Effects of soil water content and environmental conditions on vine water status and gas exchange of Vitis vinifera L. cv. chardonnay

AIM: Three Oenococcus oeni strains previously isolated from spontaneous malolactic fermentation were characterized for their surface properties. Planktonic and sessile cells were investigated for aroma compounds production and the expression of genes involved in citrate and malate metabolism (citE and mleA, respectively), glycoside-hydrolase (dsrO), fructansucrase (levO), rhamnosyl-transferase (wobB), glycosyltransferase (wobO).

The use of barrels is a practice that improves the quality of wines. The porous structure of wood favors the accumulation of microorganisms that can deteriorate the quality of wines so that barrel cleaning and sanitizing treatments are essential. The burning of sulphur discs has been the most common practice in winemaking because ots biocide effect. Nevertheless, its effectiveness is still insufficient and it is harmful for human health.

The application of remote and proximal sensing in viticulture have been demonstrated as a fast and efficient method to monitor vegetative and physiological parameters of grapevines. The collection of these parameters could be highly valuable to derive information on associated yield and quality traits in the vineyard. However, to leverage the informative potential of the sensing systems, a series of preliminary evaluations should be carried out to standardize working protocols for the specific features of a winegrowing area (e.g., pedoclimate, topography, cultivar, training system). This work aims at evaluating remote and proximal sensing systems for their performance and suitability to provide information on the vegetative, physiological, yield and qualitative aspects of vines and grapes as a function of different training systems in the Valpolicella wine region (Verona, Italy).

The foundation of wine production lies in the use of high-quality grapes. To produce wines that meet the highest standards, a fast and reliable analytical assessment of grape quality is essential. Many wineries currently employ Fourier-Transform Middle-Infrared Spectroscopy (FTIR) for this purpose.

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.