Effects of abscisic acid treatment on Vitis vinifera L. Savvatiano and Mouchtaro grapes and wine characteristics

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

In the Burgundy vineyard, frequent tractor traffic and management of inter-rows alternating grass cover and chemical weed-control lead to structural soil contrast between row and inter-row. The aim of this study was to characterize and model water flow in relation with topsoil structure modifications induced by these practices. Void ratio of the different soil volumes were determined using bulk density measurements.

Climate change is altering water balances, thereby compromising water availability for crops. In grapevine, the strategic selection of genotypes more tolerant to soil water deficit can improve the resilience of the vineyard under this scenario. Previous studies demonstrated that root anatomical and morphological traits determine vine performance under water deficit conditions. Therefore, 13 ungrafted rootstock genotypes, 6 commercial (420 A, 41 B, Evex 13-5, Fercal, 140 Ru y 110 R), and 7 from new breeding programs (RG2, RG3, RG4, RG7, RG8, RG9 and RM2) were evaluated in pots during 2021 and 2022.

The application of remote and proximal sensing in viticulture have been demonstrated as a fast and efficient method to monitor vegetative and physiological parameters of grapevines. The collection of these parameters could be highly valuable to derive information on associated yield and quality traits in the vineyard. However, to leverage the informative potential of the sensing systems, a series of preliminary evaluations should be carried out to standardize working protocols for the specific features of a winegrowing area (e.g., pedoclimate, topography, cultivar, training system). This work aims at evaluating remote and proximal sensing systems for their performance and suitability to provide information on the vegetative, physiological, yield and qualitative aspects of vines and grapes as a function of different training systems in the Valpolicella wine region (Verona, Italy).

The crunchy texture of table grapes is one of the key quality parameters during production. This varies from cultivar to cultivar, stage of harvest and vineyard performance. Cell wall properties are key drivers of berry quality (e.g., pericarp firmness and intactness) at harvest and beyond. Common practise amongst producers is to continuously monitor firmness by evaluating pericarp appearance of cross-sectioned berries prior to harvest. These qualitative methods can be quite arbitrary and imprecise in their execution, but more quantitative, yet simple and high-throughput methods to evaluate these cell wall polymers are not yet readily available.