The terroir of winter hardiness: a three year investigation of spatial variation in winter hardiness, water status, yield, and berry composition of riesling in the niagara region using geomatic technologies

Regarding the food quality, authenticity is one of the most important issues in the context of ensuring the safety and security of consumers, but is also more important when it comes to wine (one of the most counterfeited foods in the world).

The color is the first attribute perceived by consumers and a major factor determining the quality of red wines. This depends mainly on the content of grape anthocyanins and their extraction into the juice/wine during winemaking. Furthermore, these compounds can undergo reactions that influence the chemical and sensory characteristics of the wine. Monomeric forms are prone to oxidation and adsorption on solid parts.

Aims: Due to climate change and the desire to decrease enological inputs (organic farming), the vineyard has to be modified and the selection of new resistant grape varieties as an alternative is researched intensively today. From January 2018, four new grape varieties that are resistant against mildew and odium have been added to the official

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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.