HPLC and SEC analysis on the flavonoids and the skin cell wall material of Merlot berries reveals new insights into the study of the phenolic maturity

A critical aspect of wine quality is the overall expression of wine flavour, which is formed by the interplay of volatile aroma compounds, their precursors, and taste and matrix components.
Grapes directly contribute to wine only a small number of potent aroma compounds, and the unique
sensory attributes and perceived quality of a wine result from combining 100s of metabolites of grapes, yeast and bacteria, and oak wood.

In the last few years the development of HPLC techniques together with multivariate statistical methods allowed to set methodics of large discriminant and classing efficacy in the study of wine-grapes.

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.

White wines are commonly stabilised by removing the heat unstable proteins through adsorption by bentonite, an effective but inefficient wine processing step. Alternative absorbents are thus sought and zirconium dioxide (zirconia) is recognised as a promising candidate.

The present work contributes by developing a rapid sensory-directed methodology for the screening and selection of high quality wines with different sensory profiles Therefore, Verdejo and Tempranillo musts were fermented with 50 different yeasts each under controlled laboratory conditions. Resulting samples were firstly categorized according to five levels of quality by a panel of wine professionals (Sáenz-Navajas, Ballester et al. 2013). Higher quality samples were described by flash profiling by a semi-trained panel
(Valentin, Chollet et al. 2012) and most distinctive samples were screened by gas chromatography-olfactometry (GC-O) (López, Aznar et al. 2002).