A.O.C. taureau de Camargue

Historically bounded by strict regulations with a focus on taxation since the 19th century, the japanese wine industry stands at a crossroads in the 21st century, necessitated by alignment with international standards and opening towards global markets.

In recent years, the ageing bouquet of red Bordeaux wines has been partially unveiled by a chemical and sensory point of view1–3. Minty and fresh notes were found to play a key role in the definition of this complex concept, moreover the freshness dimension in fine aged red wines plays an important role in typicity judgement by wine professionals

Egri Bikavér (Bull’s Blood) is one of the most remarkable Hungarian red wines on inland and foreign markets as well. From the end of the 70’s the quality of Egri Bikavér was decreasing continually due to mass production. The concept of production of quality wines became general in the mid 90’s again and it resulted in a new Origin Control System, for the first time that of Egri Bikavér in Hungary.

Soil is a three-dimensional complex system, which constitutes a major component of Terroir. Soil characteristics strongly influence vine development, grape oenological potentialities and thus wine quality and style.

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.