Description of the effect of the practical management in the characterization of « terroir effect »

Most consumers enjoy wine in moderation, however, there remains a minority that may develop risky drinking habits, potentially harming themselves and those around them. For the last fifteen years, a prime objective of the wine in moderation programme has been to educate and empower the wine sector and now for the first time, a central education tool has been developed, integrating the topic of moderate consumption horizontally in all wine activities. The entire wine value chain – from the producer to the salesperson to the restaurant service staff – can contribute to reduce harmful consumption and encourage responsible drinking patterns.

Minervois is a vine region where the first detailed soil map was begun 30 years ago. In 2003, a new map was drawn plotting the soil-landscape associations. This map distinguishes 8 large soil units based on geology. The widest (called « marnes ») is the most complex : it is made of 57 sub-units, which leads to a high variability of the vine behaviour on this unit.

Wines differ from each other based on seven different factors: the type of grape; the bedrock geology and resulting soils; the climate; the soil hydrology; physiography of the site; the winemaker and the vineyard management techniques. The first five of these factors make up what the French call terroir, “the taste of the place”.

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.

It is well known that lactic acid bacteria modify the wine volatile compound. However, very few data are available regarding metabolite changes that occurred during the malolactic fermentation (MLF).