WORK PLAN

WP1: BIORESOURCE SELECTION AND OPTIMIZATION

WP led by Universidade de Évora

OBJECTIVES

SpeedyFermHub begins by identifying the most promising combinations of microbial strains and plant-based ingredients. Using culture collections, regional resources, and microbiome diversity, the consortium will explore both regulatory-ready ingredients and more innovative options. This dual approach balances fast market potential with breakthrough innovation, enabling rapid movement from discovery to pilot-scale prototypes.

WP2: SPEEDY 'OMICS

WP led by INRAE

OBJECTIVES

Advanced ‘omics technologies will be used to screen and characterize microbial strains and fermentation systems at unprecedented speed and depth. Genome sequencing, metagenomics, and rapid profiling tools will identify safety and functional traits, while real-time aroma monitoring and high-resolution chemical analysis will guide the selection of the most promising ingredient–microbe combinations.

WP3: TECHNOLOGICAL CHARACTERIZATION

WP led by CSIC - ICTAN 

OBJECTIVES

Selected fermentation prototypes will undergo comprehensive evaluation, including safety, sensory quality, nutritional value, and functional performance. Rapid sensory methods and advanced analytical techniques will assess aroma, texture, stability, and bioactive compounds. Shelf-life testing will benchmark new products against existing commercial alternatives.

WP4: PROTOTYPE PRODUCTION

WP led by VTT Technical Research Centre of Finland

OBJECTIVES

SpeedyFermHub will translate laboratory discoveries into real food products. Iterative prototyping will lead to pilot-scale production using food-grade fermenters and industrial kitchen facilities. Final prototypes will be fully validated through volatilomic, sensory, and technological analyses to ensure readiness for industrial application.

WP5: INDUSTRY, MARKET AND SOCIETY

WP led by Aarhus University 

OBJECTIVES

Consumer and market insights will guide product development throughout the project. Studies in Italy and Denmark will assess acceptability, willingness-to-pay, and dietary attitudes, including gender-related differences. An Advisory Board of industry and stakeholder representatives will provide continuous feedback to ensure real-world relevance and societal impact.

WP6: AI/ML DIGITAL TWIN PREDICTORS

WP led by Universidad del País Vasco/Euskal Herriko Unibertsitatea

OBJECTIVES

Artificial intelligence and machine learning will integrate data across all project activities. Predictive models will forecast fermentation outcomes, sensory properties, and consumer preferences, enabling faster, data-driven decision-making. These digital twin tools will accelerate optimization and reduce development time.

WP7: PROJECT MANAGEMENT

WP led by Fondazione Edmund Mach

OBJECTIVES

Strong governance will ensure effective coordination, quality assurance, and impact. The Steering Committee will oversee scientific, technical, and ethical aspects, while dedicated plans for dissemination, communication, and collaboration with other FutureFoodS initiatives will maximize the reach and long-term value of SpeedyFermHub.