Analysis of climate spatio-temporal variability in the Conegliano-Valdobbiadene DOCG wine district

Among the different strategies to cope with the negative impacts of climate change on viticulture, the exploitation of genetic diversity is one of the most promising to adapt to new conditions and maintain wine production and quality. One of the biggest concerns in the context of climate change is to improve water use efficiency (WUE). In this way, the use of genotypes that present a better response to drought and high WUE is a key issue. In this work, physiological performance analysis was conducted to compare the water deficit stress (WDS) responses of local and widespread grapevines cultivars. Leaf gas exchange, water use efficiency (WUE) at different levels (leaf and long-term WUE (∆13C)), leaf osmotic adjustment and other water relations parameters were determined in plants under well-watered and WDS conditions alongside assessment of the levels of foliar hormones concentrations. Results denote that local cultivars displayed better physiological performance under WDS as compared to the widely-distributed ones. he results corroborate the hypothesis that better stomatal control allows increasing leaf WUE under drought as occurred in the local Callet cv.; but the minority local cultivar Escursac cv. showed high WUE under both treatments. In this case, high WUE can be related to maintaining higher photosynthetic activity under drought. The different mechanisms underlying the better performance under WDS and high WUE of minority local cultivars are discussed.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

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Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.

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