Location: Microbial and Chemical Food Safety
2023 Annual Report
Objectives
Objective 1: Utilize one-step dynamic modeling and Bayesian analysis for prediction of growth and survival of foodborne pathogens throughout the supply chain.
Objective 2: Utilize logistic modeling for determination of growth and no-growth boundary of high-risk pathogens in ready-to-eat foods.
Objective 3: Utilize finite element analysis for prediction of bacterial growth and survival during food processing.
Objective 4: User-friendly tools for predictive modeling.
Approach
A new dynamic approach will be developed and optimized to simulate and predict the growth and survival of major foodborne pathogens in meat and poultry products exposed to complex changes in the environmental conditions during heating, cooling, and storage. The research will utilize an advanced computational framework and probabilistic Monte Carlo simulation to analyze the dynamic changes in the population of foodborne pathogens, and will develop an expert decision support system to assist the food industry and regulatory agencies in making scientifically sound food safety decisions for products of concern. This project will continue to improve and upgrade the USDA Integrated Pathogen Modeling Program (IPMP) for data analysis, and develop a new data analysis tool, IPMP Global Fit, that minimizes the global residual errors for curve-fitting of growth and survival curves.
Progress Report
For Objective 1, a study was conducted to investigate the effect of curing agent (nitrite, NaNO2) and curing accelerator (erythorbate) on the growth of Clostridium perfringens (C. perfringens) from spores in cooked cured beef exposed to a long cooling process (5 hours from 54.4 deg. C to 26.7 deg. C and another 10 hours from 26.7 deg. C to 7.2 deg. C), as required in the USDA FSIS Appendix B, Option 1.3. The study was conducted in both Shahidi-Ferguson Perfringens agar (SFP) and ground beef. Samples mixed with different levels of nitrite (100-200 ppm), erythorbate (0 to 574 ppm), sodium tripolyphosphate (STPP, 0 to 0.5%), and salt (1-3%) were first subjected to a curing process at 4 deg. C for 24 hours. After curing, the samples were heated to 80 deg. C to simulate cooking and then programmatically cooled according to the cooling schedule of the USDA FSIS Appendix B, Options 1.3. The samples were also programmatically cooled to and held at 46 deg. C, the optimum growth temperature for C. perfringens, to observe the interactive effects of nitrite, erythorbate, STPP, and salt on its growth. The experimental results showed that STPP and salt at proper concentrations could effectively inhibit the growth of C. perfringens even at the optimum growth temperature, while erythorbate, used as a curing accelerator, provides protection to germinated cells and limits their effectiveness. A mathematical model was developed to define the growth boundaries of C. perfringens as affected by combined effects of nitrite, erythorbate, STPP, and sodium chloride (NaCl). It was also observed that the lag time of C. perfringens in SFP agar was much longer than that in cooked beef. Therefore, experiments were conducted to study the effect of amino acids and other spore germinants on growth of C. perfringens from spores. Results showed that meat peptone and potassium chloride added to the agar medium as spore germinants could significantly reduce the lag time for C. perfringens. Therefore, additional experiments were conducted to develop a solid laboratory agar medium for use in lieu of meat samples for studying the germination, outgrowth, and multiplication of C. perfringens from spores, which would make it easier and more efficient to study the effect of different antimicrobials for inhibition of this pathogen in cured meats during cooling.
For Objective 2, a study was conducted to develop a growth probability model for C. perfringens in cured meat containing salt and sodium tripolyphosphate (STPP). Ground beef was added with 200 ppm nitrite, 1.0-4.0% NaCl, and 0.25-1.5% STPP and inoculated with C. perfringens spores. Five grams of meat were vacuum-packed in bags and heated in 70 deg. C water bath for 30 min. Ten bags from each treatment were incubated at 46 deg. C for 48 h. The populations of C. perfringens before and after incubation were enumerated to determine the growth event of C. perfringens (an increase of greater than 1.0 log cfu/g population after incubation) in each bag. The growth event data were fitted to a logistic model as a function of the concentrations of salt, STPP, and their interaction. The resulting model was acceptable based on the indices for the model’s predictive ability and indicated that salt and STPP were significant factors affecting the growth probability of C. perfringens, in which the increase of salt or STPP concentrations reduced the growth probability. The model can be used to predict the growth probabilities of C. perfringens in cured meat containing 1-4% salt and 0.25-1.5% STPP and indicates the growth/no-growth boundaries of C. perfringens in cured meat are at 2% salt-1.5% STPP, 3% salt-1.25%, STPP, and 4% salt-0.8% STPP. The model could be used to predict the growth probability of C. perfringens as affected by salt and STPP concentrations and for selecting the additive concentrations that reduce the growth probability of C. perfringens in cured meat. The use of high salt and STPP concentrations to achieve no growth of C. perfringens in cured meat may limit their applications. Therefore, for poultry products, the growth probability of C. perfringens was examined with the addition of sodium lactate and sodium diacetate, two permitted preservatives for meat and poultry products. Results have shown that the addition of 1.5% lactate and 0.2% diacetate achieve no growth of C. perfringens in cooked cured chicken meat at 1% salt and 0.5% STPP.
For Objective 3, a study was conducted to investigate the effect of temperature on the thermal properties of different meats using the plane-source method. These properties are needed for numerical analysis of heat transfer to simulate the temperature history during heating or cooling of solid foods. The thermal physical properties of different raw ground meats (beef, pork, chicken, and turkey), chicken breast, and cured ground beef and ground pork were measured using the C-Therm (TM) thermal property analyzer between 5 and 60 deg. C. A finite volume method was used to numerically solve a partial differential equation (PDE) governing unsteady-state heat conduction with its initial conditions and convective surface boundary conditions. The Internation Mathematics and Statistics Library (IMSL) was applied to solve the PDE to simulate the dynamic heating profile in meat balls (ground beef and ground chicken) heated in an oven of 135 or 150 deg. C. The simulation results showed that the temperature histories at the geometric center of meat balls could be accurately simulated. The numerical simulation model can be used in combination with the growth kinetic models and thermal inactivation models to predict the growth and survival of foodborne pathogens during food processing, distribution, and storage. In addition, the D and z values of several foodborne pathogens, e.g., Salmonella, Escherichia coli (E. coli) O157:H7, Uro-Pathogenic E. coli (UPEC) were evaluated using the one-step method.
For Objective 4, we have been evaluating the best technology platform for online delivery of our predictive microbiology computational technology. We have evaluated different frameworks for online computing in a platform outside of the USDA secured network. One alternative is to use the PyScript framework or Streamlit framework in a commercial cloud provider. A DotNet application based on C# was also considered.
Per an interagency agreement with USDA FSIS, a study was conducted to evaluate the safety of liquid egg yolk production, which involves an enzymatic treatment process using phospholipase a2 to improve the emulsification capability and thermal stability of end products. The treatment, occurring at temperatures between 20 and 50 deg. C for extended time, may allow foodborne pathogens, such as Bacillus cereus to grow. B. cytotoxicus, a new species in the B. cereus group, was chosen for this study due to its high thermotolerance. Experimental results showed that this pathogen could grow prolifically and quickly at 50 deg. C, a common condition used in the enzymatic treatment process used by the egg industry. Mathematical models were developed to describe its growth behaviors over the entire biokinetic temperature range. This study also identified that this pathogen was very heat-resistant and may survive the common thermal pasteurization conditions used in the industry to kill other foodborne pathogens, such as Salmonella and Listeria monocytogenes. The study further discovered that an enzymatic treatment temperature of 55 deg. C could not only effectively inhibit the growth of B. cytotoxicus and other species in the B. cereus group but also inactivate other pathogens such as Salmonella and Listeria monocytogenes often found in raw eggs. The results of this study have been communicated to USDA FSIS.
A study was conducted to evaluate the safety of cold smoked salmon concerning the growth boundary of Listeria monocytogenes. Logistic regression was used to analyze the growth data extracted from ComBase (116 records, 465 data points) to develop a shelf-life boundary for Listeria (L.) monocytogenes according to 7 different control thresholds ranging from 0 to 3 log CFU/g in relative growth, representing different degrees of tolerance to this pathogen in cold smoked salmon under different food safety regulation systems. The model was validated and showed greater than 89% of true negative rate for not exceeding the control thresholds. A dynamic method was then developed to predict the growth probabilities under fluctuating temperature conditions. The result of this study suggested that storage time and temperature could be used to predict the growth of L. monocytogenes in cold smoked salmon and to reduce listeriosis using a risk-based strategy.
Accomplishments
