Tormod Næs has coauthored the paper “A new approach in TDS data analysis: a case study on sweetened coffee” which has been accepted for publication in Food Quality and preference. TDS is an acronym for Temporal Dominance of Sensations, and is a technique for recording record several sensory attributes simultaneously over time and is used to study how sensory properties of food and drinks change during consumption.
TDS data are difficult to handle with statistical methods generally used to validate and analyze sensory data set. Summarizing subject responses as frequency values in a given number of time periods instead of considering all the acquisition time points has recently be proposed to obtain data matrix to be handled by ANOVA models. In this work a methodology for validation and analysis of TDS data transformed in frequency values is proposed to study the temporal evolution of sensations in coffee added with three different sweeteners. Criteria for selecting the most appropriate TDS curve splitting in time period for frequency value computation are discussed. ANOVA models on frequency values are proposed to estimate differences in attribute dominance among products and to test the effect of collecting intensity ratings along with TDS evaluations on the frequency with which attributes were selected as dominant.
Authors and affiliations:
Caterina Dinnella, Camilla Masi, Tormod Næs and Erminio Monteleone
The other authors are from Departement of Agricultural Biotechnology, University of Florence