Abstract
Wheat flour is one of the principal ingredients in extruded wheat products. Wheat-based extruded products have relatively low protein and high gluten contents as well as a high glycemic index. Incorporation of nutrient-rich supplements could overcome those limitations. A D-optimal statistical experimental design was used to develop high-value and nutrient-rich extruded products by supplementing wheat flour (WF), with tef flour (TF), sesame protein concentrate (SPC) and tomato powder (TM). Effects of feed compositions on physical and functional properties of the extruded products were evaluated and modeled using an artificial neural network (ANN). SPC contributed to elevate the protein and simultaneously lower the carbohydrate content of the extruded products while TF and TM contributed to improving crude fiber and antioxidant properties. Evaluated physicochemical properties were adequately predicted by the ANN models (R(2) = 0.979-0.998) with root mean square error of less than 0.008. Physical properties and sensorial evaluation correlated well and revealed that TF, SPC and TP addition to wheat flour produced distinct extruded products rich in protein and antioxidants with lowered carbohydrate and gluten contents.