The objective of this study was to examine the effects of the fluidized-bed drying method on the final quality of two varieties of Iranian rice, medium- and long grain. The results were compared to that of paddy drying using a traditional method. Rough rice was treated in the fluidized bed drier at 140°C for 2 minutes. Similar samples were dried for 8-10 hrs by the traditional method. Dried samples were dehusked and polished. Quality factors, including trade quality (head rice yield percent and whiteness), cooking quality (amylose content, gelatinization temperature, gel consistency, aroma and flavor) and nutritional quality (thiamine and lysine contents), were then measured for each sample. Finally, the data was analyzed. Results show that paddy drying in a fluidized bed dryer would reduce the quality factors except for rice whiteness for which conventional drying is more acceptable. Therefore modification of fluidized-bed drying technique is recommended.

For efficiency evaluation of some of the Decision Making Units that have uncertain information, Rough Data Envelopment Analysis technique is used, which is derived from Rough set theorem and Data Envelopment Analysis (DEA). In some situations Rough data alter nonradially. To this end, this paper proposes additive Rough–DEA model and illustrates the proposed model by a numerical example.

Simulation of Rough rice drying is one of the proper methods for predicting moisture distribution in the product, and thRoughout the process of drying. The drying process must be well understood and controlled so that design guidelines which reduce or minimize drying damage to Rough rice can be established and improved. Therefore, an accurate understanding and description of the drying mechanism must be implemented. Finite element technique for formulation and solution of a set of coupled conductive heat and a diffusive moisture transfer equation to improve grain drying simulation of axisymmetric bodies is hereby employed. A long grain variety, ‘Ali-Kazemi’, was used for the study. During the thin layer drying, the drying air temperature and initial moisture content were 40oC and 32% (d.b.), respectively. Moisture content was measured by minute. Good agreement was observed when the output of the model compared to experimental data obtained by others. The root mean squre error (RMSE) and modelling efficiency (EF) calculated from nonlinear model vs. experimental data, were 0.01 and 0.991, respectively. This shows that simulation data is close to the experimental ones, and the model can be used for moisture content simulation of Rough rice drying. The simulated moisture profile and gradient are directly applicable to stress cracking analyses of Rough rice. The results of the finite element analysis obtained can be used in Rough rice quality evaluation as well as drying simulation studies.

Stress cracking susceptibility during drying process of two varieties of Khazar (Long-grain), and Hashemi (longer-grain) rice was investigated. Thin-layer drying tests were conducted with air drying temperatures of 35°C, 45°C, 55°C and 65°C. Stress-cracking development reactions in the endosperm of rice kernels was investigated during drying with various temperatures of drying air and in passing from moisture contents of 18%, 15% and 12%(w.b.). Stress-cracking index (SCI) was applied to quantify stress cracking susceptibility (severity of damage to endosperm) induced to kernels by drying. The drying air temperature and the removal of moisture content have important effects on the development of stress cracking. For Hashemi variety, from 45°C on, and for Khazar variety a moment lower than that (by increase in temperature), SCI increased intensively. To attain the moisture content of 15%(w.b.), either of the varieties could be dried with higher temperatures without inducing any high SCI. Air drying temperatures of 55°C for Hashemi variety and a moment higher than 45°C for Khazar variety were recommended, Then the drying process should continue with the lowest possible temperature. Khazar (long-grain) variety was more susceptible to fissuring than Hashemi (longer-grain).

The objective of this research was to predict head rice yield (HRY) in fluidized bed dryer using artificial neural network approaches. Several parameters considered here as input variables for artificial neural network affect operation of fluidized bed dryers. These variables include: air relative humidity, air temperature, inlet air velocity, bed depth, initial moisture content, final moisture content and inlet air temperature. In aggregate, 274 drying experiments were conducted for creating training and testing patterns by a laboratory dryer. Samples were collected from dryer, and then dehulling and polishing operations were done using laboratory apparatus. HRY was measured at several different depths, average of which was considered as HRY for each experiment. Three networks and two training algorithms were used for training presented patterns. Results showed that the cascade forward back propagation algorithm with topology of 7-13-7-1 and Levenberg-Marquardt training algorithm and activation function of Sigmoid Tangent predicted HRY with determination coefficient of 95.48% and mean absolute error 0.019 in different conditions of fluidized bed paddy drying method. Results showed that the input air temperature and final moisture content has the most significant effect on HRY.

Fluidized bed drying method is one of the most important new drying methods of agricultural materials. In this study the Rough rice drying process by fixed and fluidized methods was compared based on thermal efficiency, drying rate and kernel fissuring percent. The experiments were conducted by a laboratory fluidized bed dryer with ability of the inlet air temperature and airflow rate control to operate in fixed and fluidized conditions. The Rough rice samples were dried from 17.7 initial moisture content to 11% final moisture content (dry basis) at three temperatures of 40, 60 and 80oC. The air velocity in fixed, semi-fluidized and fluidized bed conditions was 0.1, 1.1 and 3.5 m/s, respectively. The thermal efficiency of dryer was calculated based on the ratio of thermal energy utilized for evaporating water from the drying product to thermal energy supplied to the drying air. The maximum and minimum thermal efficiency of 22.84 and 3.3% were belonged to the fixed bed condition at 80oC and the fluidized bed condition at 40oC, respectively. The fixed bed condition was determined as the main factor influencing kernels fissuring, so that the maximum drying time of 280 minutes and the maximum kernel fissuring of 78% were measured in this condition at 80oC. The minimum drying time of 40 minutes and the minimum kernel fissuring of 17% were belonged to the semi-fluidized bed condition at 80 and 40oC, respectively.

Artificial drying of Rough rice products is one of the most common methods of its preservation. Rapid drying can increase brittleness and induce internal cracks which predispose the product to breakage during subsequent activities. The drying process must be understood and product to breakage during subsequent activities. The drying process must be understood and controlled so that design guidelines which reduce or minimize drying damage to Rough rice can be established and improved. This requires an accurate description of the drying mechanism. A finite element formulation and solution of a set of linear and nonlinear coupled conductive heat and diffusive moisture transfer equations to improve grain drying simulation of ax symmetric bodies is presented. Ax symmetric linear triangular elements with two degrees of freedom per node are used to decretive the rice grain in both models. One medium grain, "Binam", was used. During the thin layer drying, moisture was measured every minute. Good agreement has been observed when the output of nonlinear model was compared to experimental data obtained by others. Relative deviance average that calculated of linear and nonlinear model with experimental data, respectively 10.5% and 3.5%. This result shows that nonlinear is near experimental data. Nonlinear model is used for moisture simulation of Rough rice drying. The simulated moisture profile and gradient are directly usable for stress cracking analyses of Rough rice. The results of the finite element analysis can be used for Rough rice quality evaluation and drying simulation studies.

Artificial drying of Rough rice products is one of the most common methods of preservation. Rapid drying can increase brittleness and induce internal cracks which predispose the product to breakage during subsequent activities. The drying process must be designed and controlled so that design guidelines which reduce or minimize drying damage to Rough rice products can be established and improved. This requires an accurate description of the drying mechanism. A finite element formulation and solution of a set of linear and nonlinear coupled conductive heat and diffusive moisture transfer equations to improve grain drying simulation of axisymmetric bodies is presented. Axisymmetric linear triangular elements with two degree of freedom per node are used to discretize the rice grain in both models. One medium grain, 'Cepidrod', was used. During the thin layer drying, temperature was measured every five second. Relative deviations of predicted values for linear and nonlinear models from measured data were calculated. The deviation obtained for nonlinear model was less than the linear model. Nonlinear model was improved by changing coefficient of latent heat of evaporation specific heat equation. The simulated temperature profile and gradient are directly usable for stress cracking analyses of Rough rice. The results of the finite element analysis can be used for Rough rice quality evaluation and drying simulation studies.      

ThRoughout the present study, the efficacy of intermittent as well as continuous drying processes on fissuring of Hashemi and Koohsar varieties was investigated. The fissuring of the kernels was assessed as based on Stress Cracking Index (SCI). The experiments were carried out at drying and tempering temperatures of 30, 45 and 60oC, drying durations of 20, 40 and 60 min, and a constant tempering duration of 80 min. In comparison with continuous drying method, under intermittent drying method, SCI value reduced significantly from 43.5 to 17; 74.5 to 28.3, and from 83 to 58.4, respectively at temperatures of 30, 45 and 60oC. Also, the value of SCI measured 48 h following the drying process being finished, compared with its corresponding value measured immediately after drying operation increased significantly from 28.72 to 46.73. Both the total operation time (sum of all passes durations) and SCI decreased as tempering temperature increased, due to the faster elimination of moisture gradients inside the kernels. Therefore, by appropriate tempering operation, in addition to maintaining the quality of the final product, the total operation time too, could be reduced.