|
|
|
|
| |
|
| |
|
|
Scala,Karina Di; Meschino,Gustavo; Vega-gálvez,Antonio; Lemus-mondaca,Roberto; Roura,Sara; Mascheroni,Rodolfo. |
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. |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial neural networks; Quality attributes; Genetic algorithm; Process optimization; Dried apple. |
Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612013000300004 |
| |
|
| |
|
|
|