Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture (DigiSal)

Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. Project DigiSal will lay the foundations for a Digital Salmon: an ensemble of mathematical descriptions of salmon physiology, combining mathematics, high-dimensional data analysis, computer science and measurement technology with genomics and experimental biology into a concerted whole.

DigiSal will focus on challenges of novel feedstuffs, collaborating with the Foods of Norway centre for research-based innovation at NBMU. Salmon are carnivores but today aquaculture provides more than half their fat and protein from plants, challenging the metabolic system and affecting fish health and nutritional value of salmon meat. The newly sequenced salmon genome and related resources will enable a tightly integrated theoretical-experimental study of mechanistic interactions among genetic and feed factors.

Project objective: Establish a systems biology framework for adapting salmon breeding and nutrition strategies to modern feedstuffs, blazing the trail for a Digital Salmon endeavour. • Provide and validate a framework for a model-based account of genetic and environmental variation in salmon metabolism • Unravelling the systemic role of gut microbiota in adapting to new feeds • Provide and validate a theoretical framework for systematic identification of targets for steering EPA/DHA metabolism through concerted use of nutrition and genetics • Provide the foundation for a Digital Salmon knowledge base enabling adaption of a transformative pre-emptive research and development strategy

DigiSal is part of the Digital Life project by the BIOTEK2021 biotechnology programme of the Research Council of Norway.

FAIRDOM PALs: No PALs for this Project

Project created: 2nd Feb 2016

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