Soft computing modelling of moisture sorption isotherms of milk-foxtail millet powder and determination of thermodynamic properties

摘要

Moisture sorption isotherms of spray-dried milk-foxtail millet powder were determined at 10, 25 and 40 °C. Sorption data was fitted using classical and soft-computing approaches. The isotherms were of type II, and equilibrium moisture content (EMC) was temperature dependent. The BET monolayer moisture content decreased from 3.30 to 2.67 % as temperature increased from 10 to 40 °C. Amongst the classical models, Ferro-Fontan gave the best fit of EMC-aw data. However, the Sugeno-type adaptive neuro-fuzzy inference system (ANFIS) with generalized bell-shaped membership function performed better than artificial neural network and classical models with RMSE as low as 0.0099. The isosteric heat of sorption decreased from 150.32 kJ mol⁻¹ at 1 % moisture content to 44.11 kJ mol⁻¹ at 15 % moisture. The enthalpy-entropy compensation theory was validated, and the isokinetic and harmonic mean temperatures were determined as 333.1 and 297.5 K, respectively.Electronic supplementary materialThe online version of this article (doi:10.1007/s13197-016-2242-8) contains supplementary material, which is available to authorized users.