Development of analytical sampling technique to study the aroma profile of Pinot Noir wine

Oxidation in wine is mostly related to the Michael addition of nucleophiles on two quinones formed from the oxidation of ortho-diphenols. In wine this mechanism is responsible for the increase of the yellow hue and aroma loss. Glutathione exerts its antioxidant activity throughout its competitive addition onto quinones, but many other compounds can have the same behavior: sulfanyl compounds, amino acids, etc. Addition of yeast derivates during the winemaking process can increase the level of those nucleophilic compounds and then confer to the wine a higher resistance

Developing rootstocks adapted to environmental constraints constitutes a key lever for grapevine adaptation to climate change. In this context, Near Infrared Spectroscopy (NIRS) could be used as a high-throughput phenotyping technique to simplify the study of rootstocks in grafted situations. This study is an exploratory analysis to evaluate the potential of NIRS acquired on grafted tissues to reveal rootstock effects as well as the plasticity of combinations of scion/rootstock to better characterize these interactions.
Through the study of 25 combinations (5 scions times 5 rootstocks) in a dedicated experimental vineyard, we showed that NIRS obtained from grafted tissues capture rootstock and scion/rootstock interaction signals, up to 20% of the total variance at specific wavelengths.

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.

This article compares alcohol regulations across 22 Arab League member countries.

Morphological image analysis is a powerful technique used in various fields, including agriculture, to quantitatively assess the physical characteristics of objects. In viticulture, the accurate assessment of grapevine characteristics is essential for optimizing crop management and improving the quality of wine production.