An Investigation on Drying of Millets in A Microwave Oven

An Investigation on Drying of Millets in A Microwave Oven G. B. Radhika 1, S.V. Satyanarayana, D. G. Rao 3 1 B.V.Raju Institute of Technology, Hyderabad, India Jawaharlal Nehru Technological University Anantapur, Anantapur, India 3 Caledonian College of Engineering, Muscat (Oman) Abstract - Finger millet (Eluesine coracana) and foxtail millet (Setaria italica), are highly nutritious minor millets and hence is used in most of the staple foods. The present study was to estimate the thin layer drying characteristics of foxtail and finger millet and developing a thin layer model which adequately fits the data. Foxtail and finger millet with an initial moisture content of 0.314 and 0.313 (kg moisture/kg dry solid) respectively, were dried in a domestic microwave oven at different microwave output powers ranging from 180 to 900W. The data were fitted to different thin layer models and the logarithmic model was found to best describe the drying behavior of the millets among the other models. The experimental moisture ratio values were compared with that predicted from the logarithmic model and was found to be in good agreement. Also, effective diffusivity was calculated by using Fick s law, which varied from.4 *10-10 to 5.87 *10-10 m /s and 1.786*10-10 to 5.14*10-10 m /s for finger millet and foxtail millet respectively. The values of effective diffusivity were increased with microwave output powers. Keywords- Foxtail millet, Finger millet, microwave drying, thin layer drying models, effective diffusivity I. INTRODUCTION Finger millet (Eluesine coracana), is an annual cereal plant which was widely grown in the arid areas of Africa and Asia. It is the main food grain for many people, especially in the dry areas of India and Srilanka. Foxtail millet (Setaria italica) is one of the oldest of the millets cultivated. It is gluten - free grain and is a staple food in most parts of eastern hemisphere since ancient times. It is healthier than rice [1]. Foxtail millet is rich in vitamins and minerals. The products made of millet flour are easily digestible and could be recommended for all age groups [1]. Drying of materials is a complicated process involving simultaneous heat and mass transfer. Thin layer drying is the process of drying in single layer of sample particles or slices. In a microwave drying system, the heat generates within the material and heats the entire volume at about the same rate. Microwave energy penetrates through the interior layers and directly absorbs the moisture in the sample. The quick energy absorption causes rapid evaporation of moisture, creating an outward flux of rapidly escaping vapor, hence, both thermal gradient and moisture gradient are in the same direction. Theoretically, the microwave drying technique can reduce drying time and produce a high quality end product []. Microwave drying has flexibility in producing wide variety of products [3] [4]. Microwave technology can be combined with conventional heating and drying units and is easily automated [5]. The microwave drying is considered as the fourth generation drying technology [6]. The advantages associated with microwave drying had made it superior to conventional drying methods such as, Sun drying, hot air drying, vacuum drying. These methods would result in lower drying rates in the falling rate period due to large exposure times of the material to the hot conditions [7]. This may lead to undesirable thermal degradation of the final product [8]. Literature reports on the drying kinetics of the food materials undergoing microwave treatment are available. Few reports were available on treating of grains using microwave and various reports on vegetables and fruits. Drying and grinding characteristics of wheat has been reported [9], Iraz and co workers [10] had studied the microwave assisted fluidized bed drying kinetics of macaroni beads, [11] has reported the microwave drying characteristics of corn. Reports on microwave treatment of rice, maize and yellow pea were also available [1][13][14]. There appears to be no information in the literature on the microwave drying characteristics of millets and the diffusion parameters. Hence, there is a need to study the drying characteristics of the millets, with a view to providing useful information which would enhance the drying process. The present study therefore investigates the thin layer characteristics of millets in a microwave oven and fits the experimental data to the thin layer models reported in literature. Experimental data was compared with the theoretical values. Also to calculate the effective diffusivity at different microwave output powers for the two millets studied. 583

A. Sample Preparation II. MATERIALS AND METHODS Foxtail and finger millets procured from the local market were used in the present study. The initial moisture content (IMC) was determined by the standard oven method [15]. Millet samples were soaked in water, decanted to remove dirt and other foreign materials. The samples were then conditioned to initial moisture contents of 0.314 and 0.313 (kg moisture/kg dry solid) for foxtail and finger millet respectively. B. Experimental Apparatus The drying experiments were carried out using a programmable domestic microwave oven (model no. MG 607, ARR, LG make). The oven was equipped with a provision to vary five different output microwave power levels, ranging from 180 to 900W. The oven was fitted with a digital control facility to adjust microwave output power and to control the time of processing. The dimension of the chamber was 300x300x50mm.The oven has a fan for air flow in drying chamber and cooling of magnetron. The moisture loss with time was recorded using a digital balance with an accuracy of ±0.01g. C. Experimental Procedure Samples of the two varieties of millets were dried in the microwave oven. Known weight of the samples, around 30g was spread as a single layer on a glass plate and kept in the microwave oven. Experiments were carried out at microwave output powers of 180, 360, 540, 70 and 900W, respectively. Fresh samples were taken for each experiment. The drying procedure was continued till the equilibrium was reached, indicated by no change in moisture any more. Each run was performed in triplicate. Moisture loss was recorded for every min. for first half an hour and then for every 5min. duration. The moisture content obtained at different microwave output powers were converted to moisture ratio (MR) by using equation (1). MR = M M M 0 e M e Where, MR is the moisture ratio, M 0 is the initial moisture content (% db), M e is the equilibrium moisture content (% db), M is the moisture content at any time t (% db). For the mathematical analysis, the values of M e are relatively small as compared to M 0 or M, hence the error involved in the simplification is negligible [16]. (1) 584 So, the moisture ratio was simplified as given in equation (), [17][18][19]. MR = M M 0 The drying curve for each experiment was obtained by plotting the dimensionless moisture ratio of the sample against the drying time. D. Mathematical modeling of the drying process Effectively modeling the drying behavior is important for investigation of drying characteristics of the millets. In this study, the microwave experimental drying data of millets at different power levels were fitted to the ten thin layer models, listed in Table 1. In these models, MR represents the dimensionless moisture ratio, given by equation (1) and calculated using equation (). The regression analysis was performed using the software MATLAB 9.0. Model parameters were estimated by taking the moisture ratio (MR) to be the dependent variable. The coefficient of determination (R ), the reduced chi square (χ ) and the root mean square error (RMSE) were used as criteria for adequacy of the fit. The best model describing the thin layer drying characteristics of the millet samples was chosen as the one with the highest R, the lowest χ and RMSE [0],[1],[]. The reduced χ and RMSE were evaluated as: χ = (3) RMSE = (4) n MR MR i 1 ( i ) exp, pre, i N z n i 1 ( MR pre i, MRexp, i ) N Where MR exp,i is the i th experimentally observed moisture ratio, MR pre,i is the i th predicted moisture ratio, N is the number of observations and Z, the number of constants in models [3]. E. Effective Diffusivity The experimental drying data for the determination of effective diffusivity coefficient (D eff ) were interpreted using Fick s second law for spherical bodies according to Geankoplis [4] and [5]. This is because the shape of the grains are closer to being spherical than the commonly used flat object (slab assumption). ()

The diffusivity coefficient (D eff ) was obtained from the equation for spherical objects and the moisture diffusivity coefficient (D eff ) was calculated at five different microwave output powers using equation (5) as the slope derived from the linear regression of ln (MR) against time data. lnmr = 6 ln r D eff t (5) TABLE I THIN LAYER MATHEMATICAL MODELS S.No. Model name Model equation Reference 1. Lewis MR=exp(-kt) [8]. Page MR=exp(-kt n ) [9] 3. Modified page MR=exp(-kt) n [30] 4. Henderson and MR=a exp(-kt) [31] Pabis 5. Logarithmic MR=a exp(-kt)+c [3] 6. Two term model s7. Wang and Singh 8. Modified page II 9. Simplifed Fick s Diffusion MR=aexp(- [33] k ot)+bexp(-k 1t) MR=1+at+bt [34] MR=exp(-c(t/L ) n ) [16] MR=aexp(-c (t/l )) [16] 10. Midilli et al. MR=a exp(-kt n )+bt [35] A. Drying curves III. RESULTS AND DISCUSSION The drying data were converted to dimensionless moisture ratio (MR) and then plotted against time. The drying curves indicating the variation of moisture content with drying time at different microwave output powers were presented in Figures 1 and for ragi and foxtail millet respectively. The time required to reach the dynamic equilibrium moisture within the microwave power range used, reduced with increasing power for both the millets. In all the cases, at the beginning of the drying process, drying rate was higher, but decreased continuously with decreasing moisture content as the drying time progresses. The total drying process seems to proceed in the falling rate period. The result suggests that diffusion may be the physical mechanism governing the moisture movement in millet, this is in accordance with the studies reported on drying of various food products especially grains and legumes [6], [7],[19]. 585 B. Mathematical Model Moisture ratio and time data were fitted to ten different thin layer models presented in Table 1, by multiple regression analysis using MATLAB 9.0. The regression results were presented in Tables and 3 for ragi and foxtail millet samples respectively. The results presented in Table indicated that the Logarithmic model fits well the data of microwave dried Ragi and foxtail millet samples. The R values were greater than 0.94 for the different models except for Fick s diffusion model. Logarithmic model with highest R and the lowest χ and RMSE was selected to predict the drying characteristics of the microwave dried ragi and foxtail millet samples. The effect of microwave power on the drying constants of the Logarithmic model was taken into account by developing the relation between these constants and the microwave output power. Hence, the regression equations relating the constants of the selected model and the microwave out put power (P) were: For Ragi samples MR = a exp(-kt)+c where a, k, c were constants a =.3 0.00546P, R = 0.9788 k = -0.14 + 0.0057P, R = 0.9836 c = -0.0167 + 0.0051P, R = 0.96 Thus, the thin layer model for ragi was given by equation 6. MR= (.3 0.00546P)exp[(-0.14 + 0.0057P)t]+(0.0167 + 0.0051P) (6) The moisture ratio was calculated by using the developed model, the experimental and the predicted values were compared. Deviation of experimental values from the predicted values was shown in Figure 3 for ragi samples. It could be observed from the figure that the experimental values were in good agreement with the predicted values, so the model developed could be used for explaining the drying kinetics of ragi using microwave energy. For foxtail millet samples The constants a, b, c of logarithmic model were best fitted to the linear equations with the regression coefficients of 0.954, 0.988, 0.963 respectively. The model developed to describe the drying kinetics of foxtail millet, by using these constants is given by the equation (7). MR = (0.73 + 0.0084T)*exp [ (0.0041 T 0.0175) t] + (- 0.31 + 0.009 T) (7) The experimental data were compared with the predicted values of logarithmic model at the three microwave power levels of 180W, 360W and 70W, shown in Figure 4.

This indicated that the process describing the drying behavior of the millets was diffusion governed. The Logarithmic model adequately fits the drying data and could be used to describe the drying kinetics of the millets. The experimental values of moisture ratio were in good agreement with that predicted from logarithmic model. The effective diffusivity values increased with increasing microwave output powers for both the millets. FIGURE 1. DRYING CURVES FOR MICROWAVE DRYING OF RAGI SAMPLES AT MICROWAVE OUTPUT POWERS OF 180, 360, 540, 70 AND 900W Acknowledgement One of the authors (G.B.Radhika) acknowledges the Management, Padmasri Dr. B.V.Raju Institute of Technology, for providing the necessary facilities to carry out the work. FIGURE II. DRYING CURVES FOR MICROWAVE DRIED FOXTAIL MILLET SAMPLES AT MICROWAVE OUTPUT POWERS OF 180, 360, 540, 70 AND 900W. C. Effective Diffusivity The effective diffusivity of the two millet samples were calculated using Fick s law simplified for falling rate period and the results were presented in Table 4. The results indicated that the effective diffusivities of the Ragi(finger millet) varied from.41*10-10 to 5.87 * 10-10 m /s and the effective diffusivities of the foxtail millet varied from 1.786 * 10-10 to 4.65 * 10-10 m /s for 180 to 900W respectively. The values increased with the increasing microwave output power. IV. CONCLUSIONS The conclusions drawn from the present study were that the drying of millets using microwave processed in the falling rate period and the drying time decreased with the microwave output power. FIGURE III. EXPERIMENTAL AND THE PREDICTED VALUES OF RAGI SAMPLES AT THE MICROWAVE OUTPUT POWERS OF 900, 540 &180W. FIGURE IV. DRYING CURVES FOR THE EXPERIMENTAL DATA AND THAT PREDICTED BASED ON THE LOGARITHMIC MODEL OF FOXTAIL MILLET AT THE MICROWAVE POWER LEVELS OF 180, 360 AND 70W. 586

TABLE II STATISTICAL REGRESSION RESULTS OF DIFFERENT THIN LAYER MODELS FOR RAGI Microwave R RMSE χ Model output power (W) Page 180 0.993 0.0098 0.0094 360 0.9891 0.0335 0.003 540 0.985 0.0439 0.01437 70 0.9935 0.0677 0.00645 900 0.9911 0.03084 0.00856 Modified page 180 0.9696 0.04444 0.04147 360 0.938 0.03 0.1416 540 0.8815 0.101 0.1153 70 0.895 0.137 0.1694 900 0.8835 0.1113 0.1116 Modified page II 180 0.993 0.0150 0.0094 360 0.9891 0.03449 0.003 540 0.985 0.04531 0.01437 70 0.9935 0.0839 0.00645 900 0.9911 0.037 0.00856 Lewis 180 0.9833 0.0395 0.081 360 0.9574 0.06635 0.0793 540 0.9558 0.07335 0.04304 70 0.9090 0.100 0.0904 900 0.9455 0.07611 0.0513 Henderson and Pabis 180 0.9833 0.0395 0.081 360 0.9574 0.06635 0.0793 540 0.9558 0.0734 0.04304 70 0.909 0.100 0.0904 900 0.9455 0.0761 0.0513 Logarithmic 180 0.9989 0.0096 0.0019 360 0.9987 0.0138 0.008 540 0.9997 0.03366 0.00906 70 0.9951 0.0314 0.0089 900 0.999 0.008 0.0013 Two term model 180 0.9833 0.03465 0.081 360 0.9574 0.07037 0.0793 540 0.9558 0.0847 0.04304 70 0.9090 0.1137 0.0904 900 0.9455 0.0863 0.0513 Simplified Fick s diffusion 180 0.8416 0.104 0.163 360 0.815 0.1397 0.3317 540 0.783 0.1736 0.110 70 0.7046 0.1915 0.935 900 0.7845 0.1606 0.063 180 0.9833 0.0395 0.081 360 0.9574 0.06635 0.0793 Wang and Singh 540 0.9558 0.07335 0.04304 70 0.9091 0.100 0.0904 900 0.9455 0.07611 0.0513 Midilli et al 180 0.9948 0.0196 0.00705 360 0.9986 0.017 0.0059 540 0.993 0.0331 0.00658 70 0.9930 0.03146 0.00693 900 0.9989 0.011 0.00103 587

TABLE III STATISTICAL REGRESSION RESULTS OF DIFFERENT THIN LAYER MODELS FOR FOXTAIL MILLET SAMPLES Microwave R RMSE χ Model output power (W) Page 180 0.9989 0.0050 0.00060 360 0.9891 0.0555 0.01044 540 0.9967 0.01601 0.00409 70 0.9971 0.01647 0.00515 900 0.9956 0.036 0.00599 Modified page 180 0.9871 0.01717 0.00707 360 0.9855 0.095 0.01394 540 0.9973 0.01606 0.0041 70 0.9931 0.0513 0.0110 900 0.991 0.03331 0.011 Modified page II 180 0.9989 0.00513 0.00060 360 0.9891 0.0639 0.01044 540 0.9968 0.01606 0.00413 70 0.994 0.0513 0.011 900 0.986 0.4111 0.1069 Lewis 180 0.9871 0.0168 0.00701 360 0.9855 0.0864 0.01390 540 0.9966 0.05583 0.00410 70 0.9933 0.0449 0.01 900 0.9607 0.06411 0.05346 Henderson and Pabis 180 0.9914 0.01399 0.0047 360 0.9855 0.0951 0.0139 540 0.9973 0.01441 0.0033 70 0.9983 0.00777 0.0011 900 0.991 0.03189 0.01 Logarithmic 180 0.9994 0.0113 0.0031 360 0.9987 0.01048 0.0016 540 0.9983 0.01181 0.00 70 0.9994 0.0068 0.0011 900 0.998 0.0087 0.0111 Two term model 180 0.9934 0.01461 0.0047 360 0.9985 0.0107 0.0015 540 0.9973 0.01541 0.0033 70 0.9963 0.01945 0.0064 900 0.994 0.03493 0.01 Simplified Fick s diffusion 180 0.9904 0.0315 0.0011 360 0.951 0.05411 0.03 540 0.9437 0.07543 0.0415 70 0.9975 0.00798 0.0011 900 0.91 0.089 0.0175 180 0.9978 0.0071 0.001 Wang and Singh 360 0.9871 0.0784 0.014 540 0.9818 0.03771 0.08 70 0.995 0.0153 0.0088 900 0.9844 0.0405 0.01 Midilli et al 180 0.995 0.04001 0.0036 360 0.9877 0.0314 0.041 540 0.9985 0.0065 0.0058 70 0.9984 0.00805 0.0011 900 0.9971 0.01647 0.007 588

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