Using machine learning to improve fish growth media

2020-2021

Dr. Ovissipour at Virginia Tech is applying machine learning techniques to develop and optimize low-cost serum free growth media for seafood cell lines.

PRODUCTION PLATFORM: Cultivated

TECHNOLOGY SECTOR:  Cell culture media

Gfi's competitive research grants program badge, featuring a whole cut of meat within a magnifying glass representing research

Project aims

This project uses Response Surface Methodology and Artificial Neural Networks to produce an optimized media formulation for culturing stem cells from fish. It also creates predictive models that will guide and hasten future media optimization efforts.

This work will produce optimized media formulations that accelerate future research on cultivated seafood. It will also inform future efforts to optimize media for different species and cell types.

Principal researchers

Headshot of gfi grantee dr. Reza ovissipour, assistant professor, virginia tech, usa

Dr. Reza Ovissipour

Assistant Professor, Virginia Tech, USA

Dr. Ovissipour has extensive experience in both conventional aquaculture and the use of mathematical modeling techniques for optimization.

Headshot of gfi grantee inayat batish, phd student, virginia tech, usa

Inayat Batish

PhD student, Virginia Tech, USA

Inayat Batish has a background in cell culture research and mathematical modeling.

Headshot of gfi grantee thet aung, msc student, virginia tech, usa

Thet Aung

MSc student, Virginia Tech, USA

Thet Aung has a background in food science and sustainability.

Headshot of gfi grantee dr. Lexi duscher, postdoctoral associate, virginia tech, usa

Dr. Lexi Duscher

Postdoctoral Associate, Virginia Tech, USA

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Page

Sustainable Seafood Initiative

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