Otimização e modelagem do processamento de cereal matinal hidratado com leite sem lactose

Abstract

Morning cereals are extruded products and have crispness as an important sensory attribute. Usually it is consumed in the hydrated form with milk which can cause great absorption of humidity and alteration of its characteristics. In order to know a hydration kinetics and a change in product quality, a 2³ design with 3 central points was performed, with time, hydration temperature and cereal / milk ratio as independent variables. The data were treated using the response surface methodology, empirical models and the artificial neural network. Physicochemical analyzes were performed during hydration to monitor the loss of quality and to analyze possible changes in the composition of both milk and cereal. The processing conditions caused a significant effect (p <0.05) on the moisture and ash analyzes in the cereal and of ash and reducing sugars in the milk. When compared to the response surface and with empirical models of the literature, the neural network presented better adjustments and greater capacity to predict the behavior of the response variables.