Evaluation of thin-layer drying models for describing drying kinetics of figs (Ficus carica)

Babalis, Stamatios J.; Papanicolaou, E.; Κyriakis, Ν.; Belessiotis, V.

doi:10.1016/j.jfoodeng.2005.04.008

Cited by 190 publications

(105 citation statements)

References 32 publications

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“…Similar trend has also been reported by other researchers related to agricultural materials undergoing analogous drying conditions. For example 2.25 -7.29 × 10 −10 m 2 /s for Pepino (Uribe et al 2011), 1.47 × 10 −10 -2.19 × 10 −9 m 2 /s for black grapes (Togrul 2010), 0.776−9.335 × 10 −9 m 2 /s for Carrot (Doymaz 2004), 7.46 × 10 −11 to 1.87 × 10 −10 m 2 /s for cocoa (Hii et al 2009), 8.4×10 −10 -1.13 × 10 −9 m 2 /s for figs (Babalis et al 2006), 1.7 -3.31 × 10 −11 m 2 /s (Duc et al 2011). The values of effective diffusivities estimated in the present work lie within the general range of 10 −11 -10 −9 m 2 /s for food materials.…”

Section: Effect Of Temperature and Velocity On Effective Moisture Difmentioning

confidence: 96%

“…Therefore, hot air drying is a cost effective method of drying which provides uniformity and hygiene, and is inevitable for food drying process (Diamante and Munro 1993;Doymaz and Pala 2002). Several studies have been carried out by researchers to investigate the convective hot air drying characteristics of the fruits and vegetables: apple (Sacilik and Elicin 2006), carrot (Doymaz 2004), red pepper (Doymaz and Pala 2002), banana (Karim and Hawlader 2005), kiwi fruit (Simal et al 2005), black grapes (Togrul 2010), eggplant (Ertekın andYaldız 2004), figs (Babalis et al 2006) and sweet potato (Diamante and Munro 1993). There is no literature available on hot air drying behavior of mango ginger in spite of its high medicinal and food value even though research work has been reported on microwave drying of mango ginger by the present authors (Krishna Murthy and Manohar 2012).…”

Section: Introductionmentioning

confidence: 99%

“…The theoretical models suggest that the moisture transport is controlled mainly by internal moisture mechanism and needs assumption of geometry of the food material, mass diffusivity and heat conductivity. The most widely investigated theoretical drying model is Fick's second law of diffusion (Babalis et al 2006). Semi theoretical models and empirical models consider only the external resistance to the moisture transport and are valid only in the specific range of temperature, air velocity and humidity for which they were developed (Ozdemir and Devres 1999).…”

Section: Introductionmentioning

confidence: 99%

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Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network

Murthy

Manohar

2013

J Food Sci Technol

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Mango ginger (Curcuma amada) was dried in a through-flow dryer system at different temperatures (40-70°C) and air velocities (0.84 -2.25 m/s) to determine the effect of drying on drying rate and effective diffusivity. As the temperature and air velocity increased, drying time significantly decreased. Among the ten different thin layer drying models considered to determine the kinetic drying parameters, semi empirical Midilli et al., model gave the best fit for all drying conditions. Effective moisture diffusivity varied from 3.7 × 10 −10 m 2 /s to 12.5 × 10 −10 m 2 /s over the temperature and air velocity range of study. Effective moisture diffusivity regressed well with Arrhenius model and activation energy of the model was found to be 32.6 kJ/mol. Artificial neural network modeling was also employed to predict the drying behaviour and found suitable to describe the drying kinetics with very high correlation coefficient of 0.998.

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Section: Effect Of Temperature and Velocity On Effective Moisture Difmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network

Murthy

Manohar

2013

J Food Sci Technol

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“…Thus, the definition of accurate mathematical models is necessary to simulate the drying kinetics of biological materials. Simulation models of the drying process are used for designing new drying systems, improving the existing systems, predicting the air flow over the product, and even for controlling the process (Xia & Sun 2002;Babalis et al 2006). Recently, Supported by the University of Tehran, Iran. many literature data have been published by several researches covering mathematical modelling of food products drying using laboratory dryers (Ozdemir & Devres 1999;Doymaz 2004;Ertekin & Yaldiz 2004;Sacilik & Unal 2005;Menges & Ertekin 2006;Celma et al 2007;Kashaninejad et al 2007;Jokić et al 2009;Gazor & Mohsenimanesh 2010), but little information is available on mathematical modelling food products of drying in industrial or semi-industrial dryers.…”

mentioning

confidence: 99%

Modelling the carrot thin-layer drying in a semi-industrial continuous band dryer

Aghbashlo¹,

Kianmehr²,

Arabhosseini³

et al. 2011

Czech J. Food Sci.

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Aghbashlo M., Kianmehr M.H., Arabhosseini A., Nazghelichi T. (2011): Modelling the carrot thin-layer drying in a semi-industrial continuous band dryer. Czech J. Food Sci., 29: 528-538. This paper presents a mathematical modelling of the drying process in a semi-industrial continuous band dryer. Carrot slices with the thickness of 5 mm were used for the drying experiments. The experiments were conducted at three air temperatures, 50, 60, and 70°C, three air velocities, 0.5, 1.0, and 1.5 m/s, and three chain linear velocities, 2.38 × 10 -4 , 2.78 × 10 -4 , and 3.33 × 10 -4 m/s with three replications for each treatment. The Lewis, Henderson & Pabis, and Page models were fitted to the experimental data of the moisture ratio against the sample position using nonlinear regression analysis by MATLAB computer program. The models were compared based on their coefficients of determination (r 2 ), root mean square errors (RMSE), and reduced chi-squares (χ 2 ) between the experimental and predicted moisture ratios. Consequently, the Page model was selected as the best mathematical model for describing the drying kinetics of the carrot slices. The correlations of the Page model constants k and m with the variables T, U a and U c were determined. The effective moisture diffusivity varied from 3.21 × 10 -7 to 8.98 × 10 -7 m 2 /s. The energy of activation varied from 23.02 kJ/mol to 28.1 kJ/mol using Arrhenius type equation.

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“…Babalis et al (2006) observaram o efeito da temperatura na secagem de figos nas temperaturas de 55-85 °C e velocidade do ar de 0,5-3,0 m s -1 e concluíram que o aumento da taxa de secagem com o aumento da temperatura é uma tendência amplamente verificada para a maioria dos produtos. Carlesso et al (2005) realizaram um experimento com secagem de sementes de maracujá em camada delgada utilizando um protótipo de secador de leito fixo, com três níveis de temperatura do ar de secagem (30, 37 e 40 °C) e três níveis de fluxo de ar para secagem (24, 48 e 71 m³ min -1 m²) e constataram que o tempo de secagem diminuiu em função do aumento da temperatura porém não houve influência da vazão específica do ar de secagem.…”

Section: Tabela 3 Dados Do Enriquecimento Proteico Do Resíduo Do Abaunclassified

Cinética de secagem do resíduo de abacaxi enriquecido

Alexandre¹,

Silva

Gomes³

et al. 2013

Rev. bras. eng. agríc. ambient.

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RESUMOO Brasil é um dos maiores produtores de abacaxi do mundo e o maior da América do Sul. O fruto é a parte comercializável da planta enquanto o restante é formado por caule, folha, casca, coroa e talos, considerado resíduo agrícola e não tem sido devidamente aproveitado, resultando em perdas econômicas. Caracterizar e avaliar a cinética de secagem do resíduo (casca) de abacaxi (Ananas comosus L.) enriquecido utilizando a levedura Saccharomyces cerevisiae em leito estático, em camada fina de secagem, utilizando-se de planejamento experimental fatorial, foi o objetivo deste estudo. A temperatura (40 a 60 ºC) e a velocidade do ar de secagem (0,8 a 1,3 m s -1 ) são as variáveis do processo. O resíduo enriquecido e caracterizado apresentou alto teor de matéria seca (90,27%) e elevado teor de proteína (20,21%) em relação ao resíduo in natura (7,61%). A cinética de secagem ocorreu no período de taxa decrescente. Os modelos Page, Henderson & Pabis e Lewis, ajustaram os dados experimentais satisfatoriamente, sendo Page discretamente superior aos demais. Verificou-se influência da variável temperatura apenas para a variável resposta umidade, não sendo observada influência estatisticamente significativa da velocidade do ar de secagem. Palavras-chave: Ananas comosus L., Saccharomyces cerevisiae, secagemDrying kinetics of enriched pineapple residue ABSTRACT Brazil is the largest producer of pineapple (Ananas comosus L.) in South America and one of the largest in the world. The fruit is the marketable part of the plant, while the rest formed by stem, leaves, peel, crowns and shafts is considered as agricultural residue and is not properly used, resulting in economic loss. The aim of this study was to characterize and to evaluate the drying kinetics of enriched pineapple residue (peel) using Saccharomyces cerevisiae yeast in static bed in fine layer, using of experimental factorial planning. The temperature (40 to 60 °C) and the wind speed (0.8 to 1.3 m s -1 ) were the process variables. The characterized enriched residue exhibited a high dry matter content (90.27%) and a high protein content (20.21%) in relation to fresh residue (7.61%). The drying kinetics occurred in falling rate period. The Page, Henderson & Lewis and Pabis models adjusted satisfactorily to experimental data, being the Page model slightly superior to the others. Influence of the temperature variable was verified only for the moisture response variable, while no significant influence of the wind speed of drying was observed.

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Evaluation of thin-layer drying models for describing drying kinetics of figs (Ficus carica)

Cited by 190 publications

References 32 publications

Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network

Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network

Modelling the carrot thin-layer drying in a semi-industrial continuous band dryer

Cinética de secagem do resíduo de abacaxi enriquecido

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