scholarly journals Study on Thin Layer Drying of <i>Rosa laevigata</i> Michx

Engineering ◽  
2013 ◽  
Vol 05 (01) ◽  
pp. 16-21 ◽  
Author(s):  
Bing Lin ◽  
Ying Wang ◽  
Ying Zhou ◽  
Zhi Zhao
Keyword(s):  
Thin Layer ◽  
Thin Layer Drying ◽  
Rosa Laevigata

MATHEMATICAL MODELING OF THIN LAYER DRYING OF CANOLA PODS

2012 ◽  
Vol 3 (2) ◽  
pp. 297-312
Author(s):  
A. M. Matouk ◽  
H. N. Abd El-Mageed ◽  
A. Tharwat ◽  
S. E. El-Far
Keyword(s):  
Mathematical Modeling ◽  
Thin Layer ◽  
Thin Layer Drying

Studies on thin layer drying of bagasse

2007 ◽  
Vol 31 (4) ◽  
pp. 422-437 ◽  
Author(s):  
B. Vijayaraj ◽  
R. Saravanan ◽  
S. Renganarayanan
Keyword(s):  
Thin Layer ◽  
Thin Layer Drying

Optimization of a thin layer drying process for coroba slices

2008 ◽  
Vol 85 (3) ◽  
pp. 372-380 ◽  
Author(s):  
Otoniel Corzo ◽  
Nelson Bracho ◽  
Alberto Vásquez ◽  
Angel Pereira
Keyword(s):  
Thin Layer ◽  
Drying Process ◽  
Thin Layer Drying

Evaluation of the mass transfer process on thin layer drying of papaya seeds from the perspective of diffusive models

2017 ◽  
Vol 54 (2) ◽  
pp. 463-471
Author(s):  
Guilherme Luiz Dotto ◽  
Lucas Meili ◽  
Eduardo Hiromitsu Tanabe ◽  
Daniel Padoin Chielle ◽  
Marcos Flávio Pinto Moreira
Keyword(s):  
Mass Transfer ◽  
Thin Layer ◽  
Transfer Process ◽  
Mass Transfer Process ◽  
Thin Layer Drying ◽  
Papaya Seeds

scholarly journals Thin layer drying of zucchini in solar dryer located in Osmaniye region

2018 ◽  
Vol 12 (2) ◽  
pp. 79-85 ◽  
Author(s):  
Kamil Neyfel Çerçi ◽  
Özge Sufer
Keyword(s):  
Thin Layer ◽  
Linear Regression Analysis ◽  
Chi Square ◽  
Mathematical Expressions ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Drying System ◽  
Thin Layer Drying Models ◽  
Dehydration Behavior ◽  
And Diffusion

In this study, the dehydration behavior of zucchini using solar assisted drying system was examined according to 22 thin layer drying models available in literature. The correlation coefficient (R2), chi-square (χ2) and root mean square error (RMSE) values were calculated to check the suitability of models by non-linear regression analysis. It was found that Cubic and Modified Midilli-1 models were the most suitable equations and their R2 values were calculated as 0.99963. χ2 and RMSE values of related mathematical expressions were 1.89343×10‒5, 1.91692×10‒5 and 0.01685×10‒3, 0.01721×10‒3 respectively. In addition, heat transfer, mass transfer and diffusion coefficients, which were important parameters in design of drying systems were also determined as 5.18124 W/m2°C, 1.57129×10‒7 m/s and 2.335718×10‒9 m2/s respectively.

scholarly journals Suitable model for thin-layer drying of root vegetables and onion

2020 ◽  
Vol 1 (34) ◽  
pp. 79-86 ◽  
Author(s):  
Krzysztof Górnicki ◽  
Agnieszka Kaleta ◽  
Aneta Choińska
Keyword(s):  
Thin Layer ◽  
Suitable Model ◽  
Thin Layer Drying ◽  
Root Vegetables

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.

scholarly journals Thin-layer mathematical modeling of apple slices drying, using open sun and cabinet solar drying methods

2021 ◽  
Vol 4 (2) ◽  
pp. 43-52
Author(s):  
Abdul Wasim Noori ◽  
Mohammad Jafar Royen ◽  
Juma Haydary
Keyword(s):  
Thin Layer ◽  
Mathematical Models ◽  
Water Activity ◽  
Model Fitting ◽  
Coefficient Of Determination ◽  
Drying Methods ◽  
Solar Drying ◽  
Drying Time ◽  
Climate Conditions ◽  
Thin Layer Drying

This paper aims to investigate the effect of climate conditions such as ambient temperature, humidity, pressure, sun radiation and pollution on sliced apples quality and drying time which are dried in an indirect forced cabinet solar drying (IFCSD) and open sun drying (OSD) systems. Both experiments were implemented at same place (Kabul, Afghanistan) and time. The IFCSD yield for saving time is 42.8 % which is more effective than drying in the OSD system. Simultaneously with the decreasing of sliced apple weight from 512.9 g down to 73.9 g, the water activity decreased from 0.955 down to 0.355 in the IFCSD system. For OSD system, the sample weight decreased from 512.6 g down to 78.4 g and its water activity from 0.955 down to 0.411. On the experiment day the average sun radiation was 571 w/m2 . The pressure drop between inlet and outlet of the dryer was 0.1 kPa. Different thin-layer mathematical models were investigated to identify the best model fitting the experimental data. The mathematical models’ performances were investigated by comparing the coefficient of determination (R 2 ), reduced chi-square (X2 ) and root mean square error (RMSE) coefficients. From all 11 applied thin-layer drying models the Page, Approximation diffusion, Verma et al and Midilli and Kacuk models are more fitted to our data.

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.

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