Heat processing

10 Heat processing Abstract: This chapter describes the thermal properties of foods and mechanisms of heat transfer, and how these are used to calculate rates of heat transfer in food processing operations. It describes common sources of heat and outlines the operation of heating equipment and methods used to reduce energy consumption. Finally, the effects of heat on micro-organisms, enzymes and food components are outlined. Key words: thermal conductivity, thermal diffusivity, heat transfer, conduction, convection, heat exchangers, properties of steam, energy saving, heat resistance of micro-organisms, D-value, z-value.

This chapter describes the thermal properties of foods and mechanisms of heat transfer, and how these are used to calculate rates of heat transfer under different conditions. It describes the sources of heat that are commonly used in food processing and outlines the methods of operation of heating equipment. Details of individual types of equipment are given in subsequent chapters (11±20), in which unit operations that involve heating are described. Finally, the effects of heat on micro-organisms, enzymes and food components are outlined, again with details of the effects of each unit operation provided in subsequent chapters. Further details of each of these aspects are given by Richardson (2001).

10.1

Theory

10.1.1 Thermal properties of foods Three important thermal properties of foods are specific heat, thermal conductivity and thermal diffusivity. Specific heat is the amount of heat needed to raise the temperature of 1 kg of a material by 1 ëC. It is found using Equation 10.1 and specific heat values for selected foods and other materials are given in Table 10.1. Q 10:1 cp ˆ m…1 ÿ 2 † where cp (J kgÿ1 ëCÿ1) ˆ specific heat of food at constant pressure, Q (J) ˆ heat gained or lost, m (kg) ˆ mass and 1 ÿ 2 (ëC) ˆ temperature difference.

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Table 10.1 Specific heat of selected foods and other materials Material Foods ± solid Apples Apples Bacon Beef Bread Butter Carrots Cod Cod Cottage cheese Cucumber Flour Lamb Lamb Mango Milk ± dry Milk ± skim Potatoes Potatoes Sardines Shrimps Foods ± liquid Acetic acid Ethanol Milk ± whole Oil ± maize Oil ± sunflower Orange juice Water Water Water vapour Ice Non-foods ± solid Aluminium Brick Copper Glass Glass wool Iron Stainless steel Stone Tin Wood Non-foods ± gases Air Carbon dioxide Oxygen Nitrogen

Specific heat (kJ kgÿ1 ëCÿ1)

Temperature (ëC)

3.59 1.88 2.85 3.44 2.72 2.04 3.86 3.76 2.05 3.21 4.06 1.80 2.80 1.25 3.77 1.52 3.93 3.48 1.80 3.00 3.40

Ambient Frozen Ambient Ambient ± Ambient Ambient Ambient Frozen Ambient Ambient ± Ambient Frozen Ambient Ambient Ambient Ambient Frozen Ambient Ambient

2.20 2.30 3.83 1.73 1.93 3.89

20 20 Ambient 20 20 Ambient

4.18 2.09 2.04

15 100 0

0.89 0.84 0.38 0.84 0.7 0.45 0.46 0.71±0.90 0.23 2.4±2.8

20 20 20 20 20 20 20 20 20 20

1.005 0.80 0.92 1.05

Ambient 0 20 0

Adapted from Anon (2005c, 2007a), Singh and Heldman (2001a) and Polley et al. (1980)

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The specific heat of compressible gases is usually quoted at constant pressure, but in some applications where the pressure changes (e.g. vacuum evaporation (Chapter 14, section 14.1) or high-pressure processing (Chapter 8) it is quoted at constant volume (Cv). The specific heat of foods depends on their composition, especially the moisture content (Equation 10.2). Equation 10.3 is used to estimate specific heat and takes account of the mass fraction of the solids contained in the food: cp ˆ 0:837 ‡ 3:348M

10:2

where M ˆ moisture content (wet-weight basis, expressed as a fraction not percentage), cp ˆ 4:180Xw ‡ 1:711Xp ‡ 1:928Xf ‡ 1:547Xc ‡ 0:908Xa

10:3

where X ˆ mass fraction and subscripts w ˆ water, p ˆ protein, f ˆ fat, c ˆ carbohydrate and a ˆ ash. Thermal conductivity is a measure of how well a material conducts heat. It is the amount of heat that is conducted through unit thickness of a material per second at a constant temperature difference across the material and is found using Equation 10.4. kˆ

Q t

10:4

where k (J sÿ1 mÿ1 ëCÿ1 or W mÿ1 ëCÿ1) ˆ thermal conductivity and t (s) ˆ time. Thermal conductivity is influenced by a number of factors concerned with the nature of the food (e.g. cell structure, the amount of air trapped between cells, moisture content), and the temperature and pressure of the surroundings. A formula to predict thermal conductivity based on the composition of foods is shown in Equation 10.5: k ˆ kw Xw ‡ ks …1 ÿ Xw †

10:5

where kw (W mÿ1 ëCÿ1) ˆ thermal conductivity of water, Xw ˆ mass fraction of water, ks ˆ (W mÿ1 ëCÿ1) ˆ thermal conductivity of solids (assumed to be 0.259 W mÿ1 ëCÿ1). A reduction in moisture content causes a substantial reduction in thermal conductivity. This has important implications in unit operations which involve conduction of heat through food to remove water (e.g. drying (Chapter 16), frying (Chapter 19) and freeze drying (Chapter 23)). In freeze drying the reduction in atmospheric pressure also influences the thermal conductivity of the food. Ice has a higher thermal conductivity than water and this is important in determining the rate of freezing and thawing (Chapter 22). The importance of thermal conductivity is shown in sample problem 10.1 and sample problem 11.1 (Chapter 11). The thermal conductivities of some materials found in food processing are shown in Table 10.2. Although, for example, stainless steel conducts heat ten times less well than aluminium (Table 10.2), the difference is small compared with the low thermal conductivity of foods (20 to 30 times lower than steel) and does not limit the rate of heat transfer. Stainless steel is much less reactive than other metals, and is therefore used in most food processing equipment that comes into contact with foods. Thermal diffusivity is a measure of a material's ability to conduct heat relative to its ability to store heat. It is a ratio involving thermal conductivity, density and specific heat, and is found using Equation 10.6: ˆ

k cp

10:6

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Table 10.2 Thermal conductivity of selected foods and other materials Material Food Acetic acid Apple juice Avocado Beef, frozen Bread Carrot Cauliflower, frozen Cod, frozen Egg, frozen liquid Ethanol Freeze dried foods Green beans, frozen Ice Milk, whole Oil, olive Orange Parsnip Peach Pear Pork Potato Strawberry Turnip Water Gases Air Air Carbon dioxide Nitrogen Packaging materials Cardboard Glass Polyethylene Poly(vinylchloride) Metals Aluminium Copper Stainless steel Other materials Brick Concrete Insulation Polystyrene foam Polyurethane foam

Thermal conductivity (W mÿ1 ëCÿ1)

Temperature (ëC)

0.17 0.56 0.43 1.30 0.16 0.56 0.80 1.66 0.96 0.18 0.01±0.04 0.80 2.25 0.56 0.17 0.41 0.39 0.58 0.59 0.48 0.55 0.46 0.48 0.57

20 20 28 ÿ10 25 40 ÿ8 ÿ10 ÿ8 20 0 ÿ12 0 20 20 15 40 28 28 3.8 40 28 40 20

0.024 0.031 0.015 0.024

0 100 0 0

0.07 0.52 0.55 0.29

20 20 20 20

220 388 17±21

0 0 20

0.69 0.87 0.026±0.052 0.036 0.026

20 20 30 0 0

Adapted from Anon (2007a,b), Choi and Okos (2003), Singh and Heldman (2001a) and Lewis (1990)

where  (m2 sÿ1) ˆ thermal diffusivity and  (kg mÿ3) ˆ density. Thermal diffusivity is used to calculate time±temperature distribution in materials undergoing heating or cooling and selected examples are given in Table 10.3. The thermal diffusivity of foods is influenced by their composition, especially their moisture content, and it can be estimated using Equation 10.7:

Heat processing Table 10.3

343

Thermal diffusivity of selected foods

Food Apples Avocado Banana Beef Cod Ham, smoked Lemon Peach Potato Strawberry Sweet potato Tomato Water Water Ice

Thermal diffusivity ( 10ÿ7 m2 sÿ1)

Temperature (ëC)

1.37 1.24 1.18 1.33 1.22 1.18 1.07 1.39 1.70 1.27 1.06 1.48 1.48 1.60 11.82

0±30 41 5 40 5 5 0 4 25 5 35 4 30 65 0

Adapted from Singh and Heldman (2001a) and Murakami (2003)

 ˆ 0:146  10ÿ6 Xw ‡ 0:100  10ÿ6 Xf ‡ 0:075  10ÿ6 Xp ‡ 0:082  10ÿ6 Xc

10:7

where X ˆ mass fraction and subscripts w ˆ water, f ˆ fat, p ˆ protein and c ˆ carbohydrate. For example, every 1% increase in the moisture content of vegetables corresponds to a 1±3% increase in their thermal diffusivity (Murakami 2003). Changes in the volume fraction of air can also significantly alter the thermal diffusivity of foods. During heating, the temperature does not have a substantial effect on thermal diffusivity, but in freezing the temperature is important because of the different thermal diffusivities of ice and water. `Sensible' heat is the heat needed to raise the temperature of a food and is found using Equation 10.4, rearranged from Equation 10.1: Q ˆ m  cp …1 ÿ 2 †

10:8 ÿ1

ÿ1

ÿ1

where Q (J) ˆ sensible heat, m (kg) ˆ mass, cp (J kg ëC or K ) ˆ specific heat of food at constant pressure and  (ëC) ˆ temperature with subscripts 1 and 2 being initial and final values. Phase changes in water are important in many types of food processing including steam generation for process heating (section 10.2), evaporation by boiling (Chapter 14, section 14.1), loss of water during dehydration, baking and frying (Chapters 16, 18, 19) and in freezing (Chapter 22). `Latent' heat is the heat used to change phase (e.g. latent heat of fusion to form ice, or latent heat of vaporisation to change water to vapour) where the temperature remains constant while the phase change takes place. A phase diagram (Fig. 23.2 in Chapter 23) shows how temperature and pressure control the state of water (solid, liquid or vapour). Vapour pressure is a measure of the rate at which water molecules escape as a gas from the liquid. Boiling occurs when the vapour pressure of the water is equal to the external pressure on the water surface (boiling point ˆ100 ëC at atmospheric pressure at sea level). At reduced pressures below atmospheric, water boils at lower temperatures as shown in Chapter 14 (Fig. 14.1). The changes in phase can be represented on a pressure±enthalpy diagram (Fig. 10.1) where the bell-shaped curve shows the pressure, temperature and enthalpy relationships

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Fig. 10.1 Pressure±enthalpy diagram for water: Hc = enthalpy of condensate; Hv = enthalpy of saturated vapour; Hs = enthalpy of superheated steam (from Straub and Scheibner 1984, with kind permission of Springer Science and Business Media).

of water in its different states. Left of the curve is liquid water, becoming subcooled the further to the left, and right of the curve is vapour, becoming superheated the further to the right. Inside the curve is a mixture of liquid and vapour. At atmospheric pressure, the addition of sensible heat to liquid water increases its heat content (enthalpy) until it reaches the saturated liquid curve (A±B in Fig 10.1). The water at A is at 80 ëC and has an enthalpy of 335 kJ kgÿ1 and when heated to 100 ëC the enthalpy increases to 418 kJ kgÿ1. Further addition of heat as latent heat causes a phase change. Moving further across the line (B±C) indicates more water changing to vapour, until at point C all the water is in vapour form. This is then saturated steam that has an enthalpy of 2675 kJ kgÿ1 (i.e. the latent heat of vaporisation of water is 2257 (2675 ÿ 418) kJ kgÿ1 at atmospheric pressure while the temperature remains constant at 100 ëC). Within the curve along B±C, the changing proportions of water and vapour are described by the `steam quality'. For example at point E, the steam quality is 0.9, meaning that 90% is vapour and 10% is water. The specific volume of steam with a quality <100% can be found using Equation 10.9. Further heating (C±D) produces superheated steam. At point D it is at 250 ëC and has an enthalpy of 2800 kJ kgÿ1. Vs ˆ …1 ÿ xs †Vl ‡ xs Vv

10:9

where Vs (m3 kgÿ1) ˆ specific volume of steam, xs (%) ˆ steam quality, Vl (m3 kgÿ1) ˆ specific volume of liquid and Vv (m3 kgÿ1) ˆ specific volume of vapour. The data summarised in Fig. 10.1 is also available as steam tables (Keenan et al. 1969), and

Heat processing Table 10.4 Temperature (ëC)

30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 250 300

345

Properties of saturated steam Vapour pressure (kPa)

Latent heat (kJ kgÿ1)

4.246 7.384 12.349 19.940 31.19 47.39 70.14 101.35 143.27 198.53 270.1 316.3 475.8 617.8 791.7 1002.1 1254.4 1553.8 3973.0 8581.0

2431 2407 2383 2359 2334 2309 2283 2257 2230 2203 2174 2145 2114 2083 2046 2015 1972 1941 1716 1405

Enthalpy (kJ kgÿ1)

Specific volume (m3 kgÿ1)

Liquid

Saturated vapour

Liquid

Saturated vapour

125.79 167.57 209.33 251.13 292.98 334.91 376.92 419.04 461.30 503.71 546.31 589.13 632.20 675.55 719.21 763.22 807.62 852.45 1085.36 1344.0

2556.3 2574.3 2592.1 2609.6 2626.8 2643.7 2660.1 2676.1 2691.5 2706.3 2720.5 2733.9 2746.5 2758.1 2768.7 2778.2 2786.4 2793.2 2801.5 2749.0

0.001 004 0.001 008 0.001 012 0.001 017 0.001 023 0.001 029 0.001 036 0.001 043 0.001 052 0.001 060 0.001 070 0.001 080 0.001 091 0.001 102 0.001 114 0.001 127 0.001 141 0.001 156 0.001 251 0.001 044

32.89 19.52 12.03 7.67 5.04 3.41 2.36 1.67 1.21 0.89 0.67 0.51 0.39 0.31 0.24 0.19 0.15 0.13 0.05 0.02

Adapted from Singh and Heldman (2001b) original data from Keenan, J.H., Keyes, F.G., Hill, P.G. and Moore, J.G., (1969), Steam tables metric units, Wiley, New York, copyright John Wiley & Sons

selected values are shown in Table 10.4 (`steam' is another term for hot water vapour). When a phase change from water to vapour occurs, there is a substantial increase in the volume of vapour. In some unit operations, such as dehydration, this is not important, but in freeze drying (Chapter 23, section 23.1) and evaporation (Chapter 14, section 14.1) the removal of large volumes of vapour requires special equipment designs. In steam production using boilers, the vapour produced by the phase change is contained within the fixed volume of the boiler vessel and there is therefore an increase in vapour (or steam) pressure. Higher pressures result in higher-temperature steam (moving further right of the curve in the superheated vapour section of Fig. 10.1). The required pressure and temperature of process steam are controlled by the rate of heating in the boiler (see also section 10.2). 10.1.2 Heat transfer Energy balances The first law of thermodynamics states that `energy can be neither created nor destroyed but can be transformed from one form to another'. This can be expressed as an energy balance (Equation 10.10): Total amount of heat total energy leaving energy lost or mechanical energy ˆ with the products ‡ stored energy ‡ to the entering a process

and wastes

surroundings

10:10

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Food processing technology

If heat losses are minimised, energy losses to the surroundings may be ignored for approximate solutions to calculation of, for example, the quantity of steam, hot air or refrigerant required. For more accurate solutions, compensation should be made for heat losses. An example of the use of an energy balance is given in sample problem 21.1. Types of heat transfer Many unit operations in food processing involve the transfer of heat into or out of a food. There are three ways in which heat may be transferred: by conduction, by convection or by radiation. In the majority of applications more than one type of heat transfer occur simultaneously but one type may be more important than others in particular applications. Further details are given by Hayhurst (1997). Radiation heat transfer is by emission and absorption of electromagnetic waves as, for example, in an electric grill, and is described in detail in Chapter 20 (section 20.3). Both conduction and convection can take place under `steady state' or `unsteady state' conditions. Steady state heat transfer takes place when there is a constant temperature difference between two materials. The amount of heat entering a section of the material equals the amount of heat leaving, and there is no change in temperature of that section of the material. This occurs for example when heat is transferred through the wall of a cold store if the store temperature and ambient temperature are both constant (Chapter 21, section 21.2.3), and in continuous processes once operating conditions have stabilised. However, in the majority of food processing applications the temperature of the food and/or the heating or cooling medium are constantly changing, and unsteady state heat transfer is more commonly found. Calculations of heat transfer under these conditions are complex. They are described by Singh and Heldman (2001a) and Toledo (1999), and a simplified example of unsteady state calculations in heat sterilisation is given in Chapter 11 (section 11.1). The examples below assume steady state conditions, which are simpler to analyse. They are simplified by making a number of assumptions and using prepared charts to obtain useful information for the design and operating conditions of heat processing equipment. Computer models used to give solutions to these calculations are described by Toledo (1999) and Singh and Heldman (2001a). Conduction Conduction is the movement of heat by direct transfer of molecular energy within solid materials. Energy transfer is either by movement of free electrons (e.g. through metals) or by vibration of molecules. As molecules gain thermal energy they vibrate with increased amplitude, and this vibration is passed from one molecule to another. Therefore conducted heat moves from an area of higher temperature to an area of lower temperature without actual movement of the molecules through the material. The rate at which heat is transferred by conduction is determined by the temperature difference between the food and the heating or cooling medium, and the total resistance to heat transfer. The resistance to heat transfer is expressed as the thermal conductivity (section 10.1.1). Under steady-state conditions the rate of heat transfer is calculated using Fourier's Law: Q ˆ ÿkA

…1 ÿ 2 † x

10:11

where Q (J sÿ1) ˆ rate of heat transfer, k (J mÿ1 sÿ1 ëCÿ1 or W mÿ1 ëCÿ1) ˆ thermal conductivity, A (m2) ˆ surface area, 1 ÿ 2 (ëC) ˆ temperature difference and x (m) ˆ thickness of the material. …1 ÿ 2 †=x is also known as the temperature gradient.

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Because the temperature decreases with increasing distance through the food away from the heat source, the negative sign in Equation 10.11 is used to obtain a positive value for heat flow in the direction of decreasing temperature. A calculation based on Equation 10.11 is given in sample problem 10.1 and related problems are given in Chapters 12 and 14. In contrast to steady state heat transfer, where the temperature varies only with location, in unsteady state conduction, the temperature at a given point within a food depends on the rate of heating or cooling and the position in the food. The temperature therefore changes continuously with both location and time. The factors that influence the temperature change are the: · temperature of the heating medium; · thermal conductivity of the food; and · specific heat of the food. The basic equation for unsteady state heat transfer in a single direction x is d k d2  ˆ dt c dx2

10:12

where d=dt ˆ change in temperature with time. Examples of solutions to this equation for simple shapes (e.g. a slab, cylinder or sphere) are described by Singh and Heldman (2001a) and Toledo (1999). Convection When a fluid changes temperature, the resulting changes in density establish natural convection currents. Convection is therefore the transfer of heat by groups of molecules that move as a result of differences in density. Examples include natural-circulation evaporators (Chapter 14, section 14.1.3), air movement in bakery ovens (Chapter 18, section 18.2), and movement of liquids inside cans during sterilisation (Chapter 13, section 13.1). Forced convection takes place when a stirrer or fan is used to agitate the fluid. This reduces the boundary film thickness (see Chapter 1, section 1.3.4) to produce higher rates of heat transfer and a more rapid temperature redistribution. Consequently, forced convection is more commonly used than natural convection in food processing. Examples of forced convection include mixers (Chapter 4, section 4.1.3), fluidised-bed driers (Chapter 16, section 16.2.1), air blast freezers (Chapter 22, section 22.2.1) and liquids pumped through heat exchangers (Chapters 12 and 14). When liquids or gases are heated in a vessel or a pipe, the rate of heat transfer is complicated because of the motion of the fluid and the presence of boundary layers under laminar flow. A temperature profile (Fig. 10.2) develops in a similar way to a fluid velocity profile, with the fluid nearest to the vessel/pipe wall heating fastest and that at the centre the slowest. This profile depends on the viscosity of the fluid and the type of flow. Calculations of heat transfer are complex and further details are given by Singh and Heldman (2001a), Rotstein et al. (1997) and Heldman and Lund (1992) for both Newtonian and non-Newtonian fluids (Chapter 1, section 1.1.2). Convective heat transfer is found using: Q ˆ hs A…b ÿ s † ÿ1

10:13 2

where Q (J s ) ˆ rate of heat transfer, A (m ) ˆ surface area, s (ëC) ˆ surface temperature, b (ëC) ˆ bulk fluid temperature and hs (Wmÿ2 Kÿ1) ˆ surface (or film) heat transfer coefficient.

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Food processing technology

Sample problem 10.1 Part 1: In a bakery oven, combustion gases heat one side of a 2.5 cm steel plate at 300 ëC and the temperature in the oven is 285 ëC. Assuming steady state conditions, and a thermal conductivity for steel of 17 W mÿ2 ëCÿ1, calculate the rate of heat transfer per m2 through the plate. Part 2: The internal surface of the oven is 285 ëC and air enters the oven at 18 ëC. Calculate the surface heat transfer coefficient per m2, assuming the rate of heat transfer is 10.2 kW. Solution to sample problem 10.1 Part 1: From Equation 10.11, Qˆÿ

17  1  …300 ÿ 285† 0:025

ˆ 10 200 W Part 2: From Equation 10.13, hˆ

10 200 …285 ÿ 18†

ˆ 38.2 W mÿ1  Cÿ1 This value indicates that natural convection is taking place in the oven.

The surface heat transfer coefficient is a measure of the resistance to heat flow, caused by the boundary film, and is therefore equivalent to the term k/x in the conduction equation (Equation 10.1). It is higher in turbulent flow than in streamline flow. Typical values of hs are given in Table 10.5. An example of a calculation of heat transfer coefficient is given in Chapter 14 (sample problem 14.2). The calculations can be simplified by using formulae that relate the physical properties of a fluid (e.g. density, viscosity, specific heat, gravity (which causes circulation due to changes in density)), temperature difference and the length or diameter of the container under investigation. The these factors are expressed as dimensionless numbers as follows: Nusselt number Nu ˆ

hc D k

10:14

Fig. 10.2 Temperature profile of liquid being heated in a pipe (reprinted from Singh and Heldman 2001a) ß 2001, with permission from Academic Press).

Heat processing Table 10.5

349

Values of surface heat transfer coefficients Surface heat transfer coefficient (W mÿ2 Kÿ1)

Typical applications

2400±60 000 12 000

Evaporation Canning, evaporation

Boiling liquids Condensing saturated steam Condensing steam With 3% air With 6% air Condensing ammonia Liquid flowing through pipes Low viscosity High viscosity Moving air (3 m sÿ1) Still air

3500 1200 6000 1200±1600 120±1200 30 6

Canning Refrigeration Pasteurisation Evaporation Freezing, baking Cold stores

Adapted from Delgado and Sun (2003) and Earle (1983)

Prandtl number Pr ˆ

cp  k

Grashof number Gr ˆ

D3 2 g
 2

10:15 10:16

where hc (W mÿ2 ëCÿ1) ˆ convection heat transfer coefficient at the solid-liquid interface, D (m) ˆ the characteristic dimension (length or diameter), k (W mÿ1 ëCÿ1) ˆ thermal conductivity of the fluid, cp (J kgÿ1 ëCÿ1) ˆ specific heat at constant pressure,  (kg mÿ3) ˆ density,  (N s mÿ2) ˆ viscosity, g (m sÿ2) ˆ acceleration due to gravity ˆ 9.81 m sÿ2, (m mÿ1 ëCÿ1) ˆ coefficient of thermal expansion,
 (ëC) ˆ temperature difference and v (m sÿ1) ˆ velocity. The Nusselt number is found by dividing Equation 10.13 for convection by Equation 10.1 for conduction and replacing the thickness value with the characteristic dimension (D). It can be considered as a measure of the improvement in heat transfer caused by convection over that due to conduction (i.e. if Nu ˆ 1 there is no improvement, whereas if Nu ˆ 4, the rate of convective heat transfer is four times the rate that would occur by conduction alone in stagnant liquid). The Prandtl number relates the boundary layer caused by the fluid velocity (using the fluid viscosity as a measure) with the thermal boundary layer. If Pr ˆ 1 the thickness of the two layers is the same. For gases, Pr ˆ approximately 0.7 and Pr ˆ around 10 for water. The Grashof number is a ratio of the forces that cause lighter liquids to become more buoyant and rise and the viscous forces that slow their movement. It is used for natural convection when there is no turbulence in the fluid to determine whether flow is streamline or turbulent. A further number, the Rayleigh number, is a multiple of the Grashof and Prandtl numbers. Formulae for other types of flow conditions and different vessels are described by Singh and Heldman (2001a) and Toledo (1999). The Reynolds Number (Chapter 1, section 1.3.4) is used to determine the type of fluid flow. For streamline flow through pipes: D Nu ˆ 1:62…Re Pr †0:33 L

10:17

where L (m) ˆ length of pipe, when Re Pr D/L > 120 and all physical properties are measured at the mean bulk temperature of the fluid.

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For turbulent flow through pipes: Nu ˆ 0:023…Re†0:8 …Pr†n

10:18

where n ˆ 0.4 for heating or n ˆ 0.3 for cooling, when Re > 10 000, viscosity is measured at the mean film temperature and other physical properties are measured at the mean bulk temperature of the fluid. The surface heat transfer data (Table 10.5) indicate that heat transfer through air is lower than through liquids. Larger heat exchangers are therefore necessary when air is used for heating (Chapters 16 and 18) or cooling (Chapters 21 and 22) compared with those needed for liquids. Condensing steam produces higher rates of heat transfer than hot water at the same temperature and the presence of air in steam reduces the rate of heat transfer. This has important implications for canning (Chapter 13, section 13.1) as any air in the steam lowers the temperature and hence lowers that amount of heat received by the food. Both thermometers and pressure gauges are therefore needed to assess whether steam is saturated. Most cases of heat transfer in food processing involve heat transfer through a number of different materials. For example heat transfer in a heat exchanger from a hot fluid, through the wall of a pipe or vessel to a second fluid, is shown in Fig. 10.3. The heat must first transfer through the boundary film on the hot side, through the metal wall by conduction, and then through the boundary layer of the cold side. The overall temperature difference is found using:   Q 1x 1 10:19 ‡ a ÿ b ˆ A ha k h b The unknown wall temperatures 2 and 3 are therefore not required and all factors to solve the equation can be measured. The sum of the resistances to heat flow is termed the overall heat transfer coefficient (OHTC) and the rate of heat transfer may be expressed as: Q ˆ UA…a ÿ b †

10:20

The OHTC is an important term that is used, for example, to indicate the effectiveness of heating or cooling in different types of processing equipment. Examples are shown in Table 10.6.

Fig. 10.3 Temperature changes from a hot liquid through a vessel wall to a cold liquid.

Heat processing Table 10.6

351

OHTCs in food processing

Heat transfer fluids Hot water±air Viscous liquid±hot water Viscous liquid±hot water Viscous liquid±steam Non-viscous liquid±steam Flue gas±water Evaporating ammonia±water

Example

OHTC (W mÿ2 Kÿ1)

Air heater Jacketed vessel Agitated jacketed vessel Evaporator Evaporator Boiler Chilled water plant

10±50 100 500 500 1000±3000 5±50 500

Adapted from Lewis (1990)

In a heat exchanger, liquids can be made to flow in either the same direction (cocurrent (or `concurrent' or `parallel') flow) (Fig. 10.4a) or in opposite directions (`counter-current' flow) (Fig. 10.4b). In co-current operation, a cold liquid enters the inner pipe at temperature 1 , flows through the pipe and exits at temperature 2 . A hot liquid enters at temperature 3 , flows around the annular space between the inner and outer pipes and exits at temperature 4 . In the process heat is gained by the cold liquid and lost by the hot liquid. The heat exchanger is insulated to minimise heat losses to the surrounding air and an energy balance (Equation 10.11) can be used to show that the decrease in energy of the hot liquid equals the increase in energy of the cold liquid. This equation is useful to determine the flowrates or temperature changes in a heat exchanger. Q ˆ mh  Cph …3 ÿ 4 † ˆ mc  Cpc …2 ÿ 1 †

10:21

where m (kg sÿ1) ˆ mass flowrate, cp (kJ kgÿ1 ëCÿ1) ˆ specific heat, both with suffixes `h' for hot and `c' for cold, and  (ëC) ˆ temperatures numbered as shown in Fig. 10.4. Counter-current flow has a higher heat transfer efficiency than co-current flow and is therefore widely used in heat exchangers (e.g. Chapters 11±14). However, the temperature difference varies at different points in the heat exchanger and it is necessary to use a logarithmic mean temperature difference in calculations (sample problem 10.2):
m ˆ


1 ÿ
2 ln…
1 =2 †

where 1 is higher than 2 .

Fig. 10.4 (a) Co-current and (b) counter-current flow through a heat exchanger.

10:22

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Sample problem 10.2 A heat exchanger is to be used to heat orange juice from 18 ëC to 80 ëC at a flowrate of 0.5 kg sÿ1. A counter-current heat exchanger is required and hot water is available at 95 ëC to pass through the annular pipe at a flowrate of 1.5 kg sÿ1. Calculate the required length of the inner juice pipe having a diameter of 8 cm. Assume steady state conditions, no heat losses to the surroundings and an OHTC of 2400 W mÿ2 ëCÿ1. The specific heat of the juice is 3.89 kJ kgÿ1 ëCÿ1 and the specific heat of water ˆ 4.18 kJ kgÿ1 ëCÿ1 (Table 10.1). Solution to sample problem 10.2 Heat gained by juice ˆ mcp …1 ÿ 2 † ˆ 0:5  3:89  …80 ÿ 18† ˆ 120:59 kJ Use a heat balance: Heat gained by juice ˆ heat lost by water Q ˆ mcp …1 ÿ 2 † ˆ 0:5  3:89  …80 ÿ 18† ˆ mcp …3 ÿ 4 † ˆ 1:5  4:18  …95 ÿ 2 † The exit temperature of the hot water ˆ 2 ˆ 76 ëC From Equation 10.22:
m ˆ

…95 ÿ 80† ÿ …76 ÿ 18† ln …95 ÿ 80†=…76 ÿ 18†

ˆ 31:8  C From Equation 10.20: Q ˆ UA
 ˆ udl
 Therefore l ˆ Q=Ud
 ˆ

120:59  1000 2400  3:142  0:08  31:8

ˆ 6:29 m

Related sample problems are shown in Chapters 11 (sample problem 11.1) and 12 (sample problems 12.1 to 12.3). The heating time in batch processing is found using:   mc h ÿ i ln 10:23 tˆ UA h ÿ f where m (kg) ˆ the mass, cp (J kgÿ1 ëCÿ1) ˆ specific heat capacity, h (ëC) ˆ temperature of the heating medium, i (ëC) ˆ initial temperature, f (ëC) ˆ final temperature, A (m2) ˆ surface area and U (W mÿ2 ëCÿ1) ˆ OHTC.

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Unsteady state heat transfer by conduction and convection When a solid piece of food is heated or cooled by a fluid the resistances to heat transfer are the surface heat transfer coefficient and the thermal conductivity of the food. These two factors are related by the Biot number (Bi): Bi ˆ

h k

10:24

where h (W mÿ2 ëCÿ1) ˆ heat transfer coefficient,  ˆ the characteristic `half dimension' (e.g. radius of a sphere or cylinder, half thickness of a slab) and k (W mÿ1 ëCÿ1) ˆ thermal conductivity. At small Bi values (< 0.2) the surface film is the main resistance to heat flow and the internal resistance of the food is negligible. The time required to heat the solid food is found using Equation 10.23, using the film heat transfer coefficient hs instead of U. However, in most applications the thermal conductivity of the food limits the rate of heat transfer (Bi ˆ 0:2 ÿ 40) rather than the surface film resistance. These calculations are complex, and a series of charts is available to solve the unsteady state equations for simple shaped foods (Fig. 10.5), known as Gurney±Lurie and Heisler charts. The charts relate the Bi number (Equation 10.24), the temperature factor (the fraction of the temperature change that remains to be accomplished (Equation 10.25) and the Fourier number Fo (a dimensionless number which relates the thermal diffusivity, the size of the piece and the time of heating or cooling (Equation 10.26)): h ÿ f h ÿ i

10:25

Fig. 10.5 Chart for unsteady state heat transfer: (a) sphere, (b) slab, (c) cylinder (after Henderson and Perry 1955).

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Food processing technology

where the subscript `h' indicates the heating medium, the subscript `f' the final value and the subscript `i' the initial value. Fo ˆ

k t c 2

10:26

Singh and Heldman (2001b) describe computer spreadsheets to perform unsteady state calculations and artificial neural networks have been trained to perform the calculations represented on the charts. They have produced more accurate results than reading from the charts (Pandharipande and Badhe 2004). An example of an unsteady state calculation is shown in Chapter 11 (sample problem 11.1) and more complex calculations are described by Singh and Heldman (2001b), Toledo (1999), Lewis (1990), Earle (1983) and Jackson and Lamb (1981).

10.2

Sources of heat and methods of application to foods

The cost of energy for heating is one of the major considerations in the selection of processing methods and ultimately in the cost of the processed food and the profitability of the operation. Different fuels have specific advantages and limitations in terms of cost, safety, risk of contamination of the food, flexibility of use, and capital and operating costs for heat transfer equipment. The following sources of energy are the main ones that are used in food processing: · electricity; · gas (natural or liquid petroleum gas); · liquid fuel oil. In many developing countries, solid fuels are the main source of process heating but in industrialised countries, solid fuels (anthracite, coal, wood and charcoal) are only used to a small extent for heating boilers to generate steam or in specialised applications such as wood chips for food smoking (Chapter 17) or bagasse for sugar boiling. The advantages and limitations of each type of energy source (Table 10.7) can change over time depending on reserves of natural resources and the economics of production in different countries. However, electricity is the preferred source of energy for most applications and gas is widely used for boiler and oven heating. Recent developments include the adaptation of boilers to operate using biomass, including combustible waste materials, which also reduces waste disposal costs. Table 10.7 Advantages and limitations of different energy sources for food processing Electricity

Gas

Liquid fuel

Solid fuel

8.6±9.3 (fuel oil) Low High Moderate/ Low Low Low High Low

5.26±6.7 (coal) 3.8±5.26 (wood) Low High Low

Energy per unit mass/ volume ( 103 kJ kgÿ1) Cost per kJ of energy Heat transfer equipment cost Efficiency of heatinga

±

1.17±4.78

High Low High

Flexibility of use Fire/explosion hazard Risk of contaminating food Labour and handling costs

High Low Low Low

Low Low Moderate/ high High High Low Low

a

Efficiency ˆ amount of energy used for heating divided by amount of energy supplied

Low Low High High

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10.2.1 Direct heating methods In direct methods the heat and products of combustion from the burning fuel come directly into contact with the food. There is an obvious risk of contamination of the food by odours or incompletely burned fuel and for this reason only gas and, to a lesser extent, liquid fuels are used. Applications include kiln driers (Chapter 16, section 16.2.1) and baking ovens (Chapter 18, section 18.2.1). These direct methods should not be used confused with `direct' steam injection where the steam is produced in a separate location from the processing plant. Electricity is not a fuel in the same sense as the other types described above. It is generated by steam turbines heated by a primary fuel (e.g. coal, gas or fuel oil) or by hydro-power or nuclear energy. However, electrical energy may also be used directly by pulsed electric field processing (Chapter 9, section 9.1), dielectric heating or ohmic heating (Chapter 20). 10.2.2 Indirect heating methods Indirect electrical heating uses resistance heaters or infrared heaters. Resistance heaters are nickel±chromium wires contained in solid plates or coils that are attached to the walls of process vessels, in flexible jackets that wrap around vessels, or in immersion heaters that are submerged in the food. These types of heaters are used for localised or intermittent heating. Infrared heaters are described in Chapter 20 (section 20.3). Indirect heating using fuels requires a heat exchanger to separate the food from the products of combustion. At its simplest an indirect system consists of burning fuel beneath a metal plate and heating by energy radiated from the plate or conducted through it. The most common type of indirect-heating system used in food processing is steam or hot water generated by a heat exchanger (a boiler) located close to the processing area. A second heat exchanger transfers the heat from the steam or water to the food under controlled conditions, or alternatively a heat exchanger transfers heat to air in order to dry foods or to heat them under dry conditions. If steam is directly injected into the food, it is first filtered to remove any traces of condensate and all particles. Details of steam injection are given by Demetrakakes (1997) and in Chapter 13 (section 13.2). Steam generation Steam boilers used in food processing are usually the `water-tube' design in which water is pumped through tubes in the boiler that are surrounded by hot combustion gases from a burner or firebox. An alternative design (the `fire-tube' boiler) has the combustion gases contained in tubes that pass through water in the boiler vessel. The advantages of the water-tube design include: · · · ·

more rapid heat transfer because water is pumped under turbulent flow; larger capacities and higher pressures can be obtained; greater flexibility of operation; safer because steam is generated in small tubes rather than the large boiler vessel (Singh and Heldman 2001b).

To calculate the size of a steam boiler for a particular process, the following steps are taken: 1 Assess the thermal energy requirements of all operations that use steam, including the maximum temperature required. This determines the pressure that the steam is supplied at. 2 Calculate the quantity of steam needed to supply the required energy and using the

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Food processing technology

specific volume of steam (section 10.1.1) at the given pressure, calculate the size of pipework required to meet the volumetric flowrate. 3 Take account of energy losses (e.g. due to friction losses in pipework (Chapter 1, section 1.3.4) and heat losses through insulated pipes) to calculate the boiler power output required. 4 Take account of the boiler efficiency to calculate the size of boiler needed to meet the process requirements. Properties of steam are discussed by Brennan et al. (1990) and Toledo (1999), and selected properties of saturated steam at different temperatures are shown in Table 10.4. Anon (2007c) describes the advantages of electrically powered steam generators that can be located alongside processing equipment. In larger plants, steam generation may also be combined with power generation using a steam turbine. Anon (2006) describes the on-site generation of electricity and heat from a single fuel source, known as `combined heat and power' (CHP) or `cogeneration'. Waste heat from electricity production can be used to produce process heat, generate steam or heat buildings rather than using additional energy from electricity or gas. The most efficient CHP systems have high thermal loads compared with electric loads and can achieve >80% efficiency. CHP also minimises electricity transmission losses between the generator and end-user. These losses are 73% for electricity produced at power stations and transmitted along a grid (comprising about 65% of fuel lost as waste heat during generation and 8% of power lost along transmission lines). Further cost savings can be made if CHP uses waste products (e.g. methane or biomass) instead of fossil fuels. Since electricity is generated on site, processing is also not affected by disruptions in the grid power supply. Sutter (2007) notes the advantages of hot water compared with steam for heating jacketed vessels: the temperature can be controlled more accurately using hot water, which prevents overheating and product damage; and hot water distributes heat more evenly than steam, which eliminates hot spots that cause product damage. Steam injection is superior to indirect heat exchangers for heating water. It can be programmed to adjust the process temperature at a predetermined rate, giving a rapid response to changing process conditions and ensuring precise temperature control within a fraction of a degree. In contrast to indirect steam heating, where condensate at a relatively high temperature is returned to the boiler with inherent heat losses, the condensate in steam injection has most of the heat extracted, saving up to 17% in fuel costs. 10.2.3 Energy use and methods to reduce energy consumption In all types of food processing, most of the energy (40±80%) is used for actual processing, and heating, refrigeration and dehydration in particular require significant amounts of energy. For example, Okos et al. (1998) report that in the USA, process heating uses approximately 29% of the total energy used by the food industry, while process cooling and refrigeration uses about 16% of total energy inputs. Examples of data from Carlsson-Kanyama and Faist (2000) on energy inputs in different types of food processing are shown in Table 10.8. The types of process that consume the most energy include wet maize milling, production of sugar from beet, soybean oil mills, production of malted beverages, meat packing plants, canning, and production of frozen foods and bakery products. Less than 8% of the energy consumed by food manufacturing is for non-process uses (e.g. room lighting, heating, air conditioning and on-site transportation). However, in some processes significant amounts of energy are also used for packaging (11%; range, 15±40%), distribution

Heat processing Table 10.8

357

Comparative energy inputs in different types of food processing

Product

Energy (MJ) used per kg product

Bread Breakfast cereals Canned fruit and vegetables Canned meats Chocolate Chilled retail display cabinets Coffee instant Cold storage (e.g. apples)

1.53±4.56 19±66 2.1±3.8 5.2±25 8.6 0.12 50 0.0009±0.017

Drying Beet pulp (80% to 10% moisture) 6.4 Soybeans (17% to 11% moisture) 0.47 Potato flakes/granules 15±42 Freezing 0.3±7.6 Ice cream 2.2±3.7 Juice from concentrate Juice from fresh citrus fruit Milk processing Milling wheat flour Oil extraction

1.15 4.6 0.50±2.6 0.32±2.58 0.28±1.5

Pasta Sausages

0.8±2.4 3.9±36

Sugar extraction Sugar confectionery

2.3±26 6

Notes

MJ electricity kgÿ1 per day. Use varies with the size of the cold-room ± e.g. 0.0010 MJ lÿ1 net volume per day in room of 10 000 m3 compared with 0.015 MJ l±1 in a room of 10 m3 (factor of 15 difference) Theoretical value for evaporating 1 kg of water ˆ 2.60 MJ but actual use is 2±6 times higher, or 5.2±15.6 MJ (Pimentel and Pimentel 1996) A-rated equipmenta uses 2.7 times less energy per litre of usable volume than older equipment (typically 0.012 MJ l±1 net volume/day)

Electricity the only energy recorded Energy use allocated between two products (oil and press-cake) Large variation according to the extent of processing

a

EU labelling system for energy efficiency (A-label ˆ most energy efficient, B, C and D labels ˆ descending order of efficiency). Adapted from data of Carlsson-Kanyama and Faist (2000) and Pimentel and Pimentel (1996)

transport (12%; range, 0.56±30%), cleaning water (15%) and storage (up to 85% of total energy input for deep-frozen foods). Dalsgaard and Abbotts (2003) analyse energy use in different types of food processing and describe methods for improving energy use. Energy efficiency audits Energy audits are holistic surveys of a production plant that are undertaken to understand how energy is currently used and to identify areas of potential savings. An energy audit consists of three main parts: understanding energy costs, identifying potential savings and making cost±benefit recommendations. It is used to identify specific areas and equipment within a factory where energy savings can be made. Energy audits can: · · · ·

lower energy expenses; increase production reliability; increase productivity; reduce environmental impacts (Anon 2005a).

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Food processing technology

Details of how to conduct an energy audit are given by Barron and Burcham (2001). Improvements in energy efficiency make food companies more competitive. Energy saving can be achieved by improving existing plants, developing more energy-efficient processing technologies and creating informed energy policies. Reductions in energy use are possible by changing the type of process technology to a method that uses less energy: for example, supercritical extraction (Chapter 5, section 5.4.3) could be used instead of concentration by boiling; irradiation (Chapter 7) instead of pasteurisation or sterilisation; or drying by vapour recompression supercritical extraction instead of using hot air. Potentially the main energy savings in food processing are associated with boiler operation, the supply of steam or hot air and re-use of waste heat. Food processors are aware of the potential savings that can be made by reducing energy consumption, and meeting new environmental legislation. Other measures to improve boiler operation are returning condensate as feed water, pre-heating air for fuel combustion, and recovering heat from the flue. Fletcher (2004) reports flue gas loss as a key value in assessing the efficiency of high-pressure boilers. The amount of energy contained in the flue gases that are emitted through the chimney can result in significant energy losses. EU legislation on reduced CO2 emissions and energy consumption has defined limits and flue gas losses from oil and gas-fired boilers over 50 kW must not now exceed 9%. Flue gas heat exchangers reduce the temperature of flue gas from for example 350 ëC to 150 ëC to produce a 5% saving in fuel. If a typical factory boiler operates for 8000 hours a year, the efficiency can be increased by up to 15% and fuel cost savings are significant. The substitution of biomass fuels for fossil fuels can reduce hydrocarbon and carbon dioxide emissions. Although their production and use are technologically feasible, there are varying opinions on the economic viability of fuels from renewable resources, with some countries progressing their use more quickly than others. Computer control of boiler operation increases fuel efficiency and is described in detail by Anon (2001). Energy savings in steam supply to processing areas are achieved by proper insulation of steam and hot-water pipes, minimising steam leaks and fitting steam traps. Individual processing equipment is designed for energy saving and examples include regeneration of heat in heat exchangers (examples in Chapter 11, section 11.2, and Chapter 12, section 12.2), multiple-effect or vapour recompression systems (Chapter 14, section 14.1.2) and automatic defrosting and correct insulation of freezing equipment (Chapter 22, section 22.2). Microprocessor control of processing equipment is widely used to reduce energy consumption. Recovery of heat from drying air is more difficult than from steam or vapours, but a number of heat exchanger designs are used to recover waste heat from air or gases, described in Chapter 18 (section 18.2) for baking ovens and Chapter 19 (section 19.2.3) for deep-fat fryers. Heat pumps are similar to refrigeration plant (see Chapter 21, Fig. 21.1) but operate by removing heat from a low-temperature source and concentrating it in a heat `sink' which is then used to heat air or water. Anon (2005b) and Anon (2008) describe the operation of heat pumps. 10.2.4 Types of heat exchangers Heat exchangers to heat or cool foods are among the most common types of equipment found in food processing operations. Cooling equipment is described in Chapter 21, section 21.1.1. There is a wide variety of heat exchangers used to heat foods (e.g. for blanching, pasteurisation, heat sterilisation, evaporation, drying, frying and baking (Chapters 11±19)). Their design and operation depend on the properties of the foods

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being processed and the degree of heating required. Equipment can be grouped into direct heating types ± steam injection or steam infusion (Chapter 13, section 13.2.3) ± and indirect types: · scraped surface used for evaporation (Chapter 14, section 14.1.3) and freezing (Chapter 22, section 22.2.1); · tubular used for pasteurisation (Chapter 12, section 12.2) and evaporation; · shell and tube used for evaporation; and · plate heat exchangers used for pasteurisation or evaporation. Details of their operation are given in the chapters as indicated.

10.3 Effect of heat on micro-organisms and enzymes The preservative effect of heat processing is due to the denaturation of proteins, which destroys enzyme activity and enzyme-controlled metabolism in micro-organisms. The rate of destruction of many micro-organisms is a first-order reaction (see also below for other types): that is when food is heated to a temperature that is high enough to inactivate contaminating micro-organisms, the same percentage die in a given time interval regardless of the numbers present initially. This is known as the `logarithmic order of death' and is described by a `death rate curve' (Fig. 10.6). The time needed to destroy 90% of the micro-organisms (to reduce their numbers by a factor of 10) is referred to as the `decimal reduction time' or D-value (5 min in Fig. 10.6). D-values differ for different microbial species (Table 10.9) and a higher D-value indicates greater heat resistance.

Fig. 10.6 Death rate curve.

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Food processing technology

Table 10.9 Heat resistance of selected pathogens Micro-organism Vegetative cells Aeromonas hydrophila Bacillus stearothermophilus B. subtilis B. cereus Campylobacter jejuni Campylobacter jejuni Clostridium sporogenes Cl. thermosaccharolyticum Escherichia coli O111:B4 E. coli O157:H7 E. coli O157:H8 Listeria monocytogenes L. monocytogenes Staphylococcus aureus Staph. aureus Staph. aureus Salmonella senftenberg S. senftenberg S. typhimurium S. typhimurium Vibrio cholerae V. parahaemolyticus V. parahaemolyticus Yersinia enterocolitica Spores Bacillus subtilis Bacillus cereus Clostridium botulinum 62A Cl. botulinum B Cl. botulinum E Clostridium perfringens

D-value (min)

z-value

Temperature (ëC)

Substrate/ typical food

2.2±6.6 3.0±4.0 0.3±0.76 3.8 0.62±2.25 0.74±1.0 0.7±1.5 3.0±4.0 5.5±6.6 4.1±6.4 0.26±0.47 0.22±0.58 1.6±16.7 6 3 0.9 276±480 0.56±1.11 396±1050 2.13±2.67 0.35±2.65 0.02±2.5 10±16 0.067±0.51

5.2±7.7 9±10 4.1±7.2 36 ± ± 8.8±11.1 7.2±10.0 ± ± 5.3 5.5 ± ± ± 9.5 18.9 4.4±5.6 17.7 17±21 5.6±12.4 5.6±12.4 4±5.78

48 ± ± ± 55±56 55 ± ± 55 57.2 62.8 63.3 60 60 60 60 70±71 65.5 70±71 57 60 55 48 60

Milk Vegetables, milk Milk products Milk Beef/lamb/chicken Skim milk Meats Vegetables Skim/whole milk Ground beef Ground beef Milk Meat products Meat macerate Pasta Milk Milk chocolate Various foods Milk chocolate Ground beef Crab/oyster Clam/crab Fish homogenate Milk

30.2 1.5±36.2 0.61±2.48 0.49±12.42 6.8±13 6.6

9.16 6.7±10.1 7.5±11.6 7.4±10.8 9.78 ±

88 95 110 110 74 104.4

0.1% NaCl Various foods Vegetable products Vegetable products Seafood Beef gravy

Adapted from Anon (2000), Heldman and Hartel (1997) and Brennan et al. (1990)

There are two important implications arising from the decimal reduction time: first, the higher the number of micro-organisms present in a raw material, the longer it takes to reduce the numbers to a specified level. In commercial operation the number of microorganisms varies in each batch of raw material, but it is difficult to recalculate process times for each batch of food. A specific temperature±time combination is therefore used to process every batch of a particular product, and adequate preparation procedures (Chapter 2) are used to ensure that the raw material has a satisfactory and uniform microbiological quality. Secondly, because microbial destruction takes place logarithmically, it is theoretically possible to destroy all cells only after heating for an infinite time. Processing therefore aims to reduce the number of surviving micro-organisms by a predetermined amount. This gives rise to the concept of `commercial sterility', which is discussed further in Chapter 13 (section 13.1.1). The destruction of micro-organisms is temperature dependent; cells die more rapidly at higher temperatures. By collating D-values at different temperatures, a semilogarithmic thermal death time (TDT) curve is constructed (Fig. 10.7). The slope of the TDT curve is termed the z-value and is defined as the number of degrees Celsius required

Heat processing

Fig. 10.7

361

TDT curve. Microbial destruction is faster at higher temperatures (e.g. 100 min at 102.5 ëC has the same lethal effect as 10 min at 113 ëC.

to bring about a ten-fold change in decimal reduction time (10.5 ëC in Fig. 10.7). The Dvalue and z-value are used to characterise the heat resistance of a micro-organism and its temperature dependence respectively. There are a large number of factors that determine the heat resistance of microorganisms, but general statements of the effect of a given variable on heat resistance are not always possible. The following factors are known to be important: 1 Type of micro-organism: different species and strains show wide variation in their heat resistance (Table 10.9). Spores are much more heat resistant than vegetative cells. 2 Incubation conditions during cell growth or spore formation. These include: · temperature (spores produced at higher temperatures are more resistant than those produced at lower temperatures), · age of the culture (the stage of growth of vegetative cells affects their heat resistance, and · culture medium used (for example mineral salts and fatty acids influence the heat resistance of spores). 3 Conditions during heat treatment. The important conditions are: · pH of the food (pathogenic and spoilage bacteria are more heat resistant near to neutrality; yeasts and fungi are able to tolerate more acidic conditions but are less heat resistant than bacterial spores), · water activity of the food (Chapter 1, section 1.1.2) influences the heat resistance of vegetative cells; in addition moist heat is more effective than dry heat for spore destruction, · composition of the food (proteins, fats and high concentration of sucrose increase the heat resistance of micro-organisms; the low concentration of sodium chloride

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used in most foods does not have a significant effect; the physical state of the food, particularly the presence of colloids, affects the heat resistance of vegetative cells), and · the growth media and incubation conditions used to assess recovery of microorganisms in heat resistance studies affect the number of survivors observed. There is growing evidence that survival curves show deviations from the straight semilogarithmic lines in Figs 10.6 and 10.7 for many vegetative micro-organisms and spores. Peleg and Cole (1998) describe curves that have sigmoidal shapes with shoulders and tails and Geeraerd et al. (2004) have characterised eight different types of curve (Fig. 10.8). Peleg (2000, 2002, 2003) has interpreted different shapes in terms of microbial

Fig. 10.8 Types of microbial inactivation curves: A, linear curve; B, linear curve with tailing; C, sigmoidal-like curve; D, curve with a shoulder; E, biphasic curve; F, concave curve; G biphasic curve with a shoulder; H, convex curve (adapted from Geeraerd et al. 2004).

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mortality by using mathematical models based on a `Weibull' distribution. Further details of the model are described by Peleg (2004), and Geeraerd et al. (2004) have reviewed the different models so far developed. Increases in computer power enable these types of mathematical models to be used to re-evaluate the processes based on first-order (linear) inactivation, to predict the survival of newly discovered and heat-resistant strains of pathogens, and to assess whether heat processing conditions are adequate. They can also be used to assess the effects of changes to other factors (e.g. pH, salt content) on microbial survival during heating and so produce a range of heating conditions that can produce a safe product that has satisfactory organoleptic and nutritional properties. Most enzymes have D and z-values within a similar range to micro-organisms, and factors that influence heat resistance of enzymes are similar to those described for microorganisms. Enzymes are therefore inactivated during normal heat processing. However, some enzymes are very heat resistant. These are particularly important in acidic foods, where they may not be completely denatured by the relatively short heat treatments and lower temperatures required for microbial destruction. Knowledge of the heat resistance of the enzymes and/or micro-organisms found in a specific food is used to calculate the heating conditions needed for their inactivation. Methods for the calculation of processing time are described in Chapter 13 (section 13.1.1). In practice the most heatresistant enzyme or micro-organism likely to be present in a food is used as a basis for calculating process conditions. It is assumed that other less heat-resistant enzymes or micro-organisms are also destroyed. Examples of enzymes include peroxidase in vegetables (Chapter 11, section 11.1) and alkaline phosphatase in milk (Chapter 12, section 12.1). Bacteria include Clostridium botulinum in meat and vegetable products and Salmonella seftenberg in pasteurised liquid egg. Rosnes (2004) has described the thermal destruction of heat-resistant bacteria, bacterial spores, viruses, moulds and prions. (Prions are hypothesised to be proteins that propagate in cells by refolding into a structure that is able to convert normal protein molecules into an abnormally structured form, consisting of tightly packed beta sheets (Chapter 1, section 1.1.1) that are resistant to chemical and physical denaturation. The altered structure is very stable and accumulates in infected tissue, causing tissue damage and cell death. Prions are thought to cause a number of mammalian diseases, including bovine spongiform encephalopathy (BSE) in cattle and Creutzfeldt±Jakob disease (CJD) in humans.)

10.4

Effect of heat on nutritional and sensory characteristics of foods

The destruction of many vitamins, aroma compounds and pigments by heat follows a similar first-order reaction to microbial destruction. Examples of D and z-values of selected vitamins and pigments are shown in Table 10.10. In general z-values are higher than those of micro-organisms and enzymes. As a result, nutritional and sensory properties are better retained by the use of higher temperatures and shorter times during heat processing. It is therefore possible to select particular time±temperature combinations from a TDT curve (all of which achieve the same degree of enzyme or microbial destruction), to optimise a process for nutrient retention or preservation of desirable sensory qualities. This concept forms the basis of individual quick blanching (Chapter 11, section 11.2), high-temperature short-time (HTST) pasteurisation (Chapter 12, section 12.2.2), ultra-high-temperature (UHT) sterilisation (Chapter 13, section 13.2) and HTST extrusion (Chapter 15, section 15.1). The loss of nutrients and changes to sensory quality during individual heat processing operations are reported in Chapters 11±19.

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Food processing technology

Table 10.10 Heat resistance of selected vitamins and chemicals that contribute to sensory quality of foods in relation to heat-resistant enzymes and bacteria Component Vitamins Thiamin Thiamin Amino acids Lysine Pigments Anthocyanin Betanin Carotenoids Chlorophyll a Chlorophyll b Enzymes Pectinesterase Pectinesterase Peroxidase Peroxidase Peroxidase Polyphenoloxidase Polyphenoloxidase Polyphenoloxidase Bacteria Bacillus stearothermilophilus Clostridium botulinum spores Clostridium butyricum spores Bacillus coagulans spores Moulds Byssochlamys nivea ascospores Neosartorya fischeri ascospores Talaromyces flavus ascospores

Source

pH

Carrot pureÂe Lamb pureÂe

5.9 6.2

25 25

158 120

109±149 109±149

Soybean meal

±

21

786

100±127

Grape juice Beetroot juice Paprika Spinach Spinach

Natural 5.0 Natural 6.5 5.5

23.2 58.9 18.9 51 79

17.8a 46.6a 0.038a 13 14.7

20±121 50±100 52±65 127±149 127±149

Mandarin orange juice Acidified papaya pureÂe Peas Grape Strawberry Pear Grape Apple

4.0 3.5 Natural ± ± 3.9 3.3 3.1

10.1 14.8 37.2 35.4 19 ± ± ±

3.6 4.8 3.0 4.8 5.0 6.5 0.45 0.13

82±94 75±85 110±138 65±85 50±70 75±90 65±80 65±80

Various

>4.5

7±12

4.0±5.0

110+

Various

>4.5

Peach

z-value D-value (ëC) (min)

5.5±10 0.1±0.3a

Temperature range (ëC)

104

±

11.5

1.1

90

Tomato paste

4.0

9.0

3.5

75±90

Strawberry pulp

3.0

6.4

193.1

80±93

Apple juice

3.5

5.3

15.1

85±93

Strawberry pulp

3.0

8.2

53.9

75±90

a

D-values at temperatures other than 121 ëC. Adapted from Silva and Gibbs (2004), von Elbe et al. (1974), Stumbo (1973), Taira et al. (1966), Gupta et al. (1964), Adams and Yawger (1961), Ponting et al. (1960) and Felliciotti and Esselen (1957)

References and YAWGER, E.S., (1961), Enzyme inactivation and colour of processed peas, Food Technology, 15, 314±317. ANON, (2000), Kinetics of microbial inactivation for alternative food processing technologies, overarching principles: kinetics and pathogens of concern for all technologies, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, available at www.cfsan.fda.gov/~comm/ift-over.html. ANON, (2001), Boiler control systems, United Facilities Criteria document UFC 3-430-11, available at www.wbdg.org/ccb/DOD/UFC/ufc_3_430_11.pdf. ANON, (2005a), Energy audits, Center for Industrial Research and Service, Iowa State University, ADAMS, H.W.

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