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Measuring, monitoring, assessing, auditing and safeguarding fish welfare in aquaculture is of the utmost importance to ensure the overall sustainability of the sector. Welfare is key to many short- and long-term operational farming decisions, but the strength of a given decision depends upon the quality and context of the information the farmer has. However, it is often difficult to measure and monitor fish welfare, especially when farming large numbers of fish and when available tools are not as robust or as operational as needed. Animal welfare is measured and monitored using welfare indicators (WIs), and while there are a wide array of welfare indicators available, these may not be suitable for all species, life stages, husbandry routines, rearing systems or budgets. Digitalising this process is a way to address and resolve some of the challenges a stakeholder faces regarding documenting and auditing input- and outcome-based WIs. The following chapter outlines what welfare is and a range of technologies that one can use to measure and monitor fish welfare, with emphasis on real-time online monitoring. It also provides examples of how AI can add value to these technologies and considers how to integrate welfare indicators into a digital twin.

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Fish Health and Welfare Monitoring for Potential Digital Twins

  • 章节

  • 发表日期：

    2026年

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  • Chris Noble,
  • René Alvestad,
  • Pablo Arechavala-López,
  • Finn Olav Bjørnson,
  • Nina Bloecher,
  • Meredith Burke,
  • Petr Císař,
  • Lynne Falconer,
  • Martin Føre,
  • Gaute A. N. Helberg,
  • David Izquierdo-Gomez,
  • Kristbjörg Edda Jónsdóttir,
  • Sunil Kadri,
  • Jelena Kolarevic,
  • Santhosh K. Kumaran,
  • Thomas Larsson,
  • Ingrid Måge,
  • Jonatan Nilsson,
  • Samuel Ortega,
  • Sonia Rey Planellas,
  • Lars Erik Solberg,
  • Lars H. Stien,
  • Bjørn-Steinar Sæther,
  • Linda Tschirren,
  • Elisabeth Ytteborg,
  • Lucas Zena

摘要

Measuring, monitoring, assessing, auditing and safeguarding fish welfare in aquaculture is of the utmost importance to ensure the overall sustainability of the sector. Welfare is key to many short- and long-term operational farming decisions, but the strength of a given decision depends upon the quality and context of the information the farmer has. However, it is often difficult to measure and monitor fish welfare, especially when farming large numbers of fish and when available tools are not as robust or as operational as needed. Animal welfare is measured and monitored using welfare indicators (WIs), and while there are a wide array of welfare indicators available, these may not be suitable for all species, life stages, husbandry routines, rearing systems or budgets. Digitalising this process is a way to address and resolve some of the challenges a stakeholder faces regarding documenting and auditing input- and outcome-based WIs. The following chapter outlines what welfare is and a range of technologies that one can use to measure and monitor fish welfare, with emphasis on real-time online monitoring. It also provides examples of how AI can add value to these technologies and considers how to integrate welfare indicators into a digital twin.