Acronym DigiSal
Category
Aquaculture
Title Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture Programme National Programme
Instrument (FP6)
Contact Type (FP7)
Strand (Interreg)
NA
Theme (FP7)
Activity Area (FP6)
Regional Area (Interreg)
Action (COST)
NA
Specific Programme (FP7)
NA
Funding source National Coordinator Jon Olav Vik Coordinator email NA
Coordinator institution
NMBU - Norwegian University of Life Sciences (Norway)
Institutions involved
NA - AquaGen AS (Norway) ,
NA - EWOS Innovation AS (Norway) ,
IMR - Institute of Marine Research (Norway) ,
NTNU - Norwegian University of Science and Technology (Norway) ,
UiB - University of Bergen (Norway) ,
UoS - University of Stirling (United Kingdom) ,
WUR - Wageningen University and Research (Netherlands) ,
Start year 2016 End year 2023 Funding (€) € 4,161,290 Website https://prosjektbanken.forskningsradet.no/en/project/FORISS/248792?Kilde=FORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=date&sortOrder=desc&resultCount=30&offset=180&TemaEmne.1=Bruk%2Fdrift+av+forskningsinfrastruktur Summary "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. 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.
Systems-oriented mathematical and statistical modelling will be central, using existing and novel knowledge e.g. on metabolic reaction networks to guide design of experiments through multiple iterations. Metabolic function of fish will be characterized via multiple omics technologies in feeding trials and in vitro tissue-slice culture. Gut microbiota will receive particular attention. The resulting massive data will be summarized via multivariate models to deliver a predictive understanding of a whole range of possible diets, much more efficiently than by traditional feeding trials alone. Data and models will be annotated using bio-relevant ontologies, so that new knowledge automatically connects to that which already exists. Future challenges will be met by quickly reanalysing existing information and understanding of salmon biology, identifying knowledge gaps, acquiring new data and incorporating it into a unified whole. Thus, we begin a shift from a reactive to a pre-emptive R&D strategy in aquaculture."
Keywords
Animal feed;
Bioprospecting;
Fish;
Fish biology;
Genomic sequencing;
Microbiome;
Salmon;
Genetic;
Marine Region
76
Not associated to marine areas
0
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