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OPTIMIZATION OF A CHOCOLATE PEANUT SPREAD USING RESPONSE SURFACE METHODOLOGY (RSM)
Author(s) -
CHU C.A.,
RESURRECCION A.V.A.
Publication year - 2004
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/j.1745-459x.2004.tb00146.x
Subject(s) - response surface methodology , food science , biochemical engineering , mathematics , computer science , microbiology and biotechnology , chemistry , statistics , biology , engineering
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.