Hyperspectral imaging and machine learning for monitoring grapevine physiology

Downy mildew is one of the most important grapevine diseases, caused by the Oomycete Plasmopara viticola. The management of the disease in organic agriculture can require up to 15 copper applications per year. However, copper accumulates in the soil, is phytotoxic and is toxic for organisms living in the soil, its use has been restricted in European Union to maximum 28 kg in 7 years. Therefore, testing of alternatives with equal effectiveness is desirable. Among those, the natural biopolymer chitosan, obtained from crab shells, proved to be effective toward downy mildew in plot experiments. The aim of our trials was to extend chitosan applications in large scale experiments in different years, cultivars and environmental conditions.

The Valpolicella area (Veneto Region, Italy) is famous for its high quality wines: Amarone and Recioto, both obtained from partial post-harvest dehydrated red grapes.

Red wine is a beverage with one of the highest polyphenol concentration, which are extracted during the maceration step of the winemaking process.

Wine cellars are affected by seasonally fluctuating workloads and face challenges especially in the harvest period connected to the required timely processing of the harvested grapes.

The ability of grapevine cultivars and rootstocks to cope with and adapt to recurring water constraints is the focus of this study. The contribution of intrinsic (epigenetic) and extrinsic (rootzone microbial community) factors to water stress resilience will be discussed. The study was conducted in a validated model vineyard where three scion cultivars (Pinotage, Shiraz, and Cabernet Sauvignon) on two rootstocks (Richter 110 and USVIT8-7) grow under recurring seasonal water constraint (and control) scenarios since planting (in 2020). Comprehensive profiling of the site, soil, atmospheric conditions, plants, and their physiological responses provide contextual data for the analyses conducted.