FIRST APPLICATION OF LACHANCEA THERMOTOLERANS IN THE FERMENTATION OF “VINO SANTO” AS BIOLOGICHAL ACIDIFIER.

During wine aging many compositional changes take place. In particular, aroma undergoes dramatic modifications through a wide range of reactions that to date are only partly understood. Italy owns one of the largest ampelographic heritages worldwide, with over three-hundred different varieties. Among these, many white grapes are employed for the production of dry still white wines. Some of these wines are consumed young while others are more prone to aging. For many of these wines, the aging patterns related to volatile composition are still unknown.

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.

Winemaking is a globally significant industry in the field of food technology (218 mhL of wine estimated for 2024 harvest) [1], which activity produces tons of by-products annually, including pomace (pulp, stems, seeds, skins), lees, organic acids, CO2, and water [2].

One of the consequences of global warming is the quick berry development giving rise to a disconnection between sugar accumulation and the formation of important quality minor compounds such as phenolics and volatile compounds being a huge challenge for the oenologist [1]. Thus, this phenomenon is forcing the search on strategies for maintaining the quality of wines despite this situation. One possibility is to make an early harvest with a low sugar concentration (18ºbrix) and advanced harvest for sparkling wine (20-21ºbrix) and afterwards to combine base wines properly and carry out the second fermentation trying to compensate the lack of secondary metabolites due to the quick berry development and higher alcohol degree of the second one, not adequate itself for sparkling wine. The aim of this study was to assess the chemical and physical characteristics, mainly volatile profile, and foaming properties of sparkling wines from grapes of Chardonnay and Sauvignon blanc.

UV-Visible spectroscopy in conjunction with chemometrics, was successfully applied to objectively differentiate sparkling wine press juice fractions of Pinot noir. Two measurements methods were applied: reflectance using a fibre optic probe in-line and transmission using a benchtop spectrophotometer.