논문 상세보기
pp.25-30
In this study, predictive mathematical models were developed to predict the kinetics of Listeria monocytogenes growth in the mixed fresh-cut vegetables, which is the most popular ready-to-eat food in the world, as a function of temperature (4, 10, 20 and 30oC). At the specified storage temperatures, the primary growth curve fit well (r2 = 0.916~0.981) with a Gompertz and Baranyi equation to determine the specific growth rate (SGR). The Polynomial model for natural logarithm transformation of the SGR as a function of temperature was obtained by nonlinear regression (Prism, version 4.0, GraphPad Software). As the storage temperature decreased from 30oC to 4oC, the SGR decreased, respectively. Polynomial model was identified as appropriate secondary model for SGR on the basis of most statistical indices such as mean square error (MSE = 0.002718 by Gompertz, 0.055186 by Baranyi), bias factor (Bf = 1.050084 by Gompertz, 1.931472 by Baranyi) and accuracy factor (Af = 1.160767 by Gompertz, 2.137181 by Baranyi). Results indicate L. monocytogenes growth was affected by temperature mainly, and equation was developed by Gompertz model (−0.1606 + 0.0574*Temp + 0.0009*Temp*Temp) was more effective than equation was developed by Baranyi model (0.3502 − 0.0496*Temp + 0.0022*Temp* Temp) for specific growth rate prediction of L. monocytogenes in the mixed fresh-cut vegetables.
