Generalized Empirical Correlations for drying of thin layer hawthorn in a tray dryer

Document Type : Research Article

Authors

1 Thermo-kinetics and Catalyst Dept., Faculty of Chemical Eng., Babol Noshiravani University of Technology, Babol, Iran

2 Dept. of Thermo-kinetics & Catalyst, Faculty of Chemical Eng., Babol Noshiravani University of Technology, Babol, Iran

Abstract

Drying process of thin layer hawthorn fruits was investigated in a tray dryer in 4 different temperatures (60,65,70, 75 C) and 4 different air velocities ( 5.0, 6.0, 7.0, 8.0 m/s). The hawthorn samples were dried from original moisture content of 44.37% to final moisture content of 1.63%. The experimental data were fitted to different empirical correlations and the Genetic Algorithm optimization method was used to obtain the best parameters. The results showed that the modified Page model was the best model to describe the thin layer drying of hawthorn fruits in a tray dryer. The parameters of the empirical correlations may be presented as a function of temperature and velocity of the drying air. So, the generalized empirical correlations may describe the drying behavior of thin layer hawthorn in various conditions, while the previous empirical correlations were just applied to a certain drying experiment.

Graphical Abstract

Generalized Empirical Correlations for drying of thin layer hawthorn in a tray dryer

Highlights

  • Predicting the drying behavior of the hawthorn native fruit in a tray dryer in different operating conditions, including the temperature and air speed.
·         Creating the generalized equations for drying hawthorn fruit in a tray dryer to predict humidity and drying speed in different experimental conditions.
·       Creating detailed generalized equations for experimental coefficients as a function of air temperature and velocity.
·       Using the genetic algorithm optimization method to estimate the most appropriate parameters in the generalized.
·       Selection and optimization of the most accurate generalized equations to predict the changes in humidity.

Keywords

Main Subjects

References

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Innovative Food Technologies
Volume 7, Issue 1
November 2019
Pages 149-161

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History

  • Receive Date: 27 September 2018
  • Revise Date: 17 December 2018
  • Accept Date: 17 February 2019

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