Optimization of Vacuum Drying Technology of Yam Based on Multi-Objective Genetic Algorithm

In order to obtain the optimal process parameters of vacuum drying of yam slices, Box-Behnken response surface optimization test was carried out with average drying rate Y₁, unit energy consumption Y₂, rehydration ratio Y₃ and whiteness index Y₄ as the test indexes, and drying temperature T, pressure V and slice thickness L as the influencing factors. The mathematical model of each index was established by multiple nonlinear regression analysis. Finally, the weighted scoring method and genetic algorithm were used for multi-objective optimization. The results show that the optimization result of multi-objective genetic algorithm is more reasonable. The optimum vacuum drying parameters are as follows: drying temperature 63.76℃, pressure 0.0532 MPa and slice thickness 2.46 mm.The corresponding index values are average drying rate 0.00897 g/(g·min), unit energy consumption 14.205 kW·h/kg, rehydration ratio 2.078 and whiteness index 81.220.