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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Publications at this Location » Publication #304564

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

Title: Mathematical modeling of growth Salmonella and spoilage microorganisms in raw oysters

Author
item Fang, Ting - Fujian Agricultural & Forestry University
item Huang, Lihan
item Liu, Lijun - Fujian Agricultural & Forestry University
item Mei, Fan - Fujian Agricultural & Forestry University
item Chen, Jinquan - Fujian Agricultural & Forestry University

Submitted to: Food Control
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/14/2014
Publication Date: 1/28/2015
Publication URL: http://handle.nal.usda.gov/10113/60304
Citation: 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.

Interpretive Summary: Fresh oysters are consumed by many consumers around the world. Grown under water, however, fresh oysters can carry human pathogens that can cause foodborne infections in consumers. The objective of this research was to study the growth kinetics of Salmonella in fresh shucked oysters and develop mathematical models to predict the growth of this microorganism during storage. The results of this study can be used to conduct risk assessments of fresh shucked oysters and predict microbial shelf-life during distribution.

Technical Abstract: The main objective of this study was to develop primary and secondary models to describe the growth of Salmonella as well as background microorganisms in fresh shucked oysters. The cocktail of two Salmonella serotypes, S. Typhimurium (CICC22956) and S. Enteritidis (CICC21482), was inoculated to raw oyster flesh and incubated at temperatures of 4, 8, 12, 16, 20, 25, 30, 33, 37, 40, and 43 deg. C. Growth Salmonella was observed at all temperatures, except at 4 deg. C. The background microorganisms grew at all temperatures. All growth curves clearly exhibited lag, exponential, and stationary phases, and were analyzed using the Huang growth model. To evaluate the effect of temperature on bacterial growth, three secondary models (Ratkowsky square-root, Huang square-root, and Cardinal parameter models) were used to analyze the specific growth rates. The data analysis and curve-fitting was performed using IPMP 2013, a free predictive microbiology software tool developed by USDA ARS. The results of analysis showed the Huang model fit the growth curves well as the primary model. For both Salmonella and background microorganisms, the Cardinal parameters estimated the specific rates at low temperature and therefore, not recommended as the secondary model. Both Ratkowsky and Huang square-root models fitted the data of specific growth rates well and with similar accuracy. For Salmonella, the nominal minimum temperature estimated by the Ratkowsky square-root model was 1.87 deg. C. The minimum temperature estimated by the Huang square-root model was 4.99 deg. C. Therefore, the Huang square-root model is recommend as the secondary model for Salmonella. For background microorganisms, on the hand, the Ratkowsky square-root was recommended as the secondary. For both Salmonella and background microorganisms, the logarithms of the lag phase could be expressed as linear function of the logarithms of specific growth rates. With the primary and secondary models developed in this study, the growth of Salmonella and background microorganisms in fresh shucked oysters can be estimated. The results of this study can be used by the food retailers and regulatory agencies to estimate the microbial shelf-life of fresh shucked oysters.