Inhibition of Oenococcus oeni during alcoholic fermentation by a selected Lactiplantibacillus plantarum strain

Aim: Regional characters relating to Shiraz in Australia are not well documented. This study aimed to characterize the sensory, chemical and climate profiles of wines from various Australian Shiraz producing regions. 

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.

A major problem for winemakers is the formation of proteinaceous haze after bottling. Although the exact mechanisms remain unclear, this haze is formed by unfolding and agglomeration of grape proteins, being additionally influenced by numerous further factors.

The French viticultural appellation areas are the result of an empirical, historical and evolutionary selection which, generally, has consecrated a match between natural factors, grape varieties and viti-vinicultural practices. The notion of terroir is the main basis of the Appellation d’Origine Contrôlée in viticulture. It is based on the one hand on privileged natural factors and on the other hand on the know-how of the winegrowers; the whole allowing the production of a wine endowed with an authenticity and a sensory typicity. Wine-growing practices evolve according to progress in viticulture and oenology, while the natural factors of the terroir are much more stable, with the exception of the vintage. They therefore represent a fundamental pillar of the identity of an appellation vineyard.

The chemical composition of grape berries at harvest is one of the key aspects influencing wine quality and depends mainly on the ripeness level of grapes. Climate change affects this trait, unbalancing technological and phenolic ripeness, and this further raises the need for a fast determination of the grape maturity in order to quickly and efficiently determine the optimal time for harvesting. To this end, the characterization of variety-specific ripening curves and the development of new and rapid methods for determining grape ripeness are of key importance.