Abstract

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.

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