Testing SensoGraph, a geometric approach for fast sensory evaluation
David Orden, Encarnaci\'on Fern\'andez-Fern\'andez, Jos\'e M., Rodr\'iguez-Nogales, Josefina Vila-Crespo

TL;DR
SensoGraph is a geometric method for rapid sensory evaluation that visualizes sample similarities and connections, offering a computationally efficient alternative to traditional consensus mapping techniques like MFA.
Contribution
Introduces SensoGraph, a novel geometric approach for sensory data analysis that provides complementary insights and handles larger assessor groups efficiently.
Findings
Provides similar sample positioning as MFA
Reveals additional connection information
Handles larger assessor groups efficiently
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…
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