Genetic prospecting of rainfed viticulture in the region with the largest cultivated area in Chile

The under-trellis zone of vineyards is a sensitive area through which vines cover a significant portion of their nutrient and water needs. Mechanical and chemical methods are applied to suppress competing and tall-growing weeds to ensure optimal vine growth conditions. In addition to higher operating costs and depending on the soil conditions, these practices might lead to a long-term reduction in soil fertility and biodiversity. The presented study aims to analyse the suitability and interspecies competition of a selected green cover mixture of five local herbaceous species as potential green cover mixture in the under-trellis area of Lower Austrian vineyards.

Grape composition is strongly influenced by climate conditions. Their expected modifications in near future, notably because of increased temperatures, could significantly modify the biochemical composition of berries at harvest, and thus wine typicity and quality. Elevated temperatures favor sugar accumulation in grapes, enhance malic acid degradation and modify the amino acid content. They also reduce significantly anthocyanin accumulation in Merlot, leading to the imbalance between anthocyanins and sugars, while no significant effects on final anthocyanin levels were reported in Tempranillo[1] and finally affect aromas or aroma precursors.

Biostimulants and biofertilizers are considered environmentally friendly and cost-effective alternatives to synthetic fertilizers, plant growth regulators and crop improvement products. Broadly, plant biostimulants are expected to improve nutrient use efficiency, tolerance to abiotic stress, quality traits and availability of nutrients in the soil or rhizosphere. Currently, seaweed extracts account for more than 33% of the total plant biostimulant market. Within this category, Ascophyllum nodosum (AN), is the most widely studied and applied in biostimulant formulations.

Wine acidity is a parameter of great importance that influences different quality factors of the product such as biological stability or organoleptic characteristics. In the current context of climate change, which gives rise to wines with higher levels of ethanol and lower acidity, the biological acidification with yeast species such as Lachancea thermotolerans could be a solution.
In this work, the effect of the inoculation of different L. thermotolerans on the acidity of wine was studied.

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).