«Aztec» – the new white table grape resistant variety

In many vineyards optimal parcel size exceeds the geospatial complexity that exists in soils and topographic features that influence hydrological properties, sunlight interception and soil depth and texture (available water capacity).

This study investigates the effect of wood chips addition during the alcoholic fermentation on the phenolic
composition of the produced wines. A series of wood chips, originating from American, French, Slavonia
oak and Acacia were added at the beginning of wine alcoholic fermentation. Besides, a mixture consisting
of 50% French and 50% Americal oak chips were added during the experimentation. The wine samples
were analyzed one month after the end of malolactic fermentation, examining various chemical
parameters such as total anthocyanins, total phenolic content, tannins combined with protein (BSA) and
ellagitannin content.

The definition of the term “quality” in sensory evaluation of food products does not seem to be consensual. Descriptive or liking methods are generally used to differentiate between wines (Lawless et al., 1997). Nevertheless, quality evaluation of a product such as wine can also relate to emotional aspects. As exposed by Costell (2002), product quality is defined as an integrated impression, like acceptability, pleasure, or emotional experiences during tasting. According to the ‘modality appropriateness’ hypothesis which predicts that wine tasters weigh the most suitable sensory inputs for a specific assess- ment (Freides, 1974; Welch & Warren, 1980), the nature of the quality definitions may modulate sensory influences.

Planting grape varieties with several resistance loci towards powdery and downy mildew reduces the use of fungicides significantly. These fungus resistant or PIWI varieties (acronym of German Pilzwiderstandsfähig) contribute significantly to the 50% pesticide reduction goal, set by the European Green Deal for 2030. However, wine growers hesitate to plant PIWIs as they lack experience in vinification and are uncertain, how consumer accept and buy wines from these yet mostly unknown varieties. Grapes from four white and three red PIWI varieties were vinified in three vintages to obtain four diffe-rent white and red wine styles, respectively plus one rosé.

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.