How do the survival kinetics of Escherichia coli and Salmonella differ during poultry processing plants and thermal inactivation process?

Abstract

Salmonella and E. coli are among the most common foodborne pathogens causing human illnesses worldwide, with poultry meat being a primary source of contamination. Each stage of the poultry production chain, from farm to table, affects the prevalence of these pathogens. Despite various control strategies to improve the microbial quality of poultry products, complete eradication of these bacteria remains unattained. The objective of this study was to generate new insights into the distribution of Salmonella and E. coli throughout different stages of chicken meat production. Additionally, the study aimed to predict the fate of these bacteria across the production chain up to the point just before consumption by examining the effects of varying temperatures and pH levels using predictive modeling tools. A total of 27 samples were collected from the slaughterhouse at five critical steps, and from two butcher shops. More than 16,000 temperature readings and 92 pH measurements were taken during sampling and from cold storage equipment dedicated to chicken meat to monitor the fluctuations of these parameters. Chicken meat was contaminated with Salmonella and E.coli at several isothermal conditions (5, 25, 30 and 37°C). Results were then fitted into primary models (Logistic, Gompertz and Baranyi). Measures of goodness-of-fit such as R2, RMSE and AIc, were used for comparison for these primary models. Based on these criteria, Gompertz model described growth data the best, followed by the Baranyi model. The maximum growth rates obtained from each primary model were then modeled as a function of T⁰C using the modified Ratkowsky and the gamma concept was used to predict the effects of the T°C and pH on microbial growth. The results of the dynamic analysis indicated that the optimal specific growth rates (μopt)for Salmonella and E. coli were 1.63±0.08 1/h and 1.05±0.06 1/h, respectively. Additionally, based on the actual recorded temperatures and pH values, this study found that the populations of Salmonella and E. coli (Nmax) could reach 8.9 log CFU/g and 8.5 log CFU/g, respectively, after 41 hours, assuming an initial population (N0) of 1 log CFU/g. Results showed that T°C had a significant effect on bacterial growth, particularly during slaughter when the T°C was close to the (Topt) ( T = 0.96). In contrast, pH had a minimal effect on bacterial growth. Understanding these factors can help to act appropriately to prevent contamination. Refrigerating chicken at or below 4°C significantly slows down bacterial growth. Proper cooking effectively kills Salmonella and E. coli, and appropriate cleaning practices can prevent cross-contamination. The results of this study can be used to predict the growth and survival of Salmonella and E. coli and assess its risk in chicken or other chicken by-products exposed to a relatively wide temperature range during manufacturing, distribution and preparing.