Effect of Packaging Materials on Temperature Fluctuations in Frozen Foods: Mathematical Model and Experimental Studies

Zuritz, Carlos A.; Sastry, Sudhir K.

doi:10.1111/j.1365-2621.1986.tb11229.x

Cited by 27 publications

(5 citation statements)

References 6 publications

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“…where h i and h e are the external and internal convective heat transfer coefficient (W/m 2 K), δ p is the packaging thickness (m) and k p is the thermal conductivity (W/m K) of the packaging material. Although this expression is strictly valid for stationary heat transfer conditions, it can be used for unsteady‐state situations if the transient effects of the packaging materials can be ignored, which occurs if the following inequality is fulfilled (Zuritz and Sastry 1986):…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Uncertainty of Microbial Shelf‐life Estimations for Refrigerated Foods Due to the Experimental Variability of the Model Parameters

Almonacid¹,

Torres²

2010

J Food Process Engineering

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The uncertainty of shelf‐life estimations for refrigerated foods exposed to changing temperature was quantified by considering the contribution of the experimental variability of the model parameters. Assuming the real distribution of the parameters can be replaced by an unknown empirical distribution, this uncertainty was analyzed by a bootstrap methodology. Independent sets of heat transfer and microbial growth parameters were chosen randomly from experimental values. Shelf‐life values were estimated for each set, with the variability evaluated using an SD value. The procedure was repeated 10 times to obtain 10 shelf‐life SDs. The variation coefficient of these SDs is an absolute measurement of shelf‐life variability. At the recommended variation coefficient of 0.1, a sample size of 25 was found acceptable. The shelf‐life variability estimated was similar (±1 day) for surimi in cardboard and expanded polystyrene containers with different shelf life and temperature profiles. The method is applicable to other predictions of food stability. PRACTICAL APPLICATIONS The effect of the experimental variability of model parameters on shelf‐life estimations confirmed the need to assess the uncertainty of model predictions. Another beneficial aspect of the approach presented is that it encourages an integrated approach to food safety and shelf life. Decisions on raw materials and modifications to processing operations affect the initial microbial load of a product. Improvement of storage, distribution and retail facilities reduces temperature abuse. Product size, geometry and packaging choice are also aspects that should be considered. The impact on shelf life of all these factors can be examined by the integrated microbial and heat‐transfer models of the type here presented. The increasing availability of microbial growth parameters and electronic recorders to monitor temperature during processing, storage and distribution facilitate their implementation. The impact of the experimental variability of model parameters is important. For example, this study suggested the need for microbial determinations with lower experimental variability.

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Section: Methodsmentioning

confidence: 99%

“…The expression suggested by Zuritz and Sastry (1986) to support the use of an overall heat transfer coefficient in the heat transfer model (Eq. 2) yielded values of 451 and 182 for surimi in the EPS and cardboard containers, respectively.…”

Section: Overall Heat Transfer Coefficientsmentioning

confidence: 99%

Uncertainty of Microbial Shelf‐life Estimations for Refrigerated Foods Due to the Experimental Variability of the Model Parameters

Almonacid¹,

Torres²

2010

J Food Process Engineering

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“…Temperature fluctuations in stored frozen foods have been studied by Zuritz and Singh (1985) and the effects of packaging materials on the temperature fluctuations by Zuritz and Sastry (1986).…”

Section: Temperature Equilibration Time Prediction Modelmentioning

confidence: 99%

COMPUTER SIMULATION of MICROBIAL GROWTH DURING FREEZING and FROZEN FOOD STORAGE

Castell‐Perez

Heldman²,

Steffe

1988

J Food Process Engineering

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A computer simulation model was developed to predict the time for temperature equilibration as well as microbial growth within a food product during freezing and the equilibration to frozen storage conditions. Theoretical results indicate that freezing medium temperature, surface heat transfer coefficient and product size influence the equilibration time significantly. Storage conditions influenced the equilibration time during storage and significantly influenced the growth of microorganisms. Microbial growth is a function of the freezing time. Slow freezing of a food product from a high initial temperature and stored at a relatively high temperature can provide conditions for microbial growth as compared to very rapid freezing processes. the model is a useful tool for approximate indications of effects of freezing conditions on microbial growth within a food product.

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“…Considerable effort has been put in studying thermal load effects on refrigerated food and to relate product temperature changes to abusive ambient conditions and thermal properties of the food and packaging solutions (Zuritz and Sastry, 1986;Dolan et al, 1987;Almonacid-Merino and Torres, 1993;Moureh and Derens, 2000;Tanner et al, 2002a,b;Stubbs et al, 2004;Laguerre et al, 2008;Mai et al, 2011;Margeirsson et al, 2011aMargeirsson et al, ,b, 2012. Both experimental and numerical methods have been used in these studies to show that the temperature distribution in single packages and in whole pallets subjected to thermal load is in general inhomogeneous, with highest temperatures at the corners of the packages/pallets and the most stable temperatures at the centre of the packages/pallets.…”

Section: Introductionmentioning

confidence: 99%

Numerical modelling of temperature fluctuations of chilled and superchilled cod fillets packaged in expanded polystyrene boxes stored on pallets under dynamic temperature conditions

Margeirsson

Pálsson

Gospavić

et al. 2012

Journal of Food Engineering

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Effect of Packaging Materials on Temperature Fluctuations in Frozen Foods: Mathematical Model and Experimental Studies

Cited by 27 publications

References 6 publications

Uncertainty of Microbial Shelf‐life Estimations for Refrigerated Foods Due to the Experimental Variability of the Model Parameters

Uncertainty of Microbial Shelf‐life Estimations for Refrigerated Foods Due to the Experimental Variability of the Model Parameters

COMPUTER SIMULATION of MICROBIAL GROWTH DURING FREEZING and FROZEN FOOD STORAGE

Numerical modelling of temperature fluctuations of chilled and superchilled cod fillets packaged in expanded polystyrene boxes stored on pallets under dynamic temperature conditions

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