ADI Advances Wine Production with AI-Based Innovative Chemical Signature Detection Technology
TECHWORLD ·
✦ AI Summary
ADI announced a partnership with Moet Hennessy and UC Davis.
The collaboration aims to improve wine quality and support the long-term vitality of vineyards.
Its first outcome target was Fresh Mushroom Aroma (FMA), and the technology identified samples at high risk of FMA much earlier than conventional methods.
ADI has continued to enhance its chemical signature analysis technology platform based on innovative technology originating from early MIT research. The platform spans a wide range of applications.
Against this backdrop, ADI announced a partnership with LVMH wine and spirits division Moet Hennessy and UC Davis. The collaboration aims to improve wine quality and support the long-term vitality of vineyards.
ADI, Moet Hennessy, and UC Davis will explore ways to apply the technology to grape growing and winemaking. The collaboration aims to detect and interpret volatile chemical signatures emitted by grape pulp, juice, and wine.
The collaboration also aims to provide grape growers and winemakers with early, rapid insights into biological processes, as well as early, rapid insights into potential quality risks.
The first major outcome target of the collaboration was Fresh Mushroom Aroma (FMA), one of the wine industry’s complex quality challenges.
To this end, researchers at the Moet Hennessy Robert-Jean de Vogüé Research Center promoted the training of machine learning algorithms for recognizing the chemical signatures of quality risks related to FMA. Based on samples and related data, the researchers built a proprietary library.
As a result, the technology succeeded in identifying samples at high risk of FMA at an early stage. The identification came much earlier than defects would have been detected through conventional methods.
ADI emphasized that this development opens new possibilities for proactive quality management, enables earlier action, and fundamentally changes how quality risks are monitored throughout the winemaking process.
The system is based on ADI's sensing and machine learning platform, which analyzes a broad spectrum of chemical information and uses AI to identify key signals. This allows it to capture signal patterns that are easy to miss.
The platform is not limited to searching for predefined conditions and continues learning from complex chemical data. As a result, it deepens understanding of biological activity and also deepens understanding of emerging quality risks.
Based on these characteristics, the participating organizations said the platform could be applied more broadly to biological system analysis. The scope covers all potential applications related to the generation of meaningful chemical signatures that can be measured, interpreted, and acted upon in biological processes.
The research goal is to provide decision-support tools for researchers, grape growers, and winemakers. The purpose of decision support is early detection and deeper understanding, and the aim is not to replace human expertise but to help enhance it.
The technology is designed to provide growers and winemakers with additional information and context and to support the enhancement of expertise. At the same time, it was designed to preserve craftsmanship, experience, and judgment, which are core elements of top-tier winemaking.
Manuel Reman, a member of the Moet Hennessy executive committee and head of R&D, and a member of the French Champagne Producers Association, said the achievement marked the opening of a new chapter for grape growing and winemaking. He said it has made it possible to rapidly detect and interpret the chemical language of grapes and wine, and to predict quality risks before they become visible. He added that the achievement goes beyond a technical milestone to open new ways of understanding and working, and that it will expand resilience in the future while enabling the production of better wine.
Max Scharaker, head of ADI's Health Solutions business, said the collaboration combines AI-based sensing systems with world-class expertise in viticulture. He explained that it achieved the reading of the chemical language emitted by biological systems, which was previously impossible, and made it possible to recognize signatures at a much earlier stage than conventional methods. He also said it helps winemakers shift from reactive responses to proactive prediction when addressing quality risks, and that ADI's first outcome target is the Fresh Mushroom Aroma (FMA) issue. He added that this achievement is the starting point for a broader platform to understand biological systems, that the platform can improve quality and resilience, and that related exploration is only just beginning.
Ben Monpetit, PhD, of UC Davis said that the continued development and resilience of the grape and wine sector facing major global challenges depends on two things: better knowledge and people with the ability to put that knowledge into practice. He said the strength of this collaboration lies in developing those two elements together, as it promotes the development of technologies that provide timely, relevant information to support clear, information-based decision-making by grape growers and winemakers, while also training the next generation of experts who can interpret insights and turn them into action.
Source: TECHWORLD · Lee Kwang-jae
Original: https://www.epnc.co.kr/news/articleView.html?idxno=408239
References
This article was produced with the help of an automated content generation algorithm.
Source: TECHWORLD
View originalThis article was summarized and organized by BizCrush based on the original article from TECHWORLD. For exact quotations and full details, please refer to the original article.