Modeling growth kinetics of Listeria monocytogenes in pork cuts from packaging to fork under different storage practices

Intra- and inter-batch variability in raw pork challenge test studies and their consequences on model predictions: An intricate interplay between L. monocytogenes, the microbiome, and packaging atmosphere

The purpose of this study was to conduct challenge studies in raw pork by strictly following all aspects of the 2014 EURL technical guidance document for conducting shelf-life studies on Listeria monocytogenes. Growth potential was assessed on three batches of self-cut pork chops and one batch of in-house prepared pure minced pork without any additives in air and MAP (70 % O₂/30% CO₂) packaging. Pork chops did not support the growth of the pathogen throughout the shelf-life, given the specific conditions used in this study, with growth potential values of 0.28 and 0.46 log CFU/g, respectively, for both air and MAP. Substantial growth (>0.5 log CFU/g) was obtained in minced pork after investigating only one batch, with growth potential values of 1.69 and 0.80 log CFU/g, for air and MAP. However, both intra- and inter-batch variability for pork chops and intra-batch variability for minced pork was observed; with elevated growth being evened out by the way growth potential is calculated in the EURL 2014 document, leading to underestimations and posing a potential risk to public health. Maximum growth rate in minced pork at a constant temperature of 7 °C was estimated at μ_max = 0.680 log CFU/day and μ_max = 0.489 log CFU/day in air and MAP, respectively. Model predictions for the growth potential showed acceptable results for air-packed minced pork with better accuracy when the lag phase was implemented as indicated in the renewed protocol (CRL EU, 2021). In MAP, all models used, including the Combase Growth model and to a lesser extent the DMRI dynamic safety model, overestimate the growth potential probably due to a lack of integration of the changing CO₂ levels in the packages. The predictive models used in this study do not adequately account for the dynamics in the raw pig matrix, which may have an inhibitory effect on the growth of L. monocytogenes, including interaction with the microbiome and CO₂, and emphasize the importance of remaining critical of predictive model outcomes. In addition, the experimental intra- and inter-batch variability raise questions about the sense or nonsense of using predictive microbiology in these raw pork products.

Critical Analysis of Pork QMRA Focusing on Slaughterhouses: Lessons from the Past and Future Trends

Foodborne microbial diseases have a significant impact on public health, leading to millions of human illnesses each year worldwide. Pork is one of the most consumed meat in Europe but may also be a major source of pathogens introduced all along the farm-to-fork chain. Several quantitative microbial risk assessment (QMRA) have been developed to assess human health risks associated with pork consumption and to evaluate the efficiency of different risk reduction strategies. The present critical analysis aims to review pork QMRA. An exhaustive search was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. It resulted in identification of a collection of 2489 papers including 42 on QMRA, after screening. Among them, a total of 29 studies focused on Salmonella spp. with clear concern on impacts at the slaughterhouse, modeling the spreading of contaminations and growth at critical stages along with potential reductions. Along with strict compliance with good hygiene practices, several potential risk mitigation pathways were highlighted for each slaughterhouse step. The slaughterhouse has a key role to play to ensure food safety of pork-based products but consideration of the whole farm-to-fork chain is necessary to enable better control of bacteria. This review provides an analysis of pork meat QMRA, to facilitate their reuse, and identify gaps to guide future research activities.

Impact of Cooking Procedures and Storage Practices at Home on Consumer Exposure to Listeria Monocytogenes and Salmonella Due to the Consumption of Pork Meat

The objective of this research was to analyze the impact of different cooking procedures (i.e., gas hob and traditional static oven) and levels of cooking (i.e., rare, medium, and well-done) on inactivation of Listeria monocytogenes and Salmonella in pork loin chops. Moreover, the consumer's exposure to both microorganisms after simulation of meat leftover storage at home was assessed. The results showed that well-done cooking in a static oven was the only treatment able to inactivate the tested pathogens. The other cooking combinations allowed to reach in the product temperatures always ≥73.6 °C, decreasing both pathogens between 6 log₁₀ cfu/g and 7 log₁₀ cfu/g. However, according to simulation results, the few cells surviving cooking treatments can multiply during storage by consumers up to 1 log₁₀ cfu/g, with probabilities of 0.059 (gas hob) and 0.035 (static oven) for L. monocytogenes and 0.049 (gas hob) and 0.031 (static oven) for Salmonella. The key factors affecting consumer exposure in relation to storage practices were probability of pathogen occurrence after cooking, doneness degree, time of storage, and time of storage at room temperature. The results of this study can be combined with prevalence data and dose-response models in risk assessment models and included in guidelines for consumers on practices to be followed to manage cooking of pork meat at home.

Proposal of performance objectives and sampling schemes for Listeria monocytogenes in fresh meat intended to be eaten cooked under different storage practices

The goal of this study was to define a practical approach to derive risk management measures, such as performance objectives (POs), for Listeria monocytogenes in pork cuts intended to be eaten cooked. Moreover, sampling plans to verify the compliance of meat lots to such POs are presented. The POs were estimated as prevalence and/or concentration values that should not be exceeded at time of consumption. To derive possible POs for L. monocytogenes, ten lots of pork cuts, collected within the same slaughterhouse along a one-year period, were tested for the presence and concentration of the pathogen under four different scenarios through the product shelf life. Our results indicated that the median values of the prevalence distributions ranged between 0.41 and 0.68. The number of samples to be tested in order to verify lot compliance ranged between six, for samples tested immediately after packaging, and three, for samples tested at the end of the shelf life. The concentration values ranged between 2.02 log10 CFU/g, for samples tested immediately after packaging, up to 3.14 log10 CFU/g for samples tested after final storage at 14°C. The concentration of L. monocytogenes in the samples contaminated by less than 10 CFU/g was estimated between 7 CFU/10g to 7 CFU/g, after storage at retail and abuse temperature, respectively. Basing on the knowledge of log normal distributions, the maximum contamination level of the lots in order to achieve the suggested POs, was calculated. It was obtained that mean concentration estimated as PO should be between -0.43 and 0.48 log10 CFU/g. Other risk management options are further evaluated and discussed. These results would help food operators and authorities to establish safety targets and corrective actions regarding inhibition of L. monocytogenes in fresh pork meat.

Identification of the significant factors in food safety using global sensitivity analysis and the accept-and-reject algorithm: application to the cold chain of ham

Deterministic models describing heat transfer and microbial growth in the cold chain are widely studied. However, it is difficult to apply them in practice because of several variable parameters in the logistic supply chain (e.g., ambient temperature varying due to season and product residence time in refrigeration equipment), the product's characteristics (e.g., pH and water activity) and the microbial characteristics (e.g., initial microbial load and lag time). This variability can lead to different bacterial growth rates in food products and has to be considered to properly predict the consumer's exposure and identify the key parameters of the cold chain. This study proposes a new approach that combines deterministic (heat transfer) and stochastic (Monte Carlo) modeling to account for the variability in the logistic supply chain and the product's characteristics. The model generates a realistic time-temperature product history , contrary to existing modeling whose describe time-temperature profile Contrary to existing approaches that use directly a time-temperature profile, the proposed model predicts product temperature evolution from the thermostat setting and the ambient temperature. The developed methodology was applied to the cold chain of cooked ham including, the display cabinet, transport by the consumer and the domestic refrigerator, to predict the evolution of state variables, such as the temperature and the growth of Listeria monocytogenes. The impacts of the input factors were calculated and ranked. It was found that the product's time-temperature history and the initial contamination level are the main causes of consumers' exposure. Then, a refined analysis was applied, revealing the importance of consumer behaviors on Listeria monocytogenes exposure.