Predictive Modeling for the Growth ofSalmonellaEnteritidis in Chicken Juice by Real-Time Polymerase Chain Reaction

Propidium monoazide (PMA) qPCR assay compared to the plate count method for quantifying the growth of Salmonella enterica serotypes in vacuum-packaged turkey breast combined with a mathematical modeling approach

This study compares the plate count (PC) and the Propidium Monoazide-quantitative Polymerase Chain Reaction (PMA-qPCR) methods to assess the growth of a cocktail of three serotypes of Salmonella enterica (Heidelberg, Typhimurium, and Enteritidis) in cooked, sliced, and vacuum-packaged turkey breast (STB) under isothermal storage temperatures (8 °C-20 °C), using predictive models. Standard curves were developed for PMA-qPCR, demonstrating high efficiency (101%) and sensitivity, with quantification limits ranging from 1 to 2 log10 CFU/g for all temperatures studied. Comparative analysis revealed a significant correlation (R2 = 0.99; 95% CI) between the PC and PMA-qPCR methods; however, the agreement analysis indicated a mean difference (Bias) of -0.11 log10 CFU/g (p < 0.05), suggesting underestimation by the PC method. This indicates the presence of stressed or viable but nonculturable (VBNC) cells, detectable by PMA-qPCR but not by PC. The Baranyi and Roberts model showed a good ability to describe the behavior of S. enterica cocktail in STB for PC and PMA-qPCR data under all isothermal conditions. The exponential secondary model more accurately represented the temperature dependence of the maximum specific growth rate compared to the Ratkowsky square root model, with R2 values ≥ 0.984 and RMSE values ≤ 0.011 for both methods. These results suggest that combining PMA-qPCR with predictive modeling allows for a more accurate prediction of S. enterica growth, compared to PC method. In the event of cold chain disruptions of meat products, the use of PMA-qPCR method allow the quantification of VBNC cells, that can still pose a health risk to consumers, especially in ready-to-eat products.

Estimating Salmonella Typhimurium Growth on Chicken Breast Fillets Under Simulated Less-Than-Truckload Dynamic Temperature Abuse

Companies may have insufficient freight to fill an entire truck/trailer, and instead only pay for space that their products occupy (i.e., "less-than-truckload" shipping; LTL). As LTL delivery vehicles make multiple stops, there is an increased opportunity for product temperature abuse, which may increase microbial food safety risk. To assess LTL effects on Salmonella Typhimurium growth, commercially produced boneless skinless chicken breast fillets were inoculated and incubated under dynamic 2-h temperature cycles (i.e., 2 h at 4°C and then 2 h at 25°C), mimicking a commercially relevant LTL scenario. Bacterial kinetics were measured over 24 h and then observations compared with predictions of three published Salmonella secondary models by bias and accuracy factor measurement. One model produced more "fail-safe" estimates of Salmonella growth than the other models, although all models were defined as "acceptable." These developed tertiary models can help shippers assess supply chain performance and produce proactive food safety risk management systems.

Predictive modeling of Salmonella spp. growth behavior in cooked and raw chicken samples: Real-time PCR quantification approach and model assessment in different handling scenarios

The increasing prevalence of Salmonella contamination in poultry meat emphasizes the importance of suitable predictive microbiological models for estimating Salmonella growth behavior. This study was conducted to evaluate the potential of chicken juice as a model system to predict the behavior of Salmonella spp. in cooked and raw chicken products and to assess its ability to predict cross-contamination scenarios. A cocktail of four Salmonella serovars was inoculated into chicken juice, sliced chicken, ground chicken, and chicken patties, with subsequent incubation at 10, 15, 20, and 25°C for 39 h. The number of Salmonella spp. in each sample was determined using real-time polymerase chain reaction. Growth curves were fitted into the primary Baranyi and Roberts model to obtain growth parameters. Interactions between temperature and growth parameters were described using the secondary Ratkowsky's square root model. The predictive results generated by the chicken juice model were compared with those obtained from other chicken meat models. Furthermore, the parameters of the chicken juice model were used to predict Salmonella spp. numbers in six worst-case cross-contamination scenarios. Performance of the chicken juice model was evaluated using the acceptable prediction zone from -1.0 (fail-safe) to 0.5 (fail-dangerous) log. Chicken juice model accurately predicted all observed data points within the acceptable range, with the distribution of residuals being wider near the fail-safe zone (75%) than near the fail-dangerous zone (25%). This study offers valuable insights into a novel approach for modeling Salmonella growth in chicken meat products, with implications for food safety through the development of strategic interventions. PRACTICAL APPLICATION: The findings of this study have important implications in the food industry, as chicken juice could be a useful tool for predicting Salmonella behavior in different chicken products and thus reducing the risk of foodborne illnesses through the development of strategic interventions. However, it is important to recognize that some modifications to the chicken juice model will be necessary to accurately mimic all real-life conditions, as multiple factors particularly those related to food processing can vary between different products.

Modeling the Inactivation, Survival, and Growth of Salmonella enterica under Osmotic Stress Considering Inoculum Phase and Serotype

AIMS

This study evaluated the behaviour of the Salmonella enterica serotypes in osmotically-stressful BHI broth (0.940 ≤ a_w ≤ 0.960), assessing inoculum from two stages of the bacterial life cycle (exponential and stationary) and two temperatures (25 and 35 °C).

METHODS AND RESULTS

Four S. enterica serotypes (Typhimurium, Enteritidis, Heidelberg, and Minnesota) were grown in stressful BHI at 25 °C. A mathematical model was proposed for describing the total microbial count as the sum of two subpopulations, inactivating and surviving-then-growing. When submitted to a_w of 0.950 and 0.960, all strains showed a decreased count, followed by a period of unchanged count and then exponential growth (Phoenix Phenomenon). Strains inoculated at a_w = 0.940 and 0.945 showed inactivation kinetics only. Cells cultivated at 25 °C and inoculated from the exponential phase were the most reactive to the osmotic stress, showing a higher initial population reduction and shorter adaptation period. The proposed model described the inactivation data and the Phoenix Phenomenon accurately.

CONCLUSIONS

The results quantified the complex response of S. enterica to the osmotic environment in detail, depending on the inoculum characteristic and serotype evaluated.

SIGNIFICANCE AND IMPACT OF STUDY

Quantifying these differences is truly relevant to food safety and improves risk analysis.

Characterization of chicken meat contaminated with Salmonella by fluorescence spectroscopy

Contaminated poultry products as eggs and meat are the primary vehicles of Salmonella infection. Conventional methods for microorganisms detections involve multiple steps, and despite its accuracy, these assays are time-consuming. Biosensing methods have shown great potential for the rapid detection of foodborne pathogens. Some of the biosensors are based on fluorescence. Various fluorophores such as collagen, elastin, NAD(P)H, and porphyrins can be used to evaluate possible chemical changes in meat. In this manuscript, the fluorescence properties of chicken meat contaminated with Salmonella enterica (ATCC 14028) cell suspensions (500; 5000; 50,000 and 500,000 cells/mL) were obtained and compared with non-contaminated control, for meat kept at 25 °C for 24 and 48 h. The effects of ambient light were also considered. Our results indicated that free NAD(P)H and coproporphyrin emission bands present in contaminated meat, increased over time, and can provide access to valuable information for the detection of Salmonella in chicken meat.

qPCR quantification of Carnobacterium maltaromaticum, Brochothrix thermosphacta, and Serratia liquefaciens growth kinetics in mixed culture

Quantifying growth kinetics of specific spoilage microorganisms in mixed culture is required to describe the evolution of food microbiomes. A qPCR method was developed to selectively amplify individual meat spoilage bacteria, Carnobacterium maltaromaticum, Brochothrix thermosphacta and Serratia liquefaciens, within a broth medium designed to simulate the composition of beef. An optimized method of DNA extraction was produced for standard curve construction. Method specificity was determined by individual single peaks in melt curves. Reaction efficiency for standard curves of C. maltaromaticum, B. thermosphacta and S. liquefaciens was high (R² = 0.98-0.99), and linear quantification was achieved over a 5 log CFU/ml range. Coefficient of variation was calculated considering both threshold cycle (C_t) and bacterial concentration; the value did not exceed 14% for inter- or intra-runs for either method. Comparison of growth kinetic parameters derived from plate count and qPCR showed no significant variation (P > .05) for growth rate (GR) and maximum population density (MPD); lag phase duration (LPD) was not included in this comparison due to high innate variability. Log quantification of each isolate was validated in a mixed-culture experiment for all three species with qPCR and plate count differing less than 0.3 log CFU/ml (average 0.10 log CFU/ml, R² = 0.98).