Sensory descriptive analysis often requires a large set of attributes that needs to be defined and referenced to make the results replicable. The resulting data are important and necessary for research and development purposes but may be excessively complex for management, marketing, consumer purposes or culinary applications, such as restaurants. This study examined the use of a simplified lexicon, high identity traits (HITS), generated by trained panelists to determine if an understanding of the overall differences and similarities between samples could be achieved with fewer and more user-friendly attributes than in traditional descriptive sensory testing. Ten trained sensory panelists participated in this pilot study with cheese. The number of attributes was reduced from more than 20 for each cheese to include only one to five terms that described the main flavor characteristics or HITS of each cheese. For example, in the flavor profiles, Brie cheese scored at low to moderate intensities for 20+attributes. In this study, Brie was described only as buttery, earthy and mold-ripened, terms that can be understood quickly and by many different people. This study suggests that the HITS method is a fast procedure that adds additional, general, user-friendly information to traditional descriptive analysis techniques.


This study provides a methodology that can be used by trained sensory panels to evaluate the high identity traits or HITS of products. Those HITS provide a general understanding of the product category and the differences among products in order to help management, marketing or consumers better understand product traits.