Climate change and viticulture in Nordic Countries and the Helsinki area

The presence of acetic acid bacteria in wine can lead to the appearance of acetic acid at concentrations above the perception threshold, causing the wine rejection by the consumer. During the winemaking process, avoiding the presence of acetic acid bacteria is very difficult, as there is always a residual population accompanying the wine[1], and the problem arises with the significant development of these microorganisms that metabolizes large amounts of acetic acid.
The concern of wineries to control the presence of acetic acid bacteria in wines during their conservation is due to the absence of simple and effective analyses that allow the detection of these microorganisms in the initial stages.

Chile is considered vulnerable to climate change; and these phenomena affect several mechanisms in the grape physiology and quality. The global temperature increase affects sugar contents, organic acids, and phenolic compounds in grapes, producing an imbalance maturity. In this sense, an alternative to reduce the impact is to perform pruning after vine budburst, known as “Late Pruning” (LP).

Modern agriculture employs large amounts of plastics, such as mulching and greenhouse films, thermal covers, plant protection tubes and tying tape. The latter two types are very common in viticulture. Guard tubes are employed to protect young vines from mechanic and atmospheric damage, whilst polymeric tying tape has replaced natural-origin materials to hold the canopy of vines. Both materials are made on synthetic polymers, which include a range of additives to improve their environmental stability remaining in the environment of vineyards for years. During this time, they are exposed to the range of pesticides (fungicides, insecticides and in a lesser extend herbicides) applied to vines.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

In grapevine, phenology from bud break to berry maturation, depends on temperature and water availability. Increases in average temperatures accelerates initiation of bud break, exposing newly formed shoots to detrimental environmental stresses. It is therefore essential to identify genotypes that could delay phenology in order to adapt to the environment. The use of different rootstocks has been applied to change scion’s characteristics, to adapt and resist to abiotic and biotic stresses[1].