Genetic traceability of ‘Nebbiolo’ musts and wines by single nucleotide polymorphism (SNP) genotyping assays

One of the characteristics of the terroir zoning studies that is more complex to manage is the scale dependence. Thus, terroir zoning studies of the same area at different scales are comparable but not equal. Fractal analysis has demonstrated to be a suitable tool to characterize and model natural elements within a defined range of scales.

In interaction with climate and genetic or human factors, the soil is a major component of the viticulture terroir. The mineral composition of the soil influences vine performance and wine sensory attributes. Among the elements that vines take from the soil, nitrogen is the one that has the strongest impact on vine physiology, vigor and grape composition. In addition to its major effect on primary metabolites in berries, nitrogen plays also a decisive role in the secondary metabolism, especially in the production of key compounds for berries quality, like volatile thiols, methoxypyrazines and glutathione (GSH).

Must clarification is an important step occurring just after grape extraction in the elaboration of white wine, consisting in a solid-liquid separation. Traditionally, low must turbidity, around 50-150 NTU, is generally reached in white winemaking in order to prevent reductive aromas and facilitating alcoholic fermentation. Alternatively, a higher turbidity (300 NTU or above) can be sought for reasons such as a better expression of grapes identity (terroir), or for getting a must matrix that could supposedly lead to wines having greater ageing potential.

Results in the characterization of a new wine terroir unit in south Brazil are reported. Presently, several areas in Brazil are being studied, in an effort to define new wine terroirs and improve the quality of Brazilian wines.

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.