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

Food Science and Technology

Rodolfo Mascheroni¹  Sara Roura²  Gustavo Meschino²  Karina Di Scala²  Roberto Lemus-mondaca³  Antonio Vega-gálvez³ 

[1] Consejo Nacional de Investigaciones Científicas y Técnicas;Universidad Nacional de Mar del Plata;Universidad de La Serena;

关键词: artificial neural networks;    quality attributes;    genetic algorithm;    process optimization;    dried apple;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown