Use of UHPH to improve the implantation of non-Saccharomyces yeasts

The characterization of chemical compounds related with quality of grape must and wine is relevant for the viticulture and enology fields. Analytical methods used for these analyses require expensive instrumentation as well as a long sample preparation processes and the use of chemical solvents. On the other hand, near-infrared (NIR) spectroscopy technique is a simple, fast and non-destructive method for the detection of chemical composition showing a fingerprint of the sample. It has been reported the potential of NIR spectroscopy to measure some enological parameters such as alcohol content, pH, organic acids, glycerol, reducing sugars and phenolic compounds.

Entomopathogenic nematodes (EPN) are well-known biological control agents combined with specific adjuvants that now allow their use against aerial pests. Lobesia botrana (Lepidoptera: Tortricidae) is one of the major harmful pests detected in worldwide vineyards. Previous studies demonstrated that the EPNs Steinernema feltiae and S. carpocapsae could control L. botrana. The hypothesis was that the best combination of EPN-adjuvant/timing (season/temperatures) will support the use of EPN in the vineyard against L. botrana with no impact on the grape performance.

The presence of undesirable compounds in wines, such as OTA, biogenic amines and pesticides residues, affects wine quality and can cause health problems for the consumer. The main tool that a winemaker has to reduce their content in the wine is fining. However, some of the fining agents commonly used in the winery can cause allergies or even increase the protein content in the wine, increasing the turbidity. To avoid these problems, the use of plant fibers may be an alternative, such as those from grape pomace[1] or other plant origins.

Each grapevine variety has a specific water use regulation response under drought, and it is still unclear whether this regulation results from innate genotypic behavior (iso- and anisohydric), or is a response to environmental factors, namely recurrent water stress priming effects. In the present work, we explored the influence of the field-grown genotypes’ drought memory in the drought-response phenotype of their vegetative progenies, in Trincadeira (isohydric) and Castelão (anisohydric) varieties under a drought event followed by recovery in a glasshouse. Cuttings from both cultivars subjected to full irrigation (FI) and non-irrigation (NI) treatments for 5 consecutive years were used.

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).