Tannin potential and molecular toasting in cooperage: a tool to modulate fruity expression of red wine

The aromas found in young Bordeaux red wines made with Merlot and Cabernet Sauvignon suggest a complex mixture of aromas of fresh red fruits such as cherry or blackberry for Merlot, and strawberry or blackcurrant for Cabernet Sauvignon. The aromas of these wines are closely linked with the maturity of the grapes. The climate change that has occurred during the last decade in Bordeaux has induced changes in the ripening conditions of grape berries. It is now widely admitted that over-ripening of the berries during hot and dry summers results in the development of characteristic flavors reminiscent of cooked fruits (fig, prune). The presence of these overriding odors found in both musts and young wines affects the quality and subtlety of the wine flavor and may shorten its shelf life.

The current energy crisis means that interest in agrophotovoltaics has increased significantly. The reason behind this is that the system aims to combine agricultural production with energy production. During the three-year period from 2020 to 2022, the effects of photovoltaic panels on the vine, the yield and the quality of the must were studied in Walenstadt in northern Switzerland, an area with a cool, humid climate. 65 Pinot noir vines were planted in the 160m2 study area. Because of the large edge effects, only 3 repetitions with 4 vines each could be created. A significantly lower leaf infestation by Plasmopara viticola was observed among the panels in each of the three years.

There is currently a real need to improve and speed-up phenotyping in experimental set-ups to increase the number of modalities studied. Accurate information acquisition on plant status with high-throughput capacity is the main appeal of on-board systems.
A proximal sensing camera for a proxy of winter pruning weight was tested. We estimated the shoot volume of the vine by image analysis using algorithms that integrate the local shoot section area estimate along the shoot skeleton obtained by a morphological distance transform.
The study was carried out on the GreffAdapt experimental vineyard in Guyot simple training and a canopy management using vertical trellising. The planting density is 6250 vines/ha with a row spacing of 1.6×1m. Five scions grafted onto 55 rootstocks are present and the combination rootstock×scion is different every five plants.

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.

Erysiphe necator Schwein is a fungus that causes grapevine powdery mildew. It is one of the most problematic pathogens attacking Vitis vinifera L. The pathogen infects all green parts of the plant and reduces grape yield and quality. The suppression on mildew-susceptible cultivars requires intensive use of fungicides against pathogen, which has negative impact on the environment and human health.