Use of response surface methodology (RSM) for composite blends of low grade broken rice fractions and full-fat soybean flour by a twin-screw extrusion cooking process

Abstract

In this study, seventeen (17) composite blends of broken rice fractions and full-fat soybean, formulated using response surface methodology and central composite design within a range of barrel temperatures (100-140 o C), initial feed moisture content (15-25%) and soybean composition (8-24%), were extruded with a twin-screw extruder and the expansion and color indices were optimized. The results indicated a significant (p<0.05) effect of extrusion conditions on the responses. Fitted predictive models had coefficients of 88.9%, 95.7%, 97.3%, 95.4% and 95.2%, respectively, for expansion index, bulk density, lightness, redness and yellowness. The p-value and lack-of-fit tests of the models could well explain the observed variability and therefore could be used to establish production setting for the twin-screw extruder. The optimum extrusion conditions were found to be 130 o C (barrel temperature), 20% (feed moisture level) and 23% feed soybean composition and optimum responses in terms of bulk density, expansion index, lightness, redness and yellowness chroma indices were 0.21 g cm −3 , 128.9%, 17.1, 3.13 and 24.5, respectively. This indicates that optimum conditions can be established in twinscrew extrusion cooking of broken rice fractions and full-fat soybean composite blends that can result in product of low bulk and maximum expansion with a satisfactory light yellow product color that can be used to produce products that valorize broken rice and reduce qualitative postharvest loss.

Development and evaluation of extruded protein snacks added

“…Color is an important visual parameter that showed alteration when compared to the control sample showing a reddish-brown hue, indicating a possible occurrence of the Maillard reaction. In addition, the coloring of the flours, especially the TSP, may have contributed to the color change observed in the formulations with the highest substitution (Danbaba et al, 2019).…”