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Monte Carlo analysis of the product handling and high-pressure treatment effects on the Vibrio vulnificus risk to raw oysters consumers

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https://ir.library.oregonstate.edu/concern/articles/gh93h1069

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  • A Monte Carlo procedure considering the variability in oyster handling from harvest to raw consumption estimated reductions in the number of Vibrio vulnificus induced septicemia cases achieved by high-pressure processing (HPP). The calculations yielded pathogen load distributions in raw oysters from harvest to consumption. In the warm season, 2-6 min treatments at 250 MPa and 1°C would lower the predicted number of septicemia cases associated with raw oyster consumption from 4,932 to less than four per 100 million consumption events (95% confidence). This study highlighted that HPP conditions should be selected according to the seasonal pathogen load and environment temperature. Finally, the procedure emphasized that the variability in the V. vulnificus population at harvest, before and after HPP treatments, reflecting in part the microbiological quantification methods used, significantly affected the estimated number of septicemia cases. Therefore, improving microbiological quantification should provide better predictions of the number of septicemia cases.
  • Keywords: Beta-Poisson dose response models, Monte Carlo analysis, Vibrio vulnificus, Oyster, High pressure processing, Seafood poisoning risk
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  • Serment-Moreno, V., Deng, K., Wu, X., Su, Y. C., Fuentes, C., Torres, J. A., & Welti-Chanes, J. (2015). Monte Carlo analysis of the product handling and high-pressure treatment effects on the Vibrio vulnificus risk to raw oysters consumers. Journal of Food Engineering, 144, 86-92. doi:10.1016/j.jfoodeng.2014.07.014
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  • Authors Vinicio Serment-Moreno and Jorge Welti-Chanes acknowledge the financial support from Tecnológico de Monterrey (Research Chair Funds CAT- 200) for the Emerging Technologies and Nutrigenomic Research Groups, and CONACYT-SEP (Research Project 101700 and Scholarship Program). This project was supported also by Formula Grants no. 2011-31200-06041 and 2012-31200-06041 from the USDA National Institute of Food and Agriculture.
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