Using Latent Semantic Analysis to Investigate Wine Sensory Profiles—Application in Swedish Solaris Wines

Online text is a source of data in many fields, but it is yet to be explored by sensory scientists. The present work aimed to explore the suitability of using a bibliometric methodology such as Latent Semantic Analysis (LSA) to understand and define wine sensory spaces. Data were also explored by the more conventional Multiple Correspondence Analysis (MCA). The present work shows the potential use of LSA in sensory science; the first part of the study investigates the sensory profile of Swedish Solaris wines, while the second part focuses on understanding their fit with two international monovarietal white wines (Albariño and Chenin Blanc). The results show that the majority of Swedish Solaris wines could be associated with two different styles (LSA topics). However, there is no evidence of a cultivar typicality, as when comparing the Solaris wines with Albariño and Chenin Blanc, they shared features with both cultivars. Chenin Blanc was also found to be associated with different styles. In contrast, Albariño wines showed to have more unique features as the majority were associated with a single LSA topic.