Determination and prediction of thermal conductivity of frozen part baked bread during thawing and baking

Jury, Vanessa; Monteau, Jean‐Yves; Comiti, Jacques; Le‐Bail, Alain

doi:10.1016/j.foodres.2007.02.006

Cited by 22 publications

(16 citation statements)

References 18 publications

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“…Thermal properties can be determined using transient temperature measurements method or steady state method with the former being the dominant and preferred method for many reasons including; accuracy, efficiency, flexibility and applicability to large class of foods. The classical line heat source probe method developed by Van der Held and Van Drunen (1949) is one of the transient methods which continue to be one of the popular methods for determination of thermal conductivity (Gratzek & Toledo, 1993;Jury, Monteau, Comiti, & Le-Bail, 2007;Kumcuoglu, Tavman, Nesvadba, & Tavman, 2007;Murakami & Okos, 1988;Njie, Rumsey, & Singh, 1998;Sweat, 1974;Sweat, Haugh, & Stadelman, 1973;Wang & Hayakawa, 1993a, 1993b. The line heat source probe method was based on several assumption; including negligible mass and volume of the line heat source probe, an infinite heat conduction medium with constant thermal conductivity and initial uniform temperature distribution.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous estimation of thermal conductivity and volumetric heat capacity for solid foods using sequential parameter estimation technique

Mohamed

2009

Food Research International

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Section: Introductionmentioning

confidence: 99%

Simultaneous estimation of thermal conductivity and volumetric heat capacity for solid foods using sequential parameter estimation technique

Mohamed

2009

Food Research International

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“…The experiment with the hot wire probe is based on the application of a constant heat flux from the heat source to the material, initially at equilibrium, thereby generating a variation in temperature of T o to T. [13,[15][16][17][18] To review the theoretical thermal conductivity, the existence of a relationship between the effective thermal conductivity of a food with the intrinsic conductivities of its components and their individual volume fraction is assumed, as described by Eq. (2).…”

Section: Mathematical Analysis and Theoretical Models For The Evaluatmentioning

confidence: 99%

Thermal Conductivity of Mango Pulp (Mangifera indicaL.) Cultivar “Ubari” in Freezing Temperatures

Giarola

Pereira

Resende

2015

International Journal of Food Properties

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The aim of this study was the experimental determination of the thermal conductivity of mango pulp of cultivar "ubari" and its subsequent comparison with values estimated using different structural models, such as the serial, parallel, and Maxwell-Eucken models. A linear heating probe calibrated with a solution of 10% sucrose was utilized. Heat was applied to the probe, generating an increase in temperature, which was recorded through a signal conditioning system. The thermal conductivity of the pulp was calculated from the slope obtained by linear regression of the natural logarithm of the temperature versus time. The data was within the range of 0.465 to 1.595 W/m.K for temperatures of 0 and -30°C, respectively, showing an increase of conductivity with freezing. The initial freezing temperature and ice fraction were determined at every temperature of analysis for further use in the models. The best fit to the experimental data were obtained using the Maxwell-Eucken model, yielding minimum and maximum errors of 10.8 and 17.8%, respectively. An exponential model was fitted, which allowed for the direct calculation of the thermal conductivity of mango pulp using only the knowledge of the recorded temperature during thermal processing.

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“…This operator has been approximated by Koelman, 6 using the Fig. 6 The first part of the thermal conductivity curve is obtained from experimentation made by Jury 15 and shows an increase in conductivity with temperature. The second part of the curve represents the conductivity in the crust; this drop is due to the fall of the water content in the crust which resembles a dive in the conductivity.…”

Section: Thermal Diffusionmentioning

confidence: 99%

“…Equation 15 can be explained using Figure 9: The collision of particles is considered as a relaxation towards a local equilibrium distribution, ƒ equ , and taking relaxation time, τ r . The reciprocal of the relaxation time, 1/τ r , may be replaced by the relaxation frequency, ω, sometimes referred to as the relaxation parameter.…”

Section: Thermal Diffusionmentioning

confidence: 99%

An Innovative Micro-Modelling of Simultaneous Heat and Moisture Transfer during Bread Baking Using the Lattice Boltzmann Method

Hussein

Becker

2010

Food Biophysics

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A considerable fraction of the energy consumed in bread manufacturing is used for the baking process. A thorough understanding of internal moisture transfer mechanisms are important to optimise both the quality of the product and the economics of the process. From a transport phenomena point of view, bread baking has been considered as a simultaneous heat and mass transfer problem in a porous medium. Nevertheless, most efforts previously made have avoided modelling the phenomenon occurring in the microscale, although the mechanism occurs primarily in the microscale. In this work heat and moisture transfer models were developed to accomplish the mechanisms included, both in the microscale and the macroscale by means of Boltzmann's equation. Modelling and predictions of moisture transfer, heat transfer, modelling of effective moisture diffusivity, thermal conductivity and diffusivity have been investigated in this work. The microstructure in the dough samples was obtained using micro-computer tomography images from the samples prior to baking. The models were quantified and validated with measurements from the literature in order to assess the predictive models. The simulated crust development has shown a crust thickness of 0.8 cm, which is slightly higher than similar experimental results in which a dehydrated thickness of 0.5-0.6 cm was reported. The crust over-estimation in this work fits to the overheating occurring in the model. Additionally, investigations were made on the influence of different porosities (11-16%) of the bread; the boundary layer temperature at a porosity of 11% was reached after 25 min and after 17.5 min at a porosity of 16%. Therewith, the results showed that, with increasing porosity, the heat transfer rate towards the centre was higher, which matches the knowledge of experienced bakers.

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Determination and prediction of thermal conductivity of frozen part baked bread during thawing and baking

Cited by 22 publications

References 18 publications

Simultaneous estimation of thermal conductivity and volumetric heat capacity for solid foods using sequential parameter estimation technique

Simultaneous estimation of thermal conductivity and volumetric heat capacity for solid foods using sequential parameter estimation technique

Thermal Conductivity of Mango Pulp (Mangifera indicaL.) Cultivar “Ubari” in Freezing Temperatures

An Innovative Micro-Modelling of Simultaneous Heat and Moisture Transfer during Bread Baking Using the Lattice Boltzmann Method

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