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1 RESEARCH ARTICLE International Journal of Applied Sciences & Engineering ISSN Moisture Diffusivity and Activation Energy of Drying of Melon Seeds Nwajinka CO 1, Nwuba EIU 1 and Udoye BO 2 1 Department of Agricultural Engineering, Nnamdi Azikiwe University, Awka, Nigeria 2 Department of Mechanical Engineering, Federal Polytechnic, Oko, Nigeria ARTICLE INFO ABSTRACT Received: Revised: Accepted: August 12, 214 October 19, 214 November 2, 214 Key words: Activation energy Drying efficiency Melon seeds Specific energy consumption (SEC) *Corresponding Address: Nwajinka CO obinwajinka@yahoo.co.uk Activation energy, Specific energy consumption (SEC) and drying efficiency (DE) of melon seeds (Citrulus vulgaris) were investigated at drying temperatures of 29,, 5, and o C and varying air velocities of.6, 1., and 1.5 m/s. Curve fitting was used to determine the model constants of the drying curves under the prevailing conditions. The predicted and experimental results were compared using statistical methods for goodness of fit. Mellon seeds at average initial moisture content ranging from.17 to.38 g water /g dry matter, were dried to average final moisture content range of.7 to.9 g water /g dry matter, in a crop dryer. The activation energies were 37.1, 35. and 33.6 kj.mol -1 for air velocity of.6 m.s -1, 1. m.s -1 and 1.3 m.s -1, respectively. The Specific Energy Consumption (SEC) ranged from 1.29 x 1 1, 5.4 x 1 1, 8.85 x 1 1, x 1 1 J/kg water, for the temperatures of, 5,, and 6 o C respectively. Cite This Article as: Nwajinka CO, EIU Nwuba and BO Udoye, 214. Moisture diffusivity and activation energy of drying of melon seeds. Inter J Appl Sci Engr, 2(2): INTRODUCTION Background of study Most food crops contain more than 8% water at harvest and are therefore highly perishable if stored or left long in that state. Water loss and decay account for most of their losses, which are estimated to be more than 3% in the developing countries due to inadequate handling, transportation and storage (Jayaraman and Gupta 26; Kaya et al., 27). These losses cause serious gaps in the availability of the essential nutrients, vitamins and minerals which they supply to human diet. Harvested crops are living materials in various stages of dormancy. When placed in storage for future utilization, the quality is maintened by maintaining this dormancy as much as possible over the specified period of storage. Because of these considerations, drying has been a major part of food industry for many years, being a major way of preserving this dormancy. Moisture control creats unfavourable environment for microorganisms and enzymes, which are responsible for spoilage of foods and biomaterials. In a nutshell, freshly harvested crops have relatively high moisture content which has to be reduced to a desirable level, usually below 12% (wb) for most grains and slightly above that for fruits and vegetables before they can be safely stored. In summary, crops aredriedto enhance their mechanical properties, to reduce incidence of enzyme attacks, insect and fungal 37 infestations, stain and decay and finally to reduce the weight and volume of the crops, thereby resulting in reduction of transportation cost. Past two decades witnessed some exponential rise in Research and Development in multidisciplinary field of drying (Mujumdar, 2). Although heated air drying is usually adopted as a cost efficient method of food preservation, there is still insufficient understanding of the drying characteristics and behavior of much of Nigerian local staples, which has led to lack of interest in some of these crops due to poor processing and preservation practices. This has led to non-availability of technical information on some Nigerian crops in literature, even when they are good sources of dietary requirements. The implication of this is that they have remained unexploited. Hence, there is a need to study and understand the kinetics of drying, especially for local crops, in order to be able to develop suitable crop drying systems with optimal performances for such crops. Analysis of drying of biomaterials is not an easy task because they are affected by temperature, moisture content, relative humidity, the rate of air flow and overallvariation in the physical properties of the materials. (Mohsenin, 1986).Grain moisture content has been found to be the major single crop factor that determines the harvest timing (Hunt, 1964; Handy et al., 1977). Currently no consensus has been reached on drying equations which are suitable for all crops and that is why a

2 38 good number of works have been carried out and are still being carried out in this area of postharvest operation on various crops and their varieties. This work is aimed at finding suitable drying models for the melon crop and the influence of the drying conditions on various parameters of the drying process. MATERIALS AND METHODS The dryer, consists of a fan, air heaters, drying chamber and hot air anemometer for measurement of air flow rate (fig. 1). The airflow rate was adjusted by the fan speed control. The heating system consists of electric hot plate placed at the plenum chamber of the drying apparatus. The drying tray was placed in the heated air stream. diffusion, resulting from vapor-movement due to moisture-concentration gradient. The net flux, J(x, t), of water molecules diffusing per second across a unit area is proportional to the moisture-concentration gradient, ( M(x, t)/ x), or, (1) Where, D is the moisture-diffusion coefficient, x is the distance from the centre of mass to the surface of sample, being dried and t is drying time. Since the diffusionprocess causes the concentration of water molecules to change with time, the flux changes from J 1 to J 2 over a distance, such that J 2 = J 1 - ( J 1 / x)δx. Therefore, at the microscopic level, the amount of moisture depleting in volume per second, δj = J 2 -J 1, can be expressed as, Or (2) (3) Continuity relation requires flux-change over distance to be equal to the rate, at which the moisture concentration in the volume is decreasing with time, M/ t = - J/ x, (4) Or (5) Fig. 1: The experimental tray dryer Experimental procedure Digital thermometers (Testo 925, Germany), with reading accuracy of.1ºc was used in temperature measurement. The wet-bulb and dry-bulb temperatures were determined and used to calculate the relative humidity levels of the drying air using VAISALA humidity calculator. The velocity of air passing through the system was measured by the air anemometer. The variable parameters considered in the experiments were the drying air velocity, relative humidity and temperature. The experiments were conducted at three air flow rates (.6, 1. and, 1,5 m/s), the air temperature was controlled by voltage control gadget (Variac) setting. Three replicates each, of the experiments, were conducted. 5g of the sample was used for each run of the experiments. The fan and heater were started and the drying temperature and air flow were allowed to run without load until when all the indicators are steady at set values. Thereafter, the drying chamber was loaded with the samples for the experiments. The sample was weighed every fifteen minutes for the first one hour, and then every thirty minutes for subsequent measurements until steady weights were observed in two or more consecutive weighing. The moisture diffusion model The moisture-transfer from the sample interior to the surface is predominantly due to thermal-stimulated Equation (5) is the general form of Fick s second law for diffusion in one dimension that applies when the diffusion coefficient (D) is a function of concentration. For cases where D is considered constant, eqn. (6) reduces to a simpler form, Fick s laws of diffusion have been applied to drying analysis. The transport of water in capillary porous material can be described by the Fick s equation of unsteady state diffusion (Geankoplis, 1993) as follows: Where, D= diffusivity. For the slab of infinite length, equation (3.23) yields, x= the direction of moisture transfer. If the two surfaces are drying and the thickness is presented as 2l o (dz=2l o ), applying the following initial and boundary conditions; then the solution to the following equations takes the form of sum of series viz: (6) (7) (8)

3 39 Where, l o =half of slab thickness. Therefore, on the assumption that the initial moistureconcentration (M i ) is uniform, the average moisturecontent, M(t), of the product, after a drying time t, can be given by an analytical solution of the form (Jost, 196), and for n =, 1, 2,1` (9) (1) (11) Equations 1 & 11 are derived on the assumption that D and M e are constants. For long period of drying (t is sufficiently large), only the first-term in the series in eqn. (11) is significant (with Dt/4x 2 >.2, the error is less than 3 %) and hence, (12) such that the total time (t) required to attain an average moisture-content M is, (13) Equation (12) also represents the relative change in moisture-concentration, ( (t) M e )/(M i M e ), within the food-sample in the drying chamber If, is defined as moisture ratio (MR), equation 12 can be written as: Then if we set,, and, Therefore, equation (14) can now be written as: (14) (15) Activation energy Activation energies are usually determined experimentally by measuring the reaction rate k at different temperatures T, plotting the logarithm of k against 1/T on a graph, and determining the slope of the straight line that best fits the points.babliset al. (24) reported the value of the activation energy to vary from 3.8 to kj/mol for figs while Aghbashlo et al. (28) reported that activation energy (E a )for beriberi fruit varied within kj/mol for different air velocities. Garauet al. (26) reported a value as 36.4 kj/mol for orange skin. The activation energy and rate of a reaction are related by the following equation: k = Aexp(- E a / RT ) (16) where k is the rate constant, A is a temperatureindependent constant (often called the frequency factor), exp is the function e x, Ea is the activation energy, R is the universal gas constant, and T is the temperature. This relationship was derived by Arrhenius in Applying the solution of Fick s diffusion equation (14& 15), the drying rate constant (k) is expressed in terms of the square of half the thickness (L) of the bed and diffusion coefficient (D e ), viz: Equation 19 can be written as; (18) (17) Where, and, n=2. An Arrhenius-type equation presented a strong temperature effect on the diffusion coefficient. The relationship was as follows (Islam, 212): (19) Where, D eff =effective moisture diffusion coefficient (m 2 /sec) D o = the constant of integration and is usually referred to as a frequency factor when discussing Arrhenius equation, m 2 /sec, E a = activation energy of diffusion of water, KJ/mole R = gas constant, KJ/mole, o k T abs = absolute temperature, o k Equation 19 can be put in linear form by taking the logarithm of both sides to get the following: (2) The plot of the logarithm of moisture Diffusivity (D eff ) versus the inverse of the drying temperature (1/T) gives a line whose slope is the ratio of activation energy (E a ) to the universal gas constant (R), while the y-intercept is the frequency factor (ln D o ) RESULTS AND DISCUSSION The kinetics of water desorption in melon (egusi) seeds was investigated using the data obtained from drying experiments of melon seeds samples in the Temperature range of 29- C, relative humidity of 5, 68 and 72% and air flow rate of.6, 1. and 1.3 m/s respectively (Figs. 2&3 ). The drying rate constant was estimated by plotting the log of moisture ratio (lnmr) against drying time (t). The slope of the straight line represents the constant, k. The plots of natural log of MR (lnmr), against time (t) are presented in figure4.

4 Moisture content, (%db) Temp =29 o C Temp = o C Temp =5 o C Temp = o C Time, (mins) Fig. 2: Moisture content against time at air velocity of 1.3 m/s. Moisture ratio Drying time 29 o o 5 o o C Fig. 3: Moisture ratio against drying time at various temperatures air velocity of 1.3 m/s Ln (MR) o o 5 o o C Drying Time(min) Fig. 4: Log of moisture ratio against drying time at different temperatures air velocity of 1.3 m/s and relative humidity of 5 % The determined values of drying rate constant (k), the pre-log factor (A), coefficient of moisture diffusivity (D) and other constants of the drying curve models are presented on table 1, under different temperature levels for air flow rate of 1.3m/s. Moisture diffusivity The moisture diffusivity increases with increasing air temperature and decreases with increase in velocity, which agrees with Akpinar et al, (23) and Thorat et al, (21). The minimum value of the moisture diffusivity was observed at the air velocity of 1.3 m/s and air temperature of 29 C while the maximum value was at the air velocity of.6 m/s and air temperature of C, probably because at a low air velocity (.6 m/s), the air has a better contact with the sample surface which resulted in a greater absorption of moisture, consequently the moisture gradient of the sample with ambient increases and that leads to an increase in the moisture diffusivity. Generally, the value of D eff compares well those reported for agromaterials (Babalis&Belessiotis 24; Aghbashloet al. 28). Second degree polynomial equation was used to develop a relationship between effective moisture diffusivity (D eff ) and temperature (T) with good fit (R 2 ). Figure 6, is the plot of D eff against air velocity at different levels of air temperature. But at a higher air velocity level (1.3 m/s), the air passing through the sample is turbulent to some extent, therefore the moisture gradient may tend to decrease and the moisture diffusivity accordingly reduces. The effects of air velocity, relative humidity and temperature on effective moisture diffusivity were presented in tables 2 & 3. Activation energy The activation energies were 37.1, 35. and 33.6 kj.mol -1 for air velocity of.6 m.s -1, 1. m.s -1 and 1.3 m.s - 1, respectively at relative humidity of 5% (table 3) and other drying conditions. Thorat et al, (21), working in the same range of temperatures, reported Activation energy of kj.mol -1 for drying of ginger slices similar tothat determined for melon seeds in this study presented in Tables 4& 5. A plot of the activation energy of the melon seeds against air velocities are presented in Figure (7). The relationship between the activation energy and drying air velocity was found by regression analysis. The results shows that the power equation can predict E a based on the drying air velocity with R 2 of.94. The plot of Ea against relative humidity the plots showed that E a increased with relative humidity (figure 8). If the temperature of the system is increased, the average heat energy is increased, a greater proportion of collisions between reactants result in reaction, and the reaction proceeds more rapidly. It can be observed from the relationship between moisture diffusivity and activation energy that moisture diffusivity (D eff ) is to activation energy what drying rate constant (k) is to drying.the relationship between the activation energy, relative humidity and the air flow rate is represented in the following regression model (table 6): Specific Energy consumption The specific Energy consumption was calculated and plotted against the drying temperatures in figure 9. The values were 1.29 x 1 1, 5.4 x 1 1, 8.85 x 1 1, x 1 1 J/kg water, for the temperatures of, 5,, and 6 o C respectively. The high value was however attributed to the low efficiency of the dryer, which was in the range of 12% to 51.96%.

5 41 Table 1: Summary of model parameters at Air velocity of 1.3 m/s Model name Temp o C K 1, s -1 K 2, s -1 A B C N R 2 SSE RMSE Logarithmic Henderson &Pabis 29 5 Page 29 5 Modified Page 29 5 Newton 29 5 Two Term E The graph of drying rate constant against temperature is presented in figure Table 2: Moisture diffusion coefficient, drying rate constants, and Pre-log factor s/n Temp. ( o C) Air flow rate (m/s) Pre-log factor, (A) Drying rate constant, (k) Diffusion Coefficient x x x x x X x x x x x x 1-12 Table 3: Effect of temperature, relative humidity and air flow rate on diffusion coefficient Relative Humidity Air velocity Effective Diffusion Coefficient, D eff, (m 2 /s) (%) (m/s) 29 o C o C 5 o C o C x x x x x x x x x x x x x x x x x x x x x x x x 1-11 The following regression equations relate the drying air speed with the effective moisture diffusivity: For T= 29 o C; D eff = x1-11. V x1-11 (R2 =.8668 and RMSE = 6.149x1-12 ); For T= o C; D eff = x V x 1-11 (R2 =.987 and RMSE = x 1-12 ); For T= 5 o C; D eff = x1-11. V + 7. x1-11 (R2 =.9769 and RMSE = x1-12 ); For T= o C; D eff = x V x1-11 (R2 =.958 and RMSE = 4.5 x1-12 ) Table 4: Predicted activation energy under different Relative humidity and air velocity Relative Humidity (%) Activation Energy (Ea), V=.5 V =1. V = 1.5 m/s Regression model: Ea=.585*RH Ea=.346*RH Ea =.176*RH RMSE : R-Square (R 2 ): SSE:

6 42 Table 5: Predicted activation energy under different Relative humidity and air velocity. Air Velocity, (m/s) Activation Energy (Ea), RH= 72 % Regression model: Ea=-5.6*V Ea=-5.9*V+49.5 Ea=-7.2*V+52.2 RMSE : R-Square (R 2 ): SSE: Moisture diffusivity, m 2 /s 5 x T=29 o C T= o C T=5 o C T= o C Air velocity, m/s Fig. 6: Moisture diffusivity against air velocity for different temperatures Activation Energy, kj/mol Rel. Humidty =5% Rel. Humidity =68% Relative Humidity= 72% Air Velocity, (m/s) Fig. 7: Activation energy against air flow rate Specific Energy Consumption, kj/kg 18 x Temperature, o C Fig. 9: Specific Energy Consumption against Temperature of drying. The cubic polynomial equation fitted the data perfectly with a coefficient of determination of one (R 2 =1) as shown in equation 4.12: Conclusions Thin layer drying models were investigated using the experimental data from melon seeds drying. Comparisons of the drying models showed high coefficient of determination for page model followed by two-term model of modified diffusion equation and modified Henderson and Pabis model. Agreement between the predicted and experimental data was shown to be very good for the three selected models as indicated by the results of error analyses. Any one of these three models can be used to simulate the drying characteristics of melon seeds. It was observed that the drying rate was a decreasing function of time. However, there was a short constant rate period. This was indicated in the graphs of drying rate against time in figure (3). Consequently, the drying rate is an inverse function of time of drying. The statistical error analysis showed goodness of fit which was good enough to guarantee validity in predicting the drying parameters. The drying coefficient (rate constant) was observed to have an inverse relationship with time and increase in temperature. Relative humidity and air velocity influenced both moisture diffusivity and activation energy. Good relationships were found to exist among these parameters. The highest effective moisture diffusivity was observed at air velocity of.6 m/s and temperature of o C, while it was lowest at air velocity of 1.3 m/s and temperature of 29 o C. Activation energy of melon decreased with air velocity and relative humidity. The values of Specific Energy Consumption were 1.29 x 1 1, 5.4 x 1 1, 8.85 x 1 1, x 1 1 J/kg water, for the temperatures of, 5,, and 6 o C respectively. The high value was however attributed to the relatively small amount of water removed by the thermal energy of the drying air. REFERENCES Aghbashlo M, MH Kianmehr, H Samimi-Akhijahani, 28. Influence of drying conditions on the effective moisture diffusivity, energy of activation and energy consumption during the thin-layer drying of berberis fruit (Berberidaceae). Energy Convers. Manage, 49: Akpinar E, A Midilli and Y Bicer, 23. Single layer drying behavior of potato slices in a convective cyclone and mathematical modeling, Ener Conv Manag, 44:

7 43 Babalis SJ and VG Belessiotis, 24. Influence of drying conditions on the drying constants and moisture diffusivity during the thin-layer drying of figs. J Food Eng 65, Garau MC, S Simal, A Femenia and C Rossello, 26. Drying of orange skin: drying kinetics modeling and functional properties. J Food Eng, 75: Geankoplis CJ, Transport Processes and Unit Operations. New Jersey: Prentice-Hall, Jayaraman KS and DK DGupta, 26. Drying of fruits and vegetables. In Handbook of industrial drying, ed by Arun S. Mujumdar, CRC Press, New York. Jost W, 196. Diffusion in Solids, Liquids and Gasses, Academic Press, 3rd Printing, pp: Kaya A, O Aydın and C Demirtaş, 27. Drying kinetics of red delicious apple. Biosys Eng 96: Mohsenin NN, Physical Properties of plant and animal materials. Gordon and Breach Sci Publ, New York. Mujumdar AS, 2. Drying technology in agriculture and food sciences. Enfield-NH, USA: Science Publishers, Inc; 2. In [Montero et al., 21]. Thorat ID, D Mohaparta, RF Sutar, SS Kapdi and DD Jagtap, 21. Mathematical modeling and experimental study on thin-layer vacuum drying ofginger (Zingiberofficinale R.) Slices. Food Bioproc Technol, 5: