Characterization of consumer groups using cognitive sensory evaluation method based on multi-layer consciousness

Abstract

To understand the effects of human consciousness on cognitive food sensory evaluation for a given food, normal distribution analysis of clustered panelist (cl-NDC) was developed. Answers of the questionnaire consisted of 158 inquiries prepared for potato chips for five panelist groups were served as the source data for the normal distribution analysis. The parameters of the multi-layer consciousness (Chun, 2000) affected differently on the normal distribution curves (cl-NDC) of the three groups. Among the three layers, the 7th consciousness layer showed the most significant influence on the cl-NDC of the cognitive sensory evaluation process of food. Using cl-NDC method, a panelist group was more easily differentiated from others than the clustering analysis the case was. According to the shape of the cl-NDC, the five panelists groups were clearly characterized. The cl-NDC method was also useful to identify the most influential consciousness layer in the cognitive food sensory evaluation, and .the 7th layer was proved to the most responsible layer. In addition, the cl-NDC method reveals that the experience on food is the most important element among the contents of the 7th layer. Furthermore, the method was a valuable tool to investigate the effects of consciousness state of panelist in the cognitive food sensory evaluation process. For the effective investigation of cognitive food sensory evaluation for various foods and consumer groups, on-line/off-line database system was developed and this system was applied for the remote cognitive food sensory survey, and it could construct an on site Cognitive Food Sensory Curve (CFSC) for an individual subject through website.