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  The purpose of this study was prediction of thermal (effective moisture diffusivity and specific energy consumption), physical (shrinkage and color) and mechanical properties (rupture force) of terebinth fruit in a semi industrial continuous dryer using artificial neural networks (ANNs). Three effective factors on thermal, physical and mechanical properties, were air temperature, air velocity and belt linear speed as independent variables. Experiments were conducted with a semi industrial continuous dryer in temperature levels of 45, 60, 75 °C, air velocity levels of 1, 1.5 and 2 m/s and belt linear speed levels of 2.5, 6.5, 10.5 mm/s. Necessary data were collected using a the semi-industrial continuous dryer. Feed and cascade forward back propagation networks with learning algorithms of Levenberg-Marquardt and the Bayesian regulation were used to train the patterns. To predict the effective moisture diffusivity, feed forward networks with the Bayesian regulation, topology of 3-10-13-1 and 108 training cycles with R²=0.9999 was optimal arrangement. The optimal topology to predict the specific energy consumption was 3-10-1 with feed forward network, Levenberg-Marquardt algorithm, 117 training cycles and R²=0.9961. The best network for shrinkage prediction was feed forward network with the Bayesian regulation algorithm, topology of 3-6-4-1, 101 training cycles and R²=0.9926. To predict the total color change, feed forward networks with the Levenberg-Marquardt algorithm, topology of 3-6-7-1, 24 training cycles and R²=0.9139 was the optimal arrangement. The best network to predict the rupture force was feed forward network trained with the Bayesian regulation, topology of 3-8-6-1, 69 training cycles and R²=0.9990.

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Black tea sample was dried by a vibro-fluidized bed dryer to find its aerodynamic behavior and thermal performance during drying. The drying experiments were conducted at three different inlet air temperatures of 100, 115 and 130°C and fluidization condition at five vibration intensity levels of 0 (no vibration), 0.063, 0.189, 0.395 and 1.184. The results showed that bed channeling and defluidization problems were decreased in vibration condition. The vibration system decreased the requirement of minimum fluidization velocity of tea particles and this velocity reduced by increasing the vibration intensity. In the experiments, the maximum evaporation rate (13×10-3 kgv m-2 s-1) was at the vibration intensity of 1.184 and inlet air temperature of 130°C. Also the minimum specific energy consumption (4953.785 kJ kgv-1) was observed at 1.184 vibration intensity and 100°C inlet air temperature condition. Based on lower minimum fluidization velocity and specific energy consumption, the vibration intensity of 1.184 and inlet air temperature of 100°C were recommended for drying black tea particles.

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Energy and mass transfer investigations in thermal processing of fruits serve as a breakthrough in the design and scale up of drying systems. Diffusivity characteristics and specific energy consumption for drying of fig fruit in a laboratory scale microwave dryer were assessed. Several intervals for microwave power intensity including 0.5, 1, 1.5, 2, and 2.5 W g^-1, and 6 levels of power on-off stated as pulsing ratios of 1.5, 2, 2.5, 3, 3.5, and 4 were employed. The results showed that the drying rate decreased with the pulsing ratio and increased with microwave power intensity. Effective moisture diffusivity as an indicator of mass transfer was obtained to be higher at elevated microwave power intensities. Also, increased pulsing ratios had a reducing effect on moisture diffusivity. Using 2^nd law of Fick, moisture diffusivity was calculated to be varying from 5.93E-10 to 1.42E-08 m² s^-1 depending on the experimental conditions. Furthermore, the activation energy of fig fruit was obtained to be in the range of 60.094 to 92.189 kJ mol^-1. Specific energy consumption variations showed a positive correlation with pulsing ratio and drying time. However, due to the dependence of energy consumption on MW power intensity, a multiple regression analysis with R² of 0.968 was developed.

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In the present study, an infrared-assisted solar dryer was used to determine the drying kinetics, energy consumption and quality parameters evaluation of Echium amoenum. Experiments were conducted with two levels of drying air flow rate (0.0025 and 0.005 m³s^-1) and three levels of IR lamp power (100, 150 and 213 W). Drying time, energy consumption and evaluation of quality properties in different air flow rates and lamp powers were compared to the conventional method (shade drying). Five empirical models were fitted on the experimental data and the goodness of regression models were evaluated using coefficient of determination (R²), root mean square error (RMSE), and Chi square (χ²). Results of drying time in the different experiments showed highly significant differences respect to the conventional method (p-value<0.01). Also results showed that increasing the air flow rate and IR power caused a reduction of 37% and 17% in drying time, respectively. Best empirical model to describe the drying behavior was the Page model. The lowest specific energy consumptions (SEC) was 4.63 MJ kg^-1, which was occurred at the air flow rate and IR power of 0.005 m³s^-1 and 150 W and the highest SEC was 5.26 MJ kg^-1 and occurred at 0.0025 m³s^-1 of air flow rate and 213 W of IR lamp, respectively. Finally, the air flow rate of 0.005 m³s^-1 and the IR power of 150 W was recommended for Echium amoenum drying in the IR-ASD because of the fair energy consumption and the suitable product color.
 

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In hot air dryers, only a small percentage of the provided thermal energy is used for the drying process, while a large fraction is lost via the exhaust air. To recycle waste heat from the exhaust air, the present study aimed to develop a solar dryer equipped with a novel heat recovery system. The designed dryer comprised of a solar air collector, a drying chamber, an internal closed-loop air circuit and an open-duct heat recovery system. The evaluation tests were conducted at different allowable relative humidities (RH) and mass flow rates of the recirculating air. The results indicated that the best solar fraction was at the highest RH and air flow rate. Increasing the RH from 7 to 17% caused a reduction of 51% in electricity consumption. Furthermore, electrical energy needed for drying increased by 24% with raising the air flow rate from 0.008 to 0.016 kg s^-1. A minimum specific energy consumption of 7.54 MJ kg^-1 was observed at the highest RH and the lowest air flow rate. At a constant RH, reduction of the air flow rate led to an increasing trend in lightness and decreasing trends in browning index of the products. Moreover, increasing the RH from 7 to 17% increased lightness and decreased browning index. In general, it can be stated that the best colour quality was achieved when the minimum air flow rate and the maximum RH were used for the solar drying.

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In the present work, the effect of infrared drying power on dehydration and rehydration characteristics, energy consumption, and essential oil yield of common wormwood leaves was studied. Thin layers of the leaves were dried at power levels of 200, 300, 400, and 500W. Effective moisture diffusivity values for the leaves over the applied drying conditions were obtained to be in the range of 8.84×10^-8-2.76×10^-7 m² s^-1. Rehydration curves for the dried leaves were obtained at constant temperature of 80°C and fitted to Peleg model. Rehydration capacity of the leaves decreased with increasing infrared drying power. In comparison with the fresh levels, infrared drying caused both increment and decrement in essential oil yield. The highest and the lowest oil yields were obtained from the samples dried at the power levels of 200 and 500W, respectively. Specific energy consumption changed from 4.22 to 10.56 MJ kg^-1.