The project has developed expertise and technology for offshore aquaculture. An overarching goal of the project has been to contribute to sustainable use of the oceans and ensure production that contributes to climate neutrality and the preservation of fish health and biodiversity.
To obtain knowledge about how aquaculture at sea, and in exposed areas, affects the biodiversity in sediment and water column, environmental DNA analyses were performed. The aim was to investigate how diversity changes throughout a production cycle. Molecular markers have been identified in the water column that can be linked to production.
Researchers have developed non-invasive methods to monitor infection around facilities. Both specific markers and changes in bacterial communities have been investigated. Such markers can be used to plan the transport and handling of fish, so that this happens when the infection pressure is low. Sampling tools and protocols were developed for rapid testing of pathogens in freshwater and seawater, methods have been published and were adopted at facilities by operating personnel. A marked increase in pathogens was detected in the water column after delousing and this illustrates the importance of early detection of infection in order to plan the handling of fish. In further work to develop real-time monitoring, a protocol was developed for the detection of cortisol in seawater and various technology for rapid testing in the field was tested for assessment of changes in biodiversity.
Bioeconomic modelling tools have been developed for offshore aquaculture that include investment analyses of new technology. In this important work it was investigated how production strategies, environmental conditions and regulatory conditions affect economic sustainability. Analyses were carried out to evaluate energy storage capacity at an offshore fish farm, providing knowledge for climate neutral production. Digital monitoring tools were developed for safer fish farming. A digital twin combining structural and hydrodynamic models was created to simulate an offshore farm in real ocean conditions. Sensor-based and machine learning-based approaches were established to detect pen damage and monitor structural conditions. The model was also extended to study oxygen distribution inside cages.
To ensure optimal production, it is important that smolt is robust in the transition from freshwater to seawater. Researchers investigated how temperature and water velocity in closed systems affect the welfare and stress tolerance of farmed salmon. New potential stress markers have been developed and an optimal combination of temperature and water velocity that ensures growth has been identified. A promising behavioural trait in salmon was observed, as they appeared to avoid the upper parts of the cage in strong wave conditions. If this holds up in future observations, fish in future offshore facilities can still thrive during severe storms by swimming deeper in the cages. Therefore, offshore cage technology must have enough space in the depths. Wave properties with varying water velocities and their creation of turbulent conditions had less impact on critical thresholds, physiology and welfare of Atlantic salmon than assumed. The critical swimming speed of modern farmed salmon of varying sizes appears to be 10–30% higher than previously assumed. Natural oxygen levels offshore provide good conditions for fish farming, while oxygen in deeper fjord environments can limit production. Luring salmon to move from huge cage volumes to smaller areas can be improved by using side exits during collection, leveraging the salmon's natural behavior for easier transfer. New insights has been gained into key areas for fish welfare under more exposed conditions, and the results point to increased opportunities for successful future sustainable offshore salmon farming. To handle dynamic conditions, autonomous offshore systems must be able to both learn and self-adapt the learning process during production. A new AI framework for automated monitoring of fish underwater. The method addresses the challenge of low quality image data of fish and a method was developed to expand the existing fish dataset with virtual fish data to facilitate representative machine learning for effective training.
The project delivers scientifically and societally relevant knowledge that contributes to Norway’s capacity for evidence-based governance of offshore aquaculture. The results advance research on responsible innovation, sustainability governance, and regulatory design by integrating interdisciplinary knowledge. Through the Responsible Innovation Lab (RIL), researchers, authorities and companies have co-created knowledge that balances sustainability, innovation and competitiveness. Results include contributions to a national biosafety regulation for closed facility systems, input to public consultations on offshore licenses, and stakeholder meetings.
SusOffAqua consortium partners—experts in AI, fish health, environmental science, and aquaculture—have co-developed knowledge and innovations, working towards a GHG-zero offshore aquaculture value chain. The project has high relevance for industry and legislators, working to develop a sustainable and competitive industry that aims to provide healthy food for society, while protecting fish health, marine biodiversity and climate. The research is applied and is of direct relevance for everyday operations as well as for public administrators. In the project, advances have been made in developing continuous monitoring of environmental conditions and pathogen status throughout a production cycle. Such knowledge provides operators and administrators with early warning of environmental and infection conditions, facilitating effective management at the cage side. This highlights the value of environmental monitoring for early detection and population-wide assessment, enabling timely mitigation strategies that can reduce stress and improve overall fish welfare. To assess fish stress in a non-lethal way, we established a protocol for measuring cortisol levels from water samples, at the fish farm. To assess the potential for using renewable energy for offshore production, a modelling framework has been established with industry for evaluating energy storage capacity requirements and need for supplementary energy. Furthermore, digital and monitoring tools for safer offshore production, preventing escapes have been developed. AI based tools have also been developed for improved fish counting under water. Maintaining fish welfare and health is instrumental for success of offshore aquaculture. The effect of temperature, water current velocity in smolt production and their interaction on stress response and welfare have been evaluated. Salmon welfare, behaviour and physiology is impacted by waves, behavioural coping in submerged cages during normal and high waves have been described and oxygen levels in Norwegian offshore waters have been collected to judge feasibility for future offshore farming. Important knowledge on the future of offshore aquaculture has been gained through development of bioeconomic models for offshore aquaculture and investment analyses for emerging technologies. The work has examined how production strategies, environmental conditions and regulatory frameworks influence economic performance. Through Responsible Innovation Labs researchers, authorities and companies have co- created knowledge that balances sustainability, innovation and competitiveness. Impact has been assured through contributions to national biosecurity regulation for closed containment systems, input to government hearing on offshore licensing and two major stakeholder meetings in Oslo with ministries, agencies and industry, with the overall goal being to contribute to the development of novel resource efficient value chains for offshore aquaculture.
SusOffAqua unites a cross-disciplinary team of scientists in a unique effort to provide competence, innovation and technology to ensure sustainability and resilience in future offshore aquaculture and its value chains. Ocean resources must be carefully managed, and our oceans are under pressure with multiple users and the ever more imminent global climate change. If the novel offshore aquaculture industry is to achieve societal acceptance and its full potential, the production must be in accordance with the aim to achieve climate neutrality and preserve biodiversity.
The consortium will develop real time monitoring approaches and work towards preventive biosecurity and reduced environmental impact. The concept of an artificial intelligence based autonomous steering system will be piloted as a key enabling technology. This research tackles autonomic information technologies with processes that are autonomously synthesized to an offshore aquaculture management platform that is aware of its architecture and effects and is able to (re-) organise processes at runtime by self-adaptation and optimization. The potential for the implementation of such a technology in future offshore aquaculture will be evaluated in the areas highly relevant for offshore aquaculture, particularly feeding in view of high GHG emissions related to feed value chain. Concurrently fundamental knowledge will be built in key aspects of biological performance, biosecurity, ecological impact, fish welfare and energy systems in with relevance to developing sustainable offshore aquaculture value chains. The project will seek to develop and validate tools (LCA and economic analytics & energy system analysis) to assess to which extent uptake of technology and other innovations can propel the sector towards climate neutrality and low environmental impact.
