This study, THIN LAYER DRYING of wheat (Tajan) was modeled. A convective type experimental dryer was used. DRYING experiments were conducted at inlet temperatures of DRYING air of 35, 45, 50, 60 and 70°C, initial moisture content %25 d.b., and four replications for each treatment. Four different THIN LAYER mathematical DRYING models were compared according to their coefficient of correlation to estimate DRYING curves. The x2, root mean square error (RMSE) and coefficient of determination r2 were used as the primary criterion to select the best equation to account for variation in the DRYING curves of the dried samples. The effects of DRYING air temperature on the model constants and coefficients were predicted by regression models. The effects of DRYING air temperature on the Page model constants and coefficients were evaluated by a multiple regression technique. Multiple regression method used for calculating for simulation of moisture content during DRYING for each temperature values that x2, RMSE and r2 were used. The multiple regressions on the coefficients of that model for the effects of the DRYING air temperature gave r2, x2 and RMSE that are 99.38%. 000018 and 004, respectively. These results showed good agreement with the experimental data obtained.

This paper peresents a mathematical model for the THIN LAYER DRYING of the Viliamz cultivar of soybean. The THIN LAYER DRYING behaviour of soybean was experimentally investigated and the mathematical modelling performed by using THIN LAYER DRYING models provided in the literature. Experiments were conducted at inlet DRYING air temperatures of 30, 40, 50, 60 and 70oC and at a fixed DRYING air velocity of 1 m s-1. Thirteen different THIN LAYER mathematical DRYING models were compared according to their r values, RMSE, c2 and EF by non-linear regression analysis. The effect of DRYING air temperature on the model constants and coefficients was predicted using multiple regression analysis. According to the results, the Midilli et al. model was found to be the best mathematical equation for modelling THIN LAYER DRYING of soybean.

Orange (Citrus cinensis) is one of the most important among citrus fruits. The THIN LAYER DRYING kinetics of orange (Thompson variety) slice was here experimentally investigated in a convective dryer and through mathematical modeling and by use of THIN LAYER DRYING models. DRYING characteristics of oranges were determined using heated ambient air at temperatures from 40 to 80°C and velocities from 0.5 to 2.0 m/s. Beside the effects of DRYING air temperature and velocity, the effects of slice thickness on the DRYING characteristics, DRYING time were also determined. DRYING curves obtained from the experimental data were then fitted to the THIN LAYER DRYING models. The effects of DRYING air temperature and velocity on the model constants and coefficients were evaluated through a multiple regression technique. The models were compared according to three statistical parameters, i.e. root mean square error, chi-square and modeling efficiency. The results have shown that, increasing the DRYING air temperature and velocity causes shorter DRYING times. Midilli et al. model was found to be the most appropriate model for describing the DRYING curves of oranges. The effects of DRYING air temperature and velocity on the DRYING constant and coefficient were also investigated.

Citrus fruits are holding a prominent position among agricultural products throughout the world. One of these important fruits from economical and industrial point of view is orange. This product is consumed as fresh, juice, concentrated juice and/or dried slices. In this study, THIN LAYER DRYING of Thomson cultivar of orange (novel) was modeled. A laboratory dryer was employed to attain the goal. Experiments were conducted at five levels of dryer air temperature (30, 40, 50, 60 and 70°C), an air velocity of 0.5 m/s with orange slices of 4 mm thickness replicated three times. Under controlled conditions, samples of 5.4 to 5.7 (g/g) initial moisture content (d.b) were dried. Moisture content of the mass of orange slices was continuously calculated by constantly weighing the samples during the DRYING process. Thirteen standard mathematical models for simulation of the THIN LAYER DRYING process were asseyed through curve fitting, while three parameters of coefficient of determination (R 2), chi-square(c2) and root mean square error (RMSE) being used to compare the results of multivariate regression analysis. A new model, appearing for the first time in this paper was developed and put to test in the comparison process. Determination coefficient, chi-square and root mean square error for the new model were the most responding as compared to the rest of the models being found 99.98%, 0.00154092, and 0.03460955, respectively. Therefore, the new model provides a most promising one for predicting moisture content changes during a THIN LAYER DRYING process of orange slices.

Artificial DRYING is one of the most common methods of preservation of agricultural products. DRYING conditions can affect physical and mechanical properties of grain. The DRYING process must be designed and controlled to minimize DRYING damage. In this study, the THIN LAYER DRYING kinetics behavior of wheat (tajan) with initial moisture content of 26% (d.b.) in a convective type experimental dryer was investigated and mathematical modeling using four replications of THIN LAYER DRYING kinetics models from the literature was performed. DRYING experiments were carried out at inlet temperatures of 35, 45, 50, 60 and 70°C. DRYING time to reach 10.5 % moisture content from the initial moisture content at various DRYING air temperatures were found to be between 62 and 246 min. Six different THIN LAYER mathematical DRYING kinetics models were compared according to their correlation coefficient to estimate DRYING kinetics curves. The effects of DRYING air temperature on the model constants and coefficients were predicted by regression models. According to the results, the approximation of diffusion model represents the curves of the wheat DRYING kinetics (r=0.932). Non-linear regression method was used to simulate the DRYING kinetics as a function of the temperature.

In this research, DRYING of green bell peppers by hot air dryer at temperatures, 60, 70 and 80oc kinetic DRYING parameters were investigated. The results showed that the temperature 80oc has highest rate of DRYING and lowest time. Also increasing the temperature caused increasing the shrinkage and most shrinkages were observed in 80 centigrade .rehydration rate decrease when temperature increase and the highest rehydration rate observed in 60 centigrade due to the decreasing of destroying capillary tube. the result showed that increasing temperature increasing moisture dispersion and activation energy value was 34.577 kj/mol. Modeling based on 11 standard mathematical models was fitted to the experimental data. And criteria for evaluating models Determination of Coefficient (R3), Root Mean Square Error (RMSE), Chi-square (X2), and Mean Bias Error (MBE) were analyzed. Survey results showed that the Approximation of diffusion Model for the DRYING at temperature of 60 and 80 and Verma. et al model at temperature of 70 stages of DRYING peppers make a better assessment. So this model to predict changes in humidity and high quality product with hot air dryer for DRYING green bell peppers was diagnosed.

Lemon verbena leave is a flavoring food additive as well as a good source of valuable compounds such as essential oils, flavonoids and phenolic acids. However, similar to many other aromatic plants, lemon verbena leave is perishable due to its high moisture content. The aim of this work was to study the effect of air temperature (45, 55, and 65°C) on the quality attributes of lemon verbena leaves during hot-air DRYING (HAD).The DRYING kinetics were also modeled. The results showed that higher DRYING temperature led to a significant decrease (p˂0.05) in the rehydration ratio due to a change in the structural features of the dried leaves. The essential oil content of dried samples was also significantly different (p˂0.05) from that of the fresh leaves due to high loss of volatile components and ranged from 0.42 to 0.85. Moreover, a significant increase in the value of effective moisture diffusivity (Deff) and color change was observed when the samples were dried at 65°C compared to 45°C. The value of Deff varied from 1.140×10-10 to 2.280×10-9 m2/s and the activation energy was found to be 31.04 kJ/mol. The greatest R2 (≥0.999) and the lowest RMSE and SSE were obtained for the Naghaviet al. model (proposed in this research).

This research, presents mathematical modeling of DRYING process of Aloe vera slices with dimensions of 7×4×0.5±0.1 cm. Peeled Aloe vera slices with the initial moisture content of 5750% (d.b) were osmosed for 5 hours in NACL solution of 10% and temperature of 40 °C at a constant solution to fruit ratio of 5: 1. Osmosed and unosmosed Aloe vera samples were hot air dried at 55, 70 and 85°C with different air flow rates of 0.015, 0.036 and 0.054 m3/s for 13200s. The moisture content of Aloe vera samples were measured over different intervals of DRYING time (1200, 2400, 6000, 9600, 13200s) for each experiment. The experimental results were used to obtain two different dimensionless models based on Buckingham’s pi-theorem for both DRYING methods. To this end, three independent π terms were identified and then the relation between dependent π term andeach independent p term was sought. Finally, the dimensionless models incorporating the effect of all the independentπ terms on the dependent one derived and evaluated. The RMSE, (R2), MRD and MBE for the modeling of osmotic-convective DRYING method were calculated as 0.0185, 0.99, 0.05 and 0.034, respectively. Also these statistical parameters for the convective DRYING method were as: 0.027, 0.98, 0.061 and 0.051, respectively. Therefore the dimensionless models could predict the moisture content of Aloe vera samples during DRYING, properly.

Introduction: One of the new techniques in the DRYING of food is the application of infrared radiation that increases the DRYING rate, enhanced the final product quality, and decreases the costs of the process. Materials and Methods: In this study, DRYING kinetic modeling of strawberry in an infrared dryer was investigated. The effect of radiation lamp power (150, 250 and 375 W) and distance of the lamp from the sample (5, 7. 5 and 10 cm), on DRYING time, and moisture diffusion coefficients during the DRYING process of strawberry were evaluated. For measuring the weight of the samples during experimentation without taking them out of the dryer, the tray with samples was suspended on the digital balance. Standard models (Wang and Singh, Henderson and Pabis, Approximation of diffusion, Page, Modified Page – II, Newton, Midilli and Logarithmic) were fitted to experimental data to study the DRYING kinetics and fitting quality (coefficient of determination and standard error) of them was analyzed. Results: By increasing infrared lamp power from 150 to 375 W, the DRYING time of strawberry is reduced by 79. 8%. Decreasing the distance of the lamp from a sample from 10 to 5 cm, 40. 1 % of DRYING time is reduced. The effective diffusivity coefficient was increased by increasing heat source power and decreasing distance. Moisture effective diffusivity coefficient of strawberry was between 1. 54×10-9 to 13. 83×10-9 m2/s. Conclusion: The effect of radiation lamp power and distance on the DRYING process of strawberry is significant. Modeling of strawberry DRYING process showed that all the models led to proper results, but in total, the Page model, compared to other studied models, with the biggest coefficient of determination (R2=0. 999) and the smallest error (<0. 011), had closer results to the experimental data.