Engineering Properties of Food Materials

C H A P T E R

3 Engineering Properties of Food Materials Tadesse F. Teferra1,2 1

Hawassa University, Hawassa, Ethiopia 2Texas A&M University, College Station, TX, United States O U T L I N E

3.1 Introduction

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3.2 Mass, Density, and Porosity 3.2.1 Mass 3.2.2 Volume 3.2.3 Density 3.2.4 Porosity

46 46 47 49 51

3.3 Geometric Properties 3.3.1 Size 3.3.2 Shape 3.3.3 Angle of Repose

53 53 54 55

3.4 Rheological Properties 3.4.1 Rheology of Solids 3.4.2 Rheology of Liquids

56 57 59

3.5 Thermal Properties 3.5.1 Thermal Conductivity 3.5.2 Specific Heat Capacity of Food Materials 3.5.3 Enthalpy and Latent Heat

63 64

3.6 Electrical Properties 3.6.1 Electrical Conductivity 3.6.2 Factors Affecting Electrical Conductivity in Foods

66 66

Handbook of Farm, Dairy and Food Machinery Engineering DOI: https://doi.org/10.1016/B978-0-12-814803-7.00003-8

3.6.3 Advancement in and Application of Electrical Properties of Foods 70 3.7 Dielectric Properties 3.7.1 Basic Principles and Practices 3.7.2 Factors Influencing Dielectric Properties of Food Materials

70 71 72

3.8 Optical Properties 77 3.8.1 Refraction and Reflection 77 3.8.2 Light and Color 79 3.8.3 Color as a Vector Quantity 80 3.8.4 Color Measurement Using the L*a*b* Method 81 3.8.5 Other Forms of Optical Waves of Importance to Food Application 83 3.9 Acoustical Properties 84 3.9.1 Basics of Sound as a Wave 84 3.9.2 Speed of Sound in Various Material Mediums 84 3.9.3 Noise 86

65 66

References

86

68

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© 2019 Elsevier Inc. All rights reserved.

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3. ENGINEERING PROPERTIES OF FOOD MATERIALS

3.1 INTRODUCTION Engineering properties of foods may be defined as the characteristics exhibited by foods and other biological materials under certain form and state of energy. Engineering properties of food materials, also simply termed as physical properties of foods, are of immense technical importance in food characterization, quality determination or monitoring, and handling and processing operations. They are related to the changes in the chemical and physical organizations of the foods at micro (molecules) and macro (polymer) levels on processing or over storage. Engineering properties can be measured or qualitatively described and used to indirectly quantify or predict other properties. Food engineers have devised different mathematical models that explain the relationships of the different properties with processing parameters and food quality indicators. Engineering properties of foods dictate the design of processes and/or machines for characterization, handling, and processing (manipulation) of the materials (Barbosa-Ca´novas et al., 2009). Engineering properties of foods are also being used for determination and monitoring the aspects of food safety and quality. The quality and soundness of food products are related to their mass, density, size, shape, and color. Color and surface characteristics of fruits are indicators of the ripeness and eating quality. The sound made by a crisp apple when bitten and crushed in the mouth designates the freshness and turgidity of a quality fruit. The thickening of ketchups and salad dressings when left on the bench, and their easy flowability when shaken, are simple examples where engineering properties of foods in day-to-day applications are perceived. All these and many other phenomena have one or multiple components that can either be measured or computed using established mathematical models. The obtained values are used to design processing or quality testing equipment. Some of these components can be used to directly characterize the foods. The major categories of engineering properties of foods that are discussed in this chapter include the mass, density, and dimension related properties (Section 3.2); geometric properties (Section 3.3); rheological properties (Section 3.4); thermal properties (Section 3.5); electrical properties (Section 3.6); electromagnetic and dielectric properties (Section 3.7); optical properties (Section 3.8); and acoustic properties (Section 3.9). Many of these properties have been extensively studied since the 1970s and are now being applied in different aspects of food characterization and processing (Barbosa-Ca´novas et al., 2009; Boldor, 2007; Rahman, 1995, 2009; Rao et al., 2014). Brief details of the definitions, specific examples, and practical applications of some of these properties will be discussed in the subsequent sections of this chapter.

3.2 MASS, DENSITY, AND POROSITY 3.2.1 Mass Mass is a measure for inertia and heaviness of a material. Inertia is the resistance to motion or acceleration and it is related to the number of atoms contained in a material. The SI unit of mass is kilogram (kg), which is approximately equal to the mass of 1 m3 of water at its maximum density. The standard 1-kg prototype is made of platinum
iridium

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and is stored at the International Bureau of Weights and Measures (BIPM). Heaviness is caused by Earth’s gravitational attraction for a material. Mass is not to be confused with weight of a material. Weight is the force acting on the material due to the gravitational force of the planet Earth and is related to mass as shown in the equation below: W 5m3g where W is the weight of the material (g m/s2); m is the mass of the material (g); and g is the acceleration due to gravitational force (m/s2). Mass dictates the nature and design of transportation, handling, and packaging materials for foods. Mass is also directly used to measure the amount of foods for packaging as such or for formulating innovative food matrices from different ingredients. Mass as an engineering property is also important in separation operations like cleaning and grading. It is also used for estimating other engineering properties including density and specific gravity. Mass is also widely used in computations of mass transfer phenomena in processing unit operations that involve anabolic or catabolic transformation of materials (Saravacos and Maroulis, 2001). Mass is one of the easy to measure parameters used in the determination of material transfer kinetics in many food process engineering calculations and simulations.

3.2.2 Volume Volume is the space occupied by a material that tells how big it is in space. The SI unit of volume is m3, but it is also commonly given by cubic centimeters, liters, gallons, cups, and other traditional units. Volume of food and other agricultural materials are important in determining space and containers required for packaging, transportation, and storage. It is also important for the design of processing equipment and unit and bulk package designs. Volume is also used in the determination of other properties such as density and specific gravity. 3.2.2.1 Types of Volume Volume can be classified depending on the nature of the material and its importance for engineering operations. The physical state of the material also determines the type and ease of estimating volumes. Measuring and computation of space occupied by a given solid object is always easier than for fluids: (1) Boundary volume: Regularly shaped foods and food matrices may be characterized by boundary volumes that can easily be computed from measurable dimensions of the food particulate, although this is not always the case for many food materials. A summary of the computations of regularly shaped materials is presented in Table 3.1. (2) Pore volume: It is the void space in a solid food particulate that is usually filled by air or other fluids. It is always harder to measure pore volume in food materials, but it is doable. Common methods of volume measurements for porous and irregularly shaped objects will be presented in Section 3.2.2.2.

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TABLE 3.1 Formulas Areas and Volumes of Regularly Shaped Materials. Shape

Surface Area

Sphere

A 5 4πr

Volume
 V 5 4=3 πr3

Cylinder

A 5 2πr2 1 2πrL

V 5 πr2 L

Cube

A 5 6a2

V 5 a3

2

A 5 surface area; V 5 volume; r 5 radius; L 5 length (height); a 5 any dimension of a cubic shaped object (width/length/height); π 5 3.1416.

FIGURE 3.1 Liquid displacement technique of volume measurement for irregularly shaped intact foods.

3.2.2.2 Measurement of Volume (1) Direct volume determination: Volume can be directly calculated from known dimensions as shown in Table 3.1, if the objects have regular geometric shapes. However, this is not the case for most natural foods and other biological materials. Volume of semisolid foods and liquid beverages can also be directly measured by using graduated cylinders and other containers of known volumes. (2) Indirect volume determination: Irregularly shaped materials (like most solid foods: fruits, vegetables, roots, tubers) or processed foods (such as loaf of bread) can only be measured indirectly. For intact solid foods with very low interaction with water (e.g., fresh fruit, vegetable, roots) liquid displacement technique (Fig. 3.1) can be used to estimate the volume. Water of known volume (V1) can be poured into a graduated cylinder or beaker. The irregularly shaped food is then gently placed in the water and completely immersed. The volume of the water is increased (V2) due to displacement by the food piece. The volume (Vi) of the irregularly shaped food piece can then be computed as indicated in the equation: Vi 5 V2 2 V1 where Vi is the volume of irregularly shaped food piece; V1 is the volume of water before the food is immersed in; and V2 is the volume of water after the food is fully immersed in water.

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The same displacement principle is used with gas and solids to determine volumes of prepared foods. For instance, rape seed bulk is used to estimate the volume of a loaf of bread by solid displacement method. Inert gas and organic fluids with great permeability are used in methods for more accurate estimation of volume. These fluids can fill in all the pores without reacting with the solid matrix and are commonly used for research and volume and density measurement equipment.

3.2.3 Density Density is the space occupied by a unit mass of a food material. It is therefore given as the ratio of mass to volume (equation below) and is measured in kilogram/cubic meter (kg/m3) in the SI metric system. Density of food materials is important for quality and general characterization. It is also used for food processing operations like centrifugation. The separation of milk fat from whole milk is done based on the difference in the density of the fat globules and the protein micelles. Separation of refined flour from brans in milling and separation by cyclone is also achieved depending on the density differences. Density is also important in cleaning operation, where less dense immature seeds and other impurities can easily be separated by blowing in air separation or by floating if washing or steeping is involved in processing, like in malting. ρ5

m V

where ρ is the density (kg/m3); m is the mass of the material (kg); V is the volume of the material (m3). 3.2.3.1 Types of Density Density of materials can be classified based on the way the volume is measured or based on the nature or other engineering properties of the materials. The five most commonly considered density types are discussed below: • True density—True density (ρT) is the density of a pure substance or a composite material calculated from its components’ densities considering conservation of mass and volume. This type of density may not be common in characterizing food materials as they exist in mixture forms comprising numerous components where breaking the mass and volume to pure component level is impractical. • Material density—Material density (ρm) is the density measured when a material has been thoroughly broken into pieces small enough to guarantee that no significant closed pores remain inside the particles. This may be applicable to foods if effective size reduction operation can be applied to the food matrix in question. The size reduction should also result in particles of predictable shapes so that the bulk volume (between particles) can be negligible when the material is compacted or packed in bulk or the gaps can easily be filled by the fluid used to estimate volume (if fluid displacement it involved). • Particle density—Particle density (ρp) is the density of a particle, which includes the volume of all closed pores but not the externally connected pores. In this case, the particle is not modified structurally, as in the case of material density. This density type

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may also be applicable to food characterization. Density of seeds that do not require any size reduction can be a good example. The fluid (inert gas or liquid) used to estimate the volume will be filled into all spaces between individual seeds but is not required to diffuse into the seeds to fill all the open and closed pores. The diffusion can be controlled by the time the particles and the fluid stay in contact before reading of the volume is taken. • Apparent density—Apparent density (ρa) is the density of a substance including all pores remaining in the material. This is important in characterizing intact materials, grain bulk, or a loaf of bread where all the external pores (between particles) are taken care of by the displacement materials (fluid or solid) and the interior pores are ignored. This density is apparently close to true density for fairly compacted food materials like dried seeds of pulses and cereals. • Bulk density—Bulk density (ρB) is the density of a material when packed or stacked in bulk. The bulk density of packed materials depends on the geometry, size, and surface properties of individual particles. The bulk density of a seed or powder is measured by approximately measuring the volume using a graduated cylinder/beaker, which includes the bulk and interior porosities. 3.2.3.2 Measurement of Density The different forms of densities of materials can be measured using various techniques based on the nature, physical status (solid, liquid), and geometry of the samples. The principle is the same, which is the ratio of mass to volume, but effective measuring of volume is often challenging. The following are commonly used techniques for measuring specific types of density: (1) Geometric methods: The volume of the materials is determined from measured dimension as summarized in Table 3.1 and used for the density calculations. The challenge, however, is that food materials do not have a well-defined regularity in geometry. But this technique may be useful for determining the densities of processed food particulates molded in regular geometries. Good examples may be cheese, butter, chocolates, extrudates, and other foods molded into rectangular or cylindrical bars, or spherical shapes. (2) Buoyant force method: Apparent density of materials can be determined by weighing the samples in air and in liquid of known density (Fig. 3.2). Samples should be wrapped FIGURE 3.2 Illustration of apparent density measurement for intact food materials using buoyant force method.

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or coated with a very thin layer of plastic or wax film to avoid mass exchange with the liquid. The time of measurement should also be as brief as possible. It is also important that liquids of lower densities than the solid samples are selected to avoid partial flotation of the sample. The following equation can be used to determine the density (Rao et al., 2014): ρa 5 ρl 3

m G

where ρa is the apparent density; ρl is the density of the liquid; m and G are the mass of the sample (kg) in air and liquid, respectively. (3) Displacement method: The volume of irregularly shaped materials can be measured using solid, liquid, or gas displacement methods. The inert liquid and gases are used to fill in the voids in and between particulate foods without interacting with the matrix in a way that compromises the mass and structure. The displacement techniques, particularly those using fluids, give a more accurate estimate of the volume that can be used in calculating the density of the materials. A pycnometer is a volume measurement method based on gas displacement techniques and is commonly used for measuring true density of particulates like grains.

3.2.4 Porosity Porosity indicates the volume fraction of void space occupied by air in a solid food matrix. Porosity is mathematically defined as the ratio of the volume of the void space to the total volume of the material in question: Porosity ðεÞ 5

Void volume Total volume

Different forms of porosity are used in food process calculations and food product characterization (Smith et al., 2014). The most commonly described forms of porosities in foods (Boldor, 2007; Rao et al., 2014) include: (1) Open pore porosity—It is the volume fraction of pores connected to the exterior boundary of a material and is represented by εop (Fig. 3.3). There may be two types of open pores: one type is connected to the exterior boundary only, and another type is connected to the other open pores as well as to the exterior geometric boundary. The level of open and closed pores depends on what component (helium, nitrogen, toluene, or mercury) is used in the measurement. (2) Closed pore porosity—Closed pore porosity (εcp) is the volume fraction of pores closed inside the material and not connected to the exterior boundary of the material (Fig. 3.3). Similar methods of measurement as for the open pore porosities using inert gas and liquids (helium, nitrogen, toluene, or mercury) are used for determining the closed pores. (3) Apparent porosity—Apparent porosity (εa) is the volume fraction of total air or void space in the material boundary and is defined as the sum of the open and closed pore porosities (εa 5 εop 1 εcp). Open and closed pore porosities separately may not have

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FIGURE 3.3 Illustrating different forms of pores in solid particulate foods.

FIGURE 3.4 Demonstration of bulk porosity (void space among particles stacked in bulk).

great practical significance. Apparent porosity, however, is important for the characterization of the material as it is related to other physical properties like density. (4) Bulk porosity—Bulk porosity (εB) is the volume fraction of voids outside the boundary of individual materials when packed or stacked in bulk (Fig. 3.4). This form of porosity is largely dependent on the geometric properties (size and shape) of individual particles. It is important for the characterization of bulk materials like grains, flour, fruits and vegetables, and extrudates. (5) Total porosity—Total porosity (εT) is the total volume fraction of air or void space (i.e., inside and outside of the material particles) when material is packed or stacked as bulk. The total porosity is therefore given as the sum of the apparent and bulk porosities or the sum of all open, closed, and bulk porosities as indicated in the equation: εT 5 εa 1 εB 5 εop 1 εcp 1 εB

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3.3 GEOMETRIC PROPERTIES Geometric properties of foods are those characteristics related to shape, size, and angles of particulates or bulks. These properties are very important in designing product handling (packaging and transportation) and processing facilities. Knowledge of geometric properties of biological materials like foods is also crucial directly or indirectly in determining quality. Seed size, shape, and angle of repose (for bulk samples) can indirectly tell the moisture content or the soundness of the individual kernels (Boldor, 2007).

3.3.1 Size Size is an important physical attribute of foods used in screening solids to separate foreign materials, grading of fruits and vegetables, and evaluating the quality of food materials. For example, particle size of powdered milk must be large enough to prevent agglomeration, but small enough to allow rapid dissolution during reconstitution. Particle size was found to be inversely related to dispersion of powder and water holding capacity of whey protein powders (Resch and Daubert, 2002). It is easy to specify size for regular particles, but for irregular particles (common in foods), the term size must be systematically specified and estimated. Particle sizes are expressed in different units depending on the size range involved. Coarse particles are measured in millimeters (mm), fine particles in terms of screen size, and very fine particles in micrometers (μm) or nanometers (nm). Size can be determined using the projected area method, in which three characteristic dimensions are defined: (1) Major diameter is the longest dimension of the maximum projected area of the particle; (2) intermediate diameter is the minimum diameter of the maximum projected area or the maximum diameter of the minimum projected area; and (3) minor diameter is the shortest dimension of the minimum projected area. Length, width, and thickness terms are also commonly used corresponding to major, intermediate, and minor diameters, respectively. The dimensions can be measured using a micrometer or a caliper (Figs. 3.1
3.5). The micrometer is a simple instrument used to measure distances between surfaces. Most micrometers have a frame, anvil, spindle, sleeve, thimble, and ratchet stop. They are used to measure the outside diameters, inside diameters, the distance between parallel surfaces, and the depth of holes. Most commercial calipers are digital and gives a fairly accurate reading. Particle size of particulate foods is most commonly used in separation and grading processes using sieve systems (Fig. 3.6A). This can also be used in determining the size of particulate foods in passage through an electrically charged orifice, and settling rate methods. Particle size distribution analyzers, which determine both the size of particles and their state of distribution, are used for production control of powders. The particle size analysis and distribution can also be used in determining food quality characterization as in seed size determination reported by Campbell et al. (2007) for hard wheat (Fig. 3.6B).

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FIGURE 3.5 Digital caliper for measuring dimensions of solid particulates.

FIGURE 3.6 Sieve set systems for particle size analysis (A) and distribution (B) of particulate foods (hypothetical data based on Campbell et al., 2007).

3.3.2 Shape Shape of food materials is also important in heat and mass transfer calculations, screening solids to separate foreign materials, grading of fruits and vegetables, and evaluating the quality of food materials. The shapes of whole and intact foods dictate the design of harvesting, processing and handling machineries as well as packaging materials. The shape of a food material is usually expressed in terms of its sphericity and aspect ratio. Sphericity is an important parameter used in fluid flow and heat and mass transfer calculations. Sphericity or shape factor can be defined in different ways. According to the most commonly used definition, sphericity is the ratio of volume of irregular solid to the volume of a sphere that has a diameter equal to the major diameter of the solid so that it can circumscribe the solid object (Fig. 3.7).

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FIGURE 3.7 Definition and estimation of a sphericity as indicator of shape of an irregularly shaped food sample.

  Volume of irregular solid sample 1=3 Sphericity ðφÞ 5 Volume of circumscribed sphere Volume determination measurement and its importance were discussed under Section 3.2.2 of this chapter. The volume of the sphere is given by the following formula and that of the irregularly shaped solid sample will be determined by a liquid displacement method (Fig. 3.1). Volume 5

4 3 πr ; 3

where r is the radius of the sphere. The estimation of the sphericity of the solid sample depends on the assumption that the volume of the solid is equal to the volume of a triaxial ellipsoid with diameters equivalent to the solid sample. The sphericity is then given as  1=3 Ve φ5 Vc where φ is the sphericity; Ve is the volume of the triaxial ellipsoid; Vc is the volume of the circumscribed sphere.

3.3.3 Angle of Repose Angle of repose is another important physical property used for characterization of the bulk of particulate foods such as seeds, grains, flours, grits, and fruits. When granular solids are piled on a flat surface, the sides of the pile are at a definite reproducible angle with the horizontal leveled surface (Fig. 3.8). This angle is called the angle of repose of the HANDBOOK OF FARM, DAIRY AND FOOD MACHINERY ENGINEERING

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FIGURE 3.8 Demonstration of angle of repose for a pile of sorghum grain (A) and chia seeds (B).

material. The angle of repose is important for the design of processing, storage, and conveying systems of particulate materials. When the grains are smooth and rounded, the angle of repose is low. For very fine and sticky materials the angle of repose is high. Materials with low angle of repose are highly flowable and can be transported using gravitational force or a little energy. For determination of this property, a box with open sides at the top and bottom is placed on a horizontal surface. The angle of repose is determined by either tilting box, fixed funnel, revolving cylinder, or hollow cylinder methods, in all of which the containers are filled with a sample and gradually lifted up, allowing the sample to accumulate and form a conical heap on the surface. Then, the angle of repose can also be calculated from the ratio of the height to the base radius of the heap formed based on different mathematical models (Al-Hashemi and Al-Amoudi, 2018). The angle of repose is related to the free flowability properties of particulate materials in bulk forms (Teunou et al., 1999). The angles of repose of some common food grain bulks are given in Table 3.2. This physical property is also dependent on the surface properties of the individual particulates. For instance, flax seed has a smooth surface that prevents piling up of the seeds on top of each other and this gives it the least angle of repose compared with sesame seeds (Table 3.2), which have fairly comparable seed size and shape, but higher angle of repose. Material bulks like flax seed are known as freely flowable and usually have angle of repose less than 30 degrees, whereas materials with angle of repose greater than 55 degrees are extremely cohesive/sticky/caking and nonflowable (Al-Hashemi and Al-Amoudi, 2018).

3.4 RHEOLOGICAL PROPERTIES Rheology is the science that studies forces and materials. More precisely rheology is the branch of physics that deals with deformation of solid materials and flow of liquid HANDBOOK OF FARM, DAIRY AND FOOD MACHINERY ENGINEERING

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TABLE 3.2

Angles of Repose of Some Grain Seeds.

Seeds

Angle of Repose (π)

Flax seed

25

Peanut (unshelled/whole)

40

Peanut (shelled)

30

Soybean (whole)

35

Rapeseed/canola

45

Rice bran

45

Safflower seed

45

Sesame seed

45

FIGURE 3.9 Classification of rheological properties based on material states (solid, liquid).

materials. Rheological data are required in product quality evaluation, engineering calculations and process, as well as machine designs. An understanding of flow properties of food materials is necessary to determine the size of the pump and pipe as well as the energy requirements. Rheology can be classified into different groups as shown in Fig. 3.9.

3.4.1 Rheology of Solids The rheological property of solids is called elastic behavior. The determination of rheological properties of solid foods can be divided into two broad categories. Fundamental tests measure properties that are inherent to the material and do not depend on the geometry of the test sample, the conditions of loading, or the apparatus. Examples of these properties are modulus of elasticity, Poisson’s ratio, relaxation time, and shear modulus. Empirical or imitative tests are used to determine properties such as puncture force, where the mass of the sample and geometry determine the magnitude of the properties being estimated. The fundamental tests applied to solid foods may also be classified into two HANDBOOK OF FARM, DAIRY AND FOOD MACHINERY ENGINEERING

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different groups: those conducted under conditions of static or quasistatic loading (no or minimal motion), and those conducted under dynamic (motion) conditions (Sahin and Sumnu, 2006; Rao and Quintero, 2014). When a force is applied to a material and immediately produces a deformation that is finite and proportional to the magnitude of the force being applied and the material regaining its initial form (size and shape) on removal of the force, the test material is said to have a pure elastic behavior. Materials with pure elastic behavior are called Hookean solids. The rheological representations for these types of solids are springs and rubber bands. A material of this nature can be given a rheological constant, termed the elastic modulus. The elastic modulus is the ratio of stress (magnitude of the force acting) to strain (the magnitude of the resulting deformation) in a material. Stress is equal to force per unit area and the strain is the observed deformation due to the force, divided by the original length of the material. Three types of moduli may be calculated for a Hookean solid, depending upon the method of applying the force. These are considered as material constants, because the deformation is proportional to the applied force, and unit area and length are considered in the calculations. i. Modulus of elasticity (E) is calculated by applying a force perpendicular to the area defined by the stress. ii. Shear modulus [modulus of rigidity (G)] is calculated by applying a force parallel to the area defined by the stress. iii. Bulk modulus (K) is the case where the force is applied from all directions (isotropically). The simplest of all the quasistatic tests is perhaps the uniaxial compression tension test (Fig. 3.10), in which a sample with a convenient geometry (cylinder or rectangular prism)

FIGURE 3.10 Uniaxial (left), shear (middle), and isotropic/bulk (right) stresses of an elastic solid; broken lines represent original shape/size and solid boundaries show changes (strains).

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FIGURE 3.11 Normal (left) tensile (top) and compressive (bottom) versus shear (right) stresses; solid boundaries represent original shape/size and broken boundaries show deformed ones.

is subjected either to a deformation or to a force, and the corresponding force or deformation is recorded. If the magnitudes of force and deformation are small, then the body may be assumed to be elastic. The resultant stress (σ) and strain (ε) may be calculated as σ5

F ΔL and ε 5 A L

where F is the force, A is the cross-sectional area of the sample, ΔL is the deformation, and L is the original length of the samples Stress can be categorized into two groups: normal stress and shear stress. The difference between these two stresses depends on the area that the force is acting on. Normal stress (σ) is defined as the force applied perpendicular to the plane per unit area. Pressure is an example of a normal stress. Normal stress can be tensile or compressive depending on whether it tends to stretch or to compress the material on which it acts [Fig. 3.11 (left)]. In shear stress, the stress acts tangential to the surface. Shear stress (τ) is defined as the force applied parallel to the plane per unit area [Fig. 3.11 (right)].

3.4.2 Rheology of Liquids Fluid foods (that flow under gravity and do not retain their shape) are encountered widely in everyday life. Flow properties of foods are determined for a number of reasons, such as quality control, understanding the structure, process engineering applications, and correlations with sensory evaluation. Correlation with sensory evaluation is a unique area of rheology of liquid and semisolid foods. In particular, food rheologists have made unique contributions to the study of mouthfeel and its relation to basic rheological parameters. Viscosity is defined as the resistance of a fluid to flow. The unit of dynamic viscosity is (Pa s) in the SI system and poise (g/cm s) in the CGS system. Viscosity varies with temperature where the difference in the effect of temperature on viscosity of liquids and gases is related to the difference in their molecular structure and mobility. Viscosity of most of the liquids decreases with increasing temperature. Fluid foods can generally be categorized into three groups based on their rheological behaviors. These are viscous, plastic, and time dependent rheological properties. Details of each of these categories will be presented in the following subsections.

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3.4.2.1 Viscous: Newtonian Versus Non-Newtonian Fluids Viscous fluids tend to deform continuously under the effect of an applied stress starting immediately on the application of the force. Viscous materials can further be categorized as Newtonian or non-Newtonian fluids Fluids that follow Newton’s law of viscosity are called Newtonian fluids. The slope of the shear stress versus shear rate graph, which is viscosity, is constant and independent of shear rate in Newtonian fluids (Fig. 3.12). Oils, water, and most liquids that contain more than 90% water such as tea, coffee, beer, wine, carbonated beverages, runny fruit juices, and milk show Newtonian behavior. Fluids that do not follow Newton’s law of viscosity are known as non-Newtonian fluids. Shear thinning or shear thickening fluids obey the power law model (Ostwald
de Waele equation) (Rao et al., 2014):  n  n dvz τ yz 5 k 5 k γ yz dy where k is the consistency coefficient (Pa sn); n is the flow behavior index; where for shear thinning (pseudoplastic) fluids, n , 1 and for shear thickening fluids n . 1. Newtonian fluids can be considered as a special case of this model in which n 5 1 and k 5 μ. The slope of shear stress versus shear rate graph is not constant for non-Newtonian fluids (Fig. 3.12, right). For different shear rates, different viscosities are observed. Therefore the terms apparent viscosity or consistency are used for non-Newtonian fluids. The symbol η is often used to represent the apparent viscosity to distinguish it from a purely Newtonian viscosity, μ. The ratio of shear stress to the corresponding shear rate is therefore called apparent viscosity at that shear rate: τ ηð γ Þ 5 γ

FIGURE 3.12 Viscosities (apparent) versus shear rate of time independent (left) and slope (viscosity) of shear stress versus shear rate (right) for different categories of fluids; based on hypothetical data for illustration.

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The apparent viscosity and the Newtonian viscosity are identical for Newtonian fluids. However, the apparent viscosity for a power law fluid is determined with a different equation:  n γ ηð γ Þ 5 k 5 kðγ Þn21 γ 3.4.2.1.1 SHEAR-THINNING (PSEUDOPLASTIC) FLUIDS

In shear-thinning fluids, as shear rate increases friction between layers decreases. Shearing causes entangled, long-chain molecules to straighten out and become aligned with the flow, reducing viscosity. Krokida et al. (2001) and Ahmed et al. (2000) summarized rheological properties of fruit and vegetable purees. The consistency coefficient k increased exponentially while the flow behavior index n decreased slightly with concentration. Flow behavior index was close to 0.5 for pulpy products and close to 1.0 for clear juices. While the flow behavior index was assumed to be relatively constant with temperature, the effect of temperature on both apparent viscosity, η, and consistency coefficient of the power law model, k, was explained by an Arrhenius-type equation. The flow properties of peach pulp
granular activated carbon mixtures at temperatures of 15 C
40 C and at granular activated carbon concentrations of 0.5
5.0 kg/m3 exhibited a shear-thinning behavior (Arslanoglu et al., 2005). The flow behavior index and the consistency coefficient of peach pulp
granular activated carbon mixtures were in the ranges of 0.328
0.512 and 2.17
6.18 Pa sn, respectively. Both the consistency coefficient and the flow behavior index decreased with increasing temperature. Rheological behavior of foods may change depending on various concentrations. The rheological behavior of concentrated grape juice with a Brix value of 82.1 showed shearthinning behavior (Kaya and Belibagˇlı, 2002). However, diluted samples with a Brix value of 52.1
72.9 were found to be Newtonian, with no change in consistency with the changing shear. The rheological behavior of sesame paste
concentrated grape juice blends, which is a traditional food product in a Turkish breakfast meal, was studied at 35 C
65 C and at 20% to 32% sesame paste concentration (Arslan et al., 2005). All the blends showed shearthinning behavior with a flow behavior index of 0.70
0.85. The consistency coefficient was described by an Arrhenius-type equation. The rheological properties of cake batter with different fat concentrations and emulsifier types were characterized by Sakiyan et al. (2004). It was found that cake batter exhibited shear-thinning behaviors with an increase in fat content and addition of emulsifier. Flow behavior index, however, was found to be independent of the composition of cake batter. 3.4.2.1.2 SHEAR-THICKENING FLUIDS

These are exactly the opposite of shear-thinning fluids. In shear-thickening fluids, as shear rate increases, the internal friction and apparent viscosity increase. In food systems, corn starch suspension is an example of shear-thickening fluids. The shear-thickening phenomenon in native starches from different sources (waxy maize, waxy rice, waxy barley, waxy potato, wheat, rice, maize) that had been dissolved and dispersed at 3.0%

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concentrations in 0.2 N NaOH was demonstrated (Dintzis et al., 1996). Waxy starches (maize, rice, barley, and potato) showed shear-thickening behavior to a greater extent than did normal wheat, rice, or maize starches. The high amylopectin component of the waxy starch might be responsible for shear-thickening properties. If the increase in viscosity is accompanied by volume expansion, shear thickening fluids are called dilatant fluids. It can also be generalized that all the dilatant fluids are shear thickening but not all shear thickening fluids are dilatant. 3.4.2.2 Bingham Versus Non-Bingham Plastic Fluids Bingham plastic fluids are those remaining rigid when the magnitude of shear stress is smaller than a specific value called yield stress (τ 0) but flows like a Newtonian fluid when the yield stress τ 0, is exceeded. Examples in the food systems include mayonnaise, tomato paste, and ketchup. The equation below shows the behavior of Bingham plastic fluids, which require a particular shear stress (τ 0), before they start behaving like Newtonian fluid categories.   dvz τ yz 5 τ 0 1 k dy The apparent viscosities for Bingham plastic fluids can be determined by taking the ratio of shear stress to the corresponding shear rate as indicated in the following equation: ηð γ Þ 5

τ 0 1 kðγ Þ τ 0 5 1k γ γ

Non-Bingham plastic fluids are types of fluids that also require a minimum shear stress (yield stress) before flow begins, as in the case of Bingham plastic fluids. However, the graph of shear stress versus shear rate is not linear for the non-Bingham fluids. Fluids of this type are either shear-thinning or shear-thickening when the yield stress is exceeded. Fluids that obey the Herschel
Bulkley model (Bhattacharya et al., 1992) are characterized by the presence of a yield stress term (τ 0) in the power law equation:  n τ yz 5 τ 0 1 k γ yz Minced fish paste and raisin paste obey the Herschel
Bulkley model. Flow behavior of rice flour
based batter used in fried products was found to obey the Herschel
Bulkley model (Mukprasirt et al., 2000). Another model, the Casson model (Casson, 1959), which is detailed in the equation below, can also be used to characterize some non-Bingham plastic fluids:  0:5
0:5 τ yz 5 ðτ 0 Þ0:5 1 k γ yz Molten milk chocolate is a good example of food systems that obey the Casson model. When the effect of particle size distribution of nonfat solids on the flow characteristic of molten milk chocolate was investigated, Casson yield stress value was correlated with diameter and specific surface area of nonfat solids as reported by Mongia and Ziegler (2000). HANDBOOK OF FARM, DAIRY AND FOOD MACHINERY ENGINEERING

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FIGURE 3.13 Classes of fluids based on time dependence of their rheological properties; hypothetical data for illustration.

3.4.2.3 Time-Dependent Rheological Properties: Thixotropic Versus Rheopectic Pastes When some fluids are subjected to a constant shear rate, they become thinner (or thicker) with time (Fig. 3.13) (Sahin and Sumnu, 2006). Fluids that exhibit decreasing shear stress and apparent viscosity with respect to time at a fixed shear rate are called thixotropic fluids (shear thinning with time). This phenomenon is probably due to the breakdown in the structure of the material as shearing continues. Gelatin, egg white, and shortening can be given as examples of this type of fluid from the food systems. Thixotropic behavior may be reversible, partially reversible, or irreversible when the applied shear is removed and the fluid is allowed to be at rest for certain time. The opposites of thixotropic fluids are called rheopectic (shear thickening with time), where both the shear stress and apparent viscosity increase with time. This is the structure of the material building up as shearing continues (Fig. 3.13). Bentonite
clay suspensions show this type of flow behavior. It is rarely observed in food systems. Abu-Jdayil and Mohameed (2004) reported that starch
milk
sugar pastes showed a time dependent flow property. It was indicated that the behavior depends on the processing conditions. For instance, processing temperature played an important role where pasting process is at 85 C and 95 C, starch
milk
sugar pastes exhibited a thixotropic behavior, while pastes processed at 75 C behaved like a rheopectic fluid. It was noted that the thixotropy occurred at high shear stress (above 50 Pa), and the rheopexy occurred at low shear stress. Pulse proteins were known to change the rheological properties of certain food matrices. A study showed that when soy protein was added to tomato juices, thixotropic behavior was first observed at low shear rate but this was followed by a transition to rheopectic behavior at higher shear rates (Tiziani and Vodovotz, 2005). Similarly, I¸sıklı and Karababa (2005) showed that fenugreek paste, which is a local food in Turkey, exhibited rheopectic behavior.

3.5 THERMAL PROPERTIES Food processing operations such as blanching, cooking, pasteurization, and sterilization involve temperature-dependent biochemical or chemical changes. The safety and quality HANDBOOK OF FARM, DAIRY AND FOOD MACHINERY ENGINEERING

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of foods depend critically on correct temperature regimes; for example, in canning the classical problem is finding the optimum heating regime that inactivates any microorganisms while still preserving nutritional quality (avoiding overprocessing and destruction of vitamins). In high-moisture foods, heat transfer is often accompanied by a significant water mobility/transfer. Thus the quality and safety of foods depend critically on the entire temperature history and the state and distribution of water in the food. Since many stages in the processing and preservation of foods involve heat transfer, it is important to understand the thermal properties of foods. Thermal properties data are required in engineering and process designs. An energy balance for heating or cooling unit operations cannot be made and the temperature profile within the material cannot be determined without having knowledge of the thermal properties of the material. This section summarizes the thermal behaviors of foods that are commonly used in food process and machinery designs as well as in food product characterizations.

3.5.1 Thermal Conductivity Thermal conductivity of a material (k) is defined as a measure of its ability to conduct heat. It has a unit of W/m K in the SI system. A solid may be comprised of free electrons and atoms bound in a periodic arrangement called a lattice. Thermal energy is transported through the molecules as a result of two effects: lattice waves and free electrons. These two effects are additive and the total thermal conductivity in a given material is the sum of the two: kt 5 ke 1 kl ; where kt is total thermal conductivity; ke is free electron; and kl is lattice wave components. In pure metals, heat conduction is based mainly on the flow of free electrons and the effect of lattice vibrations is negligible. In alloys and nonmetallic solids, which have few free electrons, heat conduction between molecules is due to lattice vibrations. Therefore metals have higher thermal conductivities than alloys and also than nonmetallic solids. The regularity of the lattice arrangement has an important effect on the lattice component of thermal conductivity. For example, diamond has very high thermal conductivity because of its well-ordered structure. On the other hand, in porous solids such as foods and other agricultural materials, thermal conductivity depends mostly on composition but also on many factors that affect the heat flow paths through the material. Some of the limiting factors include void fraction, shape, size, and arrangement of void spaces; the fluid contained in the pores; and homogeneity (Sweat, 1995). Thermal conductivity in foods having fibrous structures such as meat cannot be the same in different directions (anisotropy) because heat flow paths through the material change with respect to direction. Thermal conductivity is known to increase with moisture content. Thermal conductivities of food materials vary between that of water (kwater 5 0.614 W/m  C at 27 C) and that of air (kair 5 0.026 W/m  C at 27 C), which in many food matrices are the most and the least conductive components, respectively. Thermal conductivity of ice is nearly four times greater than that of water (kice 5 2.24 W/m  C at 0 C). This partly accounts for the difference in freezing and thawing rates of food materials.

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Thermal conductivity of food matrices can be predicted using mathematical models that take the chemical compositions into account. Predictive models have been used to estimate the effective thermal conductivity of foods. It is important to include the effect of air in the porous foods and ice in the case of frozen ones. Temperature dependence of thermal conductivities of major food components has been studied. Thermal conductivities of pure water, carbohydrate (CHO), protein, fat, ash, and ice at different temperatures can be empirically expressed according to Choi and Okos (1986) as summarized below: kwater 5 0:57109 1 1:7625 3 1023 T 2 6:7036 3 1026 T2 kCHO 5 0:20141 1 1:3874 3 1023 T 2 4:3312 3 1026 T 2 kprotein 5 0:17881 1 1:1958 3 1023 T 2 2:7178 3 1026 T2 kfat 5 0:18071 2 2:7604 3 1023 T 2 1:7749 3 1027 T2 kash 5 0:32961 1 1:4011 3 1023 T 2 2:9069 3 1026 T 2 kice 5 2:2196 2 6:2489 3 1023 T 1 1:0154 3 1024 T 2 where thermal conductivities (k) are in W/m  C; temperature (T) is in  C and varies between 0 C and 90 C in these equations.

3.5.2 Specific Heat Capacity of Food Materials Specific heat is defined as the amount of heat required to increase the temperature of a unit mass of a material by a unit degree. Accordingly, its unit is J/kg K in the SI system. The specific heat depends on the nature of the process of heat addition in terms of either a constant pressure process or a constant volume process. However, because specific heats of solids and liquids do not depend on pressure much, except extremely high pressures, and because pressure changes in heat transfer problems of food materials are usually negligible, the specific heat at constant pressure is considered (Mohsenin, 1980). Like the thermal conductivity (Section 3.5.1), the specific heats of foodstuffs are greatly dependent on their composition. Knowing the specific heat of each component of a mixture is usually sufficient to predict the specific heat of the matrix (Sweat, 1995). For instance, the specific heat of highmoisture foods is largely dominated by water content. Specific heat data for different food materials below and above freezing points were reported by Rahman (1995). The temperature dependence of specific heat of major food components has also been studied. The specific heat of pure water, carbohydrate (CHO), protein, fat, ash, and ice at different temperatures can be expressed empirically in J/kg C according to Choi and Okos (1986) as indicated below: Cpwater 5 4081:7 2 5:3062T 1 0:99516T2 ðfor 2 40 C to 0 CÞ Cpwater 5 4176:2 2 0:0909T 1 5:4731 3 10 2 3T2 ðfor 0 C to 150 CÞ CpCHO 5 1548:8 1 1:9625T 2 5:9399 3 10 2 3T 2 ðfor 2 40 C to 150 CÞ Cpprotein 5 2008:2 1 1:2089T 2 1:3129 3 10 2 3T2 ðfor 2 40 C to 150 CÞ Cpfat 5 1984:2 1 1:4373T 2 4:8008 3 10 2 3T 2 ðfor 2 40 C to 150 CÞ Cpash 5 1092:6 1 1:8896T 2 3:6817 3 10 2 3T 2 ðfor 2 40 C to 150 CÞ Cpice 5 2062:3 1 6:0769T

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where Cp is specific heat at constant pressure and temperature (T) is in  C in these equations It is generally true that experimentally determined specific heat is higher than the predicted value. The difference might be due to the presence of bound water, variation of specific heat of the component phases with the source, and interaction of the component phases (Rahman, 1995).

3.5.3 Enthalpy and Latent Heat Enthalpy and latent heat are the two other thermal properties of great importance in characterizing food products and processing systems. Enthalpy is the heat content in a system per unit mass and hence the unit is J/kg in the SI system. It is a thermodynamic property that depends only on the state of the system and it is expressed in terms of internal energy, pressure, and volume as: H 5 U 1 PV; where H is the total heat content (enthalpy), U is internal energy, and PV is pressure and volume Latent heat, on the other hand, is the heat released or absorbed by a chemical substance or a thermodynamic system during a change of state that occurs without a change in temperature. Latent heat is a hidden energy as its impact on the temperature of the system is not observed. The effect of latent heat on the system is noted only as a phase change such as the melting of ice or the boiling of water and their reverse processes.

3.6 ELECTRICAL PROPERTIES Electrical properties of foods are behaviors related to the interactions between food materials and energies of the electromagnetic nature. Electromagnetic energies in the microwave frequency ranges have been well studied and microwave processing of foods are the major applications (Zhang, 2007). A more comprehensive review on the electrical properties of foods for more advanced applications in food processing was recently summarized by Jha et al. (2011). Electrical properties of foods are important in advanced processing technologies including pulsed electric field (PEF), Ohmic heating, induction heating, and radiofrequency (RF) processing, in addition to microwave heating. In this section food properties related to electrical conductivity in different phases and compositions will be summarized. More of the electromagnetic components will be covered in Section 3.7 of this chapter.

3.6.1 Electrical Conductivity Electrical conductivity (σ) of a material may be defined as the quantity of electric current driven by differences in voltage. Electrical conductivity can easily be determined and quantified from the measurement of the current, voltage, and dimensions of a material.

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FIGURE 3.14 Illustration of electrical conductivity in a food material with a known dimension.

FIGURE 3.15 Illustration of molar conductivity: plates that are 1 m apart with a solution of concentration C contains 1 mol of solution between the plates if the plates are of area, A 5 1/C.

Referring to Fig. 3.14, showing a conductor of constant cross-sectional area A and length L, if a voltage of V is applied across the faces, a quantity of current I flows through the material. Then, from Ohm’s law, the resistance is related to the voltage and the current as: R5

V ðOhm0 s lawÞ I

The electrical conductivity may be determined from the resistance by the expression: σ5

L AR

Electrical conductivity in liquid foods (electrolytic solutions) has been studied based on the concept of molar conductivity Λ, which represents the electrical conductivity normalized for a system wherein one mole of an electrolyte is contained between two parallel plates. This is visualized by considering a solution contained between two parallel plates of equal area, separated by unit distance (1 m), with one mole of electrolyte between the plates (Fig. 3.15). Thus if the solution is of concentration C (mol/m3), the volume of solution containing 1 mol would be 1/C (m3/mol). Since the volume of the system is A (m3), the area of the plates for a 1-mol enclosure would be A ðm3 Þ 3 1 ðmÞ 1 1 5 ðm3 =molÞ.A 5 1 ðmolÞ C C The molar conductivity, Λ, is therefore the electrical conductivity of a system with a cross-sectional area of 1/C, as compared with the electrical conductivity, σ, which is normalized per unit area. Thus Λ ðS m3 =molÞ σ 5 σ ðS=mÞ or Λ 5 1=C ðmol=m3 Þ C

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The molar conductivity concept is useful in product formulations and in determining the effect of individual ingredients on the overall electrical conductivity of a liquid phase. For strong electrolytes, the molar conductivity varies with the square root of electrolyte concentration,paccording to the empirical Kohlrausch law explained by (Sastry, 2014) ffiffiffiffi Λ 5 ΛN 2 k C thus the electrical conductivity at concentration C will be σ 5 ΛN C 2 kC1:5 ; which applies for dilute solutions up to 5 mol/m3. Notably, for solutions of low concentration, the electrical conductivity varies approximately linearly with concentration: σDΛN C For weak electrolytes, the molar conductivity depends on the extent of dissociation. For example, a weakly dissociated electrolyte at a low concentration C, exhibiting an equilibrium wherein only a fraction α being dissociated, will have ionized components of concentration Cα, while the undissociated part would have the concentration C(1 2 α), as follows: BA2B1 1 A2 ; and Cð1 2 αÞ2Cα 1 Cα

3.6.2 Factors Affecting Electrical Conductivity in Foods 3.6.2.1 Solid Foods 3.6.2.1.1 EFFECT OF MICROSTRUCTURE

The electrical conductivity behavior of solid foods depends on whether or not a cellular structure exists within the material. The properties of gels and gel-like materials, or foods in which a cell structure has been disrupted, are significantly different from materials with intact cells. It is necessary to treat these two categories separately. The effect of tissue microstructure has been characterized by Wang et al. (2001), who determined average electrical conductivities (between 25 C and 95 C) of different agricultural materials including bamboo, sugarcane, lettuce, and mustard stems both along and across the length. It was reported that conductivity along the stem was higher than that across the stem for bamboo shoots and sugarcane. However, the reverse was observed for lettuce and mustard stems. A microstructural examination revealed that two influences were important: the orientation of vascular bundles and the shape of parenchymal cells. When both types of tissue were present, the vascular bundles dominated the trend in electrical conductivity, since these are the primary modes of water and nutrient transport within plants. However, in the absence of vascular tissue, the shape of the parenchymal cells was the dominant factor, explaining the different results between the different types of tissue. 3.6.2.1.2 TEMPERATURE AND ELECTRIC FIELD STRENGTH 3.6.2.1.2.1 GELS AND NONCELLULAR SOLIDS The electrical conductivity of noncellular solids tends to increase with temperature. The trend is generally a linear one, as reported by Yongsawatdigul et al. (1995) for surimi pastes (fish/meat). On the other hand, Castro et al. (2004) have reported a slight nonlinearly increasing trend for strawberry jelly.

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Various reasons may be advanced for such effects, including the breakdown of the gel, resulting in lower drag on ions, and enhanced conductivity at higher temperatures. Electroosmotic effects are unlikely in such cases, since, as noted by Yongsawatdigul et al. (1995), products such as surimi have their cellular structures severely damaged, thus no membranes or capillaries exist for osmotic effects to take place. 3.6.2.1.2.2 SOLIDS WITH UNDISRUPTED CELLULAR STRUCTURE For solids with a cellular structure, such as fruits, vegetables, and intact muscle foods, the electrical conductivity depends on temperature as well as electric field strength. As illustrated by Palaniappan and Sastry (1991b), the electrical conductivity of a conventionally heated product undergoes little change with temperature until about 70 C. Above this temperature the cellular structure starts breaking down, and the electrical conductivity undergoes a significant increase. As the electric field strength is increased, the change in electrical conductivity becomes more gradual, until at sufficiently high field strengths, the familiar linear electrical conductivity
temperature relation is seen. This suggests that under the influence of electricity, the cell structure is broken down at lower temperatures than for conventional heating. This phenomenon has been termed as electroporation or electroplasmolysis.

3.6.2.2 Liquid Foods 3.6.2.2.1 TEMPERATURE

In most cases, the electrical conductivity of foods exhibits a linear increase with temperature. The only exceptions occur with components (such as starches) that may undergo phase transitions or significant structural changes during heating. 3.6.2.2.2 ELECTRIC FIELD STRENGTH

Variations in electric field strength in the range from 0 to 100 V/cm have negligible effects on the electrical conductivity
temperature relationship of juices, as shown by Palaniappan and Sastry (1991a). This is to be expected when the solids are inert and unaffected by the electric field. This was demonstrated by Castro et al. (2004), where obvious field strength effects for 14.5 Brix strawberry pulp were reported. 3.6.2.2.3 EFFECT OF INGREDIENTS 3.6.2.2.3.1 ELECTROLYTIC SOLUTES Effects of electrolytes are discussed under the earlier section on theory of electrolytic conductivity. The most notable electrolytes within foods are salts and acids; some gums and thickeners such as pectin may also possess charged groups that would migrate towards electrodes and contribute to electrical conductivity. 3.6.2.2.3.2 INERT SUSPENDED SOLIDS Suspended solids such as pulp and cellular matrices are typically insulators and will tend to reduce the electrical conductivity of the liquid media in which they are suspended. Liquid and semisolid materials such as fruit juices and vegetable purees can be considered as good examples of foods under these

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categories. Addition of charged gums such as carrageenan, alginates, and xanthan may be considered to improve the electrical properties of foods these types. 3.6.2.2.3.3 HYDROCOLLOIDS The influence of various hydrocolloids has been presented by Marcotte et al. (1998), who also studied the effects of concentration on electrical conductivities of hydrocolloids (starch, carrageenan, pectin, gelatin, and xanthan). It was found as expected that a neutral polysaccharide such as starch showed the lowest electrical conductivity of the group. The more highly charged hydrocolloids such as carrageenan and xanthan exhibited the highest electrical conductivity, while pectin, which is less charged than the other hydrocolloids but more charged than starch, exhibited intermediate values of electrical conductivity.

3.6.3 Advancement in and Application of Electrical Properties of Foods Interest in the electrical conductivity of foods, once primarily restricted to various testing applications, has increased in recent years, in line with the development of ohmic heating and PEF processing technologies. Ohmic heating relies on the flow of alternating (or other wave form) current through a food material to heat it by internal generation. PEF processing is application of high intensity electric field pulses of short duration (fraction of seconds), to cause microbial inactivation via membrane rupture. PEF is a nonthermal processing technology (Jeyamkondan et al., 1999; Toepfl et al., 2006) and is advantageous in retaining nutrients and other food properties susceptible to heat damage. Ohmic heating, on the other hand, is a necessary consequence of PEF processing but is minimized by external cooling methods. In recent years, both PEF and Ohmic heating technologies have been greatly explored for a variety of other applications, leading to an emergence of a class of processing technologies termed as moderate electric field (MEF) (Sastry, 2008). Equipment design and product safety assurance in both ohmic and PEF technologies depend on the electrical conductivity of a particular food. Knowledge of the electrical properties of foods of different composition and physical states is crucial in designing effective PEF, Ohmic heating, and MEF processes.

3.7 DIELECTRIC PROPERTIES Electromagnetic heating, such as microwave and RF application, depends on the way the food in question interacts with waves (Sosa-Morales et al., 2010). Microwave and RF heating find applications in many food processing techniques both in industrial and home use, including reheating, precooking, cooking, tempering, baking, drying, pasteurization, and sterilization. Electromagnetic heating processes are governed by the material’s behaviors known as dielectric properties. As microwave heating gains increasing use in food processing systems in industry and in the home, knowledge of dielectric properties becomes increasingly critical for consistent and predictable product, process, and equipment development. This section summarizes the basic principles of dielectric properties of food materials and associated factors.

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3.7.1 Basic Principles and Practices Similar to visible light waves, microwaves are part of the electromagnetic spectrum. The entire electromagnetic wave spectrum is shown in Fig. 3.16. The frequencies allowed by the Federal Communication Commission (FCC) of the United States for microwave and RF heating are shown in Table 3.3 (Datta and Davidson, 2000). When microwave energy is incident on a food material, part of the energy is absorbed by the food, leading to its

FIGURE 3.16 Spectrum of electromagnetic waves (image from Ronan, 2007 shared under Creative Commons Attribution-Share Alike 3.0 Unported license).

TABLE 3.3 Frequencies Recommended by the Federal Communication Commission (FCC) for Industrial, Scientific and Medical (ISM) Applications. Wave

Frequency

Microwave

915.00 6 13.00 MHza 2450.00 6 50.00 MHza 5800.00 6 75 MHz 24,125.00 6 125 MHz

RF

13.56 MHz 6 6.68 kHz 27.12 MHz 6 160.00 kHza 40.68 MHz 6 20.00 kHz

a

Typically, microwave heating of foods is done at 2450 or 915 MHz and RF heating at 27.12.

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temperature rise. The amount and distribution of microwave energy absorption in a food material is described by Maxwell’s equations of electromagnetics (Reitz et al., 2008). Electromagnetic waves are composed of an electric field and a magnetic field. Dielectric properties may be categorized into two: dielectric constant and dielectric loss factor. Dielectric constant (ε) is the ability of a material to store microwave energy and dielectric loss factor (ε˝) is the ability of a material to dissipate microwave energy into heat (Rao et al., 2014). The parameter that measures microwave absorptivity is the loss factor. The values of dielectric constant and loss factor will play important roles in determining the interaction of microwaves with food and dictating the effectiveness of microwave processing. Electromagnetic wave spectrum (Fig. 3.16) is characterized by wavelength and frequency. The two properties are inversely related and their multiplication product gives a constant that is the same as the speed of light and this is the same for all electromagnetic waves. Waves of high frequency (or low wavelength) are more energetic. This means that γ rays have higher energy (highest frequency and least wavelength) than long radio waves (least frequency and highest wavelength). Electromagnetic waves of higher energies are known to be highly ionizing and are known to adversely affect living entities. There is therefore a great deal of control over their generation and applications. The categories and their specific frequencies allowed for different applications are summarized in Table 3.3. Microwave and RF heating applications in food processing are common both at industrial and domestic levels. The FCC of the United States controls applications of electromagnetic and only three frequencies are allowed for food uses (Venkatesh and Raghavan, 2004).

3.7.2 Factors Influencing Dielectric Properties of Food Materials 3.7.2.1 Physical Properties 3.7.2.1.1 MOISTURE CONTENT

Water in its liquid state is very polar and can easily absorb microwave energy based on the mechanism of dipolar rotation. The dielectric constant (ε) and loss factor (ε˝) of free water are predicted by Debye models and shown in the following first and second equations, respectively (Mudgett, 1986). Debye models are expressed in terms of wavelength and temperature-dependent parameters. εs 2 εo ε0 5
2 1 εo 1 1 λs =λ εv 5

εs 2 εo
2 1 ε o 1 1 λs =λ

where εs is static dielectric constant, ε0 is optical dielectric constant, λ is wavelength of water, and λs is critical wavelength of polar solvent. Water can exist in either free or bound state in food matrices. Free water is found in capillaries but bound water is physically adsorbed to the surface of dry material. The dielectric loss factor is affected by the losses in free and bound water but since relaxation

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FIGURE 3.17 Variation of dielectric loss factor with moisture content (hypothetical data for illustration based on explanations by Sahin and Sumnu, 2006).

of bound water takes place below microwave frequencies, its effects are small in microwave processing (Calay et al., 1994). Fig. 3.17 shows the variation of dielectric loss factor with moisture content. The dielectric loss factor is constant in the bound moisture region (Fig. 3.17, region I) up to a critical moisture content but then increases sharply for high moisture contents (Fig. 3.17, region II) (Sahin and Sumnu, 2006). It can be concluded that the effect of bound water on dielectric properties of food materials is negligible. The interaction of food components with water is a significant factor in influencing their dielectric properties. The stronger the binding forces between protein or carbohydrates and water, the smaller the value of the dielectric constant and loss factor since free water in the system decreases as it is being tied with other components. This means that adjusting the moisture content is the key step in formulating microwaveable foods. The increase in water increases the polarization, which increases both dielectric constant and loss factor. Feng et al. (2002) reported that the dielectric properties of apple juice were higher compared with levels for dehydrated apples. At low moisture contents, variation of dielectric properties with moisture is small. There is a critical moisture content below which loss factor is not affected significantly (Fig. 3.17). For food materials having high moisture contents, bound water does not play a significant role and the dielectric properties are affected by dissolved constituents as well as water content. In another recent study, it was demonstrated that the dielectric loss factor of apples increased rapidly at water activity of around 0.9, which was explained by the contribution of greater amounts of mobile water to dielectric loss mechanisms (Martı´n-Esparza et al., 2006). Dielectric properties of foods decrease during drying, since free moisture content in the system decreases. 3.7.2.1.2 TEMPERATURE

It is well established that free and bound moisture content and ionic conductivity influence the rate of change of dielectric constant and loss factor with temperature. If the water is in bound form, the increase in temperature increases the dielectric properties. However,

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in the presence of free water, dielectric properties of free water decrease as temperature increases. Therefore the rate of variation of dielectric properties depends on the ratio of bound to free moisture content. During thawing of frozen/refrigerated foods for instance, both dielectric constant and loss factor show large increases with temperature. After the material thaws, dielectric properties decrease with increasing temperature for different food materials except for a salted food like ham, where the dielectric properties are affected by the ionic solution. The loss factor of ham specifically shows a continuous increase during heating. The increase in loss factor with temperature was also observed in turkey meat, which contains high amounts of ash (Sipahioglu and Barringer, 2003; Sipahioglu et al., 2003b). The variation of dielectric loss factor of a salt solution or a salty material with respect to temperature is different because the loss factor of a salt solution is composed of two components: dipolar loss and ionic loss. Dipolar loss decreases with temperature at frequencies used in microwave processing. In contrast to dipolar loss, loss factor from ionic conduction increases with temperature owing to the decreased viscosity of the liquid and increased mobility of the ions. At higher temperatures, ions become more mobile and not tightly bound to water, and thus the loss factor from ionic loss component keeps increasing with temperature. On the other hand, microwave heating of water molecules or food containing free water/moisture decreases with increasing temperature (Venkatesh and Raghavan, 2004). The reasons for this are the rare hydrogen bonds and more intense movements, which require less energy to overcome intermolecular bonds at higher temperatures. For materials containing both dipolar and ionic components, it is possible to observe first a decrease and then an increase in loss factor with increasing temperature. There are limited dielectric properties data for foods below freezing temperatures. Data obtained for frozen foods and during melting of these foods are important to achieve uniform heating and prevent runaway heating in microwave thawing and tempering processes. Sipahioglu et al. (2003a) investigated the effects of moisture and ash content on dielectric properties of ham below and above freezing temperatures (235 C to 70 C). Frozen ham samples had low dielectric properties until melting started at 220 C to 210 C. After melting took place, loss factor of ham increased with ash content (Sipahioglu et al., 2003a). On the other hand, increasing ash content reduced dielectric constant of a ham sample (Sipahioglu and Barringer, 2003). This could be explained by the fact that salts are capable of binding water, which decreases the amount of free water available for polarization. Ash content was not found to be significant in affecting dielectric constant of fruits since ash concentration is naturally low in fruits and their products (Sipahioglu and Barringer, 2003). There is a limited understanding of the dielectric properties of food at higher temperatures (above the boiling point of water). Dielectric properties at high temperatures are important for microwave sterilization and pasteurization. Dielectric properties of whey protein gel, liquid whey protein mixture, macaroni noodles, and macaroni and cheese mixture were measured over a temperature range of 20 C
121 C at different frequencies (Wang et al., 2003). The dielectric constant of all samples except noodles decreased as temperature increased at frequencies of 915 and 1800 MHz. The increase in dielectric constant of cooked macaroni noodles with temperature is likely due to its low moisture content. There was a mild increase in the loss factor of samples with temperature.

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3.7.2.2 Chemical Composition Dielectric properties of food products depend on composition. Carbohydrate, fat, moisture, protein, and salt contents are the major food components. The presence of free and bound water, surface charges, electrolytes, nonelectrolytes, and hydrogen bonding in the food product affect the dielectric properties. The physical changes that take place during processing such as moisture loss and protein denaturation also have an effect on dielectric properties. Therefore the investigation of dielectric behavior of major food components and the effects of processing on dielectric properties are important for food technologists and engineers to improve the quality of microwaveable foods, to design microwaveable foods, and to develop new microwave processes. Food components such as proteins, triglycerides, and starches have low dielectric activities at microwave frequencies. On the other hand, free water, monosaccharides, and ions have been reported to have high dielectric activity (Shukla et al., 2001). Details of the influences of the major food components on the dielectric properties under different settings will be discussed under the sections that follow. 3.7.2.2.1 SALT SOLUTIONS

Salt is one of the major components in food systems responsible for ionic conduction. Addition of salt to sturgeon caviar decreased dielectric constant but increased loss factor (Al-Holy et al., 2005). The decrease in dielectric constant with the addition of salt is due to binding of water in the system, which reduces the available water for polarization. On the other hand, addition of salt increases the loss factor since more charged particles are added to the system and charge migration is increased. Both dielectric constant and loss factor increased with temperature but this increase was steeper for sturgeon caviar to which salt had been added (Al-Holy et al., 2005). Datta and Nelson (2001) also reported that the loss factor of salt solutions may increase or decrease with increasing temperature for different salt concentrations. 3.7.2.2.2 CARBOHYDRATES

Starches, sugars, and gums are the major carbohydrates in food systems. For carbohydrate solutions, the effect of free water on dielectric properties becomes significant since carbohydrates themselves have small dielectric activities in the ranges of microwave frequencies. Hydrogen bonds and hydroxyl
water interactions also play a significant role in dielectric properties of high sugar, maltodextrin, starch hydrolysate, and lactose (Roebuck et al., 1972). 3.7.2.2.2.1 STARCH Variation of dielectric properties of starch with temperature depends on whether starch is in solid state or in suspension form. When the dielectric properties of different starches in powder form were measured at 2450 MHz, both the dielectric constant and the loss factor increased with temperature. The lower the bulk density, the lower the loss factor observed. It was also reported that loss factors of other granular materials is dependent on bulk density (Calay et al., 1994; Nelson, 1983). For starch suspensions, the effect of free water on dielectric properties becomes significant. Dielectric constant and loss factor of different starch suspensions were shown to

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decrease as temperature and starch concentration increased (Ndife et al., 1998; Ryyna¨nen and Ohlsson, 1996). The dielectric properties of aqueous solutions are inversely related with temperature in the absence of ions. The increase in starch concentration decreases both the dielectric constant and loss factor since starch molecules bind water and reduce the amount of free water in the system. Gelatinization of starch is an important physical phenomenon in thermal processing of moist foods. Starch gelatinization affects dielectric properties of foods. When the dielectric properties of gelatinized and ungelatinized potato starch were compared, dielectric constant of gelatinized potato starch was found to be higher than that of ungelatinized starch (Motwani et al., 2007). 3.7.2.2.2.2 SUGAR Sugar is an important microwave absorbing food ingredient as compared with other hydrocolloids. Sugars modify the dielectric behavior of water. The hydroxyl
water interactions stabilize liquid water by hydrogen bonds and affect the dielectric properties of sugar solutions. Dielectric properties of glucose solutions having different concentrations (10%
60%) were found to be a function of temperature and composition (Liao, 2003). Dielectric constant of glucose solution increased but the loss factor of glucose solution decreased with temperature. Increasing glucose concentration decreased dielectric constant since less water was free to respond to the electric field. There is a critical sugar concentration that affects the dielectric loss factor of sugar solution. When the temperatures exceeded 40 C, loss factor increased with an increase in concentration since more hydrogen bonds are stabilized by the presence of more hydroxyl groups of sugars. However, at lower temperatures glucose solution became saturated at lower concentration and loss factor decreased with glucose concentration. 3.7.2.2.3 GUMS

Gums have the ability to bind high amounts of free water in the system. Therefore depending on the amount of moisture bound to the gums, dielectric constant and loss factor of the system change. Charge of the gum is a significant factor in affecting its dielectric properties. As the charge increases, the amount of moisture bound to the charged groups increases, which lowers the dielectric constant and loss factor (Prakash et al., 1992). For microwaveable food formulations, it is important to know the water binding capacity of the gums and viscosity of the solution to have an idea about the dielectric properties of a particular food and its suitability for microwave heating. When hydrocolloids are used in the range of 0.1%
2.0%, they can immobilize 25%
60% of water (Shukla et al., 2001). Since hydrocolloids can bind different amounts of water, food formulations containing one or more than one hydrocolloid are expected to have different amounts of free water in the system, which can affect polarization. Therefore interaction of food with microwaves is expected to change in the presence of gums. 3.7.2.2.4 PROTEINS

Proteins in different forms (peptides, free amino acids) are the second most abundant component of many dry foods. Free amino acids are dielectrically active. Free amino acids and polypeptides contribute to the increase in dielectric loss factor. Since protein dipole moments are a function of their amino acids and pH of the medium, the dielectric

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properties and microwave reactivity of cereal, legume, milk, meat, and fish proteins are expected to be different. The water adsorbed on the protein also affects their dielectric properties. Dielectric properties of proteins change during denaturation. Protein denaturation is defined as the physical change of the protein molecule due to heat, UV, acidity, or agitation, which results in a reduction in protein solubility and increase in solution viscosity. During denaturation of proteins, since the structure of protein is disturbed, the asymmetry of the charge distribution will increase. This will result in large dipole moment and polarization, which will affect the dielectric properties. Moreover, moisture is either bound by the denaturing protein molecule and causes a decrease in dielectric properties or water may also be released to the system resulting in an increase in the dielectric properties. It is therefore important to carefully investigate and optimize the conditions for proteinaceous foods designed for microwave processing operations. 3.7.2.2.5 FATS

Since lipids are hydrophobic except for ionizable carboxyl groups of fatty acids, they do not interact much with microwaves (Mudgett and Westphal, 1989). This means that the dielectric properties of fats and oils are very low. The effect of fat on dielectric properties of food systems is mainly the result of their dilution effect in the system. The increase in fat content reduces the free water content in the system, which reduces the dielectric properties.

3.8 OPTICAL PROPERTIES Optical properties of foods are behaviors associated with the interactions of food materials and electromagnetic radiation in the range of optical wavelengths and frequencies, which include visible light and colors. Studies and application of optical properties of materials also deal with the medium dependent transmission, reflection, and refraction of the electromagnetic spectrums in the visible ranges. This section provides brief summary of the importance of optical properties in food processing and quality management.

3.8.1 Refraction and Reflection The speed of light is much lower when it must travel through a material medium, and the speed will depend on the physical properties of the medium. When a beam of light (electromagnetic waves) crosses the interface between two different media, the different physical properties of these media will cause the light waves to travel at different propagation velocities in the different mediums. This results in the electromagnetic light beam changing direction when it crosses the boundary between the two mediums and this phenomenon is called refraction and is shown in Fig. 3.18. Consider a light beam like that shown in Fig. 3.19, in which the light is passing from medium 1 into medium 2; part of the light “bounces back” at the interface and this phenomenon is called reflection, while the other part is refracted as it enters material 2.

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FIGURE 3.18

Refraction as a consequence of different speeds of wave propagation through different materials.

FIGURE 3.19 Angles of reflection (α) and refraction (β) when light strikes an interface of different materials with refraction indices n1 and n2.

According to Huygen’s principle (Sommerfeld, 1964), all points at the interface are starting points of spherical waves propagating through medium 2. If these waves have a lower propagation speed in medium 2 than they did in medium 1, they will change the direction of the light beam as a consequence. The refraction angle β in Fig. 3.19 can be calculated with Snell’s law (Bryant, 1958): C

sinα C1 n10 5 sinβ C2 Cn 0 2

sinα n2 5 sinβ n1 where C1 is the speed of light in material 1 in m/s; C2 is the speed of light in material 2 in m/s; C0 is the speed of light in vacuum in m/s; n1 is the refraction index of material 1; n2

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FIGURE 3.20 Measurement of refraction by total reflection.

is the refraction index of material 2; α is the angle of incidence (incoming light); β is the angle of refraction (outgoing light). As the angle of incidence α increases, so does the refraction angle β (Snell’s law). When β 5 90 degrees, no light will enter the material at all, and all incident light will be reflected. The angle of incidence causing this to happen is called the critical angle of total reflection. It can be used for measurement of refraction indices as detailed in the equation below. Fig. 3.20 shows a schematic diagram of a refractometer based on measurement of the angle of total reflection. By adjusting the angle g of the incoming light (angle of incidence α) until the detector (placed at position 8) gets a signal, the critical incident angle αg is reached when the outgoing light has an angle of refraction β 5 90 degrees. When n1 is known, we can calculate the remaining using the following equation: sinαg sinα n2 5 5 sinβ n1 sin90 where αg is the critical angle for total reflection. Snell’s law and the simplified definition of the refraction index as ratio of wave propagation speeds are only valid in regular geometric optics in the range of small wavelengths, and in optically transparent media, which is not the case for most foods. The refractive indices of some food components and other nonfood materials are presented in Table 3.4 (Shafei, 2015).

3.8.2 Light and Color Visible light is electromagnetic radiation with wavelength ranging between 380 and 750 nm. Larger wavelengths belong to infrared (IR) radiation and smaller wavelengths belong to ultraviolet radiation (UV), and are invisible to the human eye. The visible light is only a small part of the total spectrum of electromagnetic waves (Section 3.7.1; Fig. 3.16) and ranges of wavelength for the different colors are presented in Table 3.5. The speed of light is the speed at which the light waves propagate, and can be calculated mathematically as the product of wavelength and frequency. C 5 λ 3 f; where C is speed of wave propagation in m/s; λ is the wavelength in m; and f is the frequency wave in s21.

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TABLE 3.4 Refractive Indices of Some Materials. Materials

Refractive Index at 20 C, 20 kPa, λ 5 589 nm

Water

1.333

Ethanol

1.362

Aqueous sucrose solution, 20% (m/m)

1.364

Air

1.0003

Quartz glass

1.459

Diamond

2.414

TABLE 3.5 Approximate Wavelength Ranges of Some Colors. Colors

Wavelength (nm)

Red

700
770

Yellow

570
590

Green

490
560

Blue

400
475

The range of wavelengths for visible light can be further subdivided into smaller ranges that are each responsible for the different colors, such as the colors of the rainbow. The wavelength ranges for the primary colors: red (high), yellow (medium), and blue (low) are as listed in Table 3.5.

3.8.3 Color as a Vector Quantity A convenient way to describe a color as a quantity is to treat it like a vector quantity with three components. Based on this vector system with three components, we can indicate a color with numbers after the development of different color systems. For example, we can say color number 80
70
50 after Commission Internationale de l’Elcairage (CIE) or number 7:3:2 after Deutsche Institut fu¨r Normung - German Standards Institute (DIN) 6164, in which cases the communication for describing a color is not vulnerable to problems of human perception and subjective judgment. The systems devised to quantitatively express colors based on their wavelengths are important in engineering and technical applications. Three attributes of color are commonly used for the purposes of technical descriptions. These attributes are hue, chroma, and brightness. A summary of the brief descriptions of these attributes is presented in Table 3.6. Fig. 3.21 also presents the chromaticity diagram developed by the CIE system in the early 1930s, where colors are arranged in a horseshoe shape with the three attributes ranging for different colors at the edges of the diagram.

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TABLE 3.6 Terms Used in Colorimetry. Attribute

Description

Example

Hue

Region in chromaticity diagram

Red, red-yellow, yellow, green yellow, green, green-blue purple, blue, purple-blue

Brightness Degree b/n darkness and maximum brightness Chroma

Bright red-yellow or dark red yellow

Degree of color or colorlessness (brilliance or paleness) Brilliant red-yellow or pale red yellow

FIGURE 3.21 Chromaticity diagram (CIE 1931) with approximate color regions based on original description by Judd et al. (1964) (taken from Carmona-Te´llez et al., 2015 with permission).

3.8.4 Color Measurement Using the L*a*b* Method One of the first laboratory methods for quantifying colors is the system devised by Munsell, who was an artist and published his color notation in 1905 to have a rational way to describe them. In this system, a color is marked by a vector, which points to a place in the color space indicating the hue of the color. The length of the vector d indicates the distance from the point of zero color, and quantifies the chroma of the color, while the angle α gives the hue. The vertical axis is scaled for the brightness of the color (Fig. 3.22). So, to describe the color of interest we have to specify hue (α) and d of the vector and the value of brightness. Another presentation of the color vector is made in the Judd
Hunter system. Here, the vector pointing to the place in the color space is indicated with the coordinates a and b. The brightness L again is scaled on the vertical axis (Fig. 3.23). This system often is called the L
a
b system. The a-axis and b-axis are scaled from
100 to 1100. So, with the

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FIGURE 3.22 Illustration of color description as a vector using the Munsell system with brightness, hue and chroma parameters.

FIGURE 3.23

Illustration (approximate) of the color space in the CIE Lab or L*a*b* system.

Judd
Hunter system we describe a color with three numbers (L
a
b), which are all between 0 and 100. Using the L
a
b system we see positive values to represent red, 2 a for green, 1 b for yellow, and 2 b for blue. The L
a
b system is more commonly used in recent food characterization research and quality control.

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When we compare Fig. 3.22 with Fig. 3.23, we see that they are based on the same idea of specifying a point in the three-dimensional color space, but there are differences in the terms used. The angle, α, can be calculated from a and b as per the following relationship: tanα 5 Then the chroma d calculated by d5

b a

pffiffiffiffiffiffiffiffiffiffiffiffiffiffi a2 1 b2

In the Munsell system, an arrow (vector) points to a place in the color space. The arrow is described by angle α and length d. The vertical axis represents the brightness scale. The Judd
Hunter system is widely used, and is often called the L
a
b system. Variations of the name include L*a*b system and CIE Lab system. It should also be understood that all standards for describing colors are based on defined conditions of illumination and observation.

3.8.5 Other Forms of Optical Waves of Importance to Food Application 3.8.5.1 Infrared IR radiation is the part of the electromagnetic spectrum (Fig. 3.16) with wavelengths in the range from λ 5 0.8 to 1000 μm. In IR spectroscopy the reciprocal of wavelength, also called wave number, is used instead of the wavelength. The SI unit for wave number is the reciprocal of that of the wavelength (m21), but most commonly the unit of cm21 is in use. The range of IR wavelengths is further subdivided into the near infrared (NIR), middle infrared (MIR), and far infrared (FIR) (Table 3.7). IR spectroscopy is increasingly becoming a convenient and often nondestructive analysis method in food characterization. Analysis of the results from IR spectroscopy is accomplished by plotting the infrared absorption in a sample material against frequency. These plots are known as the absorption spectrum of the sample material. However, for reasons of tradition in IR spectroscopy, the wave number is used instead of the frequency. In addition to absorption spectra, transmission spectra can also be obtained and used in IR spectroscopic analysis techniques. IR spectroscopy has certain limitations that depend on the nature of the materials under investigation. One of the limitations is that it can only be used with materials that contain IR active molecules, which are capable of absorbing IR radiation. The IR has gotten wider TABLE 3.7 The Different Categories of Infrared. Abbreviations

Description

λ (nm)

ʋ (cm21)

NIR

Near IR

800
2500

4000
12,500

MIR

Middle IR

2500
5000

2000
4000

FIR

Far IR

5000
1000,000

10
2000

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application in food processing industries such as in quality control, chemical analysis, and process monitoring, among others. 3.8.5.2 Ultraviolet UV light is electromagnetic region with a wavelength shorter than that of visible light, but longer than soft X-rays (Fig. 3.16). UV rays can also be subdivided into near UV radiation with wavelengths in the range 380
200 nm, far or vacuum UV with wavelengths in the range 200
10 nm, and extreme UV with wavelengths in the range 1
31 nm. When considering the effect of UV radiation on human health and the environment, the range of near UV wavelengths is even further subdivided into UV α (380
315 nm), also called long wave or “black light” UV β (315
280 nm), also called medium wave; and UV γ ( , 280 nm), also called short wave or “germicidal.” UV light is a known carcinogen (Ananthaswamy and Pierceall, 1990) and should carefully be handled. UV radiation is often used in connection with visible spectroscopy or photometry to determine the existence of fluorescence in a given sample, and it is widely used as an analytical technique in chemistry for the determination of chemical structures. Perhaps more importantly, UV radiation has become increasingly appealing as an effective disinfecting agent in treatment of drinking water and in cold food processing. It is also used for disinfection of equipment surfaces and microbial analysis laboratory rooms (Rutala et al., 2010; Jinadatha et al., 2014).

3.9 ACOUSTICAL PROPERTIES 3.9.1 Basics of Sound as a Wave Acoustical properties of foods are those that govern how materials respond to sound waves, which are what we perceive as sound (Figura and Teixeira, 2007). We are all familiar with how a disturbance in a body of water will cause waves to develop and travel along the surface of the water in all directions away from the disturbance. Air is also a fluid and responds to a disturbance in the same way, by creating air waves that travel in all directions away from the point of disturbance. Just as with waves on the surface of water, the air waves are peaks and valleys of relatively high and low pressure that can be sensed as oscillations of air pressure at a given frequency. These oscillating air waves with frequencies ranging between 16 Hz and about 16,000 Hz (16 kHz) are sensed by the human ear as audible sound. Sound waves with higher frequencies are called ultrasound, and those having frequencies larger than 109 Hz are known as hypersound (Table 3.8).

3.9.2 Speed of Sound in Various Material Mediums The speed of sound depends on the coupling or bonding strength between the vibrating molecules or atoms within the material medium through which the sound waves are being transmitted. This bonding strength is much greater in solids than in liquids and greater in liquids than in gases where molecules have little interaction. For this reason, sound waves travel much faster in solids than in liquids, and faster in liquids than in gases. Sound

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TABLE 3.8 Categories of Sound Waves With Varying Frequencies. Categories

Frequencies

Infrasound

0
16 Hz

Audible sound

16 Hz
16 kHz

Ultrasound

20 kHz
10 GHz

Hypersound

109
1012 Hz

TABLE 3.9

Speed of Sound in Different Media.

Material Medium

Speed of Sound [v (m/s)]

Iron

5170

Lead

1250

Water

1464

Hydrogen

1284

Oxygen

316

Air

331

TABLE 3.10

Temperature Dependency of Speed of Sound in Air.

Material

Temperature ( C)

Speed of Sound [v (m/s)]

Dry air

220

319

Dry air

0

331

Dry air

20

344

Dry air

100

387

Water vapor

130

450

cannot travel through a vacuum due to the absence of particles that vibrate and facilitate the passage of sound waves. For comparison purposes some data on the speed of sound in different material examples are shown in Table 3.9. Because of the weak coupling strength in gases, the speed of sound through a gaseous medium depends more on how close together the molecules are. The distance between molecules in a gas will depend on its density, which will be a function of pressure and temperature. Therefore the speed of sound in air depends on its density, which in turn will depend on temperature and pressure, as well as humidity (Table 3.10). Knowledge of the acoustical properties of different food materials is important in designing and applying ultra and hypersound processes for food preservation and quality management activities.

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3.9.3 Noise The definition of sound waves as simple oscillations of air pressure with a given frequency, wavelength, and speed is clearly discussed in the previous subsections. When simple sound waves of this type reach our ear, we perceive the sound to be like a tone in music. Several distinct tones being received at the same time together is perceived as what is known as a clang. When we receive sound, which contains a continuous range of frequencies, it is called noise. A noise can be typical and expected for a given process, and can be used to analyze or to characterize the process. For instance, noises like cracking, crushing, popping, crackling, sizzling, frizzling, and detonating can be an expected characteristic for a given process or event. Such noises are time dependent combinations of tones with different intensities. When we wish to characterize a food material for purposes of consumer perception, we often use specific terms for the acoustic information provided by taste panelists during sensory analysis. One can a bite a crispy or crusty food and try to describe the crispiness; the perception of crispiness is taken from the sound that is made in our mouth. A person without an acoustic sense would not be able to describe crispy food with the acoustic properties. Such a person would have to rely on dental sensations coming from the teeth breaking or crushing the food item. The perception of sound can be used as a descriptor of the textural quality of food. For example, the noise we hear when biting a piece of food may give us information about the freshness of vegetables or about how well cooked they are. The acoustic properties of foods are applied in determining the freshness of fruits such as apple and the moisture contents of dried products such as grains. Similarly, the crispy nature of dried and fried foods is also analyzed using ultrasound-based technologies.

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