dc.creator | Di Scala, Karina Cecilia | |
dc.creator | Meschino, Gustavo | |
dc.creator | Vega Gálvez, Antonio | |
dc.creator | Lemus Mondaca, Roberto | |
dc.creator | Roura, Sara Ines | |
dc.creator | Mascheroni, Rodolfo Horacio | |
dc.date.accessioned | 2017-03-29T21:36:49Z | |
dc.date.accessioned | 2018-11-06T12:38:40Z | |
dc.date.available | 2017-03-29T21:36:49Z | |
dc.date.available | 2018-11-06T12:38:40Z | |
dc.date.created | 2017-03-29T21:36:49Z | |
dc.date.issued | 2013-08 | |
dc.identifier | 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 | |
dc.identifier | 0101-2061 | |
dc.identifier | http://hdl.handle.net/11336/14481 | |
dc.identifier | 1678-457X | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1868634 | |
dc.description.abstract | 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. | |
dc.language | eng | |
dc.publisher | Soc Brasileira Ciencia Tecnologia Alimentos | |
dc.relation | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1590/S0101-20612013005000064 | |
dc.relation | info:eu-repo/semantics/altIdentifier/url/http://ref.scielo.org/8v6jfr | |
dc.relation | info:eu-repo/semantics/altIdentifier/url/http://www.redalyc.org/articulo.oa?id=395940117004 | |
dc.rights | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | Artificial neural networks | |
dc.subject | Quality attributes | |
dc.subject | Genetic algorithm | |
dc.subject | Process optimization | |
dc.title | An artificial neural network model for prediction of quality characteristics of apples during convective dehydration | |
dc.type | Artículos de revistas | |
dc.type | Artículos de revistas | |
dc.type | Artículos de revistas | |