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Composite breads were made by supplementing wheat flour with chemically modified African yam bean and cassava starches after the flour – starch blends were produced from the cleaned seeds and roots using hammer milling system. Three mixture components were obtained from the D-optimal mixture design of Response Surface Methodology (RSM). The physical and sensory properties of the bread was determined and subjected to statistical analysis of variance (ANOVA) using cubic models to generate the regression equations from the experimental values. The linear, binary and ternary effects of the dependent responses and their interactions was generated and graphically represented using 3D response surface plots. The developed models were tested for adequacy and validated using criterion at p0.05) lack-of-fit (LoF), >0.7 adjusted R2 and >4 adequate precision to confirm adequate model signals. The numerical optimization outcomes had the desirability value of 0.86 depicting the ideal value. The optimized values for the optimum blends selected were 80.15 g wheat flour, 11.23 g African yam bean starch and 8.53 g cassava starch which will give the best composite flour -starch blends for enhanced bread products. The optimization was confirmed by performing confirmatory runs determining the 95 % confidence levels of the blends. The D – optimal mixture design of response surface methodology with three experimental components was adequate (propagated the design space) in evaluating and optimizing of the dependent responses tested; bread height, oven spring, loaf weight, loaf volume, specific volume and bulk density, appearance, crumb and crust, taste, aroma and acceptability. |
