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The Use of Artificial Intelligence in Sturgeon Aquaculture

Author

Listed:
  • Dragos Sebastian Cristea

    (Dunarea de Jos University of Gala?i, Romania)

  • Alexandru Adrian Gavrila

    (Bucharest University of Economic Studies, Romania)

  • Stefan Mihai Petrea

    (Dunarea de Jos University of Gala?i, Romania)

  • Dan Munteanu

    (Dunarea de Jos University of Gala?i, Romania)

  • Sofia David

    (Dunarea de Jos University of Gala?i, Romania)

  • Catalin Octavian Manescu

    (Bucharest University of Economic Studies, Romania)

Abstract
This paper presents the experience and lessons learned in a pilot project aimed at integrating artificial intelligence (AI) technologies in sturgeon aquaculture. The project used convolutional neural networks and visual intelligence for the evaluation of fish biomass and the optimisation of sturgeon rearing technologies in integrated multitrophic production systems. Similar solutions have been used before to determine the biomass of other fish species, but this is the first documentation of the application of such a solution for sturgeons. The application challenges were significant, which was determined by the special morphological peculiarities of the sturgeons (shape, way of swimming, their dimensions). Both YOLACT technology and a computer vision context were tested using LAB and HSV colour spaces to estimate fish biomass based on imaging data. It was found that the LAB colour space provided superior results in terms of precision and efficiency, but maximum accuracy was achieved using convolutional neural networks (YOLACT). The analysis of the project results confirms the significant advantages of using the AI system for biomass monitoring, advantages consisting of the reduction of unit costs with labour and feed, improvement of water quality, active optimisation of sturgeon growing conditions. In this way, conditions are created for the sustainable growth of sturgeon production, both for consumption and for the restocking of various aquatic ecosystems with brood. It also proves that the large-scale implementation of AI-based technologies in the fisheries industry can make an important contribution to the achievement of Romania s National Multiannual Aquaculture Strategic Plan 2022-2030, as well as to the implementation of the European Union s strategies on food security and biodiversity.

Suggested Citation

  • Dragos Sebastian Cristea & Alexandru Adrian Gavrila & Stefan Mihai Petrea & Dan Munteanu & Sofia David & Catalin Octavian Manescu, 2024. "The Use of Artificial Intelligence in Sturgeon Aquaculture," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(67), pages 957-957, August.
  • Handle: RePEc:aes:amfeco:v:26:y:2024:i:67:p:957
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    References listed on IDEAS

    as
    1. Cristina Venera GEAMBASU & Iulia JIANU & Ionel JIANU & Alexandru GAVRILA, 2011. "Influence Factors for the Choice of a Software Development Methodology," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 10(4), pages 479-494, December.
    2. Lavinia-Andreea GRUIA & Nicolae BIBU & Marian NASTASE & Alexandru ROJA & Nicoleta CRISTACHE, 2020. "Approaches to Digitalization within Organizations and Romania," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 21(3), pages 287-297, July.
    3. Cristina Venera Tartavulea & Catalin Nicolae Albu & Nadia Albu & Ramona Iulia Dieaconescu & Silvia Petre, 2020. "Online Teaching Practices and the Effectiveness of the Educational Process in the Wake of the COVID-19 Pandemic," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(55), pages 920-920, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    artificial intelligence; deep learning; fishery industry; process optimisation; sustainability;
    All these keywords.

    JEL classification:

    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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