FOOD SCIENCE ›› 2018, Vol. 39 ›› Issue (23): 1-6.doi: 10.7506/spkx1002-6630-201823001

• Basic Research •     Next Articles

Development of Predictive Models Based on qPCR for the Growth of Listeria monocytogenes and Vibrio parahaemolyticus Coexisting on Cooked Shrimps Stored at Low Temperatures

NIU Ben1, MU Lili1, ZHANG Zhaohuan1, LIU Haiquan1,2,3,4, PAN Yingjie1,2,3, ZHAO Yong1,2,3,*   

  1. 1. College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; 2. Laboratory of Quality and Safety Risk Assessment for Aquatic Product on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai 201306, China; 3. Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, Shanghai 201306, China; 4. Engineering Research Center of Food Thermal-Processing Technology, Shanghai Ocean University, Shanghai 201306, China
  • Online:2018-12-15 Published:2018-12-17

Abstract: The aim of this study was to develop predictive models based on quantitative real-time polymerase chain reaction (qPCR) for describing the growth of Listeria monocytogenes and Vibrio parahaemolyticus co-cultured on cooked shrimps. The strains were inoculated at the same level ((5.0 ± 0.5) (lg(CFU/g))) and cultured at low temperatures (4 and 10 ℃), and then the dynamic changes in microbial load were detected by qPCR. Three growth curve models, modified Gompertz, Logistic and Baranyi were fitted for each of the strains as well as two inactivation curve models, Log-linear and Weibull. The results showed that the modified Gompertz, Logistic and Baranyi models could successfully describe the growth curve of L. monocytogenes at low temperatures, with a coefficient of determination (R2) greater than 0.98. The inactivation of V. parahaemolyticus at 4 ℃ could be clearly described by the Log-linear and Weibull models, with R2 of 0.950 and 0.945, respectively; however, the inactivation models failed to describe the behavior changes at 10 ℃, with R2 of only 0.784 and 0.775, respectively. The results from this study provide a new clue for growth modelling of food-borne pathogens based on molecular biological techniques.

Key words: mixed bacteria, quantitative real-time polymerase chain reaction, predictive models, Listeria monocytogenes, Vibrio parahaemolyticus, cooked shrimp

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