Optimization of a Chocolate Peanut Spread Using Response Surface Methodology (Rsm)

Response surface methodology was used to optimize formulations of chocolate peanut spread. Thirty‐six formulations with varying levels of peanut (25‐90%), chocolate (5‐70%) and sugar (5‐55%) were processed using a three‐component constrained simplex lattice design. The processing variable, roast (light, medium, dark) was also included in the design. Response variables, measured with consumers (n = 60) participating in the test, were spreadability, overall acceptability, appearance, color, flavor, sweetness and texture/mouthfeel, using a 9‐point hedonic scale. Regression analysis was performed and models were built for each significant (p < 0.01) response variable. Contour plots for each attribute, at each level of roast, were generated and superimposed to determine areas of overlap. Optimum formulations (consumer acceptance rating of ≥ 6.0 for all attributes) for chocolate peanut spread were all combinations of 29‐65% peanut, 9‐41% chocolate, and 17‐36% sugar, adding up to 100%, at a medium roast. Verification of two formulations indicated no difference between predicted and observed values.