Project: sPectraL tools and digitalization for the development of sustAinable structured food with plaNt Proteins

Acronym	PLAN P (Reference Number: 862676)
Duration	02/01/2021 - 31/12/2023
Project Topic	The food industry currently finds itself in a pivotal and changing period when the consumer wants to take control over what they eat. In recent years, food manufacturers have reacted to growing flexitarian and vegetarian trends. PLAN P project aims to develop a smart and innovative system in order to design sustainable food and control quality online during the production and shelf life. In order to accelerate the plant food transition, a digital solution will be developed for the conception and production of sustainable food based on plant proteins. Data linked to the external and internal quality of the dispersed systems such as emulsions and foams will be acquired by non-invasive hyperspectral analysis. The application of artificial intelligence is rapidly shifting the way our food is produced. Deep Neural Networks is seen as a winning approach, but due to the limited amount of properly annotated ground truth data in the agri-food sector, the proposed solution will not rely on deep architectures. Instead, we will use a multi-model approach, where a set of components, each using different machine learning methodologies, will be trained and evaluated. The development of sensors will ensure online control of high-quality plant-based diet production with reduced waste. The multidisciplinary and transnational approach of the partnership will ensure the transfer of innovations to companies with the aim of accelerating the food transition in Europe with a positive impact for the economy and the environment. The project will include six strongly interacting work packages. The four scientific and technology-based work packages are interconnected and will be arranged in sequential form reflecting the logical flow of data within the project. The overall project is structured so that experimental production of products and product knowledge will be investigated by spectral analysis, producing data for modelling. Based on the modelling outcome, the work will ultimately lead to the development/testing of an adapted sensor platform which will be validated on a real online production chain.
Website	visit project website
Network	ICT-AGRI-FOOD
Call	1st ICT-AGRI-FOOD Joint Cofund Call

Project partner

Number	Name	Role	Country
1	ADRIA Développement	Coordinator	France
2	University of Copenhagen	Partner	Denmark
3	SCiO Private Company	Partner	Greece
4	Diafir	Partner	France