Orthonasal and retronasal detection thresholds of 26 aroma compounds in a model alcohol-free beer: Effect of threshold calculation method. (September 2019) - Piornos, José A.; Delgado, Alexia; de La Burgade, Rémi C.J.; Methven, Lisa; Balagiannis, Dimitrios P.; Koussissi, Elisabeth; Brouwer, Eric; Parker, Jane K.
Abstract: Detection thresholds are used routinely to determine the odour-active compounds in foods. The composition of a food matrix, such as hydrophobicity or solids content, has an impact on the release of flavour compounds, and thus on thresholds. In the case of beer, thresholds determined in alcoholic beer may not be the same for alcohol-free beer (AFB). Therefore, the aim of this study was to determine detection thresholds for aroma compounds typically found in beer, within a model AFB. The model was designed to match the sugar concentration and pH of an AFB brewed by a cold contact process. Thresholds were measured using a 3-AFC procedure and calculated using either Best Estimate Threshold (BET) method or by logistic regression. Moreover, an algorithm for the removal of false positives was applied to adjust the assessors' raw responses. Retronasal thresholds were generally lower than orthonasal. Those calculated by BET were significantly higher ( p < 0.05) than those from logistic regression, and removal of false positives also produced significantly higher thresholds than those from raw data. The use of logistic regression has the advantage of providing the mathematical model describing the behaviour of the group. The results from this study can be used to better understand the role of flavour compounds in AFB and the effect of the calculation method to prevent under- or overestimated results. Graphical abstract: Unlabelled Image Highlights: Aroma thresholds for 26 compounds were determined in an alcohol-free beer matrix. Polar compounds showed an increase in orthonasal aroma thresholds in this matrix. Methods for calculating aroma thresholds from 3-AFC tests were compared. Best Estimate Thresholds gave significantly higher values than logistic regression. Results and confidence intervals were affected by the presence of false positives.