Determining the effective moisture diffusivity and activation energy for Button Mushroom and Presentation Mathematical Models and Neuro-Fuzzy Inference System (ANFIS).

The present study investigates the effect of temperature changes (۵۰, ۶۰, ۷۰, ۸۰ ° C) on the kinetics anddrying speed of button mushroom using a hot air dryer during the drying process, and compares them byeleven mathematical models and Neuro-Fuzzy Inference System (ANFIS) of artificial neural networks.Moisture ratio was fitted during the drying process with eleven mathematical models and ANFIS. Thedrying rate and drying curves at different temperatures was plotted and the diffusivity and activationenergy was determined for each temperature. Nonlinear regression was used in R software version ۳.۶.۳to determine the best model for thin layer drying. MRDM, RMSE, χ۲ and R۲ indices were used todetermine the best thin layer drying model. Results ANFIS showed that the best suitable model for thinlayer drying of button mushroom with the highest correlation coefficient (R۲ = ۰.۹۹۹۹) and root meansquare error (RMSE = ۰.۰۰۱) was Two term model. The amount of activation energy was ۲۲۷۷.۳ (kJ/kg)and the diffusivity was ۰.۰۱۶۲۷۷۶۳ to ۰.۰۲۸۳۴۴۹۷ m۲ /s which increased with increasing temperature.

کلیدواژه ها:

Effective diffusivity ، Activation Energy ، Drying rate ، Mathematical Model ، ANFIS ، RSoftware