Multiobjective process optimization for betaine enriched spelt flour based extrudates

The main purposes of this work are successful modeling of twin‐screw extrusion process using predictive models, investigating the effect of process parameters such as screw speed, feed rate, and feed moisture content on the process and product responses and finally optimizing the process regarding betaine content in the extruded product and energy consumption. The second order polynomial approximation models and the artificial neural network were developed to predict the betaine content, showing the high accuracy in the prediction of experimental results. This study introduces the multiobjective optimization (MOO) approach in the extrusion process of spelt flour. The maximal betaine content (between 1,506.8 and 1,605.2 mg/40 g) and minimal energy consumption (between 101.3 and 108.5 W hr/kg) were indicated by MOO procedure, which were gained using the following input parameters: feed flow rate feed about 24 kg/h, screw speed about 252 RPM and moisture content from 21.6 to 23.4%. PRACTICAL APPLICATIONS: This study introduces the multiobjective optimization (MOO) approach in the extrusion process of spelt flour, which provides the selection of optimal solution that enables the extruder to reach the optimum conditions of the process and provide decision maker with deeper understanding of the process. The present study analyzes the influence of extrusion cooking parameters like: screw speed, feed flow rate, and feed moisture content on the betaine content in the extrudate product and specific mechanical energy input during the processing of betaine enriched spelt flour based extrudates. One way to improve the intake of betaine in the general population can be to enrich foods with betaine. According to European Breakfast Cereal Association for extruded products portion sizes should be 40 g. Consuming a portion of a functional extrudate product with the addition of betaine (1,500 mg/day) could give expected health effects. Final extrudate product from this study satisfies these statements.