Combining Cluster Analysis, Surface Response Methodology and JAR Scales to Increase Consumer Input in Optimizing Acceptability of a High‐Protein Soy Dessert

Abstract

AbstractAcceptance of a new high‐protein (6.75 g/serving), citrus‐flavored, soy‐based dessert with different concentrations of sucrose (5–17%) and citrus flavor (50–350 ppm) has been optimizing using the response surface method (RSM) in conjunction with consumer segmentation and with just‐about‐right (JAR) scales. Relationships between acceptability scores and composition variables were determined for the overall consumer population (130 consumers) and for two subgroups of consumers with different preference criteria, identified by cluster analysis. While for subgroup I (44 consumers) the composition factors did not show a clear influence on acceptability, for subgroup II (86 consumers) acceptability was well explained in terms of sucrose and citrus flavor contents (R2 = 94.4). Results obtained using JAR scales showed that the main differences between both consumer subgroups were related to adequacy of citrus flavor, sweetness and consistency data. Relating JAR percentages and hedonic data provide useful information for explaining differences in hedonic scores.Practical ApplicationsThe design of soy‐based dessert formulations, with adequate protein content and good sensory quality, is important to ensure their market success. It is important to take consumer opinions into account during formulation development to obtain a marketable product. In this respect, considering possible differences in preference criteria among consumer populations and combining information provided by RSM and by JAR scales can be very useful. Such tools can help to improve product acceptance through the modification of product formulation.