Contaminated poultry litter, serving as a reservoir for Salmonella, can be linked to both food safety concerns when contaminated birds enter processing plants and environmental concerns when used as a fertilizer. Predictive modeling allows for the estimation of microbial growth or inactivation as a function of controlling environmental growth factors. A study was conducted to observe the combined effects of pH and water activity (A(w)) at a constant temperature on Salmonella populations in used turkey litter to predict microbial response over time. Litter, first pH-adjusted and then inoculated with a 3-strain Salmonella serovar cocktail to an initial concentration of approximately 10(7) cfu/g, was placed into individual sealed plastic containers with saturated salt solutions for controlling A(w). A balanced design including 3 A(w) values (0.84, 0.91, 0.96), 3 pH values (4, 7, 9), and a constant temperature of 30 degrees C was used, with litter samples periodically removed and analyzed for Salmonella populations, pH, and A(w). At each combination of environmental factors, the Churchill or exponential inactivation mathematical models were used to describe the growth and death of Salmonella over time. Salmonella populations exhibited growth (approximately 2 log) with little decline up to 42 d in litter environments of pH 7 and 9 and a A(w) of 0.96. As litter A(w) and pH levels were reduced, populations declined, with the most drastic reductions (approximately 5 log in 9 h) occurring in low-pH (4) and low-A(w) (0.84) environments. Generalized models for bacterial growth and death under grouped pH environments were successfully developed to predict Salmonella behavior in litter over time. These findings suggest that the best management practices and litter treatments that lower litter A(w) to < or =0.84 and pH to < or =4 are effective in reducing Salmonella populations. The use of a single equation to predict the growth and decline of Salmonella populations as a function of pH and A(w) has potential application for use in the development of effective pathogen control strategies at the farm level.
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