Project description
Digital platform for sustainable use and research of seaweed biomass
Europe boasts over 100 megatons of seaweed, its largest biomass. Surprisingly, only 0.25 % of this resource is utilised, primarily as low-cost fertiliser. Current methods struggle to harness the potential of thousands of identified macroalgae. Nevertheless, the data collected on them is crucial for the sustainable utilisation of this resource. The EU-funded iCULTURE project aims to establish a cross-disciplinary consortium of European experts in ICT, biodiversity, and related fields to create a digital platform and toolsets for the sustainable utilisation of seaweed biomass. These toolsets will facilitate the discovery of new species, research on them, and provide specialised AI algorithms for the curation of over 80TB of currently available data.
Objective
Over 100 Megatons of seaweed constitute Europe's largest biomass, but less than 0.25% is utilized. Marine industry stakeholders are currently left with 50-70% of residual side-streams sold as low-cost fertilizers. Existing data on more than 10000 macroalgae species could help this industry to improve their processes but the data is too large and manual curation is not feasible. Despite the progression of artificial intelligence (A.I.) and digital instruments, these techniques have barely entered the biobased sector.
iCulture is a cross-disciplinary consortium where European expertise on ICT, bioinformatic, biodiversity, biotechnology, synthetic biology and bioprocessing is combined to develop a set of digital toolboxes that can prospect for new species of seaweed, utilize these in microbial fermentation, and understand how to use it responsibly and sustainably.
Over 80 TB of existing seaweed data and 700.000 genes will be mined by machine learning algorithms in an A.I. toolbox to identify macroalgae characteristics: growth, response to environmental conditions, chemical composition and more. These will be used by a predictive Model toolbox, with models for compositional changes, recovery, resilience and Dispersion, to deliver key features that are important for responsible resource management. A Bioprocess technology toolbox will use this information for a machine learning controlled microbial co-culture, that will convert complex sugar mixtures to catalysts producing high-value antimicrobials.
The multiple benefits of this digital platform are 1) boost the prospecting efficiency of new species by using powerful A.I. algorithms 2) help to understand the potential and vulnerability of resources, so that a responsible management strategy can guide the operations of stakeholders, and 3) create a novel value-chain, valorizing European seaweed side-streams into valuable antimicrobials (>$150/kg) for feed, food and pharma, while reducing CO2 footprint more than 20%.
Fields of science
- natural sciencesbiological sciencessynthetic biology
- natural sciencesbiological sciencesecologyecosystems
- natural scienceschemical sciencescatalysis
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- engineering and technologyindustrial biotechnologybioprocessing technologiesfermentation
Keywords
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
7491 Trondheim
Norway
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Participants (15)
9000 Gent
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8005-139 FARO
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89081 Ulm
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4450 208 Matosinhos
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33615 Bielefeld
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5525 Haugesund
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
5525 Haugesund
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
9610 Rypefjord
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
21000 Split
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
38122 Trento
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731 00 Chania
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29870 Lannilis
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2629 JG Delft
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2830 565 COINA
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
00124 Roma
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partners (3)
67063 Ludwigshafen Am Rhein
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Participation ended
8952 Schlieren
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8038 ZURICH
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.