Varieties and rootstocks: an important mean for adaptation to terroir

New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season.

The acquisition of wine expertise is a multi-faceted and multisensory process with implications for sensory perception, attention, memory, and language production. With the prevalence of the predictive model of brain functioning, one area of burgeoning research interest involves wine mental imagery, since the brain relies on imagined experiences to build predictions for the future. Recent evidence has shown that, for instance, those with higher imagery vividness are more susceptible to wine advertising. However, little is known about the association between mental imagery and other associated cognitive processes, such as the ability to produce words that describe such imagery. 

Consumers predominantly use visual, aromatic and texture cues as quality/preference indicators to describe olfactory sensations. In this study, the effect of micro-organism in wine production was investigated using analytical and sensory techniques to achieve relevant analytical characterisation. Selected anthocyanins, flavan-3-ols, flavonols and phenolic acids were quantified in Syrah wines using RP-HPLC-DAD. Standard oenological parameters were also measured. Syrah grape must was fermented with various combinations of Saccharomyces cerevisiae (S. cerevisiae) and non-Saccharomyces (Metschnikowia pulcherrima or Hanseniaspora uvarum) yeasts, which was followed by sequential inoculation of lactic acid bacteria (LAB) (Oenococcus oeni or Lactobacillus plantarum).

The selection of ancient grapevine varieties aims to achieve genetic gains in several important traits that can make the variety more interesting for the objectives of the producers. Traditionally, yield and quality traits of the must have been considered for selection, but many others can be taken into account. Linear mixed models are fitted to the data to predict the empirical best linear unbiased predictors (EBLUPs) of genotypic effects for each evaluated trait, which will be the basis for selection.

The Rară Neagră 2.0 project aims to restore and safeguard the intra-varietal diversity of the ancient Eastern European grape variety Rară Neagră through polyclonal selection and the establishment of a certified genetic conservatory.