In DIGIRAS, the microbiota in 4 commercial RAS facilities and 5 corresponding fish species (Seabream, seabass, seriola, charr and salmon) were monitored periods between 6-9 months. More than 1000 samples were taken, subjected to DNA extraction and 16S rRNA amplicon sequencing according to standard operation procedures to ensure direct comparability of results. Processing of sequencing data was standardized and is carried out in a cloud solution that is available to all partners. Microbiome profiling of fish samples (taken from skin, gill and gut mucus) revealed community structure similarities in species cultivated in fresh- and seawater, respectively. This approach was also used to identify samples potentially containing problematic bacteria, such as pathogens and sulfate reducing bacteria. These samples will be further analyzed more detailed for precise quantification of the suspected microbes using qPCR methods. Full metagenome sequencing has been conducted for 10 selected samples so far and results are currently processed.
A novel H2S sensor prototype has been developed for rapid analysis of ultra-low H2S levels. The sensor system has been tested successfully in Milli-Q water and will be validated in real RAS water.
Recently, we have conducted a H2S exposure experiment to study the impact of low H2S concentrations on the behaviour of salmon smolt in RAS. Fish behaviour was monitored using a newly developed underwater camera system. Preliminary results showed that addition of H2S resulted to a significant change in swimming velocity and synchronization. Additional video data was acquired using a top-down surveillance camera but corresponding data have not been processed yet. Fish tissue and cortisol samples were taken during the experiment and are currently under processing.
During the monitoring campaign in the commercial RAS facilities, classical fish welfare was also investigated for seabream, seabass and seriola by histopathological and water cortisol analyses. However, only minor indications for gill damage were found for a very limited number of fish.
We also studied the removal of problematic compounds in RAS water, such as off-flavour and nitrogen compounds. Besides advanced oxidation processes, a covalent framework (COF) matrix was developed for the removal of off-flavour compounds. The COF matrix was tested successfully in Milli-Q water and will be validated in real RAS water. In addition, different microalgae species have been tested for their potential of NH3 removal from RAS water and the first results are promising.
Major focus is currently on integrating sequencing data and chemical water quality parameters recorded at the commercial facilities employing linear regression models and subsequently supervised machine learning approaches. The aim is to identify indicators for potentially problematic deviations that can be used as early warning tools.
Recirculating aquaculture systems (RASs) have been developed for land-based production of sea- and freshwater species. These systems are designed to provide high biomass production while reducing resource usage and maximizing control of operational parameters. However, only a few of these parameters are systematically monitored, and currently applied analysis techniques are often insufficiently sensitive, slow or laborious. Consequently, the full potential of RASs for more sustainable food production remains unexploited. The over-all goal of the DIGIRAS project is to develop innovative and data-driven solutions for digitalization of future RAS technology in order to increase environmental compatibility, fish health and productivity. The project intends to reach this goal by systematic acquisition of relevant water quality data, parameterization of fish behaviour, developing new biological and chemical sensors and efficient water treatment technology. DIGIRAS will strive to integrate all generated data towards decision support and predictive tools for next generation digital RAS operation. In DIGIRAS, R&D institutions with strong competence in (micro)biology and chemistry, fish health, video monitoring/machine learning, modelling and water treatment technology will join forces with industrial partners from the fish farming and RAS technology sector. Together, this consortium will contribute to improve land-based fish farming technology significanlty, with respect to animal health, production conditions, environmental benefits and sustainability. Moreover, DIGIRAS aims at contributing to more sustainable growth in the aquaculture sector by developing new technologies, and thus, generating new jobs in infrastructurally less developed areas in Europe.
In DIGIRAS, 6 R&D institutions and 5 industry partners (1 external contributor) from 5 participating European countries will collaborate for 36 months with a total funding budget of 1.68 Mio € (project budget 1.94 Mio €).
