Defoliation combined with exogenous ABA application results in slower ripening and improved anthocyanin profile

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.

In the O Ribeiro Denomination of Origin, there is a winemaking tradition of growing vines under a high-density plantation framework (8,920 vines/ha) and maintaining its vegetative cycle under rainfed conditions.
Currently, viticulture is advancing to plantation frames in which the density is considered medium (5,555 vines/ha), thus allowing mechanized work to be carried out for vineyard management operations. Although, the application of irrigation applied proportionally to the needs of the vegetative cycle of the vine, is a factor that increasingly helps a good development of the vine compared to the summer period, with increasingly uncertain weather forecasts.

The sustainability of viticulture in response to climate change has been addressed mainly considering agronomic impacts, such as water management and diseases, either separately or together.
In grapevines, there is strong evidence that different genotypes respond differently to biotic and abiotic stresses. A screening was conducted on various local cultivars in response to drought and Neofusicoum parvum infection aiming to evaluate their susceptibility to abiotic stress and resistance to fungal diseases.

Sparkling wine (SW) production entails a two-steps process where grape must undergoes a primary fermentation to produce a base wine (BW) which is then refermented to become a SW. This process allows for the development of a new physicochemical profile characterized by the presence of foam and a different organoleptic profile.

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).