Mangosteen peel is a source of natural phenolic antioxidants. During processing, the quality and quantity of these compounds in the final product are altered. Sometimes, the important causal relationships are not easy to establish and thus process management is difficult. This is especially true when biochemical changes can occur as in the case of the drying and extraction process of bioactive materials. The aim of this work was to formulate and solve an optimization problem in order to obtain the appropriate values of the operating conditions that maximize the antioxidant capacity of the dried mangosteen peel extracts. The drying process was analyzed under different drying air temperatures (T) (50℃, 60℃, 70℃ and 80℃) at air velocity of 1 ms-1. The extraction process was done under conventional and ultrasound-assisted extraction at 400 W. Antioxidant capacity was measured by 1,1-diphenyl-2-picrylhydrazyl assay. To solve the optimization problem formulated, an artificial neural network was developed. The resolution of the optimization problem allowed the establishment of the optimal operating conditions of the process, maximizing the antioxidant capacity values depending on the characteristics of the process. Results showed that the best operating conditions to maximize the antioxidant capacity of mangosteen peels were a drying temperature of 70℃ and using high-power ultrasound as extraction method.
Keywords: Antioxidant capacity; artificial neural networks; optimization problem; process management.