Nonlinear models for infrared drying of mint

Abstract

In this paper, 105 different semi-theoretical 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 Infor-mation Criterion (AIC) and Bayesian Information Criterion (BIC). It was concluded that five parame-ter 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 investi-gated by using reduction test. Finally, it was found that the effect is statistically significant and the mod-el with separate trends fits these data better.