NONLINEAR MODELS FOR INFRARED DRYING OF MINT

Authors

  • E. K. BASAR
  • N. HEYBELI
  • M. Z. FIRAT
  • C. ERTEKIN*

DOI:

https://doi.org/10.52292/j.laar.2019.280

Keywords:

Nonlinear Modeling, AIC, BIC, Infrared Drying, Mint

Abstract

In this paper, 105 different semitheoretical and empirical thin layer drying models were used for describing the drying process of the mint leaves. Comparisons of the overall goodness of fit were based on Coefficient of Determination (R2), Root Mean Square Error (RMSE), Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). It was concluded that five parameter Cedergreen-Ritz-Streibig modified log-logistic functions with alpha equal to 0.25 (CRS5C) model describe the infrared drying process of the mint leaves. Furthermore, temperature effect was investigated by using reduction test. Finally, it was found that the effect is statistically significant and the model with separate trends fits these data better.

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Published

2019-01-31

Issue

Vol. 49 No. 1 (2019): Latin American Applied Research

Section

Chemical Engineering

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