A novel dataset and deep learning object detection benchmark for grapevine pest surveillance

The dynamic evolution of some bioclimatic indices largely used to define the vocation of areas to grape growing was assessed over 43 years (1965-2007) in four sites of the Abruzzo Region (Central Italy).

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).

Planting vineyards in cooler climates has been used over recent years as
a strategy to counter the climatic shifts caused by climate change. A move towards higher altitudes in hilly and mountainous wine regions may provide a solution to deleterious effects that increased ambient temperatures have on wine quality. Until now, the influences of higher altitudes and their climates, as well as their effect on vine growing cycles, still holds a lot of scientific uncertainty. The transnational EU-funded project REBECKA (Interreg V-A IT-AT: ITAT1002, duration: 2017-2019) has the objective to develop a regional valuation method to rate the suitability for viticulture in South Tyrol (Italy) and Carinthia (Austria). Preliminary surveys were performed regarding the effects of altitude on ripening performance of the cultivar Pinot Noir.

Climate is clearly one of the most important factors in the success of all agricultural systems, influencing whether a crop is suitable to a given region, largely controlling crop production and quality, and ultimately driving economic sustainability. Today many assessments of a region’s climate comes from a combination of station and spatial climate data analyses that facilitate the evaluation of the general suitability for viticulture and potential wine styles, allows for comparisons between wine regions, and offers growers a measure of assessing appropriate cultivars and sites.

Rachis browning is a common abiotic stress that occurs during postharvest storage, leading to a decrease in commercial value of table grapes and resulting in significant economic losses. Its early detection could enable the implementation of preventive strategies. In this report, we show the feasibility of a non-destructive early detection of browning based on Hyper Spectral Imaging (HSI). Furthermore, rachis samples were subjected to transcriptomic analysis to understand putative pathways causing differences in browning within varieties.