Call to exploit Ksh2 trillion deep-sea fishing capacity

By and , March 3, 2025

There is a need for improved maritime infrastructure to support deep-sea fishing to boost Kenya’s Gross Domestic Product and reduce dependency on imported fish products.

Shipping and Logistics, Ocean and Blue Economy Secretary at the Office of President, Stanley Chai noted that there is a huge economic potential in deepsea fishing to the tune of over Sh2 trillion that is yet to be exploited.

“The economic potential of tuna fishing which is worth $20 billion (about Sh2.6 trillion) is huge globally, yet Kenya continues to underutilise its Indian Ocean resources,” Chai said.

He spoke during a conference on the maritime economy hosted by Mount Kenya University (MKU) in Mombasa and convened by a diverse group of scholars, researchers, innovators, industry leaders and policymakers to discuss the Blue Economy.

The inaugural Research and Innovation Conference 2025 was held at MKU Mombasa campus earlier last week which emphasised the advancements in the Blue Economy resulting from the passage of legislation in Parliament. Mr Chai urged the university to start a course in Maritime Law to offer legal training in piracy, illegal fishing and maritime dispute resolutions.

“These initiatives will close the training and professional divide in the prosecution of crimes committed on the seas and oceans. Maritime logistics research is also a prime opportunity that bolsters the blue economy,” he added.

Ayub Mohamed, the Campus Programme Manager at Swahilipot Hub, which has been collaborating with MKU, emphasised the importance of fostering innovations aimed at propelling the economic growth of the coastal region.

The conference focused on ocean conservation; mitigating marine pollution, reducing plastic waste, and protecting of marine ecosystems. It also touched on recycling plastic waste into high-quality 3D filaments, which can be used to create visual learning aids and models.

Phillip Bittok and Biko Magati from the School of Computing and Informatics examined Machine Learning Methods to forecast metal contamination in the coastal water, sediments and fauna

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