Interaction Between Armenian Clay-based Ceramic and Model Wine

An appellation or geographic indication should be based on the terroir concept in order to ensure its integrity. The delimitation of viticultural terroirs must include two consecutive or parallel steps, namely (a) the characterisation of the environment and identification of homogenous environmental units (basic terroir units, natural terroir units) taking all natural factors into account, as well as (b) the characterisation of the viticultural and oenological potential of these units over time.

The aim of this study was to evaluate the effects of different soil types on the chemical composition of Mediterranean red wines, through untargeted and targeted 1H-NMR metabolomics. One milliliter of raw wine was analyzed by means of a Bruker Avance II 400 spectrometer operating at 400.15 MHz. The spectra were recorded by applying the NOESYGPPS1D pulse sequency, to achieve water and ethanol signals suppression. No modification of the pH was performed to avoid any chemical alteration of the matrix. The generation of input variables for untargeted analysis was done via bucketing the spectra. The resulting dataset was preprocessed prior to perform unsupervised PCA, by means of MetaboAnalyst web-based tool suite. The identification of compounds for the targeted analysis was performed by comparison to pure compounds spectra by means of SMA plug-in of MNova 14.2.3 software. The dataset containing the concentrations (%) of identified compounds was subjected to one-way analysis of variance (ANOVA) to highlight significant differences among the wines. The untargeted analysis, carried out through the PCA, revealed a clear differentiation among the wines. The fragments of the spectra contributing mostly to the separation were attributed to flavonoids, aroma compounds and amino acids. The targeted analysis leaded to the identification of 68 compounds, whose concentrations were significant different among the wines. The results were related to soils physical-chemical analysis and showed that: 1) high concentrations of flavan-3-ols and flavonols are correlated with high clay content in soils; 2) high concentrations of anthocyanins, amino acids, and aroma compounds are correlated with neutral and moderately alkaline soil pH; 3) low concentrations of flavonoids and aroma compounds are correlated with high soil organic matter content and acidic pH. The 1H-NMR metabolomic analysis proved to be an excellent tool to discriminate between wines originating from grapes grown on different soil types and revealed that soils in the Mediterranean area exert a strong impact on the chemical composition of the wines.

Vineyard exposure to smoke can lead to grapes and wine which exhibit objectionable smoky and ashy aromas and flavours, more commonly known as ‘smoke taint’ [1, 2]. In the last decade, significant bushfires have occurred around the world, including near wine regions in Australia, Canada, South Africa and the USA, as a consequence of the warmer, drier conditions associated with climate change. Considerable research has subsequently been undertaken to determine the chemical, sensory and physiological consequences of grapevine exposure to smoke. The sensory attributes associated with smoke-tainted wine have been linked to the presence of several smoke-derived volatile phenols, such as guaiacols, syringols and cresols [2].

Viticulture has spread to unexpected locations, such as high-altitude terrain. Among these, high-altitude viticulture has captured considerable attention, not only for the uniqueness of its products and landscapes but also because it offers an effective response to climate changes
The aim of this study is to analyse and compare wineries that used Piwi varieties (acronym for the German Pilzwiderstandfähig, i.e., cryptogame-resistant) at high altitudes (between 500 and 920 m a.s.l.) with the traditional non-mountainous viticulture model.

Soil Electrical Resistivity measurement is a zoning tool used by soil scientists and agronomists in viticulture. Indeed, the measure enables to optimize pedological surveys