Thank you to Jean-Luc SALASC, head of the winery “Les Trois Grappes” and Nicolas ALLEGRE, head of the production and marketing Union “ Les Vignerons de la Vicomté” who enabled members of INRAE working on BigDataGrapes to visit:
Dr. Nikos Manouselis (Coordinator of the BigDataGrapes Project) was invited by John Keogh from Shantalla Inc., to share his perspective on the challenges and opportunities of the food industry, as part of his 2020 Future of Food – 10X10 CEO Interview Series. This was an amazing opportunity to discuss some of the first findings of the BigDataGrapes project, ranging from the importance of using trusted data sources for critical food safety decisions to whether AI algorithms can go wrong.
First of all, data management in the field of the vine and wine section is a major challenge. Large amount of heterogeneous data is collected at several stage of the process like in the field, at harvest, during winemaking, sensory analysis or in the lab. Diverse formats are used, and diverse teams are gathering these data. This shows how difficult it is to link these data together.
One part of the success of the BigDataGrapes project is based on the FOODAKAI software, which helps on the collection and prediction of the big data. During October, Agroknow's technology team had their hands full, our sprint planning was showing that by the end of the month our new module was to be released! And this was one of the most exciting modules in their platform: their Predictions Dashboard.
BigDataGrapes is about how the Grapevine industry can be supported with new Big Data technologies to generate new insights and allow informed decisions.
In the Farm Management Pilot Abaco together with Geocledian, KUL and CNR are developing a Dashboard on Water Availability and Irrigation Recommendations to help farmers decide on these critical business decisions:
BigDataGrapes aims to help European companies in the vine, wine, and natural cosmetics sectors to become more competitive in international markets. More specifically, it aims at helping companies across the grapevine-powered value chain to use, exploit and benefit from big data tools, by supporting business decisions, while providing decision-making processes and support, resulting from the real-time and transversal analysis of relevant and heterogeneous data sources.
It all started back in 2017 when our consortium had an ambitious dream; to create a data-powered solution, collecting, processing, translating, enriching food and agriculture data supporting the communities in and around the grapevine-powered industries. From this year the BigDataGrapes transformed from a dream into an EU-funded Horizon 2020 project, and we are already in the third -and final - year of the project.
So let’s start with introductions: “The BigDataGrapes Big Data Platform”
BigDataGrapes aims to help European companies in the wine and natural cosmetics industries become more competitive in the international markets. It specifically tries to help companies across the grapevine-powered value chain ride the big data wave, supporting business decisions with real-time and cross-stream analysis of very large and multimodal data sources. One of the scopes of the project is the integration with existing real-life Software Systems.
BigDataGrapes as a feature-leader, dealing with the unexpected is not a piece of cake. Especially, when it comes to challenging decisions that can cost product reputation and brand trust such as food safety issues. But what is happening behind the scenes when the decision-making is in progress?
BigDataGrapes aims to help European companies in the wine and natural cosmetics sectors to become more competitive in international markets. In particular, it aims to help companies in the wine value chain to benefit from Big Data tools, by providing decision support resulting from the real-time and transversal analysis of important and diverse data sources. For example, as part of the BigDataGrape project, works based on deep learning techniques have been carried out to develop a tool capable, from images, of automatically counting the number of leaves per vinestock.
BigDataGrapes
