Dispersive liquid-liquid microextraction for the quantification of terpens in wines

The timing of phenology is critical if grape quality potential is to be optimized. Phenological process based models are used to predict phenology. In this study, three different models

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.

Recently, there has been a shift toward sustainable wine production, according to EU policy (F2F and Green Deal), to reduce pesticide usage, improve workplace health and safety, and prevent the impacts of climate change. These trends have gained the interest of consumers and winemakers. The cultivation of disease resistant hybrid grape cultivars (DRHGC), known as ‘PIWI’ grapes can help with these objectives [1]. This study aimed to profile white and red wines produced from DRHGC in South Tyrol (Italy). Wines produced from DRHGCs were compared with conventional wines produced by the same wineries. The measured parameters were residual sugars, organic acids, alcohol content, pigments and other phenolics by LC-QqQ/MS, colorimetric indexes (CIELab); and volatile profiles (HS-SPME-GCxGC-ToF/MS [2]).

The viticultural regions of the world have the advantage of a remarkable diversity of landscapes which are the reflection of the winegrowers’ capacity to adapt to the different geomorphological and climatic specificities of the terroirs, more generally speaking, this aesthetic and heritage aspect of the terroir is also part and parcel of the notion of sustainable viticulture.

One of the major problems affecting the viticulture sector is the quantity of plant protection products (especially copper) used to control the main foliar diseases of the vine. The Life Green Grapes project enter in the production context with the aim of reducing the use of fungicides throughout