Cristin-prosjekt-ID: 415876
Sist endret: 9. januar 2015 15:59
Cristin-prosjekt-ID: 415876
Sist endret: 9. januar 2015 15:59
Prosjekt

Improved methodology for analyzing survival data in fish breeding programs

prosjektleder

Ingrid Olesen
ved NOFIMA

prosjekteier / koordinerende forskningsansvarlig enhet

  • NOFIMA
  • Institutt for husdyr- og akvakulturvitenskap ved Norges miljø- og biovitenskapelige universitet
  • Realfag og teknologi ved Norges miljø- og biovitenskapelige universitet
  • Diverse norske bedrifter og organisasjoner

Klassifisering

Vitenskapsdisipliner

Akvakultur • Husdyravl, oppdrett, forplantning

Tidsramme

Avsluttet
Start: 1. september 2003 Slutt: 31. august 2006

Beskrivelse Beskrivelse

Tittel

Improved methodology for analyzing survival data in fish breeding programs

Sammendrag

Selection for increased disease resistance based on survival data obtained in commercial farm environments is inefficient due to low genetic variation for such survival traits. Higher genetic variation has been observed for specific disease resistance observed as survival in controlled challenge tests. However, the current statistical methodology used to obtain estimates of genetic variances and prediction of family breeding values for such challenge test survival data (a normal univariate mixed linear model), does not utilize all information in the data. The objective of this project is to evaluate available statistical methods developed for genetic evaluation of livestock (i.e. threshold and survival models) that will utilize more of the information in the observed survival data to better describe the genetic variation in disease resistance and thus improve the selection for increased disease resistance in fish breeding programs. Existing data from Atlantic salmon, Pacific prawn and Nile tilapia will be used when evaluating available statistical models. However, the methodology will also be suitable to analyze survival data for traits in other aquaculture species and for other traits that may be recorded in challenge tests (e.g. cold-water and salinity tolerance).

Vitenskapelig sammendrag

Selection for increased disease resistance based on survival data obtained in commercial farm environments is inefficient due to low genetic variation for such survival traits. Higher genetic variation has been observed for specific disease resistance observed as survival in controlled challenge tests. However, the current statistical methodology used to obtain estimates of genetic variances and prediction of family breeding values for such challenge test survival data (a normal univariate mixed linear model), does not utilize all information in the data. The objective of this project is to evaluate available statistical methods developed for genetic evaluation of livestock (i.e. threshold and survival models) that will utilize more of the information in the observed survival data to better describe the genetic variation in disease resistance and thus improve the selection for increased disease resistance in fish breeding programs. Existing data from Atlantic salmon, Pacific prawn and Nile tilapia will be used when evaluating available statistical models. However, the methodology will also be suitable to analyze survival data for traits in other aquaculture species and for other traits that may be recorded in challenge tests (e.g. cold-water and salinity tolerance).

prosjektdeltakere

prosjektleder

Ingrid Olesen

  • Tilknyttet:
    Prosjektleder
    ved NOFIMA

Bjarne Gjerde

  • Tilknyttet:
    Prosjektdeltaker
    ved Diverse norske bedrifter og organisasjoner

Gunnar Klemetsdal

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for husdyr- og akvakulturvitenskap ved Norges miljø- og biovitenskapelige universitet

Jørgen Ødegård

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for husdyr- og akvakulturvitenskap ved Norges miljø- og biovitenskapelige universitet

Ragnar Salte

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for husdyr- og akvakulturvitenskap ved Norges miljø- og biovitenskapelige universitet
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Resultater Resultater

Evaluation of statistical models for genetic analysis of challenge test data on furunculosis resistance in Atlantic salmon (Salmo salar): Prediction of field survival.

Ødegård, Jørgen; Olesen, Ingrid; Gjerde, Bjarne; Klemetsdal, Gunnar. 2006, Aquaculture. NMBU, NOFIMAVitenskapelig artikkel

Genetic analysis of survival data from challenge testing of furunculosis in Atlantic salmon: Model comparison using field survival data.

Ødegård, Jørgen; Olesen, Ingrid; Gjerde, Bjarne; Klemetsdal, Gunnar. 2005, 56th annual meeting of the European association for animal production.. NMBU, NOFIMAVitenskapelig foredrag
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