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

Murthy, T P Krishna; Manohar, B.

doi:10.1007/s13197-013-0941-y

Cited by 54 publications

(34 citation statements)

References 51 publications

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“…Thus, the Midilli et al and Two Term models were found to be best models to represent the thin-layer drying characteristics of the date slices. These observations are in good agreement with earlier results reported for the Midilli et al model in describing the thin-layer drying of pear (Doymaz, 2013) and mango ginger (Murthy & Manohar, 2014) and for the Two term model in drying of sultana grapes (Yaldiz et al, 2001) and squash seeds (Chayjan et al, 2013).…”

Section: Fitting Of Drying Curvessupporting

confidence: 92%

Total phenolics, antioxidant capacity, colour and drying characteristics of date fruit dried with different methods

İzli

2016

Food Sci. Technol

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Date slices were dried with the three drying methods convective (60, 70 and 80 °C), microwave (120 W) and freeze drying to determine drying characteristics and to compare the dried fruit quality. All colour parameters changed depending on the drying method and colours closest to the fresh sample were obtained with freeze drying. It is interesting to note that the total phenolic content and antioxidant capacity in each sample rose when looked at in relation to the fresh sample. In particular, microwave-dried samples were recorded as having the highest total phenolic content and the highest antioxidant capacity. To explain the drying kinetics of the date slices, nine thin-layer drying models were also attempted. Based on statistical tests, the model developed by Midilli et al. model was found to be the best model for convective and microwave drying, but the Two Term model was the best for freeze drying. This study shows that microwave drying can produce high quality date slices with the additional advantage of reduced drying times compared to convective and freeze drying.Keywords: drying methods; thin-layer; date slices; colour; total phenolic content.Practical Applications: Microwave drying at 120W can improve the final quality of dried date slices.

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Section: Fitting Of Drying Curvessupporting

confidence: 92%

Total phenolics, antioxidant capacity, colour and drying characteristics of date fruit dried with different methods

İzli

2016

Food Sci. Technol

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“…It is also rich major components including starch, phenolic acids, volatile oils, curcuminoids and terpenoids like difurocumenonol, amadannulen and amadaldehyde (Policegoudra et al 2011). Many aspects of processing like drying (Krishna Murthy and Manohar 2013a), grinding (Krishna Murthy and Manohar 2013b) and extraction (Krishna Murthy and Manohar 2014) of mango ginger have been studied by the authors. Extraction of mango ginger for its bioactives on a commercial scale is not in practice and such extraction shall result in value-added products.…”

Section: Introductionmentioning

confidence: 99%

Modelling solubility of phenolics of mango ginger extract in supercritical carbon dioxide using equation of state and empirical models

Murthy

Manohar

2014

J Food Sci Technol

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Solubility of phenolics of mango ginger extract in supercritical carbon dioxide was studied at 40-60°C and 100-350 bar. Critical temperature, critical pressure and critical volume of caffeic acid, the principal component of the extract were calculated using group contribution methods and compared with the values obtained by CHEMDRAW®. Vapor pressure of caffeic acid was predicted by Reidel method. Solubility prediction in supercritical carbon dioxide was studied using two different equation of states (EOS) models and eight empirical models. Peng-Robinson EOS predicted the solubility very well with average deviation of 0.68 % from the experimental solubility. Empirical equations based on the simple error minimization using non-linear regression method which do not require complex physiochemical properties was also found suitable to predict the solubility at different extraction conditions. Jouyban et al. model showed very less deviation (2.25 %) for predicted solubility values from the experiment.

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“…The ANN can establish a functional relationship between input and output variables by training and learning (Chojaczyk, Teixeira, Neves, Cardoso, & Guedes Soares, ). In recent years, ANN models have been studied for the modeling of drying of potato cubes (Azadbakht, Aghili, Ziaratban, & Torshizi, ), bay leaves (Aktaş, Şevik, Özdemir, & Gönen, ), mango ginger (Murthy & Manohar, ), sour cherry (Motavali, Najafi, Abbasi, Minaei, & Ghaderi, ), onion (Jafari, Ganje, Dehnad, & Ghanbari, ), kiwi (Mahjoorian et al, ), zucchini (Tavakolipour, Mokhtarian, & Kalbasi‐Ashtari, ), green bell pepper (Jafari, Ghanbari, Ganje, & Dehnad, ), and turnip slices (Kaveh & Chayjan, ). But, there is no study about comparison between ANN model and mathematical models for PVOD treated and non‐pretreated figs during drying.…”

Section: Introductionmentioning

confidence: 99%

Comparison between Artificial Neural Network model and mathematical models for drying kinetics of osmotically dehydrated and fresh figs under open sun drying

Şahin

Öztürk

2018

J Food Process Engineering

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In this study, drying kinetics of figs (Ficus carica L) under open sun drying (OSD) was compared with using Artificial Neural Network (ANN) model and mathematical models. Pulsed vacuum osmotic dehydration (PVOD) was applied as a pretreatment. In experiments, whole figs (Sarılop variety) were immersed in sucrose solution at 50°Brix and 50 °C with a ratio of solution/food was 4:1 for 180 min. Vacuum impregnation was applied at 253 mbar for 15 min. Shrinkage effect was considered, also. Results showed that PVOD reduced drying time of figs. The mean of Deff values of PVOD treated and fresh figs were obtained as 2.55 × 10−10 m2/s and 2.36 × 10−10 m2/s, respectively. It was found that present model was the best drying model with the highest correlation coefficient (R2) values among the mathematical models whereas ANN model had a higher correlation coefficient (R2 = 0.9999) values than the mathematical models for both PVOD treated and fresh figs. Practical applications Dried figs have an economic income for Turkey and Turkey is the biggest dried fig producer and exporter in the World. Drying of figs is very important phenomena because figs have a short harvesting time. Figs are widely dried under open sun because this method has low operating cost. OD method is used before drying step and provides reducing drying time. This study presents experimental results of osmotically dehydrated and fresh figs under open sun drying. Drying kinetics of figs were modeled with empirical and semiempirical models under shrinkage consideration. Shrinkage of fresh and osmotically dehydrated figs during the drying were mathematically modeled thus these correlations can be helpful for researchers. Also, a new mathematical model was established and this model had more accuracy than other mathematical models. The ANN model was used for the prediction of drying curves of figs in different operating conditions.

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

Cited by 54 publications

References 51 publications

Total phenolics, antioxidant capacity, colour and drying characteristics of date fruit dried with different methods

Total phenolics, antioxidant capacity, colour and drying characteristics of date fruit dried with different methods

Modelling solubility of phenolics of mango ginger extract in supercritical carbon dioxide using equation of state and empirical models

Comparison between Artificial Neural Network model and mathematical models for drying kinetics of osmotically dehydrated and fresh figs under open sun drying

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