Neural network modeling of sorption isotherms of longan (Dimocarpus longan Lour.)

Janjai, Serm; Intawee, P.; Tohsing, K.; Mahayothee, Busarakorn; Bala, B. K.; Ashraf, M. Arif; Müller, Joachim

doi:10.1016/j.compag.2009.02.003

Cited by 26 publications

(18 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Em relação à energia livre de Gibbs, essa pode ser um indicativo da afinidade do sorvente com a água e estabelecer um critério de espontaneidade de sorção da molécula de água (TELIS et al, 2000). Trabalhos que aplicam essa teoria podem ser encontrados em Janjai et al (2009), Telis et al (2000), Moraes et al (2008), Simal et al (2007), entre outros.…”

Section: Introductionunclassified

Isotermas de dessorção de pimentão verde e energia envolvida no processo

Alves

Fóz

Nicoleti

2015

Braz. J. Food Technol.

View full text Add to dashboard Cite

Isotermas de dessorção de pimentão verde e energia envolvida no processo Desorption isotherms of green bell peppers and the energy involved in the process*Autor Correspondente | Corresponding Author Recebido: Out. 01, 2014 Aprovado: Maio 18, 2015 ResumoEste trabalho teve como objetivos a obtenção das isotermas de dessorção do pimentão verde e a avaliação das propriedades termodinâmicas de sorção do fruto. As isotermas foram obtidas em função da temperatura (30°C, 40°C, 50°C e 60°C) em umidades relativas entre 4,0-90,0%. Os dados experimentais foram ajustados aos modelos matemáticos GAB, BET, Halsey, Henderson e Oswin para se descrever seu comportamento. Os resultados demonstram que o modelo de GAB descreveu com maior precisão as isotermas de dessorção do pimentão verde entre as faixas de atividade de água (a w ) selecionadas, em uma temperatura fixa. O calor isostérico de sorção (q st ) pôde ser determinado a partir de dados de sorção de umidade utilizando-se a derivada da equação de Clasius-Clapeyron, obtendo-se então o calor envolvido no processo de dessorção de umidade do pimentão verde fresco. A teoria da compensação entalpia-entropia ou isocinética foi aplicada aos dados experimentais, sugerindo que o processo de dessorção é conduzido pela entalpia. Palavras-chave: Calor isostérico; Secagem; Modelo de GAB; Compensação Entálpica-Entrópica. SummaryThis study aimed to obtain the desorption isotherms of green bell peppers and evaluate the thermodynamic properties of the moisture sorption of the fruit. The isotherms were obtained as a function of temperature (30°C, 40°C, 50°C and 60 °C) between 4.0 and 90.0% of relative humidity. The experimental data were fitted to the GAB, BET, Halsey, Henderson and Oswin mathematical models to describe their behaviour. The results showed that the GAB model described the sorption isotherms of green bell peppers with greater accuracy in the range of water activities (aw) selected, at a fixed temperature. The isosteric sorption heat (qst) could be determined from the moisture sorption data using the derivative of the Clasius-Clapeyron equation, to obtain the heat involved in the desorption process of the moisture of fresh green bell peppers. The enthalpy-entropy compensation or isokinetic theory was applied to the experimental data and suggested that the desorption process was driven by enthalpy.

show abstract

Section: Introductionunclassified

Isotermas de dessorção de pimentão verde e energia envolvida no processo

Alves

Fóz

Nicoleti

2015

Braz. J. Food Technol.

View full text Add to dashboard Cite

show abstract

“…Several studies have been reported ANN on modeling of drying (Bala et al, 2005;Movagharnejad and Nikzad, 2007;Poonnoy et al, 2007;Lertworasirikul and Tipsuwan, 2008) and thermal processing (Sablani et al, 1995). ANN technique has also been applied for modeling of water sorption isotherms of black tea, (Panchariya et al, 2002), longan (Janjai et al, 2009), raisin (Amiri Chijan and Esna-Ashari, 2010) and corn starch (Peng et al, 2007). In these researches the ANN models were found to be comparable or better than other mathematical models.…”

Section: Introductionmentioning

confidence: 93%

“…3). MLP was used for prediction of sorption isotherms of longan, raisin, and corn starch by some researchers (Janjai et al, 2009;Amiri Chijan and Esna-Ashari, 2010;Peng et al, 2007). Activation function for first and fourth layers was linear (Eq.…”

Section: Sorption Curves and Mathematical Modelsmentioning

confidence: 99%

Adsorption Isotherms for Red Onion Slices Using Empirical and Neural Network Models

Gazor¹,

Eyvani²

2011

International Journal of Food Engineering

View full text Add to dashboard Cite

Moisture sorption isotherms of red onion slices were determined at 30, 40, 50, and 60°C using the standard gravimetric static method over a range of relative humidity from 0.11 to 0.83. The experimental sorption curves were fitted by seven empirical equations: modified Henderson, modified Chung-Pfost, modified Halsey, modified Oswin, modified Smith, modified BET, and GAB. Also three types of Artificial neural network models: linear, multilayer perceptron, and radial basis function were tested and developed to predict the equilibrium moisture content of onion slices and the selected models were trained by using related algorithms. The modified Oswin model was found acceptable for predicting adsorption moisture isotherms and fitting to the experimental data, based on the coefficient of determination (R 2 = 0.991), mean relative percent error (MRE=15.019), and standard error of estimation (SEE=1.371). Besides, multilayer perceptron model with four layers (2: 17: 14: 1) was selected as the best artificial neural network for estimation of onion slices' equilibrium moisture content by considering R 2 = 0.993 and good performance. The net isosteric heat of adsorption of moisture was determined by applying the Clausius-Clapeyron equation to the sorption isotherms at different temperatures. The net isosteric heat of adsorption of red onion slices varied between 1.46 and 4.96 kJ/mol at moisture content varying between 2% and 52% (d.b.).

show abstract

“…Since then, many aspects of drying processes have been modeled by this tool, such as drying kinetics [20][21][22] , moisture sorption isotherms [23] , product properties [24][25] etc. A review on the use of artificial neural networks in drying technology was recently published [26] .…”

Section: Introductionmentioning

confidence: 99%

Control of the Moisture Content of Milk Powder Produced in a Spouted Bed Dryer Using a Grey-Box Inferential Controller

Vieira

Freire

2015

Drying Technology

View full text Add to dashboard Cite

Although the moisture content of dried products is an important variable on industrial dryers, it is often not measured directly for control purposes. Alternative and simpler meters might provide information to be used by a physical-mathematical model to estimate the moisture content. When this procedure is applied to a control strategy, an inferential controller is developed. In this paper, a physical-mathematical model was used to infer the moisture content of milk powder produced in a spouted bed dryer.Afterwards, simulations of an inferential proportional-integral controller were carried out, using the inlet air heating rate as the manipulated variable. The physical-mathematical model used in the procedure was a hybrid one, which considers mass and energy balances and one term which is estimated by an artificial neural network. The controller parameters (controller gain and integral time) were tuned by trial and error. Even though the procedure was quite simple, it was proven to be effective in yielding a stable closedloop response for both servo and regulatory control of the (inferred) powder moisture content.

show abstract

Neural network modeling of sorption isotherms of longan (Dimocarpus longan Lour.)

Cited by 26 publications

References 22 publications

Isotermas de dessorção de pimentão verde e energia envolvida no processo

Isotermas de dessorção de pimentão verde e energia envolvida no processo

Adsorption Isotherms for Red Onion Slices Using Empirical and Neural Network Models

Control of the Moisture Content of Milk Powder Produced in a Spouted Bed Dryer Using a Grey-Box Inferential Controller

Contact Info

Product

Resources

About