Innovation Capabilities & Products

Application of the most advanced -omic techniques for the identification of resistance genes that can be used as biomarkers for the selection of pathogen-resistant variants of marine aquaculture species.

MIDER (mutual information distance and entropy reduction) is a general purpose software tool for inferring network structures. It has been developed with biological networks in mind but can be applied to other areas.

More information here.

Development of Deep Learning algorithms that allow automating fisheries monitoring processes and reducing time and costs compared with processing by human observers. The applications developed range from innovative systems for real-time remote electronic monitoring, which identify and quantify total catches of fishing vessels (e.g., iObserver), to new image recognition techniques that allow individually identifying fish and estimating population parameters. 

Identification of new molecular markers for species identification through Next-Generation Sequencing in environmental DNA samples, with applications for biodiversity monitoring and fisheries stock assessment. 

Development and implementation of natural additives (i.e., algae extracts and other lipophilic antioxidants) with antimicrobial and antioxidant properties, as well as innovative food processing and preservation methods (i.e. high hydrostatic pressure) to improve seafood conservation and shelf life.

Authors: Miquel Planas Oliver; Alexandre Chamorro Valverde

Description: Development of integrated culture procedures for the industrial production of seahorses of the species Hippocampus reidi.

Application of the most advanced -omic techniques, together with immunology,  microbiology and protein biochemistry, to develop immunostimulants and vaccines for aquaculture species.

MEIGO is a global optimization toolbox that includes a number of metaheuristic methods, as well as a Bayesian inference method for parameter estimation.

More information here.

Development of stock assessment models to estimate fish population status and Maximum Sustainable Yields for fisheries, based on fishing pressure data and population dynamics parameters (abundance, distribution, age, fecundity, etc.) obtained using traditional approaches and -omic techniques, which allow for a much higher spatial resolution. 

Monitoring temporal and spatial distribution of species, abundance and biomass from several taxa using different techniques such as e-DNA, pigment characterization, flow cytometry, acoustic telemetry, images collected from remote observation systems (i.e. drones, etc.) or classic taxonomic identification.