Fractal analysis as a tool for delimiting guarantee of quality areas

The main challenge faced by viticulture is to improve the quality of the wines, adapting them to the new consumer demands that demand wines with lower alcohol content and greater freshness. In the last 30 years, a clear modification has been observed in the composition of the grape due to climate change

Aim: Under the effects of climate change it is becoming increasingly common to observe excessively fast sugar accumulation while anthocyanin and flavour development are lagging behind. Understanding the impact of different leaf removal techniques on ripening will provide vineyard managers with a canopy management strategy suitable for

AIM: Bonarda, the second red grape variety in Argentina, produces high yields per hectare generating, in several cases, wines with low levels of quality compounds.

Wine quality may be compromised by mouldy off‒flavours related to cork taint. Although different compounds are considered to be involved in this wine defect, haloanisoles (HAs), and among them the 2,4,6-trichloroanisole (TCA), are claimed as the main responsible.

Consumers and the wine industry tend to agree on the ability of old vines to produce fruit that allows the production of wine of superior character. However, despite past and ongoing research, objective evidence of this point of view is still debated and studies on robust, specifically dedicated plots are scarce. Thus the impact of grapevine age on berry oenological potential and wine quality remains an open question. To try to objectively address the issue, a unique vineyard was established at Geisenheim University, Germany. It was planted in 1971 with cv. Riesling grafted on 5C Teleki. In 1995 and 2012, several rows were uprooted and replanted with the same rootstock/scion combination, resulting in a vineyard with alternate rows of identical plant material, but with different planting dates. The parameters of technical maturity and grape composition at harvest were analyzed during seasons 2014, 2015, 2016 and 2017 combining HPLC and enzymatic methods. Separate micro-vinifications were made for each age group and wine composition was analyzed by a combination of 1H-NMR and SPE-GC-MS.