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Investigating Alcohol Sweetspot Phenomena in Reduced Alcohol Red Wines.

Duc-Truc Pham^1,2, Vanessa J Stockdale^3,4, David W Jeffery^5,6

¹School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1, Glen Osmond 5064, Australia. duc-truc.pham@adelaide.edu.au.

Foods (Basel, Switzerland)

|October 17, 2019

Summary

This study investigated the wine industry's 'alcohol sweetspotting' method for reduced alcohol wine (RAW). Results show that while sweetspots appeared, they were not reproducible, questioning the phenomenon's scientific validity.

Keywords:

alcohol adjustment evaporative perstraction one proportion test partial dealcoholization reverse osmosis sensory analysis

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Area of Science:

Enology
Sensory Science
Wine Chemistry

Background:

Rising wine alcohol levels due to climate and style impact sensory qualities.
Winemakers use technological innovations to create reduced alcohol wine (RAW).
Industry practice of 'alcohol sweetspotting' aims to optimize RAW ethanol content.

Purpose of the Study:

To scientifically validate the 'alcohol sweetspotting' phenomenon in RAW.
To assess the influence of sample presentation methods on sweetspotting outcomes.
To evaluate different statistical analyses for sensory data in RAW trials.

Main Methods:

Compared sample presentation orders (ordered vs. randomized, linear vs. circular).
Evaluated statistical analyses: chi-square goodness of fit and one proportion tests.
Assessed reproducibility of alcohol sweetspots across replicate trials and panelists.

Main Results:

Alcohol sweetspots were observed in some trials but lacked reproducibility.
The one proportion test enhanced detection of significant differences between RAWs.
Individual variations in sensory sensitivity to ethanol reduction hindered validation.

Conclusions:

The scientific evidence for the alcohol sweetspot phenomenon in RAW remains unsupported by this study.
Current sensory methodologies for alcohol sweetspotting require further validation.
Individual sensory perception variability poses a challenge for optimizing RAW.