An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

AUTOR(ES)

Scala, Karina Di, Meschino, Gustavo, Vega-gálvez, Antonio, Lemus-mondaca, Roberto, Roura, Sara, Mascheroni, Rodolfo

FONTE

Food Sci. Technol

DATA DE PUBLICAÇÃO

06/08/2013

RESUMO

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

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