Effects of Blending on Phenolic, Colour, Antioxidant and Aroma Components of Cabernet Sauvignon Wine from Xinjiang (China)

Abstract

High-quality wines in industrial winemaking frequently require a professional winemaker to make adjustments according to the wine of single-batch fermentation. Blending can improve the chemical composition and certain organoleptic properties of wine, promote copigmentation, and increase the complexity of the wine body and aroma. In this study, high-performance liquid chromatography (HPLC) and headspace solid-phase microextraction with gas chromatography coupled to tandem mass spectrometry (HS-SPME-GC-MS/MS) were used to study the effects of adding 20% of Merlot, Marselan, Syrah and Pinot Noir and different blending methods on the nutritional, taste, color and aroma components of Cabernet Sauvignon wine. The results showed that the highest total phenols and flavonoids, the greatest content of antioxidant characteristics, the optimal color according to the parameter of T, red% and blue% and the most abundant aroma were observed both in CGM (grape blending Cabernet Sauvignon and Merlot) and CGS (grape blending Cabernet Sauvignon and Marselan), thus indicating the higher quality and complexity of these wines. In addition, the co-grapes treatment afforded more color and hue value than co-wines, which indicates co-grapes had more stable and more varied colors than co-wines. Our findings provide theoretical support for improving wine quality and craftsmanship.

Keywords: antioxidant activity; blending; color; organic acids; phenolic compounds; variety; volatile components.

Figure 1

The organic acid content of wine samples from different varieties and blending methods. The monovarietal wine: Cabernet Sauvignon (CS), Merlot (ML), Marselan (MS), Syran (SY) and Point Noir (PN); (CGM (CS:ML = 80:20), CGS (CS:MS = 80:20), CGY (CS:SY = 80:20), CGP (CS:PN = 80:20)) by co-grape treatment; CLM1 (CS:ML = 90:10), CLM2 (CS:ML = 80:20), CLM3 (CS:ML = 70:30) by co-wines treatment.

Figure 2

The composition of total phenol, total flavonoid, total anthocyanin and proanthocyadin of wine samples blended with different varieties and blending methods.

Figure 3

Monomeric phenol content of wine samples (mg/L) from different varieties and blending methods.

Figure 4

The antioxidant properties (mM TEs/L) of wine samples with different varieties and blending methods.

Figure 5

The correlation between phenolic compounds and antioxidant activity. Strong and weak correlations are indicated by the large and small circles, respectively. The color of the scale bar denotes the nature of the correlation; 1 indicates a perfect positive correlation (red) and -1 indicates a perfect negative correlation (green). Significant correlations p ≤ 0.05) is indicated by *.

Figure 6

The analysis of colorimetric indices in wine samples: (A) Colour intensity (CI) and tint (T); (B) %Red; %Yellow and %Blue; (C) l*, a*, b*; (D) C*, H*, E*. The * is part of the full name to distinguish it from the letters l, a, b, C, H, E.

Figure 7

The composition of volatile compounds in wines (A). The upset diagram of the wine samples (B). Black dots indicate the common aroma compounds in the sample. Different colors represent different treatments and a common number of aroma compounds. The total ion chromatogram of wine samples (C).

Figure 8

Heatmap cluster analysis of wine samples with different varieties and blending methods.

Figure 9

Principal component analysis (PCA) (A) and the loadings plot (B) of volatile compounds. Figure (A) includes all sample names. The serial numbers A1 to F5 in the chart on the right delegate the volatile compound names in Figure (B), respectively.

Figure 10

Description of aroma series of wine samples (A). The sensory analysis of Monovarietal wines (B). The sensory analysis of wine samples with co-grapes treatment (C). The sensory analysis of wine samples with co-wines treatment (D).