{"id":226722,"date":"2022-08-11T11:46:49","date_gmt":"2022-08-11T15:46:49","guid":{"rendered":"https:\/\/www.sightline.com\/?p=226722"},"modified":"2026-02-17T15:48:04","modified_gmt":"2026-02-17T20:48:04","slug":"benefits-of-machine-learning","status":"publish","type":"post","link":"https:\/\/www.sightline.com\/benefits-of-machine-learning\/aquaculture-blogs\/","title":{"rendered":"Improving Disease Prediction in Aquaculture: The Benefits of Machine Learning"},"content":{"rendered":"

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Seafood is the most traded food<\/a> commodity worldwide. In fact, approximately three billion people across the globe rely on farmed and wild-caught fish as their main source of protein. With this large consumer demand for high-quality seafood products, many countries have turned to aquaculture, or fish farming, to keep up.<\/p>\n

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Aquaculture is the process of farming aquatic organisms, including fish, mollusks (like clams), crustaceans (such as shrimp), and algae. Just like we see the mass production of land animals in large controlled environments, aquaculture farms<\/a> allow us to cultivate aquatic animals in controlled settings for human consumption. Being able to determine the pH level of the water, change the water temperature, and control the aquatic populations in these spaces allows fisheries and hatcheries to increase their productivity.<\/a><\/p>\n

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While aquaculture is necessary to satiate the global demand and alleviate the fishing pressures on wild stock, these fish farms can be ripe environments for infectious disease. The risk of disease in aquaculture can significantly increase due to overcrowding, subpar conditions, poor nutrition, and low levels of oxygen. The average size of a typical net pen is 40-50 square feet.<\/a> Depending on the efficiency of the technology used to monitor those pens or ponds, one sick and diseased fish can turn into many.<\/p>\n

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Infectious Diseases in Aquaculture Ponds<\/strong><\/h2>\n

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Most production ponds are located outside and are dirt or clay lined. Over time, they become high in organic waste due to naturally occurring circumstances like feeding, fish growth, and waste accumulation. Fish in these ponds are susceptible to an abundance of parasites, but due to the high organic waste content, sessile ciliates<\/a> are seen specifically attached to fish.<\/p>\n

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Bacterial and viral diseases may be more difficult to control and eradicate once they infect a pond population because of the logistical challenges with pond disinfection.<\/p>\n

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Infectious Diseases in Recirculating Aquaculture Systems<\/strong><\/h2>\n

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Recirculating aquaculture systems (RASs) are built within enclosed facilities; this significantly limits the access of parasitic hosts entering the fishery. However, parasites and viruses are more dangerous in RAS because these types of fish farms normally have a larger fish population and recycle water throughout the growth areas. Once one fish becomes sick, the disease spreads rapidly.<\/p>\n

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Bacterial diseases are also more problematic as well. Many conditions, such as low dissolved oxygen, low pH, and an organically rich environment (from fish growth and waste), promote the growth of bacteria.<\/p>\n

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Infectious Diseases in Net Pens\/Cage Culture<\/strong><\/h2>\n

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In theory, the open concept of ocean net pens or cage culture systems within lakes and reservoirs should dilute solid and dissolved wastes. However, this open access also allows pathogens\u2014bacteria, parasites, and viruses\u2014within the larger body of water to more easily make contact with a fish farmer\u2019s precious crop. Smaller aquatic organisms within the body of water, carrying diseases, can also enter the net pen or case culture system. Same as the pond and recirculating systems, once a fish is infected, that disease spreads rapidly throughout the rest of the population.\u00a0<\/p>\n

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Common Aquaculture Farm Diseases<\/strong><\/h2>\n

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The spread of fish diseases can take a significant toll on a company\u2019s profits. The most common types of diseases in fish farms are caused by parasites, viruses, and bacteria. Overcrowded conditions can cause stress in fish, activating naturally-occurring bacteria in their digestive tract. This can become dangerous and cause infections.<\/p>\n

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Sea Lice<\/strong><\/h3>\n

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Sea lice, the most prominent aquacultural disease, can lead to annual losses of up to $600 million a year<\/a> for farmers. This is because these infections can lead to poor fish growth, shorter lifespans, and the potential for a fish farm to lose its entire crop. Furthermore, it can be a threat to nutriment security.<\/p>\n

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This disease is a prevalent problem in the aquaculture industry, especially in salmon. These parasites will feed off the mucus, blood, and skin of the fish, weakening their cardiac muscles, heightening stress levels, and causing an imbalance of osmoregulation<\/a>, or the appropriate balance of water and salt levels.<\/p>\n

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Enteric Redmouth Disease in <\/strong>Salmonids<\/strong><\/h3>\n

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One of the biggest priorities for fish farmers is output growth. However, intensively culturing fish can lead to serious acute or chronic bacterial diseases.<\/a> Yersiniosis (enteric redmouth disease) can have a high mortality rate among salmonids, especially when paired with poor water quality and additional stressors within the fishery. This not only costs fish farmers precious time and money in trying to isolate the infected fish, but the cost of vaccination therapy for the other fish in the fish farm can become costly as well.<\/p>\n

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While many fish farmers use veterinary antibiotics<\/a> to prevent the spread of death and disease, overuse or misuse of these medicines can have an adverse effect on the animals. Antibiotics will effectively kill some bacteria, but may not ward off resistant bacteria, which can modify and multiply to further fight off the antibiotics. This will boost the risk, and even spread of, disease.<\/p>\n

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Salmon Rickettsial Septicaemia (SRS) throughout Chile<\/strong><\/h3>\n

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For Chilean salmon farmers, SRS is considered to be the most important and significant disease problem with over $300 million of losses in a single year.<\/a> While SRS affects salmonid and non-salmonid fish in fresh and saltwater worldwide, no other area has reached the high levels of outbreak like Chile.<\/p>\n

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SRS is caused by the bacterium, Piscirickettsia salmonis,<\/em> which replicates within the fish cells and tissues of infected fish. These fish will often exhibit signs of hemorrhaging and lesions of the skin along with being lethargic, dark in color, anorexic, anemic with mottled focal lesions within the liver; showing respiratory problems; and swimming near the surface.<\/p>\n

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The mortality rate of SRS averages 20% during the 18-month production time to harvest<\/a>. 11.5% of the total mortality rate<\/a> of all Atlantic salmon was attributed to this bacterium in 2021.<\/p>\n

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Vaccines have been largely ineffective against this disease and reducing the outbreaks associated with it. At this time, site following appears to be the best defense. However, finding the clinically diseased fish can be a nightmare for fish farmers, wasting time and money.<\/p>\n

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Poor Nutrition in Fisheries<\/strong><\/h3>\n

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Another common culprit of fish farm disease is feeding the animals food with high lipid levels to increase growth rates and reduce the cost of feeds. This food can cause excessive liver fat<\/a>.<\/p>\n

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These diseases can lead to substantial losses for aquaculture farms. Fortunately, there are ways to get ahead of the curve to prevent fish fatalities from happening. And it all starts with machine learning.<\/p>\n

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To mitigate these risks, many aquaculture organizations have turned to the power of machine learning to improve disease prediction. Data analytics help farmers track animal health, environmental factors, and water conditions. Moreover, machine learning can also help aquaculture farms predict future outcomes, saving them time, money, and resources.<\/p>\n

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What Can Be Done to Prevent the Spread of Aquaculture Disease?<\/strong><\/h2>\n

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Machine learning software uses multiple data points to monitor the health and living conditions of the fish. These data points, including water conditions, feed levels, pH levels, salinity, oxygen saturation, growth rates, and others, enable fisheries to stay one step ahead of the spread of disease.<\/p>\n

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Machine learning can enhance aquaculture management by:<\/p>\n

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