Studies on the Enhancement of Sparkling Wine and Chocolate Pairing through Compositional Profile Analysis

Consumers are looking to experience as many interesting culinary combinations as possible, and there is a growing tendency to associate wine with various foods. Although there are some studies associating wine with chocolate, especially red wine, no articles have been published referring to sparkling wines. Therefore, the purpose of this investigation was to identify the taste compatibility and sensory synergies between sparkling wine and chocolate, with a focus on identifying combinations that can enhance the tasting experience. For this experiment, 14 variants of sparkling wines obtained in Romania and 5 chocolate assortments were evaluated to identify the best culinary match. White chocolate fitted better with Chardonnay-demi-dry sparkling wine; ruby chocolate presented a good match with Fetească neagră-demi-dry; milk chocolate with 32% cocoa powder associated better with Tămâioasă românească-sweet; and dark chocolate with 70% and 95% cocoa powder had synergic matches with Fetească neagră-sweet. Wine attributes like sweetness, acidity, alcoholic strength and chocolate composition significantly impacted the level of match.

Flavor and Rapid Prediction of Red Wine by the Chemometrics Algorithm Based on Multidimensional Spectral Data

Since its birth, red wine has been loved by people of all walks of life. The taste of red wine has changed and the pursuit of quality has always been the most sought-after goal by sommeliers, winemakers, and the public. However, due to the rich taste of red wine, any link is willing to produce different flavors. At present, there is no quantitative control study on the flavor of red wine. The purpose of this paper is to analyze the flavor of red wine through the chemometric algorithm and establish a reasonable model to predict the flavor of red wine. Aiming at the research of red wine flavor, this paper designs a red wine flavor extraction experiment and extracts the substances that produce an aroma and flavor in red wine to the greatest extent through strict selection of extraction head and reaction time. For the rapid analysis of red wine flavor, this paper quantitatively describes the chemical category, volatilization time, molecular weight, etc., of flavor substances by analyzing the multidimensional spectral data of red wine, so that flavor substances can be quickly located. The experimental results of this paper prove that, for different red wines, the algorithm in this paper can accurately identify the flavor substances in red wine. Also, for red wine multidimensional spectral data, the algorithm in this paper can improve the accuracy by 30% and save the running time by 30%. This shows that the research in this paper can analyze and quickly predict the flavor of red wine.