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Transport Properties in Food Process Design
Abstract
Food process design is concerned with the engineering design and economics of industrial food processes. Quantitative analysis of food processing operations requires material and energy (heat) balances on the process flowsheet. Equipment and energy (heat) requirements are calculated from rate equations of momentum (flow), heat, and mass transfer.
Process engineering calculations require the thermal and transport properties of foods, which are taken from the literature. Reliable values of thermal properties (specific heat and enthalpy changes) can be predicted from empirical correlations or taken from published data.
Transport properties (viscosity, thermal conductivity, and mass diffusivity) are strongly affected by the composition and physical structure of the food product, such as apparent density and porosity.
The rheological properties of fluid foods are affected by the size and concentration of the dissolved molecules or suspended particles. Temperature has a stronger effect on the viscosity of concentrated solutions, such as sugars, than on the apparent viscosity of suspensions.
Experimental data on thermal and mass diffusivity are essential. The thermal conductivity of solids decreases at higher porosities, while the opposite effect is observed with mass diffusivity. Temperature has a small effect on thermal conductivity, while mass diffusivity is affected strongly in nonporous and less in porous solids.
Heat and mass transfer coefficients in food process design are affected by the heat transfer medium, food material, and process equipment. Approximate values of the transfer coefficients are obtained from data in the literature and empirical correlations.
... A large number of papers addressing the experimental evaluation of food properties can be found in the literature, and in many of these, great efforts have been made to estimate the diffusion coefficients of water within a solid matrix. [5] Several methods to generate such estimates have been proposed and applied to regularly shaped foods undergoing drying under well-defined experimental conditions (steady or unsteady states). ...
... A constant, linear concentration gradient develops in the sample under these conditions, and the diffusion coefficient (or permeability) can be estimated using Fick's first law. The concentration-distance curve method [5] is based on the measurement, at a definite time t, of the moisture concentration profile that develops within a sample due to mono-dimensional diffusion transport. Here, the solute concentration profile is determined by slicing and weighing the sample, though some technical problems related to the slicing process itself have been reported. ...
... Here, the solute concentration profile is determined by slicing and weighing the sample, though some technical problems related to the slicing process itself have been reported. [6] The so-called sorption/desorption method, [5] as well as the drying method, is based on the utilisation of a regularly shaped sample subjected to a drying process under constant and controlled operating conditions. The sample weight is monitored at regular intervals to evaluate the moisture loss (or the weight increase, in the case of sorption) until the sample mass remains static. ...
The aim of this work was to estimate shrinkage, apparent density changes, and the effective diffusion coefficient of water, Deff , during eggplant drying. Drying experiments were performed using a halogen moisture analyzer. This technology has several advantages over the traditional methods reported in the literature, as it is quite inexpensive, requires less energy, and, in principle, can be used for many different types of foods. The experimental data were interpreted using a classical mathematical model that describes the transient mono-dimensional transport of water in food to estimate Deff . Under the experimental conditions examined, the Deff, was found to range from 1.13.10−10 to 5.65.10−10 m2/s. Shrinkage modelling revealed a non-linear dependence of food sample volume on the food's moisture content. In addition, while the apparent density of the food did not change appreciably during the first period of drying, a marked decrease was observed during the final drying period.
... From Table 2, it is possible to note that D eff ranged from 2.60 Â 10 À6 to 7.65 Â 10 À6 m 2 /s, where the lowest value was obtained at processing conditions of 42.9 C and 3 m/s, and the highest value was obtained at 57.1 C and 3.0 m/s. The results are out of the range presented for vegetables in Saravacos and Maroulis (2001) with a range between 2.20 Â 10 À12 and 3.05 Â 10 À7 m 2 /s but are in the range presented for legumes (2.06 Â 10 À14 to 1.07 Â 10 À6 m 2 /s) and cereal (8.33 Â 10 À12 to 4.04 Â 10 À6 m 2 /s) products (Saravacos and Marouli, 2001). ...
The design and development of gluten-free foods requires a comprehensive understanding of the behavior of the raw materials to attain the same cooking and nutritional quality as gluten-based food. The objective of this study was to determine the optimal hot-air drying conditions for elaboration of cassava flour to be used in a gluten-free pasta formulation. The results showed that the operational conditions to minimize the hot-air drying time (57 min) to produce cassava flour with higher water holding capacity was 57 ℃ at 3 m/s. Then, the optimal formulation for the pasta was found to be cassava (26 g/100 g), amaranth flour (12 g/100 g), and carboxymethyl cellulose (0.23 g/100 g), which maximized the Aw (0.160), moisture content (3.10 g/100 g), hardness (5.02 N), and protein content (9.30 g/100 g), and it is used for the sensorial analysis, which showed that an earthy taste was the main problem with consumer satisfaction.
... Previous researches have not considered polynomial modeling in potato drying. The diffusion coefficient values obtained here are within the range given by Saravacos et al. (2001). This work successfully predicted drying curve for drying process by interpolation. ...
In this work studies were carried out on effect of temperature and air velocity (for low flow rates) on drying kinetics of English potatoes (batata inglesa). English potato slices of dimensions 4cm by 4cm by 5mm were put in four trays and air at different conditions and flow rates passed through them for analysis of corresponding drying characteristics. Air flow and source of heat were provided by a suction pump. Though low air flow rates were used, increase in their quantity resulted in increase in the drying rate. Increase in drying air temperature resulted in increase in rate of loss of moisture. A unique method of prediction (interpolation) is also attempted here.
... The density can be defined in different ways [3,4]: true density, substance density, apparent density, bulk density and particle density. Bulk and particle densities are vital parameters in the design, modeling and optimization of food processing operations because they have a direct affect on the thermophysical properties of food materials [3]. ...
The objective of this paper is an analysis of the influence of drying air temperature and the drying air velocity on the particle density. The particle density of apple, banana, potato and carrot slices during convective drying was experimentally determined. Drying experiments were conducted in a laboratory air-dryer, repeated at different air temperatures and air velocities. The drying air temperatures considered were 40, 50, 60 and 70 °C with drying air velocities of 1, 2 and 3 m/s. Two simple mathematical models for correlating the dimensionless particle density with the dimensionless material moisture content, drying air temperature and drying air velocity are proposed. The models were fitted to experimental data and the correlation coefficients and residual sum of squares were estimated. Nomenclature A, B, C -parameter MRD -mean relative deviation m (kg) -mass n -degrees of freedom R -dimensionless particle density RSS -residual sum of squares r -correlation coefficient V (m 3) -volume SE -standard error of the estimate X -dimensionless moisture content x (kg/kg d.b.) -moisture content Y cal -estimated value Y exp -experimental value Greek symbols ρ (kg/m 3) -density Subscripts 0 -initial a -air ap -apple ba -banana ca -carrot p -particle po -potato s -solid
... A non-linear relation between shear rate and shear stress can be observed. Such behaviour is typical of non-Newtonian fluids (Saravacos & Maroulis, 2001). All formulations (rheograms) presented a good fit to the Ostwald-de- Waelle (Power-Law) model according to Table 2as shear-thinning, as their apparent viscosity decreases as the shear rate is increased (Fig. 4). ...
In this work the stability and the rheological behaviour of salad dressing containing ‘Minas Frescal’ whey cheese was studied. The salad dressing was stabilised by xanthan gum (XG), propylene glycol alginate (PGA) and carboxymethylcellulose (CMC). All samples were stable for a period of 4 months. The rheological model of Ostwald-de-Waelle (Power-Law) was used in order to fit the data and to obtain the rheological parameters of flow behaviour index (n), consistency coefficient and apparent viscosity (ηap). All formulations showed a pseudoplastic behaviour and the PGA contributed to increase the values of flow behaviour index. Consistency coefficient was similarly affected by XG and PGA fractions. Apparent viscosity was highly influenced by the hydrocolloid CMC, with higher values of apparent viscosity in the proportion of 0.25/0.25/0.5% (PGA/XG/CMC). Hydrocolloid association (ternary mixtures) was statistically significant, resulting in an increase of K and ηap parameters. The results show that salad dressing with whey as aqueous phase and stabilised by a ternary combination of XG, PGA and CMC can be a technological alternative to the food industry.
Distributions of thermo-physical properties: such as porosity and thermal conductivity of Japanese apricot and pear during storage were determined based on X-ray CT image analysis. Japanese apricot was stored at 25 °C, whereas pear was stored at 25 °C and 5 °C. Average CT value was determined based on a series of X-ray CT images captured for each whole fruit. At the end of storage period, the average CT value decreased in Japanese apricot and pear at 25 °C, whereas it was the almost same as pear stored at 5 °C. Porosity increased, whereas thermal conductivity slightly decreased at 25 °C in Japanese apricot and pear. As a result of the experiment, it seemed that the internal structure of pear stored at 5 °C was well maintained during storage. Conversely, void space progressed in Japanese apricot and pear during storage at 25 °C. The porosity and thermal conductivity distributions were visualized based on the CT image during storage.
A food property is a particular measure of the food’s behavior as a matter or its behavior with respect to energy, or its interaction with the human senses, or its efficacy in promoting human health and well-being. An understanding of food properties is essential for scientists and engineers who have to solve the problems in food preservation, processing, storage, marketing, consumption, and even after consumption. Current methods of food processing and preservation require accurate data on food properties; simple, accurate, and low-cost measurement techniques; prediction models based on fundamentals; and links between different properties. The first edition was well received,
secured bestseller from the publisher, and received an award. Appreciation from scientists, academics, and industry professionals around the globe encouraged me to produce an updated version. This edition has been expanded with the addition of some new chapters and by updating the contents of the first edition. The seven chapters in the first edition have now been expanded to 24 chapters. In this edition, the definition of the terminology and measurement techniques are clearly presented. The theory behind the measurement techniques is described with the applications and limitations of the methods. Also, the sources of errors in measurement techniques are compiled. A compilation of the experimental data from the literature is presented in graphical or tabular form, which would be very useful for food engineers and scientists. Models can reduce the numbers of experiments, thereby reducing time and expenses of measurements. The empirical and theoretical prediction models are compiled for different foods with processing conditions. The applications of the properties are also
described, mentioning where and how to use the data and models in food processing.
Chapter 1 provides an overview of food properties including its definition, classification, and predictions. Chapters 2 through 4 present water activity and sorption isotherm including its terminology, measurement techniques, data for different foods, and its prediction models. Chapters 5 through 12 present thermodynamic and structural characteristics including freezing point, glass transition, gelatinization, crystallization, collapse, stickiness, ice content, and state diagram. Chapters 13 through
15 discuss the density, porosity, shrinkage, size, and shape of foods. Chapters 15 through 23 present the thermophysical properties including specific heat, enthalpy, thermal conductivity, thermal diffusivity, and heat transfer coefficient. Chapter 24 provides the acoustic properties of foods.
This second edition will be an invaluable resource for practicing and research food technologists, engineers, and scientists, and a valuable text for upper-level undergraduate and graduate students in food, agriculture and biological science, and engineering. Writing such a book is a challenge, and any comments to assist in future compilations will be appreciated. Any errors that remain are entirely mine. I am confident that this edition will prove to be interesting, informative, and enlightening.
Proper classification and terminology comprise an essential basis for avoiding confusion or imprecision. Classification will assist in recording available data, setting up a global database and developing predictive relationships. In this paper, an attempt to develop a well‐accepted classification of and terminology for food properties is made. The proposed four classes of food properties are: physical and physico‐chemical properties, kinetic properties, sensory properties, and health properties.
Food structure at molecular, microscopic, and macroscopic levels can be applied not only in the study and evaluation of food texture and quality, but also to the analysis and correlation of the transport properties of foods, such as viscosity, thermal conductivity/diffusivity, and mass diffusivity. At the molecular level, Aguilera and Stanley (1999) reported that food biopolymers (proteins, carbohydrates, and lipids) of importance to transport properties are structural proteins (collagen, keratin, and elastin), storage proteins (albumins, globulins, prolamins, and glutenins), structural polysaccharides (cellulose, hemicelluloses, pectins, seaweed, and plant gums), storage polysaccharides (starch–amylose and amylopectin), and lignin (plant cell walls).
Transport Phenomena of Foods and Biological Materials provides comprehensive coverage of transport phenomena modeling in foods and other biological materials. The book is unique in its consideration of models ranging from rigorous mathematical to empirical approaches, including phenomenological and semi-empirical models. It examines cell structure and descriptions of other non-traditional models, such as those based on irreversible thermodynamics or those focused on the use of the chemical and electrochemical potential as the driving forces of transport. Other topics discussed include the source term (important for the coupling transport phenomena-reaction or other intentional/unintentional phenomena) and the connections between transport phenomena modeling and design aspects. Some 100 tables provide useful summaries of the characteristics of each model and provide data about the transport properties of an extensive variety of foods. Transport Phenomena of Foods and Biological Materials will benefit a broad audience of chemists, biochemists, biotechnologists, and other scientists in the academic and industrial realm of foods and biological materials.
The effect of extrusion conditions, including feed rate (2.52-6.84 kg/h), feed moisture content (13-19% wet basis), screw speed (150-250 rpm), and extrusion temperature (150-230 degrees C) on structural properties of corn-legume based extrudates was studied. Four different types of legumes, chickpea, mexican bean, white bean, and lentil were used to form mixtures with corn flour in a ratio ranging from 10 to 90% (corn/legume). A simple power model was used to correlate porosity with extrusion conditions and material characteristics. The influence of feed rate in the extrudates porosity is incorporated into mean residence time. Porosity of extrudates was found to increase with temperature and residence time and to decrease with feed moisture content and corn to legume ratio. Screw speed did not affect extrudates properties. Expansion ratio showed a similar behavior with porosity. The addition of legumes (protein source) led to more dense products. Comparatively, the usage of white bean in mixtures for the production of snacks, led to a product with higher porosity than those with other legumes.
Through three editions, this has been the must-have resource on food properties and their variations. The book defines food properties and the necessary theoretical background for each. It also evaluates the usefulness of each property in the design and operation of important food processing equipment. This new edition addresses advanced knowledge of food properties by providing the latest developments in the field. It offers three new chapters covering glass transition temperature pertaining to food, kinetics related to non-thermal processing, and micro-structural properties of foods.
Structural properties, such as porosity, bulk density and true density, of freeze-dried rice, were investigated as affected by process conditions. Rice was boiled at different time periods and freeze-dried under various vacuum conditions. True density of dehydrated rice kernels was measured with a helium stereopycnometer, while bulk density was obtained by measuring their geometric characteristics. Porosity and pore size distribution were also measured with a mercury porosimeter. Simple mathematical models were developed in order to correlate these structural properties with process conditions. Bulk density of freeze-dried rice kernels increased with the applied pressure during freeze-drying, while porosity decreased. In addition, bulk density decreased and porosity increased with increasing boiling time. Moreover, the effect of porosity and water activity on glass transition temperature of dehydrated samples was studied using differential scanning calorimetry (DSC). Glass transition temperature decreased as moisture content and porosity increased, respectively.
The effect of drying method on bulk density, particle density, specific volume and porosity of banana, apple, carrot and potato at various moisture contents was investigated, using a large set of experimental measurements. Samples were dehydrated with five different drying methods: conventional, vacuum, microwave, freeze and osmotic drying. A simple mathematical model was used In order to correlate the above properties with the material moisture content. Four parameters with physical meaning were incorporated in the model: the enclosed water density pw, the dry solid density ps, the dry solid bulk density pbo and the volume shrinkage coefficient β'. The effect of drying method on the examined properties was taken into account through its effect on the corresponding parameters. Only, dry solid bulk density was dependent on both material and drying method. Freeze dried materials developed the highest porosity, whereas the lowest one was obtained using conventional air drying.
Bulk density, particle density, shrinkage and porosity were experimentally determined at various moisture content during air drying for apple, carrot and potato cubes. A simple mathematical model was used to predict the above properties versus material moisture content. Four parameters were incorporated in the model: enclosed water density, dry solids' density, bulk density of dry solids, and volume-shrinkage coefficient. The model was fitted to experimental data satisfactorily, and the parameters were estimated. The influence of varying drying conditions was also investigated.
Published values of food properties, such as true density, bulk density, and porosity in various foods were collected from the literature and classified in a previous work. These values of the true density were processed in order to reveal the influence of material moisture content and temperature. A simple mathematical model, relating true density to material moisture content and temperature, was developed and fitted to all examined data for each material. The data were carefully screened using residual analysis techniques. The correlation results for true density of nine materials are presented in this article.
A generic structural model to estimate the effective thermal conductivity of granular foods is proposed based on a distribution coefficient. It is assumed that granular food materials in bulk can be considered as a two-phase system containing granules and an interstitial air phase, and while the granules are also be considered as a two-phase system containing dry mater and water. Two different distribution factors are defined, one for granular materials in bulk and another for the granules. The proposed model was applied successfully to granular starch.
Transport phenomena. A unified approach
- R S Brodkey
- H C Hershey
- RS Brodkey
Engineering properties of foods
- M A Rao
- Ssh Rizvi
- A E Datta
- MA Rao
The physical properties of gases and liquids, 4th edn
- R C Reid
- J M Prausnitz
- B E Poling
- RC Reid