Study of three-stage intermittent drying of pears considering shrinkage and variable diffusion coefficient

Silva, Vítor; Costa, J.J.; Figueiredo, A.R.; Nunes, J.P. Pereira; Nunes, Catarina; Ribeiro, Tânia Bragança; Pereira, Bárbara

doi:10.1016/j.jfoodeng.2016.02.013

Cited by 30 publications

(29 citation statements)

References 32 publications

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“…The AVGS have a lower thickness while compared with corresponded values for their length and width, hence, taking a slice as an infinite slab is an accurate approximation. Analytical solution of the drying equation for an infinite slab was defined in Equation (6): (Agnihotri, Jantwal, & Joshi, ; Doymaz, ; Silva et al, )

\ln M . R . = \ln ((), \frac{8}{π^{2}}) - ((), \frac{π^{2} D_{eff} t}{L^{2}})

…”

Section: Methodsmentioning

confidence: 99%

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Kinetics and mathematical modeling of thin layer drying of osmo‐treated Aloe vera (Aloe barbadensis) gel slices

Moradi

Niakousari

Khaneghah

2019

J Food Process Engineering

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In the present work, the drying kinetics of osmo‐pretreated Aloe vera gel slices (AVGS) was investigated. AVGS with an initial moisture content of 98.29% (wet basis) were subjected to 5 hr of osmosis process (10% NaCl solution, at 40°C, NaCl solution to A. vera ratio = 5:1), prior to atmospheric thin layer drying at air temperatures of 55, 70, and 85°C and air volumetric air flow rates of 0.015, 0.036, and 0.054 m3/s for the duration of 160 min. Results showed the mean values of the moisture ratio in air temperatures of 55, 70, and 85°C were categorized into three levels (p < .01) of 0.551, 0.429, and 0.336, respectively, while the corresponding values for the osmo‐convective method were 0.561, 0.418, and 0.321, respectively. Similarly, the mean values of the moisture ratio in air flow rates of 0.015, 0.036, and 0.054 m3/s for the convective and osmo‐convective method assigned to different levels (p < .01) of 0.511, 0.417, 0.385 and 0.510, 0.416, 0.372, respectively. Superposition technique was utilized to propose a new model for each drying method. The predicted moisture ratios evaluated by the superposition technique were in a good agreement with experimental values of moisture ratio. Practical Applications In the current investigation, a superposition technique was utilized to propose a new model for two drying methods (osmo‐convective and convective). Subsequently, an equation describing the drying process for each method was derived. This technique while being a simple model, delivers high accuracy data for all influencing parameters in the drying process.

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\ln M . R . = \ln ((), \frac{8}{π^{2}}) - ((), \frac{π^{2} D_{eff} t}{L^{2}})

…”

Section: Methodsmentioning

confidence: 99%

“…An AVGS before and after the drying process has been shown in (6): (Agnihotri, Jantwal, & Joshi, 2017;Doymaz, 2012;Silva et al, 2016) ln M:…”

Section: Materials and Proceduresmentioning

confidence: 99%

Kinetics and mathematical modeling of thin layer drying of osmo‐treated Aloe vera (Aloe barbadensis) gel slices

Moradi

Niakousari

Khaneghah

2019

J Food Process Engineering

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“…Armut kurutma ve kuruma davranışlarının işlem özellikleri ile ilgili bazı çalışmalar yayınlanmıştır. Farklı armut türleri için [19], armut dilimleri için [20][21][22], osmotik-dehidrasyon ön işlemi uyguladıktan sonra [23,24], sitrik asit ile muamele ederek [21], kuruma sırasında meydana gelen büzülmeyi dikkate alarak [25,26] kurutma yapıldığı gibi, güneş enerjili kurutucularda kurutma [25], laboratuvar tipi konvekif kurutucularda kurutma [20,21] ve kesikli kurutma tekniği kullanılması [27] gibi farklı çalışmalar literatürde mevcuttur. Bu çalışmaların bazılarında kuruma sürecini açıklayan tek tabaka kuruma modelleri de tanımlanmışlardır [28].…”

Section: Gi̇ri̇ş (Introduction)unclassified

Farklı ön işlem uygulanan Ahlatın kuruma ve büzülme davranışının modellenmesi

Toğrul

Çelebi

Toğrul

2018

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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Highlights:Graphical/ Tabular Abstract  The effect of pretreatment and temperature on Ahlat drying  Modeling of drying and shrinkage behavior for non-researched Ahlat before  Calculation of the Diffusion Coefficient for the case where the diameter change is taken into account and not taken Model Adı Model Model Adı Model Newton MR=exp(-k.t) Rahman D/Do=1-a.(M-Mo) Page MR=exp(-k.tn) Ratti D/Do=a+b.(M/Mo) Henderson ve Pabis MR=a.exp(-k.t) Mayor ve Sereno D/Do= a.exp(b.M/Mo) Logaritmik MR=a.exp(-k.t)+c Correa ve ark. D/Do=1/(a+b.ln(M/Mo)) Midilli MR=a.exp(-k.t)n+c.t Hatamipour ve Mowla D/Do=a.ln(M)+b Kilpatrick, Lowe, and Van Ardsel D/Do=(M+a)/(Mo+a) Table A. Selected drying and shrinkage models Purpose: In this study, Ahlat (pyrus eleagrifolia) known as wild pear, was dried for four various drying temperatures (45-75 o C) in laboratory type dryer with and without pre-treatment. Theory and Methods: The pre-treatment solutions such as %65 maltose, sucrose, glucose, maltodekstrin, sorbitol and %55 sucrose-%10 salt %5 Na2SO5, %2 EO %5 Na2SO5, %5 K2SO5 and %2 EO %5K2SO5 was used in experiments. Dimensionless moisture content vs. drying time and drying rate vs. moisture content were investigated during drying Ahlat. Exchange of dimensionless moisture content vs time of ahlat was modelled by five model commonly used in literature. Shrinkage during drying Ahlat was investigated six models in literature. Models coefficients were tested in significance level p<0,05. The convenience between models and measured values was investigated by determination coefficient (R 2 ) and reduced chi square ( 2 ).Drying and shrinkage Models given in Table A were used for Ahlat drying. Results:Diffusion coefficients, characteristic transport coefficient for falling drying rate period, were determined with and without considering shrinkage for the whole drying temperatures and pre-treatments. There were obtained lower diffusion coefficients and lower activation energy by considering shrinkage. Conclusion:It was seen that the logarithmic model for non-pre-treatment, maltose, glucose, sucrose, sucrose-salt, %5 Na2S2O5, %2 EO %5 Na2S2O5 and %5 K2S2O5 pre-treatment and Newton model for sorbitol, maltodekstrin ve %2 EO %5K2S2O5 pre-treatment were convenient for drying Ahlat. It was seen that linear and exponential models were convenient the other models for explaining shrinkage.

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“…The drying of pears has been studied for some researchers (Guiné, ; Guiné, Rodrigues, & Figueiredo, ; Mrad, Boudhrioua, Kechaou, Courtois, & Bonazzi, ; Silva, Figueiredo, Costa, & Guiné, ; Silva et al, ). Guiné () studied the drying kinetics of some varieties of pears.…”

Section: Introductionmentioning

confidence: 99%

“…In other work, Guiné et al () studied a diffusion based model to represent the drying behavior of pears in a continuous convective drier. Silva et al () studied the drying of pears considering shrinkage and variable diffusion coefficient. Also, Silva et al () performed an experimental and mathematical study of the discontinuous drying kinetics of pears.…”

Section: Introductionmentioning

confidence: 99%

Diffusive‐convective model considering the shrinkage applied for drying of pears (pyrus spp.)

Dotto

Souza

Simões

et al. 2016

J Food Process Engineering

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In this work, a diffusive‐convective model with and without external resistance was applied to examine in detail the drying of pears (Pyrus spp.). The model was based on differential partial equations to represent the moisture content and temperature profiles along the operation. These equations were solved by the orthogonal collocation method. The drying experiments were performed with pear slices, under conditions of natural and forced air convection, at 40 and 80 °C. It was found that the diffusive‐convective model was able to predict the experimental profiles of moisture content and temperature during the pears drying. The effective mass diffusivity was two orders of magnitude higher, for the model with external resistance. The external mass transfer resistance should be considered into the model for low values of Biot number (BiM < 0.05). Also, it was verified a low sensibility of the predicted moisture content and temperature, regarding to the effective mass diffusivity (DEF) and effective thermal conductivity (kEF). Practical Applications The diffusive‐convective model with shrinkage provides a realistic and physical interpretation of the drying operation. So, this model can be applied in several cases where the shrinkage phenomena occur. Using this model, the correct time necessary to reduce the moisture content of the material, from the initial value to the commercial value, can be precisely predicted. In this way, it is possible to save energy in the drying operation.

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Study of three-stage intermittent drying of pears considering shrinkage and variable diffusion coefficient

Cited by 30 publications

References 32 publications

Kinetics and mathematical modeling of thin layer drying of osmo‐treated Aloe vera (Aloe barbadensis) gel slices

Kinetics and mathematical modeling of thin layer drying of osmo‐treated Aloe vera (Aloe barbadensis) gel slices

Farklı ön işlem uygulanan Ahlatın kuruma ve büzülme davranışının modellenmesi

Diffusive‐convective model considering the shrinkage applied for drying of pears (pyrus spp.)

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