Using PSO and GWO techniques for prediction some drying properties of tarragon (Artemisia dracunculus L.)

Abstract

AbstractIn this article, the effects of air temperature and velocity on drying characteristics of tarragon (Artemisia dracunculus L.) were investigated. The experiments were done at four temperatures of 40, 50, 60, and 70 °C and three air velocities of 1, 1.5, and 2 m/s. According to the results, the drying term of tarragon reduced significantly with increasing drying air temperature. The values of effective moisture diffusivity (Deff) were ranged between 1.34 × 10−10 and 2.74 × 10−10 m2/s. Also, by increasing drying air temperature the values of specific energy consumption (SEC) were decreased. The values of SEC were between 20.50 and 66.90 MJ/kg. Also Deff and SEC values were modeled by particle swarm optimizer (PSO) and gray wolf optimizer (GWO) algorithms. Drying air velocity and air temperature were considered as input parameters for the models. Based on three statistical parameters includes R2, MSE, and MAE for predicting Deff and SEC, GWO performance was better than the PSO.Practical applicationsThe purpose of drying crops is decreasing of moisture content for providing secure storage and significant influence on the quality of dried crops. In this research, the effective moisture diffusivity (Deff) and specific energy consumption (SEC) values were modeled by PSO and GWO algorithms. The procedure can be applied in postharvest processing of medicinal plants.