<b>Mathematical modeling of the drying process of corn ears</b> - doi: 10.4025/actasciagron.v33i4.7079

  • Paulo Cesar Corrêa Universidade Federal de Viçosa
  • Fernando Mendes Botelho Universidade Federal de Viçosa
  • Gabriel Henrique Horta Oliveira Universidade Federal de Viçosa
  • André Luis Duarte Goneli Universidade Federal da Grande Dourados
  • Osvaldo Resende Universidade Federal de Viçosa
  • Sílvia de Carvalho Campos Universidade Federal de Viçosa
Keywords: Zea mays, mathematical models, moisture content

Abstract

The objective of this work was to study and model the drying process of corn ears at different air temperatures. Thermodynamic properties associated with the drying process of this product were also determined. Corn ears with initial moisture content of 0.45 dry basis (kgw kgdm-1) were dried until they reached a final moisture content of 0.12 (kgw kgdm-1) at temperatures of 45, 55 and 65°C. Traditional models used to describe the drying process of several agricultural products were employed to fit the observed data of the drying process of corn ears. The effective diffusion coefficient (Def) was determined by means of an analytical solution of Fick’s second law. It was concluded that the Logarithmic model was the one that best fit the observed data representing the drying process. Def values increased with temperature increases, ranging from 5.490 x 10-10 to 1.163 x 10-9 m2 s-1. Based on the dependence of the drying constant of the Logarithmic model with temperature, thermodynamic properties were determined, concluding that the drying kinetics variation is dependent on the energy contributions of the surrounding environment.

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Published
2011-05-04
How to Cite
Corrêa, P. C., Botelho, F. M., Oliveira, G. H. H., Goneli, A. L. D., Resende, O., & Campos, S. de C. (2011). <b>Mathematical modeling of the drying process of corn ears</b&gt; - doi: 10.4025/actasciagron.v33i4.7079. Acta Scientiarum. Agronomy, 33(4), 575-581. https://doi.org/10.4025/actasciagron.v33i4.7079
Section
Agricultural Engineering

 

2.0
2019CiteScore
 
 
60th percentile
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2.0
2019CiteScore
 
 
60th percentile
Powered by  Scopus