Food Safety, Predictive Microbiology & Risk Assessment News
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In this study, the effect of refrigeration and freezing temperatures ('20, '12, 0, 4, and 8C) on growth and survival of Listeria innocua and Salmonella enterica serovar Typhimurium in raw chicken breasts for storage times of 3, 7, 10, 14, and 21 d were investigated. A modified Weibull model was also developed to analyze the microbial behavior of both microorganisms in raw chicken breasts under different refrigerated storage conditions over time. The results showed that the bacterial loads of L. innocua at 4 and 8C and Salmonella Typhimurium at 8C were significantly different from those at other refrigerated and frozen storage temperatures over storage times. The loads of both bacteria at frozen storage temperatures did not change significantly over time.
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Chinese researchers measured the survival rates of three C. jejuni strains inoculated onto chicken meat samples at '20C and 4C, and the survival curves of these three strains were determined. The results showed that the number of surviving cells decreased by 3.16, 2.87, and 3.14 log colony-forming unit (CFU)/g, respectively, at '20C during the 55-day storage period. The survival curves showed that the mean inactivation speeds were slow in the initial 20 days of storage at '20C, dropped rapidly between 25 and 45 days, and reached a plateau in reduction between 45 and 55 days.
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This Italian research proposed the optimization of a preserving treatment (homogenization"high-pressure homogenization (HPH)"and some safe antimicrobial compounds) able to inhibit the spoiling and pathogenic microflora of milk. Lactobacilli and bifidobacteria were the most resistant microorganisms (as a threefold treatment at 150 MPa was required to achieve a cell reduction of 1"2 log cfu/ml), followed by pathogens and then by pseudomonas and enterobacteria. Results were used to build two successive models: a primary model for the estimation of the physiological parameters of the microorganisms, whose fitting parameters were used to build a secondary model (polynomial equation) to predict the effectiveness of the combinations of HPH, citrus extract and vanillic acid.
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This European study systematically investigated laboratory and industrial scale batches of powdered infant formula, modelled the enumeration data using a range of statistical distributions, and assessed the appropriateness of individual models. Enumeration data obtained for an industrial batch of powdered infant formula were investigated in this way as well. It was found that Normal, Poisson and Zero-Inflated Poisson distributions fitted the data sets very poorly. In case of homogeneous contamination, there was not a notable difference between the ability of Negative Binomial, Poisson-Lognormal, Weibull, Gamma, and Lognormal distributions to model the data. Overall, either the Negative Binomial distribution or the Poisson-Lognormal distribution fitted the data best in the 10 batches studied, especially when part of a data set contained zeros and/or the numbers were low. The Negative Binomial fitted the laboratory batches best and the Poisson-Lognormal fitted the industrial batch best.
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The objective of this US study was to investigate the growth of Shiga toxin-producing E. coli (STEC, including serogroups O45, O103, O111, O121, and O145) in raw ground beef and to develop mathematical models to describe the bacterial growth under different temperature conditions. Analytical results showed that all 3 models were equally suitable for describing the bacterial growth under constant temperatures. The maximum cell density of STEC in raw ground beef increased exponentially with temperature, but reached a maximum of 8.53 log10 cfu/g of ground beef. The specific growth rates estimated by the 3 primary models were practically identical and can be evaluated by either the Ratkowsky square-root model or a Bělehrádek-type model.
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In this Korean study, the combined effect of temperature (15, 25, and 35C) and relative humidity (60, 70, and 80 percent) on the growth of E. coli O157:H7 on cabbage was investigated. The results demonstrated that the developed secondary models showed a good agreement between the observed and predicted values. Therefore, the established models can be suitable to estimate and control E. coli O157:H7 growth risk on cabbage at some steps from farm to table in Korea as a valuable tool.
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In the demand for a decision support tool to guide farmers wanting to control Salmonella Dublin (S. Dublin) in Danish dairy herds, researchers developed an age-structured stochastic, mechanistic and dynamic simulation model of S. Dublin in dairy herds, which incorporated six age groups and five infection states. The model simulated population and infection dynamics over a period of 10 years in weekly time steps. The effects of introducing one infectious heifer on the risk of spread of S. Dublin within the herd and on the duration of infection were estimated through 1000 simulation iterations for 48 scenarios. The scenarios covered all combinations of three herd sizes (70, 200 and 400 cows), four hygiene levels indicating infectious contact parameters, and four herd susceptibility levels indicating different susceptibility parameters for the individual animals in each of the six age groups in the herd.
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Canadian researchers monitored the temperature of packaged lettuce throughout a retail supply chain during the various stages of storage and shipping from the processor to retail. A dynamic model that predicts the effect of temperature on the growth or die-off of E. coli O157:H7 in packaged fresh-cut lettuce was applied to simulate the behavior of E. coli O157:H7 in the system. Simulations were carried out using distributions to account for variation in the temperature parameter and the die-off coefficient of the dynamic growth/death model. The results indicate that there was a predicted overall mean decline in cell numbers of 0.983 log cfu g'1 and that the extent of cell death was proportional to the total time spent in the cold chain.
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The European SOPHY project aims to develop a web-based software tool for prediction of product safety, quality and shelf life of ready-to-eat products. Fresh cut salads and deli salads were chosen as model food system. Food producers will be able to optimise their raw material selection, product formulation and processing steps virtually.
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Italian researchers developed a stochastic exposure assessment model to predict the final load (Nf, CFU/mL) of B. cereus cells after being treated by High Pressure Processing (HPP) and stored in a milk-egg-cocoa mixture beverage. Results indicated that beverage supplemented with cocoa powder had final B. cereus concentration level of 6 CFU/mL at 95% probability, being below the infectious dose (104 - 105 CFU per mL). The most important factors affecting the final load of B. cereus cells in this beverage were ranged as follows: cocoa supplementation gt; HPP treatment gt; initial load (Log N0, CFU/mL) gt; and storage time (t STORAGE, days).
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