Acronym NA
Category
Aquaculture
Title Effektivisert avl for bedre helse og sykdomsresistens hos oppdrettsarter - nye statistiske modeller - Streamlined breeding for better health and disease resistance in farmed species - new statistical models 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 Jørgen Ødegård Coordinator email jorgen.odegard@nofima.no
Coordinator institution
NOFIMA - Norwegian Institute of Food, Fisheries and Aquaculture Research (Norway)
Institutions involved
NA
Start year 2009 End year 2012 Funding (€) € 198,378 Website https://prosjektbanken.forskningsradet.no/en/project/FORISS/192331?Kilde=FORISS&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=date&sortOrder=desc&resultCount=30&offset=210&ProgAkt.3=HAVBRUKS-Havbruk+-+en+n%C3%A6ring+i+vekst Summary Traditionally, breeding for increased disease resistance has been based on infection testing against specific diseases, where the test is normally stopped when 50% mortality has been achieved. This has often been shown to be effective in practical breeding work against several diseases. Under a cold condition, however, classical infection testing and modeling will not be optimal due to conditions such as; low mortality in infection testing, mortality is unsuitable as a (sole) health indicator (eg in chronic diseases), infection testing has little rel evans for disease / mortality in the field, or a certain proportion of the population is not susceptible to the disease (breaks the preconditions for classical analyzes). The main objective of this project is therefore to develop statistical models that can contribute to solving these problems.
There are a number of diseases that are not necessarily fatal, but which can cause loss in the form of sick, surviving animals (eg streptococcal infections in tilapia, TSV in shrimp). Our first goal is therefore to develop courage or that can utilize indicator properties (eg growth) to identify sick individuals among the survivors. The models will also be relevant for identifying sick individuals in field data, based on individual growth or other indicator-own capers.
Data on a number of diseases indicate that a certain proportion of non-susceptible individuals exist (furunculosis, IPN and Gyrodactylus salaries in salmon, vibriosis in cod). The second objective is therefore to develop and apply new statistical models that can identify susceptible and non-susceptible individuals. Furthermore, the project will provide indications of how infection testing can be optimized to identify non-susceptible individuals with a high degree of certainty. The new models can be used in selection for reduced susceptibility, and have the potential to streamline breeding work against disease in farmed species by a more targeted selection, combined with better design of the infection tests.
Keywords
Fish health;
Disease;
Fish;
Salmon;
Cod;
Marine Region
76
Not associated to marine areas
0
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