Dry aging creates a unique taste and flavor in beef; however, the process also causes rancidity, which is harmful to humans. During dry aging, the microbial flora in beef changes continuously; thus, this change can be used as an indicator of rancidity. The objective of this study was to analyze the correlation between microbial flora in beef and rancidity during dry aging. The round of beef (2.5–3 kg) was dry aged under 1.5 ± 1 °C and 82 ± 5% moisture for 17 weeks. The microflora in the dry aged beef was analyzed by pyrosequencing. The volatile basic nitrogen (VBN) and thiobarbituric acid reactive substance (TBARS) values were also measured. Primers were designed to detect and quantify bacteria using real-time polymerase chain reaction (RT-PCR). The VBN and TBARS values in the dry aged beef depreciated from week 11 of aging. The levels of Streptococcus spp., Pantoea spp., and Pseudomonas spp. significantly changed at around week 11. Quantitative RT-PCR showed that the levels of Pantoea spp. and Streptococcus spp. could be used to identify rancidity during dry aging. Thus, among the microbial flora in dry aged beef, Pantoea spp. and Streptococcus spp. can be used to determine the rancidity of dry aged beef.

This study predicted Salmonella outbreak risk from eating cooked poultry in various methods. The incidence of Salmonella in poultry meat and the environment from farm to home for consumption was investigated. To develop the predictive models, Salmonella growth data were collected at 4–25 °C during storage and fitted with the Baranyi model. The effects of cooking on cell counts in poultry meat were investigated. Temperature, duration, and consumption patterns were all searched. A simulation in @Risk was run using these data to estimate the probability of foodborne Salmonella disease. In farm, Salmonella was detected from only fecal samples (8.5%; 56/660). In slaughterhouses, Salmonella was detected from feces 16.0% (38/237) for chicken and 19.5% (82/420) for duck) and from carcasses of each step (scalding, defeathering, and chilling) by cross contamination. In chicken (n = 270) and duck (n = 205), Salmonella was detected in 5 chicken (1.9%) and 16 duck meat samples (7.8%). Salmonella contamination levels were initially estimated to be −3.1 Log CFU/g and −2.5 Log CFU/g, respectively. With R2 values between 0.862 and 0.924, the predictive models were suitable for describing the fate of Salmonella in poultry meat with of 0.862 and 0.924. The Salmonella was not detected when poultry meat cooks completely. However, if poultry meat contaminated with Salmonella were cooked incompletely, Salmonella remained on the food surface. The risk of foodborne Salmonella disease from poultry consumption after cooking was 3.0 × 10−10/person/day and 8.8 × 10−11/person/day in South Korea, indicating a low risk.

This study aimed to develop dynamic mathematical models to predict the growth of Salmonella spp. and Staphylococcus aureus in a cake under fluctuating temperatures. Among the nine different types of cakes frequently served during school meals, one type of cake was selected based on bacterial growth and water activity. Cocktails of Salmonella spp. and S. aureus were inoculated in the samples and stored at 4–35 °C for up to 336 h. The growth of Salmonella spp. and S. aureus was observed above 20 and 15 °C, respectively. The bacterial cell counts were fitted in the Baranyi model, and the maximum specific growth rate (μmax; log CFU/g/h) and lag phase duration (LPD; h) were analyzed using a polynomial model as a function of temperature (R2 = 0.968–0.988), and the performance of the developed models was appropriate. Furthermore, dynamic models were developed, and the predictions were acceptable in changing the temperature, indicating that the developed dynamic models can successfully predict the outcomes of Salmonella spp. and S. aureus in cake. These results provide useful information for assessing and managing microbial risk in foods by predicting the behavior of Salmonella spp. and S. aureus in cake, especially in changing temperature.

Doenjang and ganjang are traditional, Korean fermented foods. They are manufactured by fermenting jangs, either through the traditional natural fermentation, using straw, or the commercial inoculating starter cultures. However, both Bacillus cereus and aflatoxins have been detected in jangs, compromising their safety. Aflatoxins have been detected on numerous occasions. However, studies are yet to be conducted on whether these safety issues differ depending on the manufacturing method. In this study, we evaluated whether the manufacturing methods of doenjang and ganjang alter their safety. Samples of traditional and commercial doenjang and ganjang were analyzed for aflatoxin and B. cereus contamination. Microbiome taxonomic profiling was performed to assess microbial composition. The experimental methodology involved sample collection from various stages of production, including the use of starter cultures and natural fermentation processes. Aflatoxin levels were determined using regulatory limits, and B. cereus content was evaluated against specific thresholds. Aflatoxins were detected in both traditional and commercial doenjang and ganjang, with either the total aflatoxin (15 μg/kg) or aflatoxin B1 (10 μg/kg) exceeding the regulatory limits. However, ochratoxin A was not detected in any of the samples. B. cereus was detected in some samples, within the regulatory limit (4 log CFU/g), and was not influenced by the manufacturing method. Analysis at the production stage showed that aflatoxin increased alongside the fermentation time in traditional doenjang. However, in ganjang, no significant differences were associated with the fermentation period. When using starter cultures, the fermentation period did not affect the toxin level in both foods. Both methods showed lower aflatoxin content in the initial doenjang and ganjang samples than in meju. B. cereus was not detected in either method, as its content decreased over the fermentation period. Microbiome taxonomic profiling confirmed that even when using starter cultures, B. cereus was not a dominant species and was considerably affected by the environment. Staphylococcus aureus and Pseudomonas, pathogenic in nature, were detected in products manufactured using the traditional method; hence, the potential risk of this method was higher than that of the commercial method. The experimental methodology employed in this study contributes to understanding the microbial composition and toxin contamination levels in doenjang and ganjang, contributing to the overall knowledge of their safety and quality control.

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