text: Abstract This paper introduces SensoGraph, a novel approach for fast sensory evaluation using two-dimensional geometric techniques. In the tasting sessions, the assessors follow their own criteria to place samples on a tablecloth, according to the similarity between samples. In order to analyse the data collected, first a geometric clustering is performed to each tablecloth, extracting connections between the samples. Then, these connections are used to construct a global similarity matrix. Finally, a graph drawing algorithm is used to obtain a 2D consensus graphic, which reflects the global opinion of the panel by (1) positioning closer those samples that have been globally perceived as similar and (2) showing the strength of the connections between samples. The proposal is validated by performing four tasting sessions, with three types of panels tasting different wines, and by developing a new software to implement the proposed techniques. The results obtained show that the graphics provide similar positionings of the samples as the consensus maps obtained by multiple factor analysis (MFA), further providing extra information about connections between samples, not present in any previous method. The main conclusion is that the use of geometric techniques provides information complementary to MFA, and of a different type. Finally, the method proposed is computationally able to manage a significantly larger number of assessors than MFA, which can be useful for the comparison of pictures by a huge number of consumers, via the Internet.
  @cite_6: "Sensory characterization is one of the most powerful, sophisticated and extensively applied tools in sensory science. This book focuses on sensory characterization of food and non-food products, providing an overview of classical and novel alternative methodologies. A complete description of the methodologies would be provided. Each description would be accompanied by detailed information for their implementation, discussion of examples of applications and case-studies. The implementation of the majority of the methodologies would be performed in the statistical free software R, which would make the book very useful for people non-familiar with complex statistical software"--
summary: Projective Mapping has been successfully used with many different kinds of products, among which the application to wine stands out . Other examples of beverages analysed by these methods are beers , citrus juices , drinking waters high alcohol products , hot beverages , lemon iced teas , powdered juices , or smoothies . The book by @cite_6 details more products to which consumer based descriptive methodologies have been applied.