothermal cooking trials were conducted on ground beef, turkey thigh, turkey breast and pork inoculated with Salmonella spp. or E. coli O157:H7 at 50-66C, and L. monocytogenes at 54-72C. Nonisothermal cooking trials were performed at two heating rates (5 or 10C/min) to final temperatures of 54, 60 and 66C for Salmonella spp. or E. coli, and to final temperatures of 54, 60, 66 and 70C for L. monocytogenes using a programmable thermocycler to control heating profiles. Bacterial counts were determined during each process. Isothermal survival curves for each pathogen were described by the Weibull distribution and its simplified form as a linear equation. The experimental and predicted isothermal survival curves of Salmonella spp., E. coli O157:H7 and L. monocytogenes in the four ground meats were graphed. In ground beef, the isothermal experimental data for all pathogens exhibited linear trends with slight non-linearity at lower temperatures. Non-linearity was
observed as local concave down regions at 50 and 54C for Salmonella spp.; 50 and 58C for E. coli O157:H7; and 62C or lower for L. monocytogenes. Since the data was primarily linear, it was approximated by performing linear regression (with zero y intercept) between temperature and log S values. Thus, n of the Weibull equation was taken as 1. Experimental b values were defined as the slope of the linear regression curves of isothermal data. Temperature dependence of b values was fitted using an empirical equation between experimental b values and temperature for each pathogen. There was strong temperature dependence of experimental and predicted b values indicating a higher rate of microbial inactivation at higher temperatures. The nonisothermal survival curves of Salmonella spp., E. coli O157:H7 and L. monocytogenes were obtained by solving the differential form of the Weibull equation with a program written in Mathematica. With a few exceptions, there was good agreement between
experimental and predicted non-isothermal survival curves for all three pathogens. The model under-predicted the destruction of E. coli O157:H7 at 54C for both heating rates. This can be attributed to smaller magnitudes of predicted b values at lower temperatures. The results indicate that non-isothermal survival curves of Salmonella spp., E. coli O157:H7 and L. monocytogenes in ground beef can be predicted with sufficient accuracy from isothermal data using the linear form of the Weibull equation. Analyses for Salmonella spp. inactivation in ground turkey and pork are in progress. Initial analysis of isothermal data suggests that the Weibull distribution describes pathogen inactivation better than its simplified linear form. For most isothermal tests, n values were found to be greater than one (1.2-2.0) for these meats. The b and n values predicted by the non-linear program were sensitive to the initial guess values. Multiple solutions of b and n values were predicted by the
non-linear program. Further analysis showed that in contrast to common assumption made in Weibull model-based microbial studies, b and n values were not completely independent of each other.
Impacts
Successful completion of this study will yield a computer model that can be used to compare the effect of different nonisothermal temperature histories on microbial destruction. Processors could use these models to determine the efficacy of any new/modified thermal process. A better understanding of microbial lethality and better process control will ultimately lead to a safer food supply, fewer illnesses and deaths, and reduce economic losses to the food industry.
Publications
- Gurajala, M.M., Hendrix, K., Smith, D.M. and Singh, P.P. 2004. Predicting the inactivation of Salmonella spp., Escherichia coli and Listeria monocytogenes in ground beef under nonisothermal cooking conditions. Abstract 67E-21. Abstracts of the Institute of Food Technologists Annual Meeting, Las Vegas, NV, July 12-16.
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Progress 10/01/03 to 12/01/03
Outputs
Ground beef and turkey were obtained from a local supplier. Proximate composition and pH were determined. Meat was vacuum packaged, irradiated at 10 kGy, and stored at -20C. Irradiated meat was checked for sterility. The Salmonella cocktail contains S. Thompson (FSIS 120), S. Enteritidis phage type 13A (H 3527), S. Enteritidis phage type 4 (H 3502), S. Typhimurium DT104 (H 3380), S. Hadar (MF 60404), S. Copenhagen (8454), S. Montevideo (FSIS 051) and S. Heidelberg (F5038BG1). The Listeria cocktail contains eight strains of different ribotype patterns isolated from retail ground meat. Ground meat was inoculated to contain about 10-9 CFU/g. Thermal inactivation experiments under isothermal conditions are being performed in a water bath between 50 to 75C. Nonisothermal inactivation experiments are being performed in a programmable thermocycler using cooking protocols based on USDA safe harbor guidelines using controlled heating and cooling rates. The equation parameters
of Salmonella, L. monocytogenes and E. coli O157:H7 in beef and turkey determined in the isothermal experiments will be used to devise a systematic procedure for predicting microbial inactivation in nonisothermal processes using the Weibull distribution (log S = -b tn). The parameters, b and n, of the Weibull distribution will be estimated by performing nonlinear regression of the equation with experimental data on microbial decay collected at isothermal temperatures. The parameters obtained from the isothermal experiments will be used to solve the equation for nonisothermal microbial decay.
Impacts
Successful completion of this study will yield a computer model that can be used to compare the effect of different nonisothermal temperature histories on microbial destruction. Processors could use these models to determine the efficacy of any new/modified thermal process. A better understanding of microbial lethality and better process control will ultimately lead to a safer food supply, fewer illnesses and deaths, and reduce economic losses to the food industry.
Publications
- No publications reported this period
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