Development of a quantitative microbiological spoilage risk assessment (QMSRA) model for cooked ham sliced at retail.

A quantitative microbiological spoilage risk assessment model (QMSRA) for cooked ham sliced at retail was developed based on a stochastic growth model for lactic acid bacteria (LAB), which are considered as the specific spoilage organisms (SSO), and a "spoilage-response" relationship characterizing the variability in consumer's perception of spoilage. In a simulation involving 10,000 cooked ham purchases, the QMSRA model predicted a median of zero spoilage events for up to 4.5 days of storage. After storage times of 5 and 6 days, the model predicted 1,790 and 8,570 spoilage events, respectively. A sensitivity analysis showed that domestic storage temperature was the most significant factor affecting LAB concentration in cooked ham, followed by the LAB contamination level at slicing. A scenario analysis was performed testing better temperature control of consumer's refrigerators, better hygiene conditions during slicing and a combination of the two strategies. Among the tested scenarios, a 2 log reduction in the LAB contamination at slicing combined with a 2 °C decrease in domestic storage temperature resulted in zero risk of spoilage for up to 12 days of storage. The QMSRA model developed in the present study can be a useful tool for quality management decisions.

Quantitative microbiological spoilage risk assessment (QMSRA) of fresh poultry fillets during storage at retail.

A quantitative microbiological spoilage risk assessment model (QMSRA) of aerobically stored fresh poultry fillets was developed based on pseudomonads growth and metabolic activity. Simultaneous microbiological and sensory analyses were performed in poultry fillets to evaluate the relation between pseudomonads concentration and sensory rejection due to spoilage. The analysis showed no organoleptic rejection at pseudomonads concentrations less than 6.08 log CFU/cm2. For higher concentrations, a "spoilage-response" relationship was developed using a beta-Poisson model. The above relationship was combined with a stochastic modeling approach for pseudomonads growth by taking into account both variability and uncertainty of factors affecting spoilage. To enhance the reliability of the developed QMSRA model, uncertainty was quantified and separated from variability using a second order Monte Carlo simulation. For a batch of 10,000 units, the QMSRA model predicted a median number of 11, 80, 295, 733 and 1,389 spoiled units for retail storage times of 6,7, 8, 9 and 10 days, respectively, while no spoiled units were predicted for storage time of up to 5 days at retail. Scenario analysis showed that a reduction of 1 log in the pseudomonads concentration at the time of packaging or 1 °C in retail storage temperature results in up to 90% reduction of the spoiled units while the combination of the above interventions can reduce the risk of spoilage by up to 99%, depending on the storage time. The poultry industry can utilize the QMSRA model as a transparent scientific basis to support food quality management decisions in determining appropriate expiration dates which maximize the utilization of the product's "true" shelf life while minimize the risk of spoilage to an acceptable level. Furthermore, the scenario analysis can provide the necessary components for an effective cost-benefit analysis, enabling the identification and comparison of appropriate strategies for extending the shelf life of fresh poultry products.

Development and validation of a mathematical model for pseudomonads growth as a basis for predicting spoilage of fresh poultry breast and thigh fillets.

The growth of naturally contaminated pseudomonads on fresh breast and thigh poultry fillets during aerobic storage was studied and modeled as a function of temperature (0-30°C). A statistical comparison of the models for breast and thigh fillets showed that muscle type does not significantly affect the temperature dependence of pseudomonads growth kinetics. A unified model for breast and thigh was developed and validated against pseudomonads growth rate data under isothermal conditions extracted from literature and experimental data under dynamic temperature conditions. The validation results showed a satisfactory performance of the model with the bias and accuracy factors ranging from 0.85 to 1.09 and 1.02 to 1.21, respectively. The model was further used to predict the shelf life of fresh poultry as the time required by pseudomonads to reach the spoilage level for various scenarios of temperature, initial contamination level, and physiological state of pseudomonads demonstrating its application in a risk-based shelf-life assessment of fresh poultry products.

Quantitative risk assessment of Listeria monocytogenes in ready-to-eat (RTE) cooked meat products sliced at retail stores in Greece.

A quantitative microbial risk assessment (QMRA) model predicting the listeriosis risk related to the consumption of Ready- To- Eat (RTE) cooked meat products sliced at retail stores in Greece was developed. The probability of illness per serving assessed for 87 products available in the Greek market was found highly related to the nitrite concentration; products having a lower concentration showed a higher risk per serving. The predicted 95th percentiles of the annual listeriosis cases totaled 33 of which 13 cases were <65 years old and 20 cases ≥65 years old. The highest number of cases was predicted for mortadella, smoked turkey, boiled turkey and parizer, which were the most frequently consumed product categories. Two scenarios for assessing potential interventions to reduce the risk were tested: setting a use-by date of 14 days (these products have no use-by date based on current European Union legislation) and improving the temperature control during domestic storage. The two scenarios resulted in a decrease of the 95th and 99th percentiles of the total annual cases by 97% and 88%, respectively.