# Modeling characterization and evaluation of efficiency and drying indices for microwave drying of Zingiber officianale and Curcuma mangga.

код для вставкиСкачатьASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 Published online 16 July 2010 in Wiley Online Library (wileyonlinelibrary.com) DOI:10.1002/apj.484 Research article Modeling, characterization, and evaluation of efficiency and drying indices for microwave drying of Zingiber officianale and Curcuma mangga Mahesh Ganesapillai,1 Lima Rose Miranda,1 Tejesh Reddy,2 Micheal Bruno2 and Aruna Singh3 * 1 Chemical Engineering Department, A. C. College of Technology, Anna University, Sardar Patel Road, Chennai 600025, India Department of Biotechnology, Sathyabama University, I.T. Express Highway, Chennai 600119, India 3 Department of Food Technology, Laximinarayan Institute of Technology, RTM Nagpur University, Nagpur 440033, India 2 Received 24 January 2010; Revised 7 June 2010; Accepted 7 June 2010 ABSTRACT: Methods for efficiently drying agricultural products are an ever-increasing demand. Due to its rapid and thorough dehydrating ability, microwave techniques were used to evaluate the thin-layer drying kinetics of organic ginger and mango ginger. Microwave drying characteristics, efficiency and indices determined with respect to sample thickness, microwave output power and sample load revealed higher power (300 W), lesser thickness (0.001 m) and load (25 g), increased drying rates and reduced drying time. Effective diffusivity values were found within the range reported in literatures (9.17 × 10−11 and 11.6 × 10−11 m2 s−1 ). Scanning electron microscope (SEM) and energy-dispersive X-ray (EDX) images revealed that the surface morphology and the elemental composition gradually degraded during drying. The ability of eight different thin-layer mathematical models was evaluated for representing the experimental drying profiles. Among the eight new models derived from the basic diffusion model, statistical analysis inferred that the modified diffusion model no. 4 could predict most accurately changes in drying behavior of organic ginger and mango ginger rhizomes for all drying conditions applied. 2010 Curtin University of Technology and John Wiley & Sons, Ltd. KEYWORDS: microwave drying; mango ginger; rhizomes; surface morphology; empirical models; diffusion INTRODUCTION Drying is perhaps the oldest, most common simultaneous heat and mass transfer operation in which the water activity of the material is lowered by the removal of water to a specific level at which microbial spoilage and deteriorative chemical reactions are greatly minimized.[1] However, it enhances substantial reduction in weight and volume, minimizing packing, storage and transportation costs, and enables storability of the product under ambient temperatures. Traditional techniques of drying agricultural feedstock like rhizomes are time-consuming and energy-intensive as they depend on heat conduction. Moreover, the high temperature used can destroy, denature and also induce some aerobic reaction, which is often detrimental to the quality of dried product.[2] Microwave heating is an excellent prospect to increase the rate of evaporation, where regions of higher moisture content within *Correspondence to: Aruna Singh, Department of Food Technology, Laxminarayan Institute of Technology, RTM Nagpur University, Nagpur 440033, India. E-mail: arunapcs@gmail.com 2010 Curtin University of Technology and John Wiley & Sons, Ltd. Curtin University is a trademark of Curtin University of Technology the material will absorb more microwave energy and heat generated throughout the material, leading to faster heating rates and shorter processing times compared to conventional heating, where heat is usually transferred from the surface to the interior. Other advantages include space savings and energy efficiency, because most of the electromagnetic energy was converted into heat.[3] In order to design and evaluate such new microwave dehydration techniques, mathematical modeling of drying behavior of rhizomes in these systems is necessary. However, a number of complex theoretical models have been developed in the recent past to describe these phenomena, and both design and process engineers involved in industrial drying operations clearly need simple, but accurate, analytical tools to conduct design analysis and relevant calculations. Availability of such models and correlations, verified by experimental data, will enable designers and operators to provide the optimum solution to various aspects of drying operations (energy use, operating conditions and process control), without undertaking actual experimental trials on the system itself. There has been extensive research Asia-Pacific Journal of Chemical Engineering MICROWAVE DRYING CHARACTERIZATION OF GINGER AND MANGO GINGER into microwave drying, examining a broad spectrum of fruits and vegetables including apples, green peas, cabbage, banana, tomato, brocolli, potato, carrots, onion and garlic.[4 – 10] Despite those investigations, to the best of our knowledge, no data currently exist in terms of drying kinetics, drying efficiency and drying indices for rhizomes undergoing microwave drying. The objective of the research were 1) to study the microwave drying characteristics and compare the two species of organic rhizomes, ginger and mango ginger; 2) to calculate the effective diffusivity coefficient, activation energy, specific energy consumption, drying efficiency and rehydration ratio (RR) for the microwave dehydrated rhizome samples and 3) to study the applicability of several thin-layer models selected from the literature to the thin-layer drying of rhizomes and to fit drying data into the most suitable models by appropriate statistical analyses procedures. MATERIALS AND METHODS Materials Organic ginger (Zingiber officianale) and mango ginger (Curcuma mangga) rhizomes used were collected from a local super market in Chennai, India, and were stored at 4 ± 0.5 ◦ C, before experimentation. The samples were thoroughly washed and peeled to remove skin and were cut into dimensions of 0.035 × 0.02 m (length × breadth) using a vegetable slicer. At least ten measurements of the thickness were made at different points with a dial micrometer; only slices that fell within a 5% range of the average thickness were used. The initial moisture content of the specimens determined by vacuum oven method was 94.2 and 96.1% (db) for the organic ginger and mango ginger, respectively.[11] Drying equipment and procedure The drying experiments were conducted using a programmable, domestic microwave oven, Model C–103FL (Samsung Electronic Instrument Co. Ltd.), with technical features of 230 V ≈ 50 Hz AC and a frequency of 2450 MHz (a wavelength of 12.24 cm). The microwave oven has the capability of operating at six different microwave output powers, 100, 180, 300, 450, 600 and 900 W. The area on which microwave drying was carried out was 336 × 346 × 222 mm (W × D × H ) in size and consisted of a rotating glass plate of 300 mm diameter at the base of the oven. The adjustment of microwave output power and processing time was performed with the aid of a digital control facility located in the microwave oven. The power produced by the oven in microwave function was continuous. The 2010 Curtin University of Technology and John Wiley & Sons, Ltd. fresh specimens were spread at middle of the turntable in microwave cavity and the oven was switched on. Microwave drying continued for a desired period with constant power output. The mass change of specimen during the drying process was measured online using an electronic balance. The experiments were conducted individually for sample thickness of 0.001, 0.002 and 0003 m, sample load of 25, 50, 75 and 100 g, with microwave output power of 100, 180 and 300 W, with ginger and mango ginger samples. Effective moisture diffusivity (Deff ) In almost all the research, quantitative analysis of dehydration characteristics is typically realized based on the effective diffusion coefficient. The effective moisture diffusivity as defined by Fick’s second law describes the movement of moisture within the solid solution, established on the basis of several simplifying assumption that are widely adopted in drying research as expressed in Eqn (1).[12] These assumptions include uniform initial moisture content, constant directional diffusivity, mass transfer that is symmetric with respect to the center, negligible external resistance to heat and mass transfer and more rapid heat transfer than mass transfer. δX = Deff ∇ 2 X (1) δt For moisture diffusion through a thin layer, the above equation can be modified as suggested by Saravacos[13] as 8 π 2 Deff X t (2) = 2 exp − MR = X0 π L2 2 X 8 π Deff ln(MR) = ln = ln − t (3) X0 π2 L2 where X is the moisture content at time t (kg kg−1 , dry solid), MR the moisture ratio, X0 the initial moisture content (kg kg−1 , dry solid) and L the half thickness of specimen (m). Activation energy coefficient The Arrhenius type of equation was used in a tailored form to illustrate the relationship between the diffusivity coefficient and the ratio of the microwave output power to sample thickness instead of the temperature, as the temperature within the sample is not a measurable variable in the standard microwave oven. The dependency of Deff on the ratio of microwave output power (P ) to sample thickness (q) as suggested by Dadali et al .[14] Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj 913 914 M. GANESAPILLAI et al. Asia-Pacific Journal of Chemical Engineering (Eqn 4) could be brought down to a straight-line form as Eqn (5) −Ea q = D0 exp P q = ln D0 − Ea P Deff ln Deff (4) (5) where D0 represents the pre-exponential factor (m2 s−1 ) and Ea the activation energy (W m−1 ). SEM and energy-dispersive X-ray microanalysis The structure of the dehydrated samples was examined using a scanning electron microscope (SEM; JEOL JSM-5800). Thin slices of about 0.001 m thick cut from the dried samples were fixed on the SEM stub which was subsequently coated with gold in order to provide a reflective surface for the electron beam. Gold coating was carried out in a sputter coater (BIO-RAD E-5200) under low vacuum in the presence of inert gas (Argon). The coated samples were photographed at an accelerating voltage of 15 kV. The inspected location of the rhizomes was between the epidermal layer and the vascular bundle. The elemental composition of the samples was examined using an energy-dispersive X-ray (EDX) micro-analyzer (Thermo Scientific NORAN System 7 model). To obtain information about the sample elemental composition, the characteristic spectrum of X-rays emitted by the specimen was used after excitation by high-energy electrons. The samples were examined for a live time of 100 s, at a take-off angle of 35.0◦ . Efficiency indices Effect of material thickness on the energy efficiency of microwave drying at 300 W microwave output power was evaluated by two different efficiency indices: microwave drying efficiency (%) and specific energy consumption (MJ kg−1 ) [H2 O]. The efficiency indices of ginger and mango ginger samples of 0.001–0.003 m thickness were determined from the experimental data. Specific energy consumption (Qs ) The drying of food material, a process of simultaneous heat and mass transfer, represents an energy-intensive operation of some industrial significance. The Qs for each drying condition was estimated considering the drying time involved and energy utilization by the various components of the microwave dryer, expressed in terms of MJ kg−1 of water removed, and it is used 2010 Curtin University of Technology and John Wiley & Sons, Ltd. as one of the factors in the optimization of process parameters: ton P × 10−6 (6) Qs = mw where, ton represents the total drying time (s), P is the microwave output power (W) and mw is the mass of evaporated water (kg). Microwave drying efficiency (η) The microwave drying efficiency (Eqn 7) was calculated as the ratio of heat energy utilized for evaporating water from the specimen to the heat supplied by the microwave oven. Here λw represents the latent heat of vaporization of water at the evaporating temperature (100 ◦ C), taken as 2257 kJ kg−1 as suggested by Hayes.[15] (mw )(λw ) (100) (7) ηd = (P ton ) Rehydration ratio After dehydration, samples were subjected to rehydration trials to check their capability to rehydrate in distilled water. The rehydration ability, as determined by the RR, depends on material property and drying conditions. The rehydration parameters were determined according to USDA (1944) as in the following equation. RR = WR Wd (8) where WR is the drained weight of rehydrated sample and Wd is the weight of dehydrated sample.[16] Empirical modeling Effectively modeling the drying behavior is important for the investigation of drying characteristics. In this study, the microwave experimental drying data at different process parameters were fitted to Page, Henderson, Logarithmic, Wang and Singh, Diffusion, Verma, Two term exponential and Midilli[17 – 21] and semi-empirical models. These models were derived by simplifying the general series solution of Fick’s second law and considering a direct relationship between the average moisture content and the drying time. The constants and coefficients of these equations are further described with various types of expressions like Arrhenius, logarithmic, linear, exponential and power type in terms of temperature.[22] As the temperature inside the chamber directly depends on the power input to the system, all Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj Asia-Pacific Journal of Chemical Engineering MICROWAVE DRYING CHARACTERIZATION OF GINGER AND MANGO GINGER the expressions were derived in terms of power in the current research. A suitable mathematical model to represent the effect of power on the constants and coefficients was investigated using multiple combinations of different equations using Arrhenius and logarithmic type expressions.[23] All nine models shown in Table 2 can be derived into m n number of new models, where n is the total number of constants and coefficients in the model and m is the number of combination equations. Fifty-eight new equations were derived as detailed in Table 3 (shown only for diffusion equation).[24] Regression analysis was used to determine the model constants of all basic and derived equations. Subsequently, the best model was selected based on the most commonly used statistical parameters namely coefficient of determination (R 2 ), root mean square error (RMSE), reduced chi-square (χ 2 ) and t-value. efficiency, which may be due to rapid movement of water at higher microwave output power, lower sample thickness and sample load. The Deff values obtained from this study were within the general range of 10−11 to 10−9 m2 s−1 for food materials.[26] RESULTS AND DISCUSSION SEM and EDX microanalysis Effective moisture diffusivity The SEM images reveal that the microwave-dried samples have honey comb morphology after dehydration. The surface morphology of organic ginger has gradually degraded from semi-continuous intermittent globular pattern to a continuous undifferentiated morphology (Fig. 3). This structural deformation may be due to higher diffusion rate enhanced by greater microwave power. Compared to 100 and 180 W, the presence of open structures was higher when the sample was exposed to 300 W, which may be due to some tissue expansion from internal water vapor during dehydration. Whereas in organic mango ginger, the presence of starch granules as indicated by elliptical shapes was The Deff was calculated using the methods of slopes, where the logarithm of MR values was plotted against drying time (t) for various sample thickness, sample load and microwave output power.[25] The Deff values ranged from 9.17 × 10−11 to 7.86 × 10−11 m2 s−1 for ginger samples, whereas for mango ginger it varied from 11.6 × 10−11 to 9.46 × 10−11 m2 s−1 for samples of 0.001–0.003 m thickness (Fig. 1). During the initial stage of drying, the values of Deff increased greatly with decrease in sample thickness and load and increase in microwave output power, indicating better mass transfer Activation coefficient The activation energies involved in microwave drying of rhizome specimens under different drying conditions were estimated from the slopes of the curve plotted according to Eqn (5), which was 23.19 and 30.59 (W m−1 ), while the pre-exponential factor D0 was estimated to be 9.96 × 10−11 and 12.7 × 10−11 m2 s−1 . The data more accurately fitted to Eqn (5), with a highest R 2 of 0.999 and 0.991 for ginger and mango ginger samples, respectively (Fig. 2). 1.50E-10 ln (Deff) -22.5 0 y = -1E-08x + 1E-10 R2 = 0.9861 0.006 0.009 0.012 -22.75 L/P (m2 W-1) 1.00E-10 Deff (m2 s-1) 0.003 y = -7E-09x + 1E-10 R2 = 0.9972 5.00E-11 y = -30.59x - 22.781 R2 = 0.9919 -23 -23.25 y = -23.191x - 23.037 R2 = 0.9991 0.00E+00 0 0.001 0.002 Thickness (m) 0.003 0.004 Figure 1. Comparison of Deff for organic rhizomes: , organic mango ginger and ◊, organic ginger (microwave output power: 300 W, thickness: 0.001 m, sample load: 25 g). 2010 Curtin University of Technology and John Wiley & Sons, Ltd. -23.5 Figure 2. Comparison of activation energy for organic rhizomes: , organic mango ginger and ◊, organic ginger (microwave output power: 300 W, thickness: 0.001 m, sample load: 25 g). Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj 915 916 M. GANESAPILLAI et al. Asia-Pacific Journal of Chemical Engineering (a) (b) Figure 4. Energy-dispersive X-ray spectrum of microwave dehydrated organic (a) mango ginger and (b) ginger. traces of chlorine, sodium, bromine and magnesium around 3.15, 1.25, 0.59 and 0.20% in mango ginger rhizomes (Fig. 4). Figure 3. SEM micrographs of microwave dehydrated (a) organic ginger (inset shows fresh ginger) and (b) organic mango ginger (inset shows fresh mango ginger) sample. highly disrupted as the samples underwent drying. Due to the presence of volatile matter and excess initial moisture content, the specimens became rigid during the early stages of dehydration. The tissues split and ruptured internally forming cracks in the inner structure when the interior dries finally, pulling the tissues apart forming highly porous due to the internal stresses at higher power (Fig. 3), thus resulting in more homogeneous texture. The SEM analyzer fitted with an EDX micro-analyzer allows a quantitative detection and localization of elements in the rhizome specimens. The EDX images illustrated the presence of larger amount of carbon and oxygen; in addition, elements like silicon, calcium and potassium were identified in a range of 2.54, 2.12 and 1.31%, respectively, (compound percentage) in ginger rhizomes (Fig. 4). Whereas for mango ginger, the presence of oxygen, carbon and sodium were 50.60, 36.01 and 7.46%, respectively. Also, there were 2010 Curtin University of Technology and John Wiley & Sons, Ltd. Specific energy consumption and microwave drying efficiency As sample thickness rose from 0.001 to 0.003 m, the specific energy consumption of ginger rose to 3.2060 from 2.8926 MJ kg−1 for a stipulated microwave output power of 300 W. A similar trend was observed for organic mango ginger samples at the same process conditions. However, mango ginger samples showed a lesser energy consumption while compared with ginger rhizomes, suggesting that high initial moisture content resulted in higher absorption of microwave energy. The best result with regard to energy consumption was obtained for 0.001 m sample thickness. The drying efficiency was about 70.39% for 0.003-m thick ginger samples and showed a rapid increasing tendency as the sample thickness decreased to 0.001 m with an efficiency factor of 78.02%. However, for mango ginger samples, the efficiency ranged between 74.59 and 82.94% (Table 1). Conversely, a significant increase in drying efficiency with increasing initial moisture content indicated that microwave efficiently absorbed water, as water is dielectric in nature. As water depleted, microwave absorption reduced leading to lower efficiency values.[27] Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj Asia-Pacific Journal of Chemical Engineering MICROWAVE DRYING CHARACTERIZATION OF GINGER AND MANGO GINGER Table 1. Comparison of efficiency indices and drying indices for organic rhizome specimens at 300 W microwave output power and 25 g sample load. Characterization Sl no Material 1 Ginger 2 Mango ginger Sample thickness (mm) Specific energy consumption (MJ kg−1 ) Microwave drying efficiency (%) Rehydration ratio 1 2 3 1 2 3 2.8926 2.9225 3.2060 2.6220 2.7741 3.0256 78.02 77.22 70.39 82.94 81.35 74.59 5.4805 4.9178 4.3734 4.9848 4.8394 4.5352 Rehydration ratio Table 1, compares the experimental rehydration ratio obtained for different sample thickness of organic ginger and mango ginger rhizomes, dried at 300 W microwave output power. The RR decreased with increasing sample thickness, suggesting a hardened structure of the solid material, thereby reducing the ingress of water molecules. Ginger rhizomes exhibited a higher RR compared to mango ginger. The higher rehydration at lower sample thickness (0.001 m) and higher microwave output power (300 W) attributed to the development of greater internal stresses during drying at higher power levels. The quick microwave energy absorption causes rapid evaporation of water, creating a flux of rapidly escaping water vapor, which helps in preventing shrinkage and case hardening, thus improving the rehydration characteristics.[28] Empirical modeling Comparison of all eight drying models yielded diffusion equation as the best fit to the experimental data for both ginger and mango ginger rhizomes, with higher R 2 (0.99958 and 0.99620), lower RMSE (0.00117 and 0.00625), χ 2 values (0.00019 and 0.00962) and t-values (0.0042 and 0.03129) (Table 2). The constants a, k and b of the diffusion model for ginger and mango ginger were found to be 0.3481 and 0.9986, 0.0371 and 0.1302, and 0.9999 and 1.0001, respectively, in that order. These constants were independent of the microwave output power, sample thickness, sample load and drying time. The other models except that of diffusion do not account much for the effect of drying variables, which lead to further modification of basic diffusion model to the present system by expressing the constants and coefficients in terms of microwave output power and drying time through eight different derived diffusion expressions using multiple combinations of Arrhenius and logarithmic type equations (Table 3). Among the eight newly derived diffusion models, Model 4 gave the highest R 2 value of 0.9995 and 0.9926, and lowest 2010 Curtin University of Technology and John Wiley & Sons, Ltd. t-values of 0.2615 and 0.5063, for ginger and mango ginger samples, respectively. Based on the multiple regression analysis, the acceptable and suggested model was diffusion model no. 4 for both rhizome specimens, followed by model no. 6 for ginger and model no. 1 for mango ginger. Thus, the regression equations of these parameters against microwave power level of 300 W, sample thickness of 0.001 m and sample load of 25 g, for the accepted model are as follows. For microwave dried organic ginger MR = 1.3150 + 1.0166 ln −0.0458 t P × exp −0.0005 exp 8.314P + 1 − (1.3150 + 1.0166 ln P ) −0.0458 exp −0.0005 exp 8.314P −0.9967 ×(−2.1316) × exp t 8.314 R 2 = 0.9995, (9) χ 2 = 0.0135, t-value = 0.2615, RMSE = 0.1162 (10) for microwave-dried organic mango ginger MR = 1.0130 + 1.2735 ln −0.9997 P × exp −1.0498 exp t 8.314P + 1 − (1.5815 + 1.2735 ln P ) −0.9997 exp −1.0498 exp 8.314P −1.0003 ×(−0.0535) × exp t 8.314 R 2 = 0.9926, (11) χ 2 = 0.0594, t-value = 0.5063, RMSE = 0.0594 (12) Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj 917 918 M. GANESAPILLAI et al. Asia-Pacific Journal of Chemical Engineering Table 2. Results of statistical parameters estimated by regression analyses for organic rhizome specimens of 0.001 m thickness and 25 g sample load. Microwave output power 100 W 180 W 300 W Statistical parameters Ginger Mango ginger Ginger Mango ginger Ginger Mango ginger Model Page MR = exp(−kt n ) Henderson MR = a exp(−kt) Logarithmic MR = a exp(−kt) + c Wang and Singh MR = 1 + at + bt 2 Diffusion MR = a exp(−kt) + (1 − a) exp(−kbt) Verma MR = a exp(−kt) + (1 − a) exp(−gt) Two term exponential MR = a exp(−kt) + (1 − a) exp(−kat) Midilli MR = a exp(−kt n + bt) R2 RMSE χ2 t-value R2 RMSE χ2 t-value R2 RMSE χ2 t-value R2 RMSE χ2 t-value R2 RMSE χ2 t-value R2 RMSE χ2 t-value R2 RMSE χ2 t-value R2 RMSE χ2 t-value 0.9690 0.1417 0.2321 0.3317 0.9678 0.2644 0.4521 0.5667 0.9663 0.3410 0.6156 0.7579 0.9721 0.1067 0.1093 0.1669 0.9854 0.0065 0.0389 0.0944 0.9704 0.1727 0.1734 0.2461 0.9651 0.3905 0.9431 0.9940 0.9823 0.0908 0.0956 0.1334 0.9672 0.2014 0.2100 1.1094 0.9664 0.2525 0.3229 1.3055 0.9651 0.3435 0.4121 1.6616 0.9697 0.0155 0.0793 0.9155 0.9820 0.0083 0.0251 0.7328 0.9681 0.1609 0.1105 1.0293 0.9648 0.4683 0.6250 1.9685 0.9809 0.0127 0.0223 0.8440 0.9792 0.0966 0.1908 0.1266 0.9781 0.1483 0.3273 0.3294 0.9773 0.2926 0.5114 0.6316 0.9834 0.0298 0.0510 0.0292 0.9921 0.0043 0.0105 0.0098 0.9802 0.0771 0.0679 0.1094 0.9765 0.3688 0.8273 0.9505 0.9903 0.0091 0.0330 0.1104 0.9768 0.1629 0.1409 1.0299 0.9757 0.2349 0.2134 1.0851 0.9745 0.3016 0.4008 1.0889 0.9801 0.0142 0.0311 0.8158 0.9915 0.0081 0.0151 0.5753 0.9784 0.1216 0.0798 0.9306 0.9733 0.4637 1.0155 1.0968 0.9889 0.0166 0.0185 0.4874 0.9889 0.0751 0.1503 0.0251 0.9886 0.1016 0.2139 0.1124 0.9869 0.2662 0.4826 0.3905 0.9916 0.0244 0.0497 0.0241 0.9995 0.0017 0.0001 0.0042 0.9893 0.0613 0.0531 0.0868 0.9867 0.3168 0.8980 0.9481 0.9986 0.0082 0.0237 0.0957 0.9901 0.0976 0.0865 0.9707 0.9884 0.1298 0.1034 1.0468 0.9869 0.2019 0.3039 1.0795 0.9933 0.0126 0.0376 0.5474 0.9962 0.0062 0.0096 0.3129 0.9918 0.0406 0.0699 0.7999 0.9855 0.3962 0.7364 1.0486 0.9951 0.0102 0.0165 0.4474 Table 3. Derived diffusion models for moisture ratio determination of organic rhizome specimens. Diffusion equation Arrhenius type Logarithmic type Model no. 1 2 3 4 5 6 7 8 MR = a exp(−kt) + (1 − a) exp(−kbt) a exp(−b/8.314P ) a + b ln(P ) Derived diffusion equations a exp(−a1 /8.314P ) exp −(k exp(−k1 /8.314P )t) + 1 − (a exp(−a1 /8.314P )) exp −(k exp(−k1 /8.314P ))(b exp(−b1 /8.314P )t) a exp(−a1 /8.314P ) exp −(k exp(−k1 /8.314P )t) + 1 − (a exp(−a1 /8.314P )) exp −(k exp(−k1 /8.314P )(b + b1 (ln P )t) a exp(−a1 /8.314P ) exp −(k + k1 (ln P )t) + 1 − (a exp(−a1 /8.314P )) exp −(k + k1 (ln P )b exp(−b1 /8.314P )t a + a1 (ln P ) exp −(k exp −(k1 /8.314P )t) + 1 − (a + a1 (ln P ) exp −(k exp(k1 /8.314P )(b exp(−b1 /8.314P ))t a exp(−a1 /8.314P ) exp −(k + k1 (ln P )t) + 1 − (a exp(−a1 /8.314P )) exp −(k + k1 (ln P ))(b + b1 (ln P )t a + a1 (ln P ) exp −(k + k1 (ln P )t) + 1 − (a + a1 (ln P )) exp −(k + k1 (ln P ))(b + b1 (ln P )t a + a1 (ln P ) exp −(k + k1 (ln P ))t + 1 − (a + a1 (ln P )) exp −(k + k1 (ln P ))(b exp(−b1 /8.314P ))t a + a1 (ln P ) exp −(k exp(−k1 /8.314P ))t + 1 − (a + a1 (ln P )) exp −(k exp(−k1 /8.314P ))(b + b1 (ln P ))t 2010 Curtin University of Technology and John Wiley & Sons, Ltd. Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj Asia-Pacific Journal of Chemical Engineering MICROWAVE DRYING CHARACTERIZATION OF GINGER AND MANGO GINGER 1 MR (Predicted) 0.75 0.5 0.25 0 0 0.25 0.5 MR (Experimental) 0.75 1 Figure 5. Comparison of experimental MR with predicted MR from the derived diffusion model no. 4 for rhizomes (♦: organic mango ginger; : organic ginger). with respect to microwave power were revealed by SEM images. The sample thickness strongly affected the moisture diffusivity where the lower sample thickness provided higher values of effective diffusivity of 9.17 × 10−11 and 11.6 × 10−11 m2 s−1 for organic ginger and mango ginger, respectively. In spite of higher initial moisture content of mango ginger, the efficient moisture transport within the sample led to lower values of specific energy consumption (2.622 MJ kg−1 ) and higher microwave drying efficiency (82.94%). The derived diffusion model no. 4 gave a best fit for experimental data of moisture ratio of rhizomes during this investigation. The models and parameters established in this study can be applied to food, ayurveda (traditional medicine), cosmetic and pharmaceutical industrial design and serve as an operational guide for the microwave drying of ginger and mango ginger to produce spices, essential oils and drugs. NOMENCLATURE These expressions were used to estimate the moisture ratio of ginger and mango ginger at any time during the drying process with an acceptable accuracy. Model validation Validation of the established model was made by comparing the experimental moisture ratio with the calculated ones in any particular drying run under certain conditions. The plots of experimental moisture ratio and predicted moisture ratio by modified diffusion model no. 4 for organic ginger and organic mango ginger are shown in Fig. 5. It can be seen that the model presented a little over- or underestimation in comparison with the experimental data at different stages of drying process, but they are all very close to the experimental data for both organic ginger and mango ginger. The performance of the derived diffusion model (Eqn (4)), at 300 W microwave output power, 0.001 m sample thickness, and 25 g sample load (Fig. 5), gave a higher R 2 of 0.996 and 0.991 for ginger and mango ginger specimens, thus indicating the suitability of the derived model in describing drying behavior of the organic rhizomes. CONCLUSIONS Drying of organic ginger and mango ginger rhizomes mostly occurred in the falling rate period with higher drying rates at higher microwave power (300 W), lower sample thickness of 0.001 m and load of 25 g, respectively. The changes in the surface morphology like severe tissue shrinkage and collapse during drying 2010 Curtin University of Technology and John Wiley & Sons, Ltd. a, b, k , n Empirical constants D0 Pre-exponential factor (m2 s−1 ) Effective moisture diffusivity (m2 s−1 ) Deff Ea Activation energy (W m−1 ) L Half of thickness of specimen (m) MR Moisture ratio Mass of evaporated water (kg) mw P Microwave power output (W) Qs Specific energy consumption (MJ kg−1 ) q Specimen thickness (m) RMSE Root mean square error Coefficient of determination R2 RR Rehydration ratio t Drying time (s) Total drying time (s) ton Wd Weight of dehydrated sample (kg) WR Drained weight of rehydrated sample (kg) X Moisture content at time t (kg kg−1 ), dry solid Initial moisture content (kg kg−1 ), dry solid X0 Greek symbols ήd λw Microwave drying efficiency (%) Latent heat of vaporization (J kg−1 ) REFERENCES [1] M.K. Krokida, V.T. Karathanos, Z.B. Maroulis, D.M. Kouris. J. Food Eng., 2003; 59, 391–403. [2] L.L. Chung, A.S. Mujumdar. Guide to Industrial Drying – Principles, Equipments and New Developments: IDS2008, Hyderabad, India, 2008; pp.223–249. Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj 919 920 M. GANESAPILLAI et al. [3] B. Abbasi Souraki, D. Mowla. J. Food Eng., 2008; 88, 438–449. [4] B.S. Cristina, A. Andres, F. Pedro. J. Food Eng., 2005; 68, 369–376. [5] A.K.S. Chauhan, A.K. Srivastava. Drying Technol., 2009; 27(6), 761–769. [6] X. Yanyang, Z. Min, A.S. Mujumdar, Z. Le-qun, S. Jin-cai. Drying Technol., 2004; 22(9), 2201–2209. [7] D.K. Das gupta, D. Ramesh Babu, A.S. Bawa. J. Food Sci. Technol., 2006; 43(4), 353–356. [8] J. Lee. J. Food Compos. Anal., 2002; 13, 45–57. [9] S. Abbasi, S. Azari. Int. J. Food Sci. Technol., 2009; 44(5), 974–979. [10] G. Dadali, B. Ozbek. Int. J. Food Sci. Technol., 2008; 43(8), 1443–1451. [11] P.P. Sutar, S. Prasad. Drying Technol., 2007; 27, 1695–1702. [12] C. Rossello, J. Canellas, S. Simel, A. Berna. J. Agric. Food Chem., 1992; 40, 2374–2378. [13] G.D. Saravacos. Engineering Properties of Foods, Marcel Dekker: New York, 1986. [14] G. Dadali, B. Ozbek. Drying Technol., 2007; 25, 1703–1712. [15] G.D. Hayes. Food Engineering Data Handbook, Longman Scientific and Technical: Essex, England, 1987; pp.109–128. [16] B.A. Wallace. Food Degradation, AVI Publishing Co: Westport, Connecticut, Vol. 2, 1973. [17] C. Ilhan, A. Mustafa, D. Hikmet. Appl. Therm. Eng., 2007; 27, 1931–1936. 2010 Curtin University of Technology and John Wiley & Sons, Ltd. Asia-Pacific Journal of Chemical Engineering [18] A.A. Hayaloglu, I. Karabulut, M. Alpaslan, G. Kelbaliyev. J. Food Eng., 2007; 78, 109–117. [19] M.M.I. Chowdhury, B.K. Bala, M.A. Haque. Proceedings of 6th Asia-Pacific Drying Conference, Bangkok, Thailand, 2009; pp.351–358. [20] P.M. Lamhot, H.T. Armansyah, O.N. Leoplod, R.H. Augus. Proceedings of 6th Asia-Pacific Drying Conference – 2009 , Bangkok, Thailand, 2009; pp.402–408. [21] M. Ganesapillai, L.R. Miranda, I. Regupathi. Proceedings of the 1st , International Conference of Nano-structured materials and Nano-composites, Kottayam, India, 2009; p.39. [22] C. Ertekin, O. Yaldiz. J. Food Eng., 2004; 63, 349–359. [23] R.C. Guarte. Modeling the Drying Behavior of Copra and Development of a Natural Convection Dryer for Production of High Quality Copra in the Philippines, PhD dissertation, Hohenheim, Stuttgart, Germany, 1996. [24] M. Ganesapillai, I. Regupathi, T. Murugesan. Drying Technol., 2008; 26, 963–978. [25] S.S.H. Rizvi. Thermodynamic Properties of Food in Dehydration. Engineering Properties of Foods Marcel Dekker, Inc.: New York, 1986; pp.133–214. [26] G. Dadali, E. Demirhan, B. Ozbek. Drying Technol., 2007; 25(10), 1703–1712. [27] M.S. Venkatesh, G.S.V. Raghavan. Biosystems Eng., 2004; 88(1), 1–18. [28] D.W. Lyons, J.D. Hatcher, J.E. Sunderland. Int. J. Heat Mass Transfer, 1972; 15(5), 897–905. Asia-Pac. J. Chem. Eng. 2011; 6: 912–920 DOI: 10.1002/apj

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