Shelf life estimation of refrigerated vacuum packed beef accounting for uncertainty

This study estimates the shelf life of vacuum packed beef meat (three muscles: striploin (longissimus thoracis et lumborum, LTL), tenderloin (psoas major, PM) and outside chuck (trapezius thoracis, TT)) at refrigeration temperatures (0 °C-10 °C) based on modelling the growth of two relevant groups of spoilage microorganisms: lactic acid bacteria (LAB) and Enterobacteriaceae. The growth models were developed combining a two-step and a one-step approach. The primary modelling was used to identify the parameters affecting the growth kinetics, guiding the definition of secondary growth models. For LAB, the secondary model included the effect of temperature and initial pH on the specific growth rate. On the other hand, the model for Enterobacteriaceae incorporated the effect of temperature on the specific growth rate and the lag phase; as well as the effect of the initial pH on the specific growth rate, the lag phase and the initial microbial count. We did not observe any significant effect of the type of muscle on the growth kinetics. Once the equations were defined, the models were fitted to the complete dataset using a one-step approach. Model validation was carried out by cross-validation, mitigating the impact of an arbitrary division between training and validation sets. The models were used to estimate the shelf life of the product, based on the maximum admissible microbial concentration (7 log CFU/g for LAB, 5 log CFU/g for Enterobacteriaceae). Although LAB was the dominant microbiota, in several cases, both LAB and Enterobacteriaceae reached the critical concentration practically at the same time. Furthermore, in some scenarios, the end of shelf life would be determined by Enterobacteriaceae, pointing at the potential importance of non-dominant microorganisms for product spoilage. These results can aid in the implementation of effective control measures in the meat processing industry.

The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art

Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10-20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation.

A Systematic Review of Beef Meat Quantitative Microbial Risk Assessment Models

Each year in Europe, meat is associated with 2.3 million foodborne illnesses, with a high contribution from beef meat. Many of these illnesses are attributed to pathogenic bacterial contamination and inadequate operations leading to growth and/or insufficient inactivation occurring along the whole farm-to-fork chain. To ensure consumer health, decision-making processes in food safety rely on Quantitative Microbiological Risk Assessment (QMRA) with many applications in recent decades. The present study aims to conduct a critical analysis of beef QMRAs and to identify future challenges. A systematic approach, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was used to collate beef QMRA models, identify steps of the farm-to-fork chain considered, and analyze inputs and outputs included as well as modelling methods. A total of 2343 articles were collected and 67 were selected. These studies focused mainly on western countries and considered Escherichia coli (EHEC) and Salmonella spp. pathogens. Future challenges were identified and included the need of whole-chain assessments, centralization of data collection processes, and improvement of model interoperability through harmonization. The present analysis can serve as a source of data and information to inform QMRA framework for beef meat and will help the scientific community and food safety authorities to identify specific monitoring and research needs.

Risk-Based Approach for Microbiological Food Safety Management in the Dairy Industry: The Case of Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

According to Codex Alimentarius Commission recommendations, management options applied at the process production level should be based on good hygiene practices, HACCP system, and new risk management metrics such as the food safety objective. To follow this last recommendation, the use of quantitative microbiological risk assessment is an appealing approach to link new risk-based metrics to management options that may be applied by food operators. Through a specific case study, Listeria monocytogenes in soft cheese made from pasteurized milk, the objective of the present article is to practically show how quantitative risk assessment could be used to direct potential intervention strategies at different food processing steps. Based on many assumptions, the model developed estimates the risk of listeriosis at the moment of consumption taking into account the entire manufacturing process and potential sources of contamination. From pasteurization to consumption, the amplification of a primo-contamination event of the milk, the fresh cheese or the process environment is simulated, over time, space, and between products, accounting for the impact of management options, such as hygienic operations and sampling plans. A sensitivity analysis of the model will help orientating data to be collected prioritarily for the improvement and the validation of the model. What-if scenarios were simulated and allowed for the identification of major parameters contributing to the risk of listeriosis and the optimization of preventive and corrective measures.

The influence of storing beef aerobically or in vacuum packs on the shelf life of mince

AIMS

To investigate the influence of aerobic or vacuum pack storage of beef trimmings on the microbiology, colour and odour of subsequently produced mince.

METHODS AND RESULTS

Trimmings stored aerobically for 7 or 10 days and in vacuum packs for 7, 10, 14 or 22 days at 0 or 5°C were minced, stored aerobically at 0 or 5°C for up to 7 days and examined daily to determine Total viable, Pseudomonas, Lactic acid bacteria, Brochothrix thermosphacta, and Enterobacteriaceae counts, colour and odour. Mincing reduced counts, particularly of Pseudomonas, B. thermosphacta and Enterobacteriaceae, probably because of the action free radicals released from muscle and bacterial cells. Storage of vacuum-packed trimmings for 22 days resulted in improved mince colour and inhibition of the growth of Pseudomonas.

CONCLUSIONS

The shelf life of mince from trimmings is directly influenced by the trimmings storage conditions, and longer-term vacuum storage of trimmings produced improvements in mince quality.

SIGNIFICANCE AND IMPACT OF THE STUDY

There appears to be no scientific rationale for limiting the storage of vacuum packaging beef trimmings to 15 days, prior to mince production, as stated in EU 835/2004. This study identifies advantages in storing trimmings in vacuum packs for at least 21 days prior to mincing, in terms of improved mince quality.

Predictive modelling of growth and measurement of enzymatic synthesis and activity by a cocktail of Brochothrix thermosphacta

The possibility was examined of developing a predictive model that combined microbial growth (increase in cellular number) and extracellular enzyme activity of a cocktail of three strains of Brochothrix thermosphacta. Estimations of growth and enzyme activity were made within a three-dimensional matrix of conditions: temperature 2-20 degrees C, pH value 4.0-7.5 and water activity (a(w)) 0.95-0.995. A model which predicted growth based on increases in cell number was constructed. No extracellular lipases were detected, but slight proteolytic reactions were observed. Although it was not possible to model protease activity, the growth model and information relating to enzyme activity will be made freely available in a database on the Internet.

Predictive food microbiology for the meat industry: a review

Predictive food microbiology (PFM) is an emerging multidisciplinary area of food microbiology. It encompasses such disciplines as mathematics, microbiology, engineering and chemistry to develop and apply mathematical models to predict the responses of microorganisms to specified environmental variables. This paper provides a critical review on the development of mathematical modelling with emphasis on modelling techniques, descriptions, classifications and their recent advances. It is concluded that the role and accuracy of predictive food microbiology will increase as understanding of the complex interactions between microorganisms and food becomes clearer. However the reliance of food microbiology on laboratory techniques and skilled personnel to determine process and food safety is still necessary.

A novel modelling approach for predicting microbial growth in a raw cured meat product stored at 3 degrees C and at 12 degrees C in air

To predict microbial growth during chill storage of a traditional Greek raw sausage, a numerical model was developed and validated. In our novel approach, the specific growth rate of each microbial population was calculated on the basis of the main microbial populations grown in the sausage. In addition, the specific destructive effect of the sausage ecosystem was introduced to evaluate microbial growth. The model was integrated by the Runge-Kutta method and the parameter values were optimised by the least squares method. Fitting of the model to the experimental data derived from four sausage batches stored aerobically at 3 and 12 degrees C successfully described the microbial growth kinetics in the sausage niche. Finally, the parameter values estimated by the fitting of the model on the data set from each batch were used to predict microbial growth in the other batches at both storage temperatures.

Mathematical modelling of microbial growth in packaged refrigerated beef stored at different temperatures

Gompertz and logistic models were fitted to experimental counts of microorganisms growing in beef stored at 0, 4, 7, 9 and 10 degrees C. Samples were packaged in polyethylene (high gaseous permeability) and in EVA/SARAN/EVA (low gaseous permeability) films, being EVA ethyl vinyl acetate and SARAN polyvinyl and polyvinylidene chloride copolymer. Lag phase duration (LPD) and specific growth rate (mu) were obtained as derived parameters for lactic acid bacteria, Enterobacteriaceae, Pseudomonas sp. and psychrotrophic microorganisms. The reciprocal of LPD was fitted to an Arrhenius type equation; LPD of lactic acid bacteria showed a marked dependence on temperature, with activation energy values (ELPD) of 222.2 and 216.9 kJ/mol for polyethylene and ESE respectively. The effect of initial microbial population at different storage temperatures on adaptation period was analyzed. As the initial microbial population increased, adaptation period decreased for all studied microorganisms and for both packaging films. The effect of temperature on specific growth rate was better interpreted by the Arrhenius model than by the linear or the square root equations. Psychrotrophic microorganisms in beef showed the highest activation energy values for specific growth rate (E mu) in both packaging films, being E mu 85.50 and 103.10 KJ/mol for polyethylene and ESE film respectively. In both films, Enterobacteriaceae showed the lowest E mu values, being 15.33 and 59.89 kJ/mol in ESE and polyethylene respectively. The final number of microorganisms (maximum population density) did not show significant changes with storage temperature.

A substrate-mediated assay of bacterial proton efflux/influx to predict the degree of spoilage of beef mince stored at chill temperatures

A method was developed to predict spoilage of minced meat at chill temperatures, based on the difference in proton efflux from and influx into bacterial cells. This difference depends on the number of organisms present, the available glucose in the meat sample and the ability of the organisms to metabolize amino acids. The proton efflux/influx of a meat filtrate containing bacteria was measured at 25 degrees C with a pH/ion meter in the presence of peptone with or without glucose. There was a noticeable rate of change of mV h-1 of the meat filtrate prior to the organoleptic detection of spoilage which may be used semi-predictively to determine the remaining shelf-life of meat at different storage temperatures. The method could be investigated further, encompassing type and relative numbers of organisms, incubation temperature, meat type and composition (i.e. available glucose) to produce a spoilage prediction model. The method does not require sophisticated equipment, only a standard pH/ion meter, is cheap, needing only peptone and glucose, is relatively simple, and takes less than 2 h to perform.

A predictive model for the combined effect of pH, sodium chloride and storage temperature on the growth of Brochothrix thermosphacta

Growth of Brochothrix thermosphacta was observed under ranges of pH (5.6-6.8), NaCl (0.5-8.0% w/v) and incubation temperature (1-30 degrees C). In order to compare different approaches, two models were used to fit growth curves to viable count data, and to calculate parameters from those fitted curves. Growth responses as a function of pH, NaCl and temperature were described with a quadratic function which was then used to predict growth within the limits where growth was observed. The predictions of the model show good agreement with published observations from other laboratories.