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

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dc.creatorKarina DI SCALA
dc.creatorGustavo MESCHINO
dc.creatorAntonio VEGA-GÁLVEZ
dc.creatorRoberto LEMUS-MONDACA
dc.creatorSara ROURA
dc.creatorRodolfo MASCHERONI
dc.date2013
dc.date.accessioned2026-07-07T04:19:24Z
dc.descriptionIn 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.formatapplication/pdf
dc.identifier0101-2061
dc.identifierhttps://www.redalyc.org/articulo.oa?id=395940117004
dc.identifier.urihttp://hdl.handle.net/123456789/457781
dc.languageen
dc.publisherSociedade Brasileira de Ciência e Tecnologia de Alimentos
dc.relationhttp://www.redalyc.org/revista.oa?id=3959
dc.rightsCiência e Tecnologia de Alimentos
dc.sourceCiência e Tecnologia de Alimentos (Brasil) Num.3 Vol.33
dc.subjectAgrociencias
dc.titleAn artificial neural network model for prediction of quality characteristics of apples during convective dehydration
dc.typeartículo científico

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Ciência e Tecnologia de Alimentos - Sociedade Brasileira de Ciência e Tecnologia de Alimentos