Baking of flat bread in an impingement oven: Modeling and optimization

Abstract

An artificial neural network (ANN) was developed to model the effect of baking parameters on the quality attributes of flat bread; i.e., crumb temperature, moisture content, surface color change and bread volume increase during baking process. As the hot air impinging jets were employed for baking, the baking control parameters were the jet temperature, the jet velocity, and the time elapsed from the beginning of the baking. The data used in the training of the network were acquired experimentally. In addition, using the data provided by ANN, a multi-objective optimization algorithm was employed to achieve the baking condition that provides the quality of the bread in all aspects simultaneously.