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  • Writer's pictureDanielle van Hout

Eye on AI - October 28th, 2022

Welcome to Aigora's "Eye on AI" series, where we round up exciting news at the intersection of consumer science and artificial intelligence!

 

This week, we’ll be looking at new AI-driven methods of inland shrimp farming that increase efficiencies and potentially reduce aquaculture’s weighty carbon emissions by a third.


Enjoy!


Shrimpbox Reduces Environmental Impact of Shrimp Farms



According to the article “Dirty shrimp farms are punching a huge hole in the environment. A.I. could cut it in half,” new methods of inland shrimp farming that utilize AI could cut aquaculture emissions in half.


“Most of today’s shrimp is produced at coastal farms, which, between 1980 and 2000, wiped out more than 3 million acres of mangrove forest,” writes Fortune contributor Matt Whittaker. “… These farms also discharge chemicals and antibiotics into ocean habitats… wild-caught shrimp are just as problematic.”

Shrimp is the most consumed form of seafood on the market, with per capita consumption of wild-caught and farmed aquatic animals expected to increase to 47 pounds annually in 2030, up from its record-breaking 122.6 million metric tons in 2020. Mangroves, the sea’s equivalent to tropical forests, need to be removed for shrimp farms to expand. This emits large amounts of carbon into the atmosphere while eliminating sea infrastructure that’s essential for maintaining sealife biodiversity.


Additionally, shrimp farms require immense amounts of feed to sustain shrimp harvests, as well as land needed to produce that feed. Soybeans are the plant-based feed of choice for most shrimp farms. Unlike soy feed production for livestock, feed for shrimp needs to be crushed then put through an isolation process, which is much more energy-intensive.


“Land-hungry soy farms have contributed to the reduction of another key global carbon sink—the Amazon rain forest,” continues Whittaker. “Growing soybeans as a monoculture depletes the soil at greater rates than other farming methods, increasing the need for fertilizer, which is often made with natural gas.”

AI has emerged as a potential solution for companies looking to create systems that minimize environmental issues associated with shrimp farming. Not only does AI help improve shrimp farming efficiencies, but it also allows farmers to recreate ocean-like environments on land using less energy and resources than traditional shrimp farms (and without the mangrove deforestation). Shrimpbox is one such system that’s using AI to its advantage.


“Shrimpbox technology takes feed efficiency to another level,” continues Whittaker. “It combines A.I.-powered automation with a farming method commercially introduced in the 1980s that accelerates the growth of microorganisms beneficial to shrimp—enabling the micro shrimp farms to use proportionally less feed than traditional coastal ponds.”

Described as vertical farms for shrimp, Shrimpbox’s facilities are essentially giant warehouses of shrimp-producing vats. Cloud-based artificial intelligence monitors water quality, regulates temperature and oxygenation, and feeds the shrimp. It also addresses the feed emissions issue by taking feed efficiency to another level.


“[Shirmpbox] combines A.I.-powered automation with a farming method commercially introduced in the 1980s that accelerates the growth of microorganisms beneficial to shrimp—enabling the micro shrimp farms to use proportionally less feed than traditional coastal ponds,” continues Whittaker.

Daniel Russek, CEO of Indianapolis-based Atarraya, which created the Shrimpbox, believes he’ll be able to franchise Shrimpbox tech to seafood distributors or farmers around the world. When paired with renewable energy, this model could help reduce greenhouse gas emissions as the global demand for seafood rises. Shrimpbox isn’t the only AI-driven seafood farming company making an impact. Other seafood, such as wild salmon, are being farmed using similar methods. Together, these systems could make a significant dent in the carbon impact of aquaculture in time.






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