A multivariate clustering approach for a gis based territorial characterization of the montepulciano d’abruzzo DOCG “Colline Teramane”

Pressing has a relevant impact on the characteristics of the must and subsequently on white wines produced [1]. Therefore, the adequate management of pressing can lead to the desired extraction of phenols and other grape compounds (i.e. Organic acids), aromas and their precursors, allowing the production of balanced wines [2]. This aspect is especially important to sparkling wine where the acidity and pH, and the content of phenols affect its longevity and the expected sensory character.

Over the last decades, climate change and rising temperatures have impacted the wine industry. Wines from warm regions tend to have a higher pH and lower total acidity.

The application of remote and proximal sensing in viticulture have been demonstrated as a fast and efficient method to monitor vegetative and physiological parameters of grapevines. The collection of these parameters could be highly valuable to derive information on associated yield and quality traits in the vineyard. However, to leverage the informative potential of the sensing systems, a series of preliminary evaluations should be carried out to standardize working protocols for the specific features of a winegrowing area (e.g., pedoclimate, topography, cultivar, training system). This work aims at evaluating remote and proximal sensing systems for their performance and suitability to provide information on the vegetative, physiological, yield and qualitative aspects of vines and grapes as a function of different training systems in the Valpolicella wine region (Verona, Italy).

Context and purpose of the study. Daylength is a key climatic factor within the terroir concept. However, the complex interplay of multiple variables in regions with varying daylengths makes it challenging to isolate and investigate this specific factor.

Random sampling is often considered to be the best protocol for fruit sampling because it is assumed to produce a sample that best represents the vineyard population.