Abstract
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 150.32kJmol(-1) at 1% moisture content to 44.11kJmol(-1) at 15% moisture. The enthalpy-entropy compensation theory was validated, and the isokinetic and harmonic mean temperatures were determined as 333.1 and 297.5K, respectively.
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