Drying characteristics of banana: theoretical modelling and experimental validation

Karim, Azharul; Hawlader, Mohammad Nurul Alam

doi:10.1016/j.jfoodeng.2004.09.010

Cited by 168 publications

(94 citation statements)

References 25 publications

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“…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%

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: Introductionmentioning

confidence: 99%

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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“…Some comprehensive reviews on the data and prediction models of thermo-physical properties have been published by several researchers [18,19]. Convective heat and mass transfer coefficients data have been presented and modeled during the garification process.…”

Section: Data Generationmentioning

confidence: 99%

Modeling of the Garification Process of Fermented Cassava Mash

Sobowale¹,

So²,

Ta³

et al. 2017

J Bioprocess Biotech

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IntroductionCassava (Manihot esculenta Crantz) is a staple food for over one billion people in the developing world [1]. In Nigeria, it appears to be the major staple food that matches population growth [2,3]. They are highly perishable and cannot be kept after harvest, hence it can either be consumed immediately or processed into various product [2,3]. The main form in which cassava is eaten in West Africa is in a roasted granular form known as gari, a fermented roasted granule prepared from peeled, grated and fermented cassava root through a series of processing steps [3][4][5]. The quality and yield of gari during roasting (garification) is affected by cassava root age and length of cassava mash fermentation. The garification process is an arduous and intricate operation which needs good understanding of the factors that affect the yield and quality of the gari [6]. In recent years, the inability of the process coupled with exposure of the operator to heat and smoke have been the major factors reducing the efficiency of the gari roasting in the traditional methods. The traditional gari processing methods not only gives relatively good quality, but it is highly labour-intensive, unhygienic and productivity is often too low to justify the investment of labour, time consuming and leads itself to health hazard for the operator [7]. Engineering interventions to improve the industrial process is often by way of reducing drudgery and maximizing the yield of gari and improve quality through the mechanization of the unit operations. Considerations for heat and mass transfer are also necessary to improve the working conditions of gari processing for sustainable economic development in Nigeria. The study of [8] has shown that the heat and mass transfer operations play a prominent role during reconstitution of gari into thick paste, and are among the most important physical phenomena occurring during gari processing. As a consequence, several important variables such as temperature and moisture concentration within the structure of food depend on time as well as position inside the food system [9] highlighted that gari yield and quality are highly influenced by cassava variety, maturity age, fermentation and garification temperature, convective heat and mass transfer coefficients. Mathematical modeling and computerbased numerical analyses such as Partial Differential Equation (PDE), Response Surface Methodology (RSM) have been extensively used for time and cost reduction in experimentation, design, optimization and validation of food processing operations [10]. Previous studies of baik [11,12] and Singh and Pandey [13], have shown that ANN model is an advanced modified numerical analysis method, which is capable of learning from examples through iteration and could be useful in predicting simultaneous heat and mass transfer data. ANN model was applied in this study to analyze the garification process to develop an ANN based model of steady state simultaneous heat and mass transfer for the garification process of fermente...

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“…Likewise considering shrinkage, Karim and Hawlader, provided a description of the heat and mass transfer properties of banana during drying through the use of a mathematical model [10]. Similar studies use analytical solutions of the diffusion equation by intermittent drying and continuous drying and some of them used the model describing well the drying of bananas and other agricultural products [2].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling of the Drying Kinetics of Thinly-Sliced Saba (Musa Balbasiana) Using Hot-Air Dryer

et al. 2018

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Abstract. Banana is one of the top produced crops in the Philippines, and among its cultivars is the Musa balbasiana, commonly known as saba. Due to its high moisture content, saba is perishable and one of the methods to increase its shelf-life is drying. The shelf life of saba can be extended up to six months when dried to 12% moisture content. The research focuses on the effect of banana maturity and choses a mathematical model which will best fit its drying kinetics. The banana samples, the unripe and ripe saba, were bone-dried without pre-treatment using a hot-air tray drier. To produce repeatable data, three trials were done for temperatures 40 o C, 50 o C and 60 o C. Among the three mathematical models used in the study, the treated data for both unripe and ripe saba best fit the Laplace Transform Model. Using Lagrange interpolation, the time per trial was computed; unripe saba dried at 50 o C achieved the ideal moisture content in an average time of 87.5574 minutes for the three trials while that of ripe saba dried at 40 o C achieved the same moisture content in an average time of 88.8619 minutes for the three trials. With the increase in temperature, the discoloration decreased indicating an enzymatic character ofbrowning.

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Drying characteristics of banana: theoretical modelling and experimental validation

Cited by 168 publications

References 25 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

Modeling of the Garification Process of Fermented Cassava Mash

Mathematical Modeling of the Drying Kinetics of Thinly-Sliced Saba (Musa Balbasiana) Using Hot-Air Dryer

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