RESUMEN
A dynamic model was developed to predict growth of Clostridium perfringens in cooked ground pork supplemented with salt (0-3% wt/wt) and sodium pyrophosphate (0-0.3% wt/wt) under varying temperatures. C. perfringens (NCTC 8238, NCTC 8239, and NCTC 10240) spores were heat shocked, cooled, and inoculated into ground pork. Isothermal bacterial growth was quantified with variable salt and phosphate concentrations at temperatures ranging from 15 to 51 °C. The primary Baranyi model was fitted to all C. perfringens growth profiles and gave a satisfactory fit (R2 ≥ 0.85). A quadratic polynomial secondary model was developed (P < 0.0001) to predict the maximum specific growth rate as a function of temperature, salt, and phosphate concentrations (R2 = 0.93). A dynamic model was developed and validated using growth data retrieved from 7 published studies. Thirty three out of 44 predictions were within the acceptable prediction zone (-0.5 ≤ prediction error ≤ 1.0). The developed predictive model can be used to minimize the risk of C. perfringens in pork products supplemented with additives during cooling.
Asunto(s)
Clostridium perfringens/crecimiento & desarrollo , Productos de la Carne/microbiología , Modelos Biológicos , Temperatura , Animales , Culinaria , Difosfatos , Manipulación de Alimentos/métodos , Microbiología de Alimentos , Cloruro de Sodio , Esporas Bacterianas/crecimiento & desarrollo , PorcinosRESUMEN
A dynamic model to predict the germination and outgrowth of Clostridium botulinum spores in cooked ground beef was presented. Raw ground beef was inoculated with a ten-strain C. botulinum spore cocktail to achieve approximately 2 log spores/g. The inoculated ground beef was vacuum packaged, cooked to 71 °C to heat shock the spores, cooled to below 10 °C, and incubated isothermally at temperatures from 10 to 46 °C. C. botulinum growth was quantified and fitted into the primary Baranyi Model. Secondary models were fitted to maximum specific growth rate and lag phase duration using Modified Ratkowsky equation (R2 0.96) and hyperbolic function (R2 0.94), respectively. Similar experiments were also performed under non-isothermal (cooling) conditions. Acceptable zone prediction (APZ) analysis was conducted on growth data collected over 3 linear cooling regimes from the current study. The model performance (prediction errors) for all 22 validation data points collected in the current work were within the APZ limits (-1.0 to +0.5 log CFU/g). Additionally, two other growth data sets of C. botulinum reported in the literature were also subjected to the APZ analysis. In these validations, 20/22 and 10/14 predictions fell within the APZ limits. The model presented in this work can be employed to predict C. botulinum spore germination and growth in cooked uncured beef under non-isothermal conditions. The beef industry processors and food service organizations can utilize this predictive microbial model for cooling deviations and temperature abused situations and in developing customized process schedules for cooked, uncured beef products.