Optimization, modeling, and characterization study for the physicochemical properties of raw banana and defatted soy composite extrudates.

• Development of raw banana/defatted soy composite extrudates. • Barrel temperature is the most influential parameter. • Optimum condition was reported using RSM. • ANN models proved better than RSM for response prediction. • FTIR confirmed the degradation of protein's secondary structures during extrusion. Novel raw banana and defatted soy composite extrudates were formulated to combat celiac enteropathy. The influence of four independent parameters viz. barrel temperature (BT: 60–80 °C), screw speed (SS: 200–300 rpm), moisture content (MC: 10–20%, wb), and defatted soy flour content (SFC: 0–32%) on physicochemical properties of extrudates were evaluated. Response surface methodology (RSM) identified the optimum extrusion conditions (80 °C BT, 200 rpm SS, 10% MC, and 32% SFC). Compared to RSM (R2:0.379–0.918), artificial neural network (R2:0.909–0.991) proved as a better tool for response prediction. Scanning electron microscopy confirmed the antagonistic effect of SFC addition on extrudate porosity. The addition of SFC decreased the crystallinity of the starch granules (71 to 49%), whereas, storage time had a positive effect (49 to 53%) on crystallinity of the composite extrudates. Fourier transform infrared spectroscopy analysis elucidated the secondary structures of protein in the composite flour which were degraded during the extrusion cooking. [ABSTRACT FROM AUTHOR]