Viticultural Climatic Zoning and Digital Mapping of Rio Grande do Sul – Brazil, using Indices of the Géoviticulture MCC System

Wine perception results from the interaction between the wine and its intrinsic and extrinsic characteristics and the experience [1], background and beliefs of the consumer [2,3]. Among all of the factors affecting wine perception, in this study we focused on culture and cognitive processes, working under the hypothesis that higher familiarity with wines would induce higher perceived quality. Furthermore, we hypothesised that culture would influence the verbalisation of wine properties associated with the different experiences of consumers from different cultures.

Today, there is need to design, produce and label terroir wines, with unique organoleptic properties and more “attractive to consumers”. For this purpose, two Saccharomyces cerevisiae yeast strains (Sa and Sb) isolated during spontaneous fermentations were used for white wine production from the Assyrtiko grape of Santorini. A third commercial strain was used as control.

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.

Sauvignon blanc is the most important variety in cool valleys in central Chile accounting 15,522 ha which corresponds to 42.4% of the cultivated surface with white varieties in Chile

Se justifica la utilización de los mapas de suelos detallados y muy detallados como instrumento fundamental en los estudios de microzonificación.