Investigating the role of endophytes in enhancing grapevine resilience to drought

Evaluation of the fertility management practices in wine grape varieties production. Wine grape represents one of the most important productions in Greece with major impact to the socioeconomic characteristics of the country. The objective of this study is to evaluate, with the support of Geospatial Technologies, the potential effects of an innovative foliar fertilizer system, which is composed of three parts: a mineral fertilizer in a micronized formulation, a biostimulant as an enhancing factor of the process and, an amino acid compound (SANOVITA concept). The study was established at a collaborative, private vineyard, in the area of Trilofos-Thessaloniki, at the region of Northern Greece.

Carmenère fruit during ripening of a Vertical shoot positioning, VSP, trained experimental vineyard with north-south row orientation.

The effects of anthropogenic activities on vineyard (different plant protections) and in winery
(pressing/clarification step, addition of sulfur dioxide) on fungal populations from grape to wine were studied. The studied anthropogenic activities modify the fungal diversity. Thus, lower biodiversity of grapes from organic modality was measured for the three vintages considered compared to biodiversity from ecophyto modality and conventional modality. The pressing / clarification steps strongly modify fungal populations and the influence of the winery flora is highlighted.

The need to mitigate the yield impact of Spring frosts in vineyards remains a significant challenge around the world.

Grapevine yield and fruit quality are two major drivers of input allocation and, ultimately, revenue for grape producers. Because yield and fruit quality vary substantially from year-to-year and within a single block, opportunities exist for optimization via precision management activities that could lead to more profitable and sustainable grape production. Here, we review recent advances in the techniques and technology used to measure, estimate, and forecast grapevine yield and fruit quality. First, we discuss direct “measurement” of yield and quality (i.e. ground-truth data generation), with an emphasis on potential for scalability and automation. Second, we discuss technology and techniques that do not directly measure yield and quality, but use correlated measurements for their estimation.