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Predictive model for growth of Clostridium perfringens during cooling of cooked ground pork
Authors:Vijay K. Juneja  Harry Marks  Harshavardhan H. Thippareddi
Affiliation:1. Microbial Food Safety Research Unit, Eastern Regional Research Center, Agricultural Research Service, U.S. Department of Agriculture, 600 E. Mermaid Lane, Wyndmoor, PA 19038, United States;2. U.S. Department of Agriculture, Food Safety Inspection Service, 14th and Independence S.W., Washington, DC 20250, United States;3. Department of Food Science and Technology, University of Nebraska-Lincoln, Lincoln, NE 68583, United States;1. Department of Microbiology, Osaka City Institute of Public Health and Environmental Sciences, 8-34 Tojo-cho, Tennoji-ku, Osaka 543-0026, Japan;2. Department of International Health, Institute of Tropical Medicine, Nagasaki University, Nagasaki, 1-12-4 Sakamoto, Nagasaki-shi, Nagasaki 852-8523, Japan;3. Department of Veterinary Science, Graduate School of Life and Environmental Sciences, Osaka Prefecture University, 1-58 Rinku-Orai-Kita, Izumisano-shi, Osaka 598-8531, Japan;1. College of Food Science and Technology, Henan Agricultural University, No.95 Wenhua Road, Zhengzhou, 450002, PR China;2. U.S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, 600 E. Mermaid Lane, Wyndmoor, PA, 19038, USA;1. Shenzhen Key Lab for Food Biological Safety Control, Food Safety and Technology Research Center, Hong Kong PolyU Shenzhen Research Institute, Shenzhen, PR China;2. State Key Lab of Chirosciences, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region;3. Department of Microbiology and Molecular Genetics, Medical College of Wisconsin, Milwaukee, WI, USA;1. Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493, Japan;2. Department of Bioscience, Faculty of Applied Bioscience, Tokyo University of Agriculture, 1-1-1 Sakuragaoka, Setagaya-ku, Tokyo 156-8502, Japan;3. Rigaku Corporation, 3-9-12 Matsubara-Cho, Akishima 196-8666, Japan;4. Department of Nutritional Science and Food Safety, Faculty of Applied Bioscience, Tokyo University of Agriculture, 1-1-1 Sakuragaoka, Setagaya-ku, Tokyo 156-8502, Japan
Abstract:A predictive dynamic model for Clostridium perfringens spore germination and outgrowth in cooked pork products during cooling is presented. Cooked, ground pork was inoculated with C. perfringens spores and vacuum packaged. For the isothermal experiments, all samples were incubated in a water bath stabilized at selected temperatures between 10 and 51 °C and sampled periodically. For dynamic experiments, the samples were cooled from 54.4 to 27 °C and subsequently from 27 to 4 °C for different time periods, designated as x and y hours, respectively. The growth models used were based on a model developed by Baranyi and Roberts (1994), which incorporates a constant, referred to as the physiological state constant, q0. The value of this constant captures the cells' history before the cooling begins. To estimate specific growth rates, data from isothermal experiments were used, from which a secondary model was developed, based on a particular form of Ratkowsky's 4-parameter equation. Using the data from dynamic experiments and the Ratkowsky model, an optimal value of q0 (=0.01375) was derived minimizing the mean square error of predictions. However, using this estimate, the model had a tendency to over-predict relative growth when there was observed small amounts of relative growth, and under-predict relative growth when there was observed large relative growth. To provide more fail-safe estimates, rather than using the derived value of q0, a value of 0.04 is recommended. The predictive model with this value of q0 would provide more fail-safe estimates of relative growth and could aid producers and regulatory agencies with determining disposition of products that were subjected to cooling deviations.Industrial relevanceSafe time/temperature for cooling of cooked pork is very important to guard against the pathogen in cooked products. Predictive model will assist industry to determine compliance with regulatory performance standards and to ensure microbiological safety of cooked products.
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