• Journal of Biosystems Engineering
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• v.22 no.1
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• pp.11-20
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• 1997

Thin layer drying tests of short gain rough rice were conducted in an experimental dryer equiped with air conditioning unit. The drying tests were performed in triplicate at three air temperatures of $35^circ$, $45^circ$, $55^circ$, and three relative humidities of 40%, 55%, 70%, respectively. Previously published thin layer equations were reviewed and four different models widely used as thin layer drying equations for cereal grains were selected. The selected four models were Pages, simplified diffusion, Lewis's and Thompson's models. Experimental data were fitted to these equations using stepwise multiple regression analysis. The experimental constants involved in tow equations were represented as a function of temperature and relative humidity of drying air. The results of comparing coefficients of determination and root mean square errors of miosture ratio for low equations showed that Page's and Thompsons models were found to fit adequately to all drying test data with coefficient of determination of 0.99 or better and root mean square error of moisture ratio of 0.025.

• Journal of Biosystems Engineering
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• v.27 no.1
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• pp.45-50
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• 2002

This study was performed to develop thin layer drying equations fur short grain rough rice using far-infrared ray. Thin layer drying tests was conducted at four far-infrared ray temperature levels of 30, 40, 50, 60$^{\circ}C$ and two initial moisture content levels of 20.7, 26.2%(w.b.). The measured moisture ratios were fitted to Lewis and Page drying models by stepwise multiple regression analysis. Half response time of drying was affected by both drying temperature and initial moisture content at drying temperature of below 40$^{\circ}C$, but at above 40$^{\circ}C$ was mainly affected by drying temperature. Experimental constant(k) in Lewis model was a function of drying temperature, but K and N in Page model were function of drying temperature and initial moisture content. Moisture ratios predicted by two drying models agreed well with experimental values. But in the actual range of drying temperature above 30$^{\circ}C$ Page model was more suitable for predicting of drying rates.

• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.410-415
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• 2006

This study was performed to develop thin layer drying equations for green rice. Thin layer drying tests of green rice were conducted at three temperature levels of 30, 40, $50^{\circ}C$ and two relative humidity levels of 30, 50% respectively. The measured moisture ratio were fitted to the selected four drying models (Page, Thompson, Simplified diffusion and Lewis model) using stepwise multiple regression analysis. The overall drying rate increased as the drying air temperature and as relative humidity was increased, but the effect of temperature increase was dominant. Half response time (Moisture ratio=0.5) of drying was affected by both drying temperature and relative humidity Drying rate was mainly affected by relative humidity at drying temperature of $50^{\circ}C$. The results of comparing coefficients of determination and root mean square error of moisture ratio for four drying models showed the Page model was found to ft adequately to all drying test data.

• Journal of Biosystems Engineering
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• v.29 no.6 s.107
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• pp.495-500
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• 2004

This study was performed to develop thin layer drying equations for low temperature. Thin layer drying tests of short grain rough rice were conducted at three low temperature levels of 15, 25, $35^{\circ}C$ and two relative humidity levels of 30, $50\%$, respectively. The measured moisture ratios were fitted to the selected four drying models (Page, Thompson, Simplified diffusion and Lewis model) using stepwise multiple regression analysis. The overall drying rate increased as the drying air temperature was increased and as relative humidity was decreased, but the effect of temperature increase was dominant. Half response time (Moisture ratio=0.5) of drying was affected by both drying temperature and relative humidity at drying temperature of below $25^{\circ}C$, but at $35^{\circ}C$ was mainly affected by drying temperature. The results of comparing coefficients of determination and root mean square error of moisture ratio for low drying models showed that Page model was found to fit adequately to all drying test data.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.232-239
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• 2016

Purpose: The aims of this study were to define the drying characteristics of rapeseed and to determine the optimum thin-layer drying model for rapeseed by considering the effects of drying temperature and relative humidity. Methods: The thin-layer drying experiments were conducted at different combinations of drying air temperature levels of 40, 50, and $60^{\circ}C$ and relative humidity levels of 30, 45, and 60%, on both of which drying rate depends. The drying rate increased with increasing air temperature as well as decreasing relative humidity. The 13 models were fitted to the experimental data. Results: From the results of the regression analysis for empirical constants of the Page model, the values of $R^2$ were the highest (ranging from 0.9924 to 0.9966) and the values of RMSE were the lowest (ranging from 0.0169 to 0.0296). Conclusions: For all drying conditions considered, the Page model was determined to be the most suitable model for describing the thin-layer drying of rapeseed (P-value < 0.01). The moisture diffusion coefficients were calculated using the moisture diffusion equation for a spherical shape, based on Fick's second law.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.190-198
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• 2017

Purpose: A thin-layer drying equation was developed to analyze the drying processes of soybeans (white and black beans) and investigate drying conditions by verifying the suitability of existing grain drying equations. Methods: The drying rates of domestic soybeans were measured in a drying experiment using air at a constant temperature and humidity. The drying rate of soybeans was measured at two temperatures, 50 and $60^{\circ}C$, and three relative humidities, 30, 40 and 50%. Experimental constants were determined for the selected thin layer drying models (Lewis, Page, Thompson, and moisture diffusion models), which are widely used for predicting the moisture contents of grains, and the suitability of these models was compared. The suitability of each of the four drying equations was verified using their predicted values for white beans as well as the determination coefficient ($R^2$) and the root mean square error (RMSE) of the experiment results. Results: It was found that the Thompson model was the most suitable for white beans with a $R^2$ of 0.97 or greater and RMSE of 0.0508 or less. The Thompson model was also found to be the most suitable for black beans, with a $R^2$ of 0.97 or greater and an RMSE of 0.0308 or less. Conclusions: The Thompson model was the most appropriate prediction drying model for white and black beans. Empirical constants for the Thompson model were developed in accordance with the conditions of drying temperature and relative humidity.

• Preventive Nutrition and Food Science
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• v.13 no.3
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• pp.225-230
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• 2008

Onion slices were dehydrated in a single layer at drying air temperatures ranging from $50{\sim}70^{\circ}C$ in a laboratory scale convective hot-air dryer at an air velocity of 0.66 m/s. The effect of drying air temperature on the drying kinetic characteristics were determined. It was found that onion slices would dry within $210{\sim}460\;min$ under these drying conditions. Moisture transfer during dehydration was described by applying the Fick's diffusion model and the effective diffusivity changed between $1.345{\times}10^{-8}$ and $2.658{\times}10^{-8}\;m^2/s$. A non-linear regression procedure was used to fit 9 thin layer drying models available in the literature to the experimental drying curves. The Logarithmic model provided a better fit to the experimental drying data as compared to other models. Temperature dependency of the effective diffusivity during the hot-air drying process obeyed the Arrhenius relationship with estimated activation energy being 31.36 kJ/mol. The effect of the drying air temperature on the drying model constants and coefficients were also determined.

• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.138-143
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• 2015

This paper was aimed to study the drying kinetics of coffee and to investigate the thin-layer drying kinetics of coffee by using a convective air dryer. The coffee was dried for the temperatures of 40, 50 and $60^{\circ}C$ with relative humidity in the range of 14-25% the airflow rate fixed at 1 m/s. According to the experiment result, the drying rate curve showed that drying process took place only in the falling rate period. Seven thin layer drying models (Newton, Page, Henderson and Pabis, Logarithmic, Wang and Singh, Two terms, Modified Henderson and Pabis) were fitted to the experimental moisture content data. The Two-trem model was found to be a better model for describing the characteristics of coffee for the temperatures of 40, 50 and $60^{\circ}C$. The effective moisture diffusivity of coffee increased when the drying temperature increased. The value was in the range of $4.5028{\times}10^{-11}$ to $6.4803{\times}10^{-11}m^2/s$.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.357-364
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• 2016

Purpose: This study was performed to define the drying characteristics of sorghum by developing thin layer drying equations and evaluating various grain drying equations. Thin layer drying equations lay the foundation characteristics to establish the thick layer drying equations, which can be adopted to determine the design conditions for an agricultural dryer. Methods: The drying rate of sorghum was measured under three levels of drying temperature ($40^{\circ}C$, $50^{\circ}C$, and $60^{\circ}C$) and relative humidity (30%, 40%, and 50%) to analyze the drying process and investigate the drying conditions. The drying experiment was performed until the weight of sorghum became constant. The experimental constants of four thin layer drying models were determined by developing a non-linear regression model along with the drying experiment results. Result: The half response time (moisture ratio = 0.5) of drying, which is an index of the drying rate, was increased as the drying temperature was high and relative humidity was low. When the drying temperature was $40^{\circ}C$ at a relative humidity (RH) of 50%, the maximum half response time of drying was 2.8 h. Contrastingly, the maximum half response time of drying was 1.2 h when the drying temperature was $60^{\circ}C$ at 30% RH. The coefficient of determination for the Lewis model, simplified diffusion model, Page model, and Thompson model was respectively 0.9976, 0.9977, 0.9340, and 0.9783. The Lewis model and the simplified diffusion model satisfied the drying conditions by showing the average coefficient of determination of the experimental constants and predicted values of the model as 0.9976 and Root Mean Square Error (RMSE) of 0.0236. Conclusion: The simplified diffusion model was the most suitable for every drying condition of drying temperature and relative humidity, and the model for the thin layer drying is expected to be useful to develop the thick layer drying model.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.219-226
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• 2002

Desorption equilibrium moisture contents of oak mushroom were measured by the static method using salt solutions at flour temperature levels of 35$\^{C}$, 45$\^{C}$, 55$\^{C}$ and 6$\^{C}$ and five relative humidity levels in the range from 11.0% to 90.8%. EMC data were fitted to the modified Henderson, Chung-Pfost, modified Halsey and modified Oswin models using nonlinear regression analysis. Drying tests far oak mushroom were conducted in an experimental dryer equipped with air conditioning unit. The drying test were performed in triplicate at flour air temperatures of 35$\^{C}$, 45$\^{C}$, 55$\^{C}$ and 65$\^{C}$ and three relative humidities of 30%, 50% and 70% respectively. Measured moisture ratio data were fitted to the selected four drying models(Lewis, Page, simplified diffusion and Thompson models) using stepwise multiple regression analysis. The results of comparing root mean square errors for EMC models showed that modified Halsey was the best model, and modified Oswin models could be available far oak mushroom. The results of comparing coefficients of determination and root mean square errors of moisture ratio for four drying models showed that Page model were found to fit adequately to all drying test data with a coefficient of determination of 0.9990 and root mean square error of moisture ratio of 0.00739.