## 2 Results and Discussion
### Sensory Profiling  
Wine flavor is without a doubt a very important wine quality indicator. For the elucidation of the differences in wine flavor among the 27 studied wines, a trained sensory panel evaluated all the wines as described in [25]. The panel used 27 aroma, taste and mouthfeel attributes to describe the perceived sensory differences among the wines. Of these attributes, 21 differed significantly among the wines (17 aroma terms: overall aroma, alcohol, Brett (_i.e._, aromas reminiscent of medicinal, leather, horse sweat, or barnyard, depending on the concentration and strain of the wine spoilage yeast _Brettanomyces bruxellensis_), canned vegetable, chemical, dark fruit, dried fruit, earthy, fresh green, fresh vegetable, oak, red fruit, smoky, soy sauce, spicy, sulfur, sweet aroma; two taste terms: sweet, bitter; two mouthfeel terms: astringent, hot), using analysis of variance (ANOVA) at a significance level of 5%. These significantly different attributes were used in a principal component analysis (PCA) to display the sensory differences among the 27 wines shown in Figure 1. Using the Kaiser criterion (_i.e._, all dimensions with eigenvalues above 1) and the scree test (_i.e._, observation of a \"knee\" when plotting the eigenvalues over the dimensions) the first two principal components (PCs) were kept, explaining 53% of the total variance. Wines were separated along the first principal component (PC 1), explaining 34% of the total variance, due to the large differences in oak and fruit compared to chemical and green aromas. Wines positioned on the left of the PCA score plot (Figure 1a) were rated high in descriptors that are associated with microbial and/or chemical spoilage (e.g., Brett, sulfur and chemical), and low in oak, sweet and various fruit aromas. Wines are color-coded according to the quality categories assigned in the wine competition (low quality, medium quality, high quality), but no separation due to wine quality is apparent along PC 1, as high quality wines are located next to low quality wines. It seems that the wine judges did not similarly score wines with very similar flavor profiles. Along PC 2, explaining another 19% of the total variance, mouthfeel and taste differences together with some aromas contribute to the separation of the wines. Wines W17, W24, W20, and W5 scored higher in astringency, and lowest in fruit aromas and sweet taste. Again, no separation of the wines due to their quality categories is apparent. To study if individual sensory descriptors indicate high or low quality, correlations of each sensory descriptor to the various quality indicators--points awarded in the wine competition (\"points\"), geographical origin of the vineyards (\"regions\"), wine vintage (\"vintage\"), retail bottle price (\"price\"), and expert liking scores (\"experts\")--were carried out. None of the sensory descriptors correlated significantly to the points awarded at the wine competition, while the wine expert ratings showed significant negative correlations to the aromas of soysauce (\(r(25)=-0.55\), \(p<0.05\)), and fresh green (\(r(25)=-0.41\), \(p<0.05\)). This could be explained two-ways. In the first explanation, judges at the wine competition did not use similar sensory frameworks when judging the wines and/or were not consistent in their assessment of quality, while the wine experts showed more agreement in their judgment. This explanation is supported by the studies by [PERSON] (2010) and [PERSON] _et al._[PERSON] _et al._ (2012). It is also supported by the fact that no descriptive framework was used in the wine competition. Judges were asked to rank tasted wines according to their individual criteria, and no system for judges' alignment was used. Therefore, individual differences in quality perception are most certainly contributing to the final points awarded to the wines. The second explanation could be that (high) quality is not driven by individual sensory descriptors, but is the result of several descriptors acting together.