https://www.siftdesk.org/article-details/Application-of-RSM-in-modelling-and-Numerical-optimisation-of-proximate-composition-of-instant-Extruded-kunun-gyadaporridge-from-the-blend-of-sorghum-groundnut/10788-siftdesk

Abstract

The effect of extrusion parameters on the proximate composition of Kunun-Gyada extrudates was investigated. Fifteen experimental runs were generated using Box-Behnken (RSM) designs and were processed in a single-screw extruder (WSSH-40, Runxiang). The results were subjected to statistical analyses to evaluate for significant (0.01 ≤ p ≤ 0.05) effects between the blends and the extrusion parameters. There was an increase in proximate mean composition of the extrudates, crude protein 11.60 to 13.70%, ash 1.00 to 1.13%, with decrease in both moisture content, crude fiber, crude fat and carbohydrates ranges from 8.60-7.31%, 3.03-2.96%, 6.99-5.40% and 72.32-75.57% respectively. The R2 of all the models were greater than 78% and all were having a non-significant lack-of-fit test. In view of the operability in actual production, the optimal conditions were adjusted as follows: 21.0% FC, 25.0% MC and 110oC BT. Under the adjusted conditions, the responses were 7.89% moisture content, 13.02% crude protein, 3.010% crude fibre, 5.802% fat, Ash 1.070% and 67.268% carbohydrate indicating that the model was adequate for the optimization process. The optimal result could produce kunun-gyada suitable for instant porridge which can potentially be use for industrial projection and sustainable food and nutritional security.