Model construction for characterizing the flavor quality of dry red wine based on polyphenolic indexes

Dry red wines can be sourced from the Ningxia and Xinjiang regions of China. This study aims to characterize the taste quality, according to the conventional and easily measurable polyphenol series indices. The UV-Vis spectrophotometer was used to detect the conventional polyphenols in wine. A predictive model was constructed to evaluate the astringency and aftertaste of dry red wine using the polyphenol indices. A total of 50 (Cabernet Sauvignon) dry red wines were selected as the research objects (20 from Ningxia and 30 from Xinjiang, each from different small producing areas). The total acidity, volatile acidity, and pH of the wines were tested to evaluate the acidity, according to GB/T 15038-2006. The antioxidant activity of wine was determined by DPPH scavenging activity. Total phenols were determined with the UV-Vis spectrophotometer using the Folin-Ciocalteu method. Flavanol content was determined by p-DMACA hydrochloric acid. The contents of tartrate (A₃₂₀), flavonol (A₃₆₀), and total anthocyanins (A₅₂₀) in the wines were determined at different absorbance levels. The aftertaste and astringent sensation were evaluated using the quantitative sensory description in Panel Check software. Correlation analysis (CA) was used to analyze the interaction between the indices of the wine polyphenol series, and linear discriminant analysis (LDA) was to easily distinguish different regions. The modeling samples were analyzed with the principal component analysis. The taste quality of wine samples was characterized and predicted with partial least squares regression. The CA results indicated that there were significant differences (P<0.05) in the effects of total phenols, anthocyanins, flavanols, and flavonols on the astringency and aftertaste of the dry red wines. However, there was a minimal impact of tartrate on the aftertaste. Furthermore, the total acids and pH had no significant (P>0.05) effect on the astringency of the wine. Taking the Yongning region of Ningxia as an example, LDA easily differentiated dry red wine samples from the Yongning of Ningxia and the Xinjiang region using polyphenol series indices. Two discriminant functions generated by LDA were used to explain 80.8% and 19.2% of the variance, respectively. The accurate discriminant rate of 80.0% was obtained after classification. While there was the correct discriminant rate of 62% after the cross-validation. The sensory evaluation showed that the astringency scores were 6.18 and 5.70, in Ningxia and Xinjiang wine samples, respectively, while the aftertaste scores were 5.37 and 4.85, respectively. Therefore, the total phenols, anthocyanins, flavanols, flavonols, and DPPH contributed significantly to the astringency and aftertaste of wine. Tartrate mostly influenced the wine astringency, whereas the total acids and pH dominated the wine aftertaste. Polyphenol indices with cost-saving UV-Vis spectrophotometers can be expected to better assess the taste quality of dry red wine. The sample size can be increased to promote the taste quality of dry red wine for the accuracy and stability of the model.