The Optimization of Solar Drying of Grain by Using a Genetic Algorithm

Abstract

Particularly in the low drying temperature drying is an energy intensive process and requires a suitable optimization technique. This work represents the kinetic simulation and energy efficient optimization technique for drying long grain, i.e. rice. At 30–60°C temperature the grains have been dried in a solar powered air dryer. After certain time interval the enzymatic activity and the moisture content have been measured. Genetic Algorithm (GA) has been used for the simulation and the optimization process while the experimental data have been used to fit the thin layer drying model. The results indicate that between 40 and 50°C temperature and the 1.3–1.5 m/s air flow rate the drying time for the rice is around 120–180 min. The kinetic simulation and the quality analysis confirm that the dried products have a better enzymatic activity which resembles the quality standard and the required energy for the optimized drying process is lower than the others.