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 greater than or equal to 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.