The current study deals with an innovation in the hot air convective drying process consisting of the application of two consecutive drying steps. Temperatures ranging between 60 and 80 ℃ for times between 200 and 600 s were applied for the first stage, and from 40 to 80 ℃ for the second stage. Salvia officinalis, an aromatic, medicinal Mediterranean plant with remarkable antioxidant properties, was selected for this study. A management of the process regarding the antioxidant capacity of S. officinalis extracts and energy consumption was carried out: (i) artificial neural networks were applied to model the evolution of the antioxidant capacity and moisture content of the product in the drying process; (ii) a genetic algorithm and a multiobjective genetic algorithm were selected to optimize the drying process, considering the antioxidant capacity and/or the energy consumption in the objective function. The results showed that the optimum values depended, logically, on the controllable variables values (hot air temperatures and drying times), but also on the uncontrollable variable values (room air temperature and relative humidity and the product's initial mass and moisture content).
Keywords: Salvia officinalis; antioxidant capacity; artificial neural network; drying; energy.