Chemical boundaries of wine identity: rationalizing grape and wine aroma diversity for improved terroir management

Seedless table grapes are greatly appreciated for fresh and dry consumption. There is also some interest in seedless winegrapes, because the combination of lower fruit set, smaller berries with higher skin/pulp ratio and looser bunches with the absence of seeds in crushed berries, a possible source of astringent tannins, might also have favorable effects on wine quality.
The gene VviAGL11 has been shown to play a central role in stenospermocarpy in Sultanina, but the molecular bases of other sources of stenospermocarpy as well as of parthenocarpy have not been clarified yet.

Wine perception results from the interaction between the wine and its intrinsic and extrinsic characteristics and the experience [1], background and beliefs of the consumer [2,3]. Among all of the factors affecting wine perception, in this study we focused on culture and cognitive processes, working under the hypothesis that higher familiarity with wines would induce higher perceived quality. Furthermore, we hypothesised that culture would influence the verbalisation of wine properties associated with the different experiences of consumers from different cultures.

Terroir method has been used for assessment of growing site in the world for years. In Slovakia actually regionalisation is used as the similar method which does not cover all the elements of wine quality evaluation however.

Terroir zoning studies have to manage the heterogeneity and complexity of the landscape properties and processes. The varying geology is one of the main landscape properties conditioning the spatial variability of terroirs.

Unmanned Aerial Vehicles (UAVs) are increasingly used to monitor canopy structure and vineyard performance. Compared with traditional remote sensing platforms (e.g. aircraft and satellite), UAVs offer a higher operational flexibility and can acquire ultra-high resolution images in formats such as true color red, green and blue (RGB) and multispectral. Using photogrammetry, 3D vineyard models and normalized difference vegetation index (NDVI) maps can be created from UAV images and used to study the structure and health of grapevine canopies. However, there is a lack of comparison between UAV-based images and ground-based measurements, such as leaf area index (LAI) and canopy porosity.