scholarly journals Thin-Layer Drying Characteristics and Modeling of Chinese Jujubes

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Xiao-Kang Yi ◽  
Wen-Fu Wu ◽  
Ya-Qiu Zhang ◽  
Jun-Xing Li ◽  
Hua-Ping Luo
Keyword(s):  
Thin Layer ◽  
Distribution Model ◽  
Drying Time ◽  
Drying Characteristics ◽  
Simulation And Optimization ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Higher Temperature ◽  
Drying Rates ◽  
Experimental Values

A mathematical modeling of thin-layer drying of jujubes in a convective dryer was established under controlled conditions of temperature and velocity. The drying process took place both in the accelerating rate and falling rate period. We observed that higher temperature reduced the drying time, indicating higher drying rates of jujubes. The experimental drying data of jujubes were used to fit ten different thin-layer models, then drying rate constants and coefficients of models tested were determined by nonlinear regression analysis using the Statistical Computer Program. As for all the drying models, the Weibull distribution model was superior and best predicted the experimental values. Therefore, this model can be used to facilitate dryer design and promote efficient dryer operation by simulation and optimization of the drying processes. The volumetric shrinkable coefficient of jujubes decreased as the drying air temperature increased.

Influence of Drying Conditions and Mathematical Models on the Thin-Layer Drying of Mushrooms

2014 ◽  
Author(s):  
A. Stegou-Sagia ◽  
D. V. Fragkou
Keyword(s):  
Mass Transfer ◽  
Thin Layer ◽  
Mathematical Models ◽  
Drying Methods ◽  
Suitable Model ◽  
Drying Time ◽  
Thin Layer Drying ◽  
Drying Behavior ◽  
Drying Models ◽  
Drying Rates

In the present research, experimental data from several studies about drying behavior of mushrooms have been selected and used to compare different drying methods and different mathematical thin layer drying models to simulate mushroom drying rates. The white button (Agaricus Bisporus), the oyster (Pleurotus Ostreatus) and the milky mushroom slices have been considered for drying in different dryers such as hot air cabinet dryer and fluidized bed dryer with different slice thicknesses, drying air temperatures (45 °C to 90 °C) and drying air velocities (0.2 m/s to 5 m/s). The entire drying process has taken place in the falling rate period, assuming that internal mass transfer occurred by diffusion in mushroom slices. The study shows that the drying air temperature and the drying air velocity have an effect on the moisture removal from mushrooms and also on the drying time. Mathematical models have been proved to be useful for design and analysis of heat and mass transfer during drying processes. All the drying models considered in this study could adequately represent the thin layer drying behavior of mushrooms. Furthermore, as it is obvious, any type of mushrooms has its own most suitable model.

scholarly journals Drying Modelling, Moisture Diffusivity and Sensory quality of Thin Layer dried Beef

2018 ◽  
Vol 6 (2) ◽  
pp. 552-565 ◽  
Author(s):  
Eunice Akello Mewa ◽  
Michael Wandayi Okoth ◽  
Catherine Nkirote Kunyanga ◽  
Musa Njue Rugiri
Keyword(s):  
Thin Layer ◽  
Sensory Quality ◽  
Moisture Diffusivity ◽  
Drying Kinetics ◽  
Effect Of Temperature ◽  
Slice Thickness ◽  
Drying Time ◽  
Drying Characteristics ◽  
Thin Layer Drying

The objective of the present study was to determine the drying kinetics, moisture diffusivity and sensory quality of convective air dried beef. The effect of temperature of drying (30-60°C) and thickness of samples (2.5-10 mm) on the convective thin-layer drying kinetics of beefdried in a cabinet dryer was evaluated. Five semi-theoretical models were fit to the drying experimentaldata with the aim of predicting drying characteristics of beef and fitting quality of models determined using the standard error of estimate (SEE)and coefficient of determination (R2). Determination ofeffective moisture diffusivity (Deff) from the experimental drying datawas done and sensory quality of the optimized dried cooked and uncookedbeef samplesevaluated. Drying time and rate of drying increased with an increasing temperature but decreased with increased slice thickness. However, there was overlapping of drying curves at 40-50°C. Among the selected models, Page model gave the best prediction of beef drying characteristics. Effective moisture diffusivity (Deff) ranged between 4.2337 x 10-11 and 5.5899 x 10-10 m2/s, increasing with an increase in air temperature and beef slice thickness.Of all the sensory parameters evaluated, texture was the only attribute that gave significantly different (P > 0.05) scores between the cooked and uncooked dried beef samples.

A Mathematical Model for Thin-Layer Drying of Litchi Pulp

2012 ◽  
Vol 192 ◽  
pp. 51-56
Author(s):  
Zhi Qiang Guan ◽  
Xiu Zhi Wang ◽  
Min Li ◽  
Xiao Qiang Jiang
Keyword(s):  
Experimental Data ◽  
Thin Layer ◽  
Heat Pump ◽  
Moisture Ratio ◽  
Drying Time ◽  
Page Model ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Heat Pump Drying ◽  
Predicted Values

A drying experiment of litchi pulp was done with a self-built heat-pump drying system. A few commonly-used thin-layer drying models for foods were linearized and fitted with the drying experimental data to select a relatively optimal model of depicting the relationship between moisture ratio and drying time of the heat-pump drying of litchi pulp. It was found that the Page model is relatively optimal. The multivariate linear regression approach was employed to solve for the parameters of the Page model based on experimental data and an experimental verification was conducted; the verification results show that the predicted values of the Page model have a good fitness with the measured values and thus the Page model can predict more accurately the moisture ratio and drying rate of litchi pulp in a heat-pump drying process.

Mathematical Modelling of Thin Layer Sun and Solar Drying of Cassava Chips

2010 ◽  
Vol 6 (6) ◽  
Author(s):  
Toyosi Y Tunde-Akintunde
Keyword(s):  
Thin Layer ◽  
Correlation Coefficients ◽  
Moisture Diffusivity ◽  
Solar Drying ◽  
Drying Time ◽  
Drying Characteristics ◽  
Page Model ◽  
Thin Layer Drying ◽  
Rate Period ◽  
Pretreatment Conditions

In this paper, the effect of sun and solar drying and pretreatment conditions (soaking in water; soaking in water and then blanching; blanching and then soaking) on the drying characteristics and kinetics of cassava chips were investigated. The drying time was shorter for samples pretreated by soaking only (SK) compared to the others. It was observed that pretreatment conditions and drying method significantly (P < 0.05) affected the drying rate. The drying for all experiments occurred in the falling rate period with no constant rate period. Four mathematical models were studied for the description thin layer drying characteristics of pretreated cassava chips. The models considered were the Henderson and Pabis, Newton, Logarithmic and the Page model. Comparing the correlation coefficients (R2), chi-square (c2) and root mean square error (RMSE) values of four models, it was observed that the highest values of R2 and lowest ?2 and RMSE were obtained using Page model. This shows that the Page model represents drying characteristics better than other models. The effective moisture diffusivity values were estimated from Fick’s diffusional model. These values obtained for solar dried samples were generally higher than those obtained for sun dried samples.

scholarly journals The Experimental Research of Drying Kinetics of Nagpur Orange Fruit (Citrus Sinesis- L) by Hot Air Electrical Dryer

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1131-1134
Keyword(s):  
Thin Layer ◽  
Drying Kinetics ◽  
Drying Time ◽  
Drying Characteristics ◽  
Drying Temperature ◽  
Hot Air ◽  
Thin Layer Drying ◽  
Drying Behavior ◽  
Orange Fruit ◽  
Kinetics Of

The study is aimed experimentally and compared with the theoretical results of drying kinetics of Nagpur orange fruit dried in a hot air electrical dryer. Orange fruit is highly perishable and needs to be consumed or processed immediately after harvest. Drying or dehydration is one of the most practical methods of preserving food products. Therefore, thin layer drying characteristics of falling rate of Nagpur orange are determined experimentally under different conditions of drying air temperatures, relative humidity and air velocities for different moisture contents. Thin layer models like Wang and Singh, Page and Henderson have been compared with Experimental results. The knowledge of drying kinetics helps for identification of exact drying time and air flow velocity for different moisture content. Here drying operation is carried out at a velocity of 1m/sec and 1.25 m/sec for different temperature of 55°C, 65°C and 75°C. This analysis reveals that drying temperature has a more significant effect on moisture removal while velocity has the least effect. Drying rate is found to increase with the increase in drying temperature and reduce with drying time. Experimental data is statistically correlated by plotting the drying characteristics curve. The analysis reveals that Wang and Singh's model is a better model to explain the drying behavior of Nagpur Orange fruit (R2=0.9888).

Thin-Layer Drying Characteristics of Fresh and Sun-Dried Buckwheat Hay

2021 ◽  
Vol 37 (4) ◽  
pp. 713-724
Author(s):  
Fuji Jian ◽  
Mehul Patil ◽  
Digvir S. Jayas ◽  
Jitendra Paliwal
Keyword(s):  
Activation Energy ◽  
Moisture Content ◽  
Thin Layer ◽  
Growth Time ◽  
List Type ◽  
Experimental Conditions ◽  
Drying Time ◽  
Drying Characteristics ◽  
Sun Drying ◽  
Thin Layer Drying

Highlights Thin-layer drying of fresh and sun-dried buckwheat hay was studied at 30°C to 180°C and 12.5% to 60% relative humidities. Buckwheat hay drying occurred in the falling-rate period. Partial sun-drying of the hay could reduce drying time by 50%. The D eff values of fresh flowers, leaves, and stems ranged from 1.4×10 -10 to 60×10 -10 m 2 /s. Abstract. Thin-layer drying characteristics of fresh and sun-dried buckwheat hay were studied at 30°C to 180°C, 12.5 to 60% relative humidities, and 0.2 m/s constant air velocity. The hay was harvested on three different times with a 10 to 12 d interval between the harvesting times. Half of the harvested hay was sun-dried on the field for 4 d (referred to as sun-dried hay). The drying behavior of flowers, leaves, and stems of the fresh and sun-dried hay was characterized. Moisture content of the fresh buckwheat flower was 0.777 to 1.633 (decimal dry basis), and fresh stems had a maximum moisture content of 5.64. Moisture content of the fresh hay decreased with the increase of growth time. Sun-drying on field could decrease more than half of the moisture content of the harvested fresh hay. Flowers, leaves, and stems needed varying drying times to reach their equilibrium moisture contents. The order of the drying time from the fastest to the slowest was flowers, leaves, then stems. Sun-dried and later harvested hay needed less drying time. The logarithmic model was the best fit for all drying processes of the flowers, leaves, and stems at different harvesting times and drying conditions. The effective moisture diffusivity of both fresh and sun-dried hay ranged from 1.4×10-10 to 60× 10-10 m2/s depending on different experimental conditions. The activation energy of the hay was from 21.08 to 33.85 kJ/mol. A power equation was the best equation to describe the drying constant of hay with their drying temperature. Keywords: Activation energy, Combination drying, Hay drying, Thin-layer drying, Water diffusivity.

Drying Characteristics of Soybean (Glycine Max) Using Continuous Drying and Intermittent Drying

2018 ◽  
Vol 14 (9-10) ◽  
Author(s):  
Hyeon W. Park ◽  
Won Y. Han ◽  
Won B. Yoon
Keyword(s):  
Activation Energy ◽  
Moisture Content ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Drying Time ◽  
Drying Characteristics ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Thin Layer Drying Models ◽  
Best Fit

AbstractThe effects of drying temperature by continuous and intermittent drying on the drying characteristics of soybean were determined in this study. Among the thin-layer drying models, the Midilli–Kucuk model showed the best fit (R2> 0.99) to describe the drying of soybean. At 300 min of the effective drying time, the moisture content of continuous drying at 35, 40, and 45 ºC were 9.38 (±0.00), 8.69 (±0.17), and 7.70 % (±0.48), respectively; while the moisture content of intermittent drying at 35, 40, and 45 ºC were 8.28 (±0.21), 7.31 (±0.41), and 6.97 % (±0.07), respectively. The image analysis method for detection of the crack in soybean demonstrated that at the target moisture content (7.7 %), cracked grain ratios with intermittent drying at 35, 40, and 45 ºC were reduced by 52.08, 27.59, and 18.24 %, respectively. With the effective drying time, the activation energy for intermittent drying (9.33 kJ/mol) was significantly lower than that value for continuous drying (21.23 kJ/mol).

scholarly journals Drying Kinetics of Sliced Pineapples in a Solar Conduction Dryer

2017 ◽  
Vol 7 (2) ◽  
pp. 14 ◽  
Author(s):  
Luqman Ebow Ibn Daud ◽  
Isaac Nyambe Simate
Keyword(s):  
Thin Layer ◽  
Average Moisture Content ◽  
Drying Time ◽  
Sun Drying ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Drying Model ◽  
Thin Layer Drying Models ◽  
Drying Curves ◽  
Kinetics Of

As a means of adding value to pineapple production and minimising post-harvest losses, sliced pineapples were dried using a Solar Conduction Dryer (SCD) and appropriate thin layer drying models to predict drying were developed whilst the performance of the SCD was also investigated. For the period of the experiment, ambient temperature and temperature in the dryer ranged from 24 to 37 °C and 25 to 46 ℃ respectively. The performance of the dryer was compared to open sun drying using pineapple slices of 3-5 mm in thickness where the slices were reduced from an average moisture content of 85.42 % (w.b.) to 12.23 % (w.b.) by the SCD and to 51.51 % (w.b.) by the open sun drying in 8 hours effective drying time. Pineapple slices of thicknesses 3 mm, 5 mm, 7 mm and 10 mm were simultaneously dried in the four drying chambers of the SCD and their drying curves simulated with twelve thin layer drying models. The Middilli model was found as the best fitted thin layer drying model for sliced pineapples. The optimum fraction of drying tray area that should be loaded with pineapples was also investigated by simultaneously loading 7 mm slices of pineapples at 50, 75, and 100 percent of drying tray area. Loading the slices at 50, 75 and 100 percent of drying tray area gave overall thermal efficiencies of 23, 32 and 44 percent, respectively, hence loading pineapple slices at 100 percent drying tray area was recommended as the best.

scholarly journals Some Aspects of the Modelling of Thin-Layer Drying of Sawdust

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 726
Author(s):  
Andrzej Bryś ◽  
Agnieszka Kaleta ◽  
Krzysztof Górnicki ◽  
Szymon Głowacki ◽  
Weronika Tulej ◽  
...  
Keyword(s):  
Theoretical Model ◽  
Thin Layer ◽  
Air Temperature ◽  
Mean Square ◽  
Drying Process ◽  
Airflow Velocity ◽  
Chi Square ◽  
Drying Characteristics ◽  
Thin Layer Drying ◽  
Drying Models

Drying of spruce, beech, willow, and alder sawdust was examined in a laboratory type dryer. The effect of drying air temperature T (25, 60, and 80 °C) and airflow velocity v (0.01, 0.15, and 1.5 m/s) was investigated. The obtained results demonstrated that drying air temperature and airflow velocity have impacts on the drying of sawdust. The experimental dehydration data of sawdust obtained were fitted to theoretical, semi-theoretical, and empirical thin-layer models. The accuracies of the models were estimated using the correlation coefficient (R), root mean square error (RMSE), and reduced chi-square (χ2). All models except the theoretical model of a sphere described the drying characteristics of sawdust satisfactorily. The effect of T and v on the parameters (constants and coefficients) of the drying models were determined. The effect, by the proposed equations, was also described. This work combines aspects of mechanical engineering and modelling of the drying process.

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