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  4. /Thermal Conductivity of Food

Thermal Conductivity of Food

Calculator

Results

Thermal Conductivity k (W/m·K)

0.4589

Results

Thermal Conductivity k (W/m·K)

0.4589

The Thermal Conductivity of Food calculator estimates the thermal conductivity (k) of a food product from its proximate composition using the Choi-Okos model. Thermal conductivity is the rate at which heat flows through a material per unit area per unit temperature gradient, measured in watts per metre per Kelvin (W/m·K). It is the primary material property governing heat transfer rates during cooking, pasteurisation, sterilisation, chilling, and freezing of food products.

The Choi-Okos parallel model for thermal conductivity uses component-specific coefficients at approximately 25 °C: water (0.57109 W/m·K), protein (0.17881 W/m·K), fat (0.18071 W/m·K), carbohydrate (0.20141 W/m·K), and ash (0.35765 W/m·K). Water is again the dominant component — its thermal conductivity (0.571 W/m·K) is approximately three times higher than fat (0.181 W/m·K) and protein (0.179 W/m·K). This explains why dry foods heat much more slowly than wet foods of similar dimensions.

Thermal conductivity is used in heat transfer calculations via Fourier's Law: Q = -k × A × (dT/dx), where Q is heat flux (W), A is area (m²), and dT/dx is the temperature gradient (K/m). In food engineering, this is applied to determine heating rates, hotspot and cold spot analysis during retort sterilisation, heat penetration testing for HACCP critical limit validation, and the design of heat exchangers and cooling tunnels.

The thermal conductivity of frozen food is substantially higher than that of unfrozen food, because ice has a thermal conductivity of approximately 2.22 W/m·K — nearly four times that of liquid water. This is why frozen food freezes and thaws faster than one might expect: the ice itself conducts heat more efficiently than water. The transition zone during freezing, where ice and water coexist, has complex conductivity behaviour that must be modelled carefully in freezing time calculations (Plank's equation and its modifications account for this).

Porous and aerated foods (bread, foam, emulsions) have effective thermal conductivities significantly lower than predicted by the parallel model, because air (k = 0.026 W/m·K) is a very poor conductor and disrupts heat transfer pathways. For such materials, the Maxwell-Eucken or effective medium models are more appropriate. The parallel model presented here is best applied to dense, moist food products without significant air incorporation.

How It Works

Thermal conductivity k = 0.57109·Xw + 0.17881·Xp + 0.18071·Xf + 0.20141·Xc + 0.35765·Xa (W/m·K) using Choi-Okos component coefficients at 25 °C. Mass fractions of all components must sum to 1.0.

Understanding Your Results

A result of 0.45 W/m·K for a meat product means heat transfers at a moderate rate — typical for muscle food. A result of 0.12 W/m·K for a high-fat product means heat transfer is slow, requiring longer process times to achieve the same temperature rise at the centre compared to a comparable high-moisture product.

Worked Examples

Lean Beef Muscle (Xw=0.74, Xp=0.22, Xf=0.02, Xc=0.01, Xa=0.01)

Inputs

Xw0.74
Xp0.22
Xf0.02
Xc0.01
Xa0.01

Results

k W mK0.4796

Lean beef at 0.480 W/m·K is consistent with measured literature values of 0.45–0.52 W/m·K for raw lean muscle at room temperature.

Butter (Xw=0.16, Xp=0.007, Xf=0.80, Xc=0.001, Xa=0.02)

Inputs

Xw0.16
Xp0.007
Xf0.8
Xc0.001
Xa0.02

Results

k W mK0.2396

Butter at 0.24 W/m·K has about half the thermal conductivity of lean beef, reflecting its high fat content. This means butter heats and cools more slowly per unit thickness.

Frequently Asked Questions

Thermal conductivity (k) measures how quickly heat flows through a food material. High-k foods (wet, watery) heat and cool faster. Low-k foods (dry, fatty) heat and cool more slowly. k is essential for calculating process times in pasteurisation, sterilisation, chilling, and freezing.

Ice (k ≈ 2.22 W/m·K at 0 °C) conducts heat about 4× faster than liquid water (k ≈ 0.57 W/m·K). In crystalline ice, lattice phonon vibrations transfer thermal energy efficiently, whereas in liquid water, the less-ordered structure is less efficient at conducting heat.

Fresh apples have k around 0.40–0.45 W/m·K. Fresh tomatoes: 0.50–0.56 W/m·K. Potatoes: 0.50–0.55 W/m·K. These values reflect the high water content (85–95 %) of fresh produce and allow reasonably rapid heat penetration during blanching or cooling.

Lower thermal conductivity means heat penetrates more slowly from the surface to the centre of the product. For solid or semi-solid foods (blocks of cheese, canned vegetables), k determines whether the centre reaches the lethal temperature within the process time. Under-processing due to low k is a food safety risk.

The Choi-Okos model (1986) provides temperature-dependent equations for thermal conductivity, specific heat, density, and thermal diffusivity of each major food component (water, protein, fat, carbohydrate, ash, ice). Summing the compositional contributions gives total food thermal properties at any temperature.

Air has very low thermal conductivity (0.026 W/m·K). Aerated foods (bread, foam, marshmallow) have much lower effective thermal conductivity than their composition alone predicts. For bread, measured k is 0.07–0.18 W/m·K, far below the parallel model prediction for its wet dough composition, due to the insulating effect of the numerous air cells.

Thermal diffusivity (α) = k / (ρ × Cp), where ρ is density. It represents how quickly temperature equalises within the food. Typical values for most foods: 1.0–1.7 × 10⁻⁷ m²/s. Thermal diffusivity combines conductivity, density, and specific heat into a single parameter for heat penetration calculations.

Common methods: the line-heat source probe (transient hot wire method), the guarded hot plate apparatus (steady-state), or the modified Fitch apparatus for solid foods. The probe method (ASTM D5334) is most practical for food laboratories and gives results in minutes on a small sample.

Yes significantly. Cooking reduces moisture content (increases fat fraction in apparent composition), denatures proteins (changes matrix structure), and gelatinises starches. Cooked meat typically has slightly lower k than raw meat at the same temperature due to protein denaturation and moisture loss during cooking.

Use the lowest expected value for the product under the worst-case conditions (highest fat, lowest moisture, highest temperature) to ensure conservative (safe) process design. Under-estimating k leads to under-processing; using conservative low k values ensures adequate heat treatment is always achieved.

Sources & Methodology

Choi, Y. and Okos, M.R. (1986) Effects of temperature and composition on thermal properties of foods. Food Engineering and Process Applications, Vol. 1:93-101; Saravacos, G.D. and Maroulis, Z.B. (2001) Transport Properties of Foods. Marcel Dekker.
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