Salmonella can survive in low-moisture foods for long periods of time. Reduced microbial inactivation during heating is believed to be due to the interaction of cells and water, and is thought to be related to water activity (a(w)). Little is known about the role of water mobility in influencing the survival of Salmonella in low-moisture foods. The aim of this study was to determine how the physical state of water in low-moisture foods influences the survival of Salmonella and to use this information to develop mathematical models that predict the behavior of Salmonella in these foods. Whey protein powder of differing water mobilities was produced by pH adjustment and heat denaturation, and then equilibrated to aw levels between 0.19±0.03 and 0.54±0.02. Water mobility was determined by wide-line proton-NMR. Powders were inoculated with a four-strain cocktail of Salmonella, vacuum-sealed and stored at 21, 36, 50, 60, 70 and 80°C. Survival data was fitted to the log-linear, the Geeraerd-tail, the Weibull, the biphasic-linear and the Baranyi models. The model with the best ability to describe the data over all temperatures, water activities and water mobilities (f(test)

Nuts have been identified as a vector for salmonellosis. The objective of this project was to estimate the prevalence and contamination level of Salmonella in raw tree nuts (cashews, pecans, hazelnuts, macadamia nuts, pine nuts, and walnuts) at retail markets in the United States. A total of 3,656 samples of six types of tree nuts were collected from different types of retail stores and markets nationwide between October 2014 and October 2015. These samples were analyzed using a modified version of the Salmonella culture method from the U.S. Food and Drug Administration's Bacteriological Analytical Manual. Of the 3,656 samples collected and tested, 32 were culturally confirmed as containing Salmonella. These isolates represented 25 serotypes. Salmonella was not detected in pecans and in-shell hazelnuts. Salmonella prevalence estimates (and 95% confidence intervals) in cashews, shelled hazelnuts, pine nuts, walnuts, and macadamia nuts were 0.55% [0.15, 1.40], 0.35% [0.04, 1.20], 0.48% [0.10, 1.40], 1.20% [0.53, 2.40], and 4.20% [2.40, 6.90], respectively. The rates of Salmonella isolation from major or big chain supermarkets, small chain supermarkets, discount, variety, or drug stores, and online were 0.64% [0.38, 1.00], 1.60% [0.80, 2.90], 0.00% [0.00, 2.40], and 13.64% [2.90, 35.00], respectively (Cochran-Mantel-Haenszel test: P = 0.02). The rates of Salmonella isolation for conventional and organic nuts were not significantly different. Of the samples containing Salmonella, 60.7% had levels less than 0.003 most probable number (MPN)/g. The highest contamination level observed was 0.092 MPN/g. The prevalence and levels of Salmonella in these tree nut samples were comparable to those previously reported for similar foods.

Factors such as temperature, water activity (aw), substrate, culture media, serotype, and strain influence the survival of Salmonella in low-aw foods. Predictive models for Salmonella survival in low-aw foods at temperatures ranging from 21 to 80(u) C and water activities below 0.6 were previously developed. Literature data on survival of Salmonella in low-aw foods were analyzed in the present study to validate these predictive models and to determine global influencing factors. The results showed the Weibull model provided suitable fits to the data in 75% of the curves as compared with the log-linear model. The secondary models predicting the time required for log-decimal reduction (log δ) and shape factor (log β) values were useful in predicting the survival of Salmonella in low-aw foods. Statistical analysis indicated overall fail-safe secondary models, with 88% of the residuals in the acceptable and safe zones (<0.5 log CFU) and a 59% correlation coefficient (R(2) = 0.35). A high variability in log δ-values and log β-values was observed, emphasizing the importance of experimental design. Factors of significant influence on the times required for first log-decimal reduction included temperature, aw, product, and serotype. Log β-values were significantly influenced by serotype, the type of inoculum (wet or dry), and whether the recovery media was selective or not. The results of this analysis provide a general overview of survival kinetics of Salmonella in low-aw foods and its influencing factors.

The impact of temperature, water activity (a), and nut composition on Salmonella survival on tree nuts has not been thoroughly examined. The aim of this study was to determine the effect of temperature, a, and nut composition on the survival of Salmonella on tree nuts and develop predictive models. Pecans, hazelnuts, and pine nuts were chosen based on differences in their typical fat content. Nuts were inoculated with a cocktail of five Salmonella serotypes (11 log CFU/mL) and then were dried and stored at 4, 10, and 25°C at 0.41 ± 0.06 and 0.60 ± 0.05 a for 1 year. Ten-gram quantities were removed at different intervals up to 364 days to test for surviving Salmonella populations (plating on selective and nonselective media) and a. Experiments were carried out in triplicate. Salmonella populations were relatively stable over a year at 4 and 10°C at both a levels with <1.5-log CFU/g decline. The best predictive model to describe Salmonella survival at 4 and 10°C was a log-linear model with a D-value for each tree nut and a combination. Significant declines in Salmonella levels were observed at 25°C, where the best fit was a Weibull model with a fixed ρ for all tree nuts (ρ = 0.86), a δ value for each tree nut and a combination, and a random factor to account for variability among replicates. The time for the first log reduction at 25°C and 0.37 ± 0.009 a was estimated at 24 ± 2 weeks for hazelnuts, 34 ± 3 weeks for pecans, and 52 ± 7 weeks for pine nuts. At the same temperature, but with 0.54 ± 0.009 a, the mean estimated time for the first log reduction decreased to 9 ± 1 weeks for hazelnuts, 10 ± 1 weeks for pecans, and 16 ± 1 weeks for pine nuts. Tree nut, a, and temperature were shown to have a statistically significant effect on survival ( P < 0.05). No apparent influence of fat content on survival was observed. The results of this study can be used to predict changes in Salmonella levels on pecans, hazelnuts, and pine nuts after storage at the different temperatures and a values.