scholarly journals Modeling of thin layer drying characteristics of blanch-assisted water yam (Dioscorea alata) slices

2021 ◽  
Vol 13 (1) ◽  
pp. 43-50
Author(s):  
Adebimpe Fatimat Okeleye ◽  
Charles Taiwo Akanbi ◽  
Tunde Afolabi Morakinyo
Keyword(s):  
Thin Layer ◽  
Diffusion Model ◽  
Linear Regression Analysis ◽  
Moisture Diffusivity ◽  
Coefficient Of Determination ◽  
Model Parameters ◽  
Drying Characteristics ◽  
Thin Layer Drying ◽  
Best Fit ◽  
Water Yam

The thin layer drying characteristics of blanch-assisted water yam slices were investigated with respect to its un-blanched water yam slices in a convective hot air oven. The yam slices (diameter 4 cm; thickness 0.8 cm) were dried at temperatures 50, 60 and 70 °C, respectively with a constant air velocity of 0.13 m/s. The drying data obtained were fitted into six existing drying models: Page, Newton, Midilli, Henderson and Pabis, Logarithmic and Diffusion model. Non-linear regression analysis was used to determine the model parameters; the coefficient of determination (R2) and standard error of estimates (SEE) in order to determine the model best fit. The study showed that the drying process occurred in the falling rate drying period. The blanch-assisted slices had a faster drying rate than the un-blanched yam slices. Among the models, the diffusion model gave the overall best fit for the drying data obtained. The effective moisture diffusivity ranged from 3.18×10-8 to 4.47×10-8 m2/s for the blanch-assisted slices and from 4.73×10-8 to 7.33×10-8 m2/s for the un-blanched slices. The activation energies of the blanch-assisted and un-blanched yam slices were 15.5 kJ/mol and 20.1 kJ/mol, respectively. These processing conditions obtained for water yam flour would be suitable for its process design and control thereby enhancing its utilization and overall acceptability.

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.

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 Kinetika Pengeringan Lapisan Tipis Daun Jati Belanda (Thin Layer Drying Kinetics of Guazuma Ulmifolia Leaves)

2021 ◽  
Vol 8 (2) ◽  
pp. 53-62
Author(s):  
Hendri Syah ◽  
Armansyah Halomoan Tambunan ◽  
Edy Hartulistiyoso ◽  
Lamhot Parulian Manalu
Keyword(s):  
Mass Transfer ◽  
Thin Layer ◽  
Moisture Diffusivity ◽  
Drying Kinetics ◽  
Coefficient Of Determination ◽  
Convective Mass Transfer ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Guazuma Ulmifolia ◽  
Kinetics Of

The objectives of this study were to determine a suitable thin layer drying model to describe the drying kinetics of Guazuma ulmifolia leaves and determine the mass transfer parameters of Guazuma ulmifolia leaves. The drying of Guazuma ulmifolia leaves was conducted in a laboratory scale dryer with various temperature (40oC, 50oC, and 60oC) and relative humidity (30%, 40%, 50% and 60%). Five drying models, namely, Newton, Henderson and Pabis, Page, Midilli-Kucuk, and Verma et al. were fitted to the drying data. The drying curve of guazuma leaves did not show a constant drying period during the drying period. The models suitability were compared base on coefficient of determination (R2), root square mean errors (RSME), and reduced mean square of deviation (X2). It was found that, among the models evaluated, the Midilli and Kucuk model is the best to describe the drying kinetics of Guazuma ulmifolia leaves. The effective moisture diffusivity was found to be in the range of 10-13 – 10-12 m2/s and the convective mass transfer coefficient was in the range of 10-9 – 10-10 m/s. The activation energy value was found to be 89.21 kJ/mol.

scholarly journals Drying kinetics of dill leaves in a convective dryer

2013 ◽  
Vol 27 (1) ◽  
pp. 39-47 ◽  
Author(s):  
A. Motevali ◽  
S. Younji ◽  
R. Amiri Chayjan ◽  
N. Aghilinategh ◽  
A. Banakar
Keyword(s):  
Thin Layer ◽  
Back Propagation ◽  
Moisture Diffusivity ◽  
Moisture Ratio ◽  
Coefficient Of Determination ◽  
Feed Forward ◽  
Threshold Functions ◽  
Feed Forward Back Propagation ◽  
Thin Layer Drying ◽  
Drying Behavior

Abstract Thin layer drying characteristics of dill leaves under fixed, semi-fluidized, and fluidized bed conditions were studied at air temperatures of 30, 40, 50, and 60°C. In order to find a suitable drying curve, 12 thin layer-drying models were fitted to the experimental data of the moisture ratio. Among the applied mathematical models, the Midilli et al. model was the best for drying behavior prediction in thin layer drying of dill leaves. To obtain the optimum network for drying of dill leaves, various numbers of multilayer feed-forward neural networks were made and tested with different numbers of hidden layers and neurons. The best neural network feed-forward back-propagation topology for the prediction of drying of dill leaves (moisture ratio and drying rate) was the 3-45-2 structure with the training algorithm trainlm and threshold functions logsig and purelin. The coefficient of determination for this topology for training, validation, and testing patterns was 0.9998, 0.9981, and 0.9990, respectively. Effective moisture diffusivity of dill leaves during the drying process in different bed types was found to be in the range from 7.10 10-12 to 1.62 10-10 m2 s-1. Also, the values of activation energy were determined to be between 75.435 and 80.118 kJ mol-1

scholarly journals Mathematical modeling of thin layer drying characteristics and proximate analysis of turkey berry (Solanum torvum)

2021 ◽  
pp. 75-75
Author(s):  
Sekar Sivakumar Dana ◽  
Sekar Subramani ◽  
Valarmathi Thirumalai Natesan ◽  
Mudhu Marimuthu ◽  
Godwin Arockiaraj
Keyword(s):  
Thin Layer ◽  
Proximate Analysis ◽  
Coefficient Of Determination ◽  
Positive Sign ◽  
Passive Mode ◽  
Solanum Torvum ◽  
Drying Characteristics ◽  
Active Mode ◽  
Sun Drying ◽  
Thin Layer Drying

In the present work the drying characteristics and proximate analysis of turkey berry (Solanum torvum) were analyzed under open sun drying and greenhouse drying with two different glazing materials (UV Polyethylene sheet and Drip lock sheet) under passive and active modes. The drying rate under different modes of drying are 18.73g/h in drip lock greenhouse active mode,12.50 g/h in UV polyethylene sheet greenhouse active mode,15.22 g/hin drip lock sheet greenhouse passive mode, 11.84 g/h in UV polyethylene sheet greenhouse passive mode and 10.65 g/h in open sun drying. Twelve mathematical models were chosen to determine the drying characteristics of Turkey berry. From the statistical analysis it is found that Modified Henderson and Pabis model is the best drying model describing thin layer drying characteristics of turkey berry in both open sun drying and green house drying. The goodness of the fit achieved is based on the values of coefficient of determination(R2), sum square error(SSE), root mean square error(RMSE) and reduced chi square (?2).From the proximate analysis of dried turkey berry it is found that more amount of carbohydrate is retained in UV polyethylene greenhouse dryer under passive mode. In drip lock greenhouse dryer under passive mode the retention of vitamins such as protein, vitamin C and ash content showed a positive sign. In drip lock greenhouse dryer under active mode the retention of calcium, iron and dietary fibre is found to be high. Finally it is observed that more amounts of nutrients are retained in greenhouse drying than in open sun drying.

scholarly journals Influence of temperature and thickness on thin layer drying characteristics of onion (Allium cepa L.) varieties and rehydration capacity

2020 ◽  
Vol 12 (2) ◽  
pp. 165-176
Author(s):  
Sunday Samuel Sobowale ◽  
Oluwole Benjamin Omotoso ◽  
Yusuf Olamide Kewuyemi ◽  
Olawale Paul Olatidoye
Keyword(s):  
Thin Layer ◽  
Moisture Diffusivity ◽  
Quality Characteristics ◽  
Nonlinear Regression Analysis ◽  
Rehydration Ratio ◽  
Drying Characteristics ◽  
Allium Cepa L ◽  
Thin Layer Drying ◽  
Drying Models

Nonlinear regression analysis was conducted for thin layer drying characteristics of two onion varieties (white and red) and some quality characteristics were also examined. The experimental data obtained at drying temperatures of 40, 50, and 60 oC and thicknesses of 2, 4 and 6 mm, was subsequently fitted into four commonly used models (Henderson and Pabis, Lewis, Page, and logarithmic). Moisture diffusivity and activation energy ranged from 8.9 × 10-10 to 8.4 × 10-9 m2/s and 55.98 to 65.68 KJ/mol, respectively. Significant differences (p&lt;0.05) were observed in the colour profile and rehydration ratio. The optimum desirable colour was obtained at 50 oC with 2 mm thick onion slices and the observed higher rehydration ratio indicates good quality of dried onions. Among the four selected drying models, the Page model predicted optimally (R2&gt; 0.9) and was found to be better in describing dried onion varieties, while the Lewis model provided the least fit.

scholarly journals Thin layer mathematical modelling of white maize in a mobile solar-biomass hybrid dryer

2021 ◽  
Author(s):  
Joseph Oppong Akowuah ◽  
Ato Bart-Plange ◽  
Komla A. Dzisi
Keyword(s):  
Thin Layer ◽  
Type Equation ◽  
Moisture Diffusivity ◽  
Coefficient Of Determination ◽  
Drying Rate ◽  
Mean Square ◽  
Drying Time ◽  
Thin Layer Drying ◽  
Drying Behaviour ◽  
Kinetics Of

Performance of a tractor mounted solar-biomass hybrid dryer which utilise combined energy of solar and biomass was investigated. Drying behaviour of maize grains in the dryer was also investigated using 10 thin-layer mathematical models. The models were compared based on coefficient of determination (R<sup>2</sup>) and root mean square error (RMSE) values between experimental and predicted moisture ratios. Moisture content (MC) of grains in the dryer reduced from 19 ± 0.86% to 13 ± 0.4% (w.b.) in 5 h, compared to grains dried in open-sun which reached same MC in 15 hours. This resulted in average drying rate of 1.2 %·h<sup>–1</sup> compared to 0.4 %·h<sup>–1</sup> for grains dried in the open-sun leading to net savings in drying time of 67%. Overall mean temperature, 41.93 ± 2.7 °C in the dryer was 15.3 °C higher than the ambient temperature. Midilli Kucuk model was best to describe the thin-layer drying kinetics of maize in the dryer. It showed a good fit between the predicted and experimental data. The effective moisture diffusivity of grains dried in the dryer ranged between 1.45 × 10<sup>–11</sup> m<sup>2</sup>·s<sup>–1</sup> – 3.10 × 10<sup>–11</sup> m<sup>2</sup>·s<sup>–1</sup>. An activation energy of 96.83 kJ·mol<sup>–1</sup> was determined based on the Arrhenius-type equation.

scholarly journals INFRARED DRYING OF APRICOT POMACE

2019 ◽  
Vol 49 (4) ◽  
pp. 213-218
Author(s):  
Seda Kayran ◽  
Íbrahim Doymaz
Keyword(s):  
Type Equation ◽  
Moisture Diffusivity ◽  
Coefficient Of Determination ◽  
Chi Square ◽  
Drying Characteristics ◽  
Infrared Drying ◽  
Thin Layer Drying ◽  
Apricot Pomace ◽  
Drying Conditions ◽  
Kinetics Of

Effect of infrared powers (62, 74, 88, 104 and 125 W) on drying kinetics of apricot pomace was investigated. It is observed that drying characteristics of apricot pomace were greatly influenced by infrared power. Henderson and Pabis model was investigated for describing thin-layer drying of apricot pomace. The model because of the high coefficient of determination (R2) as well as the lowest reduced chi-square (c2) and root mean square error (RMSE) values adequately described the experimental data of apple pomace drying. Effective moisture diffusivity (Deff) values were increased by increasing infrared power and changed between 1.67×10-9 and 6.03×10-9 m2/s. Activation energy was estimated by a modified Arrhenius type equation and found to be 2.32 kW/kg. The colour results were affected by drying conditions.

scholarly journals Estimating the Drying Kinetics and Effective Moisture Diffusivity of Fresh Water Prawn (Macrobrachium rosenbergii)

2021 ◽  
pp. 40-48
Author(s):  
Egbe E. W. ◽  
Davies R. M.
Keyword(s):  
Thin Layer ◽  
Fresh Water ◽  
Initial Moisture Content ◽  
Macrobrachium Rosenbergii ◽  
Moisture Diffusivity ◽  
Drying Kinetics ◽  
Effective Moisture Diffusivity ◽  
Coefficient Of Determination ◽  
Effective Moisture ◽  
Thin Layer Drying

Fresh-water prawn (Macrobrachium rosenbergii) once harvested, tends to deteriorate rapidly because of the high systemic moisture it constituent which has lead to post-harvest losses, drying as a method of preservation widely used for high moisture bio-products reduces moisture probably to bone-dry level and thereby increased the shelf-life of the fresh-water prawn. Therefore, Estimating the Drying Kinetics and Effective Moisture Diffusivity of Fresh Water Prawn (Macrobrachium rosenbergii) was investigated using a laboratory convective oven dryer and was arranged in a thin layer. 50-100°C temperatures were applied, varying on multiple of 10°C. It was observed that the drying rate increased with increasing drying temperatures. Drying data obtained were fitted into four empirical thin-layer drying models, and the best model was investigated after undergoing statistical parameters (of coefficient of determination, R2; root mean square error, RMSE and reduced chi-square, χ2). The ANN and Henderson model was found to perform satisfactorily in describing the drying behaviour of the Fresh-water prawn samples at the chosen temperature levels. The initial moisture content of all the samples was 54% wb. The final effective moisture diffusivity of the samples during the drying experiments ranges from 1.26 x 10-7m2/s - 7.06 x 10-7m2/s, and the temperature related activation energy of diffusion was found to be 12.82-kJ/mol. Drying occurred mainly in the falling rate period, and the characterizing drying curves were exponential with increase in drying temperatures.

scholarly journals Evaluation of the Dehydration Characteristics of Ginger (Zingiber Officinale) Root Slices Using Refractance Window Drying Technology

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Akinjide A Akinola ◽  
Osarhiemhen Azeta ◽  
Stanley N Ezeorah
Keyword(s):  
Moisture Content ◽  
Thin Layer ◽  
Zingiber Officinale ◽  
Moisture Diffusivity ◽  
Coefficient Of Determination ◽  
Plastic Film ◽  
Layer Model ◽  
Drying Characteristics ◽  
Drying Kinetic ◽  
Drying Technology

This study investigates the drying characteristics of ginger (zingiber officinale) root slices using the Refractance Window™ drying technology. A laboratory-scale dryer was constructed by modifying a water bath. 3 mm thick ginger root slices were dried on the transparent Mylar PET plastic film that covered the bath, and the variation of the moisture content of the slices with time was determined as the drying progressed. A water temperature of 60 oC was maintained beneath the plastic film. Various drying kinetic data curves are plotted from the drying data and the thin layer model that best fits the drying data was determined. Observations indicated that the ginger root slices dried to a moisture content of 0.1g H2O/g solid on a dry basis in about 210 minutes. The regression analysis results showed that the Haghi and Ghanadzadeh thin layer model best describes the drying data for 3 mm sized slices with the coefficient of determination (  ) value of 0.9985. An effective moisture diffusivity of 8.99 x 10-8 m2/s was observed for the ginger root slices.

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