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Role of artificial intelligence (AI) in fish growth and health status monitoring: a review on sustainable aquaculture

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Abstract

Aquaculture plays a crucial role in meeting the growing global demand for seafood, but it faces challenges in terms of fish growth and health monitoring. The advancement of artificial intelligence (AI) techniques offers promising solutions for optimizing fish farming practices and ensuring sustainable aquaculture. This abstract provides an overview of the role of AI in fish growth and health status monitoring, emphasizing its significance in promoting a sustainable aquaculture industry. AI technologies, such as machine learning and computer vision, have shown immense potential in analyzing large volumes of data collected from fish farms. By leveraging AI algorithms, fish farmers can gain valuable insights into fish growth patterns, feeding behavior, and environmental factors affecting fish health. These algorithms can detect and predict anomalies, diseases, and stress indicators, enabling proactive interventions to mitigate health issues and reduce losses. One of the key applications of AI in aquaculture is the development of smart monitoring systems. These systems employ various sensors, cameras, and data analytics tools to continuously collect real-time data on water quality, temperature, oxygen levels, and fish behavior. AI algorithms analyze this data to identify deviations from optimal conditions and provide timely alerts to farmers, allowing them to take appropriate actions such as adjusting feeding schedules, modifying water parameters, or administering treatments as needed. Furthermore, AI-based models can assist in optimizing feed management and reducing wastage. By analyzing historical data on fish growth and feed consumption, machine learning algorithms can determine the most efficient feed formulation and feeding regimes, leading to improved growth rates and minimized environmental impact. Another significant aspect of AI in fish farming is disease detection and prevention. Through image analysis and pattern recognition, AI algorithms can identify early signs of diseases, parasites, or abnormalities in fish appearance and behavior. This enables prompt disease diagnosis and targeted treatment, reducing the need for excessive use of antibiotics and chemicals while improving fish welfare. In summary, the integration of AI techniques in fish growth and health status monitoring holds great promise for the sustainability of aquaculture. By leveraging AI's capabilities in data analysis, pattern recognition, and predictive modeling, fish farmers can optimize their practices, enhance productivity, reduce environmental impact, and ensure the welfare of farmed fish. However, continued research, data sharing, and collaboration between scientists, industry stakeholders, and policymakers are essential for harnessing the full potential of AI in achieving a sustainable aquaculture industry.

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Authors and Affiliations

  1. Department of Environmental Science, The University of Burdwan, Golapbag, Purba Bardhaman, Burdwan, West Bengal, 713104, India

    Arghya Mandal & Apurba Ratan Ghosh

  2. SACT, Mankar College, Mankar, West Bengal, 713144, India

    Arghya Mandal

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  1. Arghya Mandal
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  2. Apurba Ratan Ghosh
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1st author: Writing and conceptualization.

2nd author: Editing and review.

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Correspondence to Arghya Mandal.

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Mandal, A., Ghosh, A.R. Role of artificial intelligence (AI) in fish growth and health status monitoring: a review on sustainable aquaculture. Aquacult Int (2023). https://doi.org/10.1007/s10499-023-01297-z

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