Artículos de revistas
An artificial neural network model for prediction of quality characteristics of apples during convective dehydration
Fecha
2013-08Registro en:
Di Scala, Karina Cecilia; Meschino, Gustavo; Vega Gálvez, Antonio; Lemus Mondaca, Roberto; Roura, Sara Ines; et al.; An artificial neural network model for prediction of quality characteristics of apples during convective dehydration; Soc Brasileira Ciencia Tecnologia Alimentos; Ciencia e Tecnologia de Alimentos; 33; 3; 8-2013; 411-416
0101-2061
1678-457X
Autor
Di Scala, Karina Cecilia
Meschino, Gustavo
Vega Gálvez, Antonio
Lemus Mondaca, Roberto
Roura, Sara Ines
Mascheroni, Rodolfo Horacio
Resumen
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.