Correlation between skin cell wall composition and phenolic extractability in Cabernet sauvignon wines

Biodiversity conservation and restoration are essential for guarantee the provision of ecosystem services associated to vineyard agroecosystem such as climate regulation trough carbon sequestration and control of pests and diseases. Most of published research dealing with the complexity of the vineyard agroecosystems emphasizes the necessity of innovative approaches, including the integration of information at different temporal and spatial scales and development of systemic analysis based on modelling. A biodiversity survey was conducted in the Franciacorta wine-growing area (Lombardy, Italy), one of the most important Italian wine-growing regions for sparkling wine production, considering a portion of the territory of 112 ha. The area was divided into several Environmental Units (EUs), defined as a whole vineyard or portion of vineyard homogenous in terms of four agronomic characteristics: planting year, planting density, cultivar, and training system. In each EU a set of compartments was identified and characterised by specific variables. The compartments are meteorology, morphology (altitude, slope, aspect, row orientation, and solar irradiance), ecological infrastructures and management. The landscape surrounding EU was also characterised in terms of land-use in a buffer zone of 500 m. For each component a specific methodology was identified and applied. Different statistical approaches were used to evaluate the method to integrate the information related to different compartments within the EU and related to the buffer zone. These approaches were also preliminarily evaluated for their ability to describe the contribution of biodiversity and landscape components to ecosystem services. This methodological exploration provides useful indication for the development of a fully systemic approach to structural and functional biodiversity in vineyard agroecosystems, contributing to promote a multifunctional perspective for the all wine-growing sector.

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

Viticulture worldwide is currently affected by the effects of climate change. This set of adverse phenomena lead to a deterioration of functional vine mechanisms, affecting growth, physiology and grape ripening, which may cause severe losses with respect to yield and quality. To prevent water stress and other abiotic factors from severely affecting its physiology, the vine’s response is to reduce transpiration and photosynthesis rates. This response varies depending on the cultivar and its ability to adapt to the environment. The hydroscape method is based on the internal regulation of water status in the plant. It has been recently used to classify grapevine genotypes according to their iso/anisohydric behavior when they are subjected to water stress conditions.

Botrytis cinerea, an Ascomycota pathogen with a broad host range, infects over 1200 plant species. Grapes infected by this pathogen, which subsequently develop a noble rot, remain in the vineyard for an extended period, thus being exposed to a diverse array of physical, chemical and biological factors, which give rise to a complex microbial community.

The objective of this study was to develop a methodology capable of modeling the effect of viticultural climate on wine sensory characteristics.