Pedological factor influence on the viticultural zoning of the Aljarafe Alto (Seville, Spain)

The chemical profile and sensory attributes were studied in Borrigiano IGT Toscana wine (Italy), a blend of Sangiovese 85% and Cabernet Sauvignon 15% grapes harvested in September 2020, where 2-(3,4-dihydroxyphenyl)ethanol (hydroxytyrosol, HT, [1]) was added to a 750-ml wine bottle in 3 different amounts (30, 60, 120 mg) and compared with the control (no HT addition). The study aimed to evaluate whether Polyphenol-HT1®, a high purity HT (>99%) produced by Nova Mentis using biotechnology, could be used as a supplement to sulfites and how it would impact the sensory and chemical profile of this wine [2]. Each sample was prepared in triplicate.

Winegrowing regions recognized as protected designations of origin (PDOs) are closely tied to well defined geographic locations with a specific set of pedoclimatic attributes and strictly regulated by legal specifications. However, climate change is increasingly threatening these regions by changing local conditions and altering winegrowing processes. The vulnerability to these changes is largely heterogenous across different winegrowing regions because it is determined by individual characteristics of each region, including the capacity to adapt to new climatic conditions and the sensitivity to climate change, which depend not only on natural, but also socioeconomic and legal factors. Accurate vulnerability assessments therefore need to combine information about adaptive capacity and climate change sensitivity with projected exposure to new climatic conditions. However, most existing studies focus on specific impacts neglecting important interactions between the different factors that determine climate change vulnerability. Here, we present the first comprehensive vulnerability assessment of European wine PDOs that spatially combines multiple indicators of adaptive capacity and climate change sensitivity with high-resolution climate projections. We found that the climate change vulnerability of PDO areas largely depends on the complex interactions between physical and socioeconomic factors. Homogenous topographic conditions and a narrow varietal spectrum increase climate change vulnerability, while the skills and education of farmers, together with a good economic situation, decrease their vulnerability. Assessments of climate change consequences therefore need to consider multiple variables as well as their interrelations to provide a comprehensive understanding of the expected impacts of climate change on European PDOs. Our results provide the first vulnerability assessment for European winegrowing regions at high spatiotemporal resolution that includes multiple factors related to climate exposure, sensitivity, and adaptive capacity on the level of single winegrowing regions. They will therefore help to identify hot spots of climate change vulnerability among European PDOs and efficiently direct adaptation strategies.

The aim of this study is to provide an overview of the terroir of Saint-Romain, Burgundy, based on three main information sources: official data relating to vines (CVI), soil cartography and a survey of winegrowers’ practices.

Trichoderma is a microorganism present in many agricultural soils and some of its species could be used as natural biological control agents. In this work, the presence of natural populations of Trichoderma was estimated in soil vineyard and its biocontrol capacity against Phaeoacremonium minimum, one of the main agent causals of grapevine trunk diseases instead of using pesticides. Moreover, physicochemical variables in soil such as pH, organic matter and nutrients were evaluated to determine a possible correlation to natural populations of Trichoderma.

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.