How sensor technologies combined with artificial intelligence increase the efficiency in grapevine breeding (research): current developments and future perspectives

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.

Among nitrogen compounds included in white wines, the peptide fraction is certainly the least studied, however this fraction is quantitatively the most important (Feuillat, 1974). Existing studies concern the fraction below 1 kDa and only for white and sparkling wines (Bartolomé et al, 1997, Desportes et al 2000). In this report, we have developed methods to isolate peptides from reference white wines. Then, we have applied this methodology with bitter wine to answer a research question: is there a relation between peptides and the bitterness of white wine as for some cheese for example (Furtado, 1984)?

With the aim of producing premium wines, it is admitted that moderate environmental stresses may contribute to the accumulation of compounds of interest in grapes. However the ongoing climate change, with the appearance of more limiting conditions of production is a major concern for the wine industry economic. Will it be possible to maintain the vineyards in place, to preserve the current grape varieties and how should we anticipate the adaptation measures to ensure the sustainability of vineyards? In this context, the question of the responses and adaptation of grapevine to abiotic stresses becomes a major scientific issue to tackle. An abiotic stress can be defined as the effect of a specific factor of the physico-chemical environment of the plants (temperature, availability of water and minerals, light, etc.) which reduces growth, and for a crop such as the vine, the yield, the composition of the fruits and the sustainability of the plants. Water stress is in many minds, but a systemic vision is essential for at least two reasons. The first reason is that in natural environments, a single factor is rarely limiting, and plants have to deal with a combination of constraints, as for example heat and drought, both in time and at a given time. The second reason is that plants, including grapevine, have central mechanisms of stress responses, as redox regulatory pathways, that play an important role in adaptation and survival. Here we will review the most recent studies dealing with this issue to provide a better understanding of the grapevine responses to a combination of environmental constraints and of the underlying regulatory pathways, which may be very helpful to design more adapted solutions to cope with climate change.

he final concentration of phenolic compounds in the wines is usually lower than what might be expected given the phenolic concentration measured in grapes

In the context of sustainable viticulture, modern and efficient techniques to determine water status are required to optimize irrigation practices. Proximal techniques such as thermography and spectroscopy have shown promising results. When these techniques are incorporated into mobile systems is possible to evaluate the water status on-the-go, offering the possibility to generate variability maps. However, in most cases, complex protocols of data acquisition and analysis are required. Also, the inherent physiological behaviour of the plants under certain water stress conditions needs to be considered. Therefore, the aim of this study was to evaluate the effect of scion-rootstock combinations on the performance of a predefined plant-based method based on proximal near-infrared (NIR) spectroscopy.