A combined approach to optimize the drying process of flavonoid-rich leaves (Inga edulis) using experimental design and mathematical modelling

Abstract The process of drying of the leaves of Inga edulis , a flavonoid-rich plant from Amazonia, was optimised in a forced convection dryer by combining experimental design and mathematical modelling. First, the monolayer moisture content was determined by hygroscopic studies at 25 °C and the value of this parameter (5.86 g/100 g dry matter) was fixed as a minimum to be achieved. Next, a 3 2 full-factorial design was applied, with temperature (40, 55 and 70 °C) and airflow velocity (0.6, 1.2 and 1.8 m/s) as the independent variables, the dependent variable being the drying time required to reduce the moisture content until the level determined in the monolayer was achieved. Nine kinetic models, with one to four parameters, were fitted to the experimental data. The fitting performance of these models was assessed using statistical criteria and, from these results, the Henderson and Pabis model was found to be sufficient to predict the monolayer drying times . Subsequently, a multiple linear regression was carried out by applying a second-order model to describe the relationship between the independent and dependent variables, which established the adequacy of this model ( R 2  > 0.97) and, thus, the applicability of the combined statistical and mathematical approaches. Finally, an experimental domain that could minimise the drying times ( time