The Thermal Conductivity of Beef as Affected by Temperature and Composition (original) (raw)
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Effect of Cooking on the Thermal Conductivity of Whole and Ground Lean Beef
Journal of Food Science, 1981
ABSTRACTThe probe method was used to measure thermal conductivity of beef through a temperature range of 30–120°C. Thermal conductivity of beef increases with temperature up to 70°C followed by a decrease during the denaturation of proteins and subsequent loss of water. The thermal conductivity of beef again increases with temperature after protein denaturation. The thermal conductivity of cooked beef is lower than raw beef up to about 80°C. The rate of increase for cooked meat thermal conductivity is fairly constant with temperature at a given moisture content. Models based on composition and temperature were found to predict the thermal conductivity of meat during cooking at an average standard percent error of 7%.
International Journal of Food Properties, 2008
Thermal conductivities of four fish types were measured and presented as functions of temperatures and moisture contents which ranged from 5-40°C and 30 to 75% (wet basis, wb), respectively. Transient techniques using a commercially constructed line source probe was followed. Fish types included Hamam (yellow-Spotted Trevally), Kanad (Spanish Macherel), Shaoor (Emperor) and Hamour (Grouper). The obtained values for thermal conductivities varied from 0.17±0.01 W/m.°C (for Hamour at 5°C and 30% moisture content) to 0.617±0.03 W/m.°C (for Hamam at 40°C and 75% moisture content). These results agreed well with those in the literature for other types. Based on statistical analysis, mathematical models relating thermal conductivity with temperature and moisture content were proposed using a multiple regression analysis fitting procedure. The statistical analysis results indicated that the effect of temperature and moisture content were significant with regard to the ranges studied and proved that the relationships obtained may represent the behavior for the prediction of the thermal conductivities in the measured ranges.
THERMAL CONDUCTIVITY LITERATURE DATA COMPILATION FOR FOODSTUFFS
Published experimental data on thermal conductivity of food materials are scattered, and their utilization in food processing operations is difficult. Data of thermal conductivity for various foods in recent literature were classified and analyzed. The results of more than 100 food materials, classified in 11 food categories, are presented. The results concern the reported range of variation of moisture data together with the corresponding range of material moisture content and temperature. The relative literature sources are presented for each food material.
Journal of Food Processing and Preservation, 2010
ABSTRACTThermal conductivity values of meat samples with moisture contents between 4.73 and 79.47% (wet basis) and fat contents between 1.44 and 93.17% (wet basis) were measured at temperatures ranging from−30 to 25C using the line heat source probe method. Thermal conductivities of frozen meat samples were higher than the ones in the unfrozen state. Measured thermal conductivity values were mathematically interpreted as a function of temperature, moisture, protein and fat contents by application of nonlinear regression analysis for frozen samples. Measured thermal conductivities were compared with the models given in the literature. Levy's model provided more accurate predictions than the others in the frozen state and parallel model showed the best predictions in the unfrozen state. For unfrozen state, thermal conductivity was found to increase with moisture content and decrease with fat content, although in the frozen state, thermal conductivity increases with decreasing temperature.Thermal conductivity values of meat samples with moisture contents between 4.73 and 79.47% (wet basis) and fat contents between 1.44 and 93.17% (wet basis) were measured at temperatures ranging from−30 to 25C using the line heat source probe method. Thermal conductivities of frozen meat samples were higher than the ones in the unfrozen state. Measured thermal conductivity values were mathematically interpreted as a function of temperature, moisture, protein and fat contents by application of nonlinear regression analysis for frozen samples. Measured thermal conductivities were compared with the models given in the literature. Levy's model provided more accurate predictions than the others in the frozen state and parallel model showed the best predictions in the unfrozen state. For unfrozen state, thermal conductivity was found to increase with moisture content and decrease with fat content, although in the frozen state, thermal conductivity increases with decreasing temperature.PRACTICAL APPLICATIONSThermal properties of food products are key factors in the design of thermal processes such as cooling or heating for food preservation. Analysis, design and simulation of food freezing and storage process demands reliable and easily accessible thermal property data across a wide range of temperatures, particularly below freezing. Thermal conductivity is an important property for freezing and thawing applications. An accurate knowledge of thermal conductivity as a function of composition and temperature is important to determine process parameters involved in heat transfer. Then, the total amount of heat to be added or removed from a product in a specific process can be determined as well as the rate at which heat can be added or removed. The model developed in this study can be used to model heat transfer calculations in freezing, thawing and storage of meats.Thermal properties of food products are key factors in the design of thermal processes such as cooling or heating for food preservation. Analysis, design and simulation of food freezing and storage process demands reliable and easily accessible thermal property data across a wide range of temperatures, particularly below freezing. Thermal conductivity is an important property for freezing and thawing applications. An accurate knowledge of thermal conductivity as a function of composition and temperature is important to determine process parameters involved in heat transfer. Then, the total amount of heat to be added or removed from a product in a specific process can be determined as well as the rate at which heat can be added or removed. The model developed in this study can be used to model heat transfer calculations in freezing, thawing and storage of meats.
The effects of temperature and muscle composition on the thermal conductivity of frozen meats
Journal of Food …, 2010
Thermal conductivity values of meat samples with moisture contents between 4.73 and 79.47% (wet basis) and fat contents between 1. 44 and 93.17% (wet basis) were measured at temperatures ranging from -30 to 25C using the line heat source probe method. Thermal conductivities of frozen meat samples were higher than the ones in the unfrozen state. Measured thermal conductivity values were mathematically interpreted as a function of temperature, moisture, protein and fat contents by application of nonlinear regression analysis for frozen samples. Measured thermal conductivities were compared with the models given in the literature. Levy's model provided more accurate predictions than the others in the frozen state and parallel model showed the best predictions in the unfrozen state. For unfrozen state, thermal conductivity was found to increase with moisture content and decrease with fat content, although in the frozen state, thermal conductivity increases with decreasing temperature.
Heat conductivity of some food products: theoretical models and practical measurements
2018
Thermo-physical properties are necessary for the design and prediction of heat transfer operation during handling, processing, canning, and distribution of foods. Thermal conductivity is defined as the ability of a material to conduct heat. There are steady-state and transient-state methods for measurement of thermal conductivity. The most commonly used transient methods are the thermal conductivity probe method, transient hot wire method, modified Fitch method, point heat source method, and comparative method. In this paper the modified Fitch method was used in order to measure thermal conductivity; the results were compared with the one predicted by some heat conductivity models: series model, parallel model, the weighted geometric mean method. Experimental tests and calculations were applied to the following food items: dry salami (salam uscat CrisTim); Transylvanian salami (salam ardelenesc); rustic sausage (parizer ţărănesc Caroli). The experimental tests were performed immedia...
Electrical Conductivity as an Indicator of Pork Meat Quality
Journal of Central European Agriculture, 2010
The performed experiments allowed determining to what extent meat electrical conductivity measured at two time intervals (EC 90' and EC 24h) may affect significantly the selected pork meat quality parameters. The experimental material comprised 75 carcasses, of which 32 were carcasses derived from hogs of line 990 and 43 were carcasses of Danish hybrid hogs [(L x Y) x Du]. The following parameters were investigated: electrical conductivity (EC 90' and EC 24h), thermal drip and water holding capacity content as well as meat texture (tenderness and juiciness). After the assessment of meat electrical conductivity, the obtained results were divided into three groups taking into consideration differences in their values: EC 90' : up to 3.50 mS/cm; from 3.51-5.00 mS/cm; > 5.00 mS/cm, and EC 24h measurement: up to 4.99 mS/cm; from 5.00-8.00 mS/cm; > 8.00 mS/cm. It is clear from the performed investigations that measurements of meat electrical conductivity carried out 24 h after the slaughter of animals, in comparison with the measurements taken 90' after slaughter, was correlated with the examined meat parameters higher degree.
Measurement of thermal conductivity of dairy products
Journal of Food Engineering, 1999
Thermal conductivity of eleven kinds of cheese, four kinds of yogurt and a butter sample has been measured at about 15°C and 30°C. A modi®ed hot wire method was used for thermal conductivity measurements. The eect of the water, fat and protein content on the thermal conductivity has been investigated, the measured thermal conductivity values were linearly dependent on water content, and inversely dependent on fat and protein contents of the various dairy products. A slight increase in the thermal conductivity with temperature has been noticed for four cheese samples studied over a wider range of temperature, between 4°C and 44°C. Ó 0260-8774/99/$ -see front matter Ó 1999 Elsevier Science Ltd. All rights reserved. PII: S 0 2 6 0 -8 7 7 4 ( 9 9 ) 0 0 0 7 9 -5
A model for the thermal conductivity of frozen meat
Meat Science, 1977
Even though extensive work on the experimental determination of" the thermal conductivities o./'JbodstuJ]s at different temperatures has been published, only a Jew predictive models for this important property have been developed. Calculation o f freezing times inJbods, such as meat, over the range_from-I °C to-30 °C, requires the use of mathematical models in which information on the thermal conductivity of partially f~'o-en meat as a function of ice content in the tissue is provided. In the present paper a model fbr the thermal conductivity oJmeat as a fimction of" temperature, which also accounts for its anisotropic properties, is proposed. Both directions, parallel and perpendicular to meat fibres, are considered and the model applies to unfrozen as well as to partially J~'o:en meat. Res,dts show good agreement with published experimental data obtained by a stead)' state method for different temperatures. NOM ENCLATURE A,B,C et, e2, fl, 1"2 F ka kc kcl. k~p Constants defined in eqns. (15), (16) and (17) respectively. Coefficients in eqns. (19) and (20). Constant in eqn. (18). Water thermal conductivity (W/mK). Thermal conductivity of the continuous matrix. Thermal conductivity of the continuous matrix parallel to the meat fibre direction. Thermal conductivity of the continuous matrix perpendicular to the meat fibre direction. 235 Meat Science (i) (1977)-~ Applied Science Publishers Ltd. England. 1977