Retrospective analysis of our knowledge regarding the genetics of relevant traits for rootstock breeding 

Sémillon is a cultivated grape variety known for contributing to dry and sweet white wine production. However, only seven approved clones have been officially recognized in France[1]. In this study, we aimed to characterize the genetic diversity and metabolomic profiles of a Sémillon clonal population, shedding light on the potential variations within this important grape variety.

Grapevine pruning is one of the most important practices in the vineyards. Winegrowers use it to provide the vines the shape needed, or to maintain it once achieved, and also to balance vegetative growth and fruit production. In the last decades, careless pruning has been blamed, among other factors, as responsible of the vineyard decay that is been observed even in young vines. However, to our knowledge, there is a lack of systematic research trying to elucidate to which extent the pruning method used affects plant development or its susceptibility to grapevine trunk diseases (GTD). Within this context, the aim of this work is to study the influence of different pruning method strategies on the development of field-planted young vines.

Vine growth circumstances are becoming warmer and drier because of climate change. Higher temperatures advance ripening to a point in the season less conducive to the production of fine wine, while drought reduces yields (Van Leeuwen et al., 2019). Several wine-producing regions around the world have already recognized threats to their viticultural viability (Santos et al., 2020). An economical and cost-effective strategy for adaptation is the employment of late-ripening, drought-resistant plant material (varieties, clones, and rootstocks).

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).

Climate change is resulting in more dry and hot summers, accelerating grape ripening and increasing berry sugars concentration. This results in wines with a higher alcohol content, which has a negative impact on wine quality, as well as, on consumer health. Agronomic practices that minimize these effects on berry composition and, consequently, on wine quality must be defined. In this work, different management practices have been assessed on rainfed ‘Monastrell’ grapevines in Jumilla (Murcia, Spain) from 2021 to 2023 vintages. Mulching, shading, application of kaolin and different types of pruning were evaluated, among others field adaptation practices.