Variety specific thresholds for plant-based indicators of vine nitrogen status

Since the use of sodium arsenite was banned in 2001, Grapevine Trunk Diseases (GTDs) have become even more widespread increasing (1).To avoid pathogen entry, pruning, an age-old practice, is increa- singly coming to the fore. As the vine is a liana (2), any excessive woody proliferation has to be stopped. This can preserve grapevine life, provided it does not damage the diaphragm.

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.

The Muscadet area is situated in the southeast of Nantes, close to the Atlantic coast. It constitutes the western extension
of the French vineyard “Loire Valley”. The Muscadet is renowned and often spontaneously linked to a white wine.
However it remains misconceived as an ordinary wine, lacking authenticity.

Most of the effects of ultrasound (US) result from the collapse of bubbles due to cavitation. The shockwave produced is associated with shear forces, along with high localised temperatures and pressures. However, the high-speed stream, radical species formation, and heat generated during sonication may also affect the stability of some enzymes and proteins, depending on their chemical structure. Recently, Ce-lotti et al. (2021) reported the effects of US on protein stability in wines. To investigate this further, the effect of temperature (40°C and 70°C; 60s), sonication (20 kHz and 100 % amplitude, for 20s and 60s, leading to the same temperatures as above, respectively), in combination with Aspergillopepsins I (AP-I) supplementation (100 μg/L), was studied on unstable protein concentration (TLPs and chitinases) using HPLC with an UV–Vis detector in a TLPs-supplemented model system and in an unstable white wine.

Catechins, a class of flavonoids found in foods and beverages such as wine and tea, exhibit potent antioxidant properties that contribute to various health benefits.[1]