Arsenic in berries and its correlation with natural soil content: experience in Trentino (Italy)

In this video recording of the IVES science meeting 2024, Stéphane La Guerche (Œnoppia, Paris, France) speaks about wine labelling with the list of ingredients: context, consumer’s perception and future challenges. This presentation is based on an original article accessible for free on IVES Technical Reviews.

In view of sustainability and zero-waste initiatives, the valorisation of sidestreams is a key emerging topic in the wine industry.

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.

Recent wine-like reconstitution sensory studies confirmed that several monoterpenes were the key aroma compounds in the perception of an ‘apricot’ aroma attribute in Viognier wine.

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