Summary
Two NIFTEM-K students in Haryana are developing Kinva Bio, a project that uses fungal fermentation to turn agricultural byproducts into protein. The team says an AI-powered digital twin could help optimise production.
Two students from Sonipat, Haryana, are developing Kinva Bio, a project that uses fungal fermentation to convert agricultural byproducts such as sugarcane bagasse into protein. Samsung India says the team, founded by National Institute of Food Technology Entrepreneurship and Management (NIFTEM-K) students Nitish Kumar and Gulshan Kumar, is among the Top 20 in Samsung Solve for Tomorrow 2026.
The approach combines a biological process with a computer model. The team says a fungal strain converts crop-residue biomass into protein, while an AI-powered digital twin predicts protein production and helps optimise the process.
How the proposed process works
Fermentation uses microorganisms to transform a material. In Kinva Bio’s proposed process, the starting material is agricultural biomass that might otherwise be treated as waste. A digital twin is a computer model of a real-world process; here, the team describes using one to forecast protein output and guide optimisation. The profile does not detail the model’s inputs or how it is connected to the fermentation process.
The project’s aim is to make better use of crop residues while producing protein. The team says the approach could use 98–99% less water than conventional protein production, with lower carbon emissions and substantially less land use. These are projected figures from the team: Samsung’s profile does not provide the calculation method or comparator behind the water estimate.
From a laboratory project to a potential application
Kinva Bio is presented as a developing project, not a launched food product. The team’s work at the Samsung Solve for Tomorrow Bootcamp led them to consider questions beyond the science, including who might use the solution, how it could scale and what would be needed for a viable startup.
If the process can be made practical at larger scale, converting agricultural byproducts into protein could give crop residues a higher-value use. The project brings together fermentation and AI-assisted process modelling to pursue that possibility; its environmental estimates remain potential outcomes rather than results from a production trial described in the profile.