If you are a meat alternative producer dealing with high raw material costs — this project developed a fermentation system that turns agricultural side-streams into mycoprotein. This allows you to tap into the €30 billion alternative protein market with lower-cost inputs.
AI-Driven Fungal Protein Production from Agricultural Waste for Food and Cosmetics
Imagine taking the leftovers from sugar beet or beer production and using them as food for special fungi. These fungi act like tiny factories, turning waste into high-quality protein. It's like composting, but instead of just soil, you get ingredients for burgers, pet food, or skin creams.
What needed solving
Traditional protein production is too resource-intensive and expensive, while millions of tons of agricultural waste remain underutilized. This creates a gap between the need for sustainable proteins and the cost of producing them.
What was built
An AI-powered, zero-waste fermentation system and multipurpose bioreactors capable of handling various waste substrates to produce fungal proteins.
Who needs this
Who can put this to work
If you are a pet food brand dealing with unsustainable protein sourcing — this project developed fungal-based protein ingredients. This provides a high-quality, eco-friendly protein source that reduces the carbon footprint of your supply chain.
If you are a cosmetics company dealing with a need for sustainable bio-active ingredients — this project developed a way to valorize agro-industrial waste into valuable bio-products. This enables the creation of high-value ingredients from waste streams.
Quick answers
How does this affect production costs?
The project reduces costs by using low-cost agricultural residues like sugar beet pulp and brewer's spent grain as feedstock instead of expensive nutrients.
Can this be scaled to an industrial level?
Yes, the project specifically focuses on scalable bioreactor designs and aims to engage more than 30 European biorefineries.
What are the IP and licensing options?
Based on available project data, specific licensing terms are not listed, but the project involves 7 industry partners and 5 SMEs who are developing the technology.
How is the process controlled to ensure quality?
The system uses AI-powered process optimization and digital modeling to embed knowledge into control systems, ensuring consistency across different locations.
What is the timeline for implementation?
The project runs from 2024-06-01 to 2028-05-31, indicating that industrial validation and scaling are ongoing through 2028.
Who built it
The consortium is heavily industry-weighted with a 54% industry ratio, comprising 7 industrial partners and 5 SMEs. This strong commercial presence, combined with 4 research institutions across 5 countries, suggests a high focus on market viability and industrial application rather than pure academic research.
Contact TEKNOLOGISK INSTITUT in Denmark
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