INVESTIGADORES
MASCHERONI Rodolfo Horacio
artículos
Título:
An artificial neural network model for prediction of quality characteristics of apples during convective dehydration
Autor/es:
K. DI SCALA; G. MESCHINO; A. VEGA-GÁLVEZ; R. LEMUS; S. ROURA; R.H. MASCHERONI
Revista:
CIêNCIA E TECNOLOGIA DE ALIMENTOS
Editorial:
SOC BRASILEIRA CIENCIA TECNOLOGIA ALIMENTOS
Referencias:
Lugar: Campinas; Año: 2013 vol. 33 p. 411 - 416
ISSN:
0101-2061
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.
