Biomarkers set to drive the shift towards predictive aquaculture

The ability to monitor, in real time, what is happening inside fish is set to become one of the most transformative changes in aquaculture. Biomarkers will enable a shift from a reactive model, based on visible symptoms, to a preventive approach built on early biological signals, allowing producers to act before problems impact production.

This approach will reshape farm management by adding a new layer of information based on the fish’s biological response. Moving beyond traditional control of water parameters such as oxygen or temperature, biomarkers will make it possible to understand how farming conditions truly affect the organism, placing fish biology at the centre of decision-making.

In practice, this will allow earlier disease detection, feeding strategies tailored to the animal’s physiological state, improved welfare through continuous stress monitoring, and enhanced reproduction through broodstock selection based on biomolecular profiles. Their integration with biosensors and artificial intelligence will further drive the development of precision aquaculture built on biological data, with additional benefits for product quality and traceability.

However, implementation will be gradual. The sector is currently in an intermediate phase in which some biomarkers are already used in diagnostics and trials, but are not yet embedded in day-to-day operations. Standardisation, cost and adaptation to real farm conditions remain the main barriers.

Adoption will also be uneven. Hatcheries and broodstock management are expected to lead the way, followed by large intensive producers, nutrition and health companies, and RAS systems, where control and data value are higher. In more extensive systems, uptake is likely to be slower.

Who is leading implementation?

Although not yet widespread, there are already clear examples of farm-level application. In Norway, NOFIMA and MOWI have used transcriptomic and immunological biomarkers to assess functional diets and disease resistance under production conditions. At the same time, major aquafeed manufacturers are incorporating physiological, immunological and molecular indicators into their R&D programmes to evaluate the impact of diets under farming conditions.

Joint work between Skretting and CIIMAR, in Portugal, has enabled the measurement of physiological and intestinal parameters in Mediterranean species such as European seabass and gilthead seabream under semi-commercial conditions. In Spain, IEO-CSIC has applied biomarkers to assess stress and develop farm-level management and welfare protocols.

Other institutions, such as MIGAL in Israel, are advancing early disease detection systems, while emerging technologies, including glucose biosensors and microbiome analysis, are opening the door to continuous monitoring and early warning systems.

In parallel, initiatives such as AQUA-FAANG are integrating genetic biomarkers into breeding programmes, while platforms like BiOceanOr and Observe Technologies are building the digital infrastructure needed to incorporate these data into daily farm management.

Overall, these examples highlight that biomarkers are already present in aquaculture, but mainly as validation and decision-support tools rather than fully integrated systems. The next step will be their incorporation into continuous monitoring platforms based on sensors and artificial intelligence.

This transition will not be immediate or highly visible, but gradual. Rather than fully biomarker-driven farms, the sector will move towards systems where these indicators increasingly influence decisions. All signs suggest that the technology is ready, and that full integration is now underway.