Application of Genetic Algorithm for optimization of solar powered drying

This paper represents the kinetic simulation and optimization technique for a drying process of mushroom using Genetic Algorithm (GA) for the estimation of time and temperature parameters for maintaining minimum energy consumption and maximum amylase activity. At 30-60°C temperature, the mushrooms were dried in a natural convective dryer and after certain time intervals the enzymatic activity and the moisture content were measured. Genetic Algorithm (GA) method was used for the simulation and optimization process and the experimental data were used to fit the models. The results indicated that, after 350 min of the drying process the mushrooms were dried. Among the utilized models the best result was presented by the proposed model. The result showed that around 50°C and between 300-400 min of mushroom drying process, the specific activity was found 5.12±0.05 SKB/mg and 12.5±0.05% (wet basis) of reaming moisture content with minimum energy consumption.