Simultaneous construction of PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on cooked shrimps

The aim of this study was to simultaneously construct PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on cooked shrimps at 4 and 10 degrees C. Calibration curves were established to correlate peak density of DGGE bands with microbial counts. Microbial counts derived from PCR-DGGE and plate methods were fitted by Baranyi model to obtain molecular and traditional predictive models. For L.monocytogenes, growing at 4 and 10 degrees C, molecular predictive models were constructed. It showed good evaluations of correlation coefficients (R-2>092), bias factors (B-f) and accuracy factors (A(f)) (10B(f)A(f)11). Moreover, no significant difference was found between molecular and traditional predictive models when analysed on lag phase (), maximum growth rate ((max)) and growth data (P>005). But for V.parahaemolyticus, inactivated at 4 and 10 degrees C, molecular models show significant difference when compared with traditional models. Taken together, these results suggest that PCR-DGGE based on DNA can be used to construct growth models, but it is inappropriate for inactivation models yet. This is the first report of developing PCR-DGGE to simultaneously construct multiple molecular models.