Using a grape compositional model to predict harvest time and influence wine style

Initiatives have been ongoing in recent years to safeguard biodiversity in the oenological sector via a process of enhancement of ancient varieties, under a pressure of a market strongly oriented towards production deriving from native vines of specific geographical zones. In that sense, Aosta Valley
(Italy) has raised the need to preserve and characterize its minority vine varieties which have the potentiality to give varietal wines. Fumin represents the 7% of the production of the region with 16 hectares of vineyards and 753 hectolitres of derived wine. Due to its large phenolic potential, strong astringency and deep colour, it has long been, and is still today, assembled or blended with other varieties as occurs, for example, for the Torrette.

Grapevine rootstocks have traditionally been chosen in order to manage scion vigour, soil pests and soil conditions. Riparia Gloire de Montpellier (RGM) has been in use since the turn of the 19th century, over 100 years and still a remarkably stable source of phylloxera (Daktulosphaeria vitifoliae Fitch) resistance. The original source material was probably collected near the Missouri/Mississippi river confluence, a mid-continental but more southerly location in the United States. It has been hypothesized that more northerly selections of V. riparia Michx might improve both fall acclimation rate and depth of the scion, thus mitigating late fall frost and midwinter freeze damage.

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.

Anthocyanins and tannins contribute to important sensorial traits of red wines, such as color and mouthfeel attributes.

The study analyzes a set of open innovation actions promoted by the innovation environments of the Instituto Federal do Rio Grande do Sul (IFRS), in cooperation with entities, companies in the sector and the Department of Innovation, Science and Technology of Rio Grande do Sul.