Press Release_Detail

PINOT is researching the use of artificial noses in the production of wine and in trade. "Our aim is to support winegrowers, cellars and retailers in collecting and passing on data to customers, suppliers and authorities," explains Prof. Dr. Dominik Durner, who is supervising the project on behalf of the Wine Campus. The high complexity of wines means that a large number of quality-determining parameters must be determined in wines in order to obtain an overall impression that is both objective and relevant to quality.

Multi-sensor-based analysis systems are used in the project for quality assurance, traceability, sustainability and ensuring the authenticity of wine. Developments in recent years have laid the foundation for analysis systems in the future to go far beyond what is currently known in wine production and the wine trade. Dominik Durner emphasizes: "Especially when selling wines, it will be increasingly important to link the information from the producers with quality-relevant measurement data. This must reflect human sensory impressions such as taste, aroma and appearance."

PINOT develops sensors for winemaking and the wine trade, taking into account the depth of wine production. PINOT correlates the signals from the sensors with human perception in order to generate causal information. Artificial intelligence is used to create recommendations for the processing of wine, the storage of wine and the consumption of wine. Artificial intelligence supports the human sensory impression of wines. PINOT analyzes and describes wine sensory perception in a conclusive and comprehensible way for humans. Wine producers are supported in achieving the defined production targets safely and sustainably. Salespeople and retailers are helped to establish customer-oriented approaches more reliably and easily.

Artificial intelligence (AI) is currently being developed to support processes that are defined with a concrete initial situation, concrete process parameters and concrete target specifications. The ability to learn is the central requirement for AI and an integral part of the solution. The main criterion of AI is the ability to deal with probabilities that are not part of the learned automatism.

PINOT thus makes it possible to digitally reproduce the taste of wine along the wine value chain, from the grape to the consumer, as well as throughout the entire wine value network.

For detailed questions about the research project, please contact Prof. Dr. Dominik Durner.