PROJECTIVE MAPPING AND DESCRIPTIVE ANALYSIS OF MILK AND DARK CHOCOLATES

Recently there has been renewed interest in the use of projective mapping to evaluate overall product similarity. Previous studies show a high degree of similarity between product maps from projective mapping and descriptive analysis techniques; however, trained panels had been used in these studies. In this study, three groups of untrained panelists performed projective mapping on a set of chocolates and then were trained and performed descriptive analysis. Principal component analysis and multifactor analysis were used to generate product maps of the descriptive analysis and projective mapping data, respectively. All six maps were visually similar, and RV-coefficients between the six data sets were greater than 0.8. The results indicate that the use of untrained judges for the projective mapping provided equivalent product spaces as obtained by descriptive analysis for this set of products. Furthermore, the similarity among panels indicates that overall the panelists perceived the chocolates in a similar manner.