R&D Projects

Riasearch develops tailor-made R&D projects in collaboration with research institutions and aquaculture industry partners with the ultimate goal of creating new products and technology for the aquaculture sector.

 

Below are our most relevant R&D projects:

 

ValorMar P2020

 

The ValorMar project integrates 18 companies and 13 research institutions. This project aims to develop four innovative technological solutions that add value to marine resources and potentiate their efficient use through integrating value chains and utilizing all resources in a circular economy.

 

Riasearch’s role is to set up an experimental IMTA with shrimp (Litopenaeus vannamei), halophytes (Salicornia spp.), and ragworms (Hedistes diversicolor), collaborating in the development of a new aquaculture production datamining software and establishing a new area for Salicornia production and new food applications.

 

FEEDFIRST P2020

 

The FEEDFIRST project aims to develop an integrated technological solution for a successful introduction of inert microdiets at the onset of exogenous feeding of fish larvae reared in aquaculture. This project is led by Sparos in collaboration with Riasearch, the Faculty of Engineering of the Polytechnic Institute of Porto, and the Institute for Systems and Computer Engineering, Technology and Science of Porto.

 

Riasearch’s role is to develop hydraulic improvements in rearing tanks that improve larval feeding.

 

INOVSEARCH MAR2020

 

INOVSEARCH is a project lead by Riasearch in collaboration with a fish farm using an intensive flow-through system. This project aims to implement a more sustainable and productive aquaculture system using the water effluent generated by an intensive RAS fish farm to cultivate secondary species, such as ragworms, holothuria, and halophytes using IMTA approach.

 

Riasearch has a triple role in this project. Firstly, to design and implement an IMTA system using a fish farm effluent from an intensive flow-through system at a commercial scale. Secondly, to model the data generated by this pilot system to improve this IMTA system. Finally, to train and demonstrate this system’s results in order to share the sustainability and economic benefits of an IMTA approach to other aquaculture players.