Abstract
Global fish breeders distribute improved animal material to several continents to be farmed under diverse environments, and for very different market conditions. When establishing a global breeding program, there is a need to assess whether or not a single breeding objective satisfies the markets across different countries. It may be challenging to develop a single fish stock that performs well across all environments due to genotype-by-environment interaction (GxE). GxE is a phenomenon describing the possibility that different genotypes have a different sensitivity to changes in an environment. The objective of this thesis was to develop an optimized global breeding program for rainbow trout (Oncorhynchus mykiss) in terms of a balanced breeding goal that satisfies preferences of trout producers and maximized genetic gains across environments in the presence of GxE in production traits. Analytic hierarchy process (AHP) was used to estimate preferences, which can be aggregated to consensus preference values using weighted goal programming (WGP). The analysis revealed that the 6 most important traits were thermal growth coefficient (TGC), survival (Surv), feed conversion ratio (FCR), condition factor (CF), fillet percentage (FIL%), and late maturation (LMat). Individual trait preferences are different for farmers having different farming environments and producing different end-products. Calculating consensus preference values resulted in consensus desired genetic gains. To satisfy most farmers, consensus desired genetic gains can be taken into account in a global breeding strategy. Strong genotype re-ranking was found for all growth traits across environments. Based on simulation, re-location of breeding program led to highest total genetic gain for body weight at harvest. Alternatively, including sib performance into selection index increased genetic gain in all environments. Finally, environment-specific program can be used, but this is costly. There is a possibility of a conflict between 2 profits: from a breeding company and fish farmers and an optimum solution for that conflict can be found by using macroeconomics and cost-benefit analysis.
| Original language | English |
|---|---|
| Qualification | Doctor of Philosophy |
| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 8 Mar 2012 |
| Place of Publication | S.l. |
| Publisher | |
| Print ISBNs | 9789461734648 |
| Publication status | Published - 2013 |
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Keywords
- rainbow trout
- animal breeding
- breeding programmes
- genotype environment interaction
- optimization
- traits
- genetic gain
- selective breeding
- simulation
- fish culture
- aquaculture
Cite this
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Research output: Thesis › internal PhD, WU
TY - THES
T1 - One size fits all? : optimization of rainbow trout breeding program under diverse preferences and genotype-by-environment interaction
AU - Sae-Lim, P.
N1 - WU thesis 5424
PY - 2013
Y1 - 2013
N2 - Global fish breeders distribute improved animal material to several continents to be farmed under diverse environments, and for very different market conditions. When establishing a global breeding program, there is a need to assess whether or not a single breeding objective satisfies the markets across different countries. It may be challenging to develop a single fish stock that performs well across all environments due to genotype-by-environment interaction (GxE). GxE is a phenomenon describing the possibility that different genotypes have a different sensitivity to changes in an environment. The objective of this thesis was to develop an optimized global breeding program for rainbow trout (Oncorhynchus mykiss) in terms of a balanced breeding goal that satisfies preferences of trout producers and maximized genetic gains across environments in the presence of GxE in production traits. Analytic hierarchy process (AHP) was used to estimate preferences, which can be aggregated to consensus preference values using weighted goal programming (WGP). The analysis revealed that the 6 most important traits were thermal growth coefficient (TGC), survival (Surv), feed conversion ratio (FCR), condition factor (CF), fillet percentage (FIL%), and late maturation (LMat). Individual trait preferences are different for farmers having different farming environments and producing different end-products. Calculating consensus preference values resulted in consensus desired genetic gains. To satisfy most farmers, consensus desired genetic gains can be taken into account in a global breeding strategy. Strong genotype re-ranking was found for all growth traits across environments. Based on simulation, re-location of breeding program led to highest total genetic gain for body weight at harvest. Alternatively, including sib performance into selection index increased genetic gain in all environments. Finally, environment-specific program can be used, but this is costly. There is a possibility of a conflict between 2 profits: from a breeding company and fish farmers and an optimum solution for that conflict can be found by using macroeconomics and cost-benefit analysis.
AB - Global fish breeders distribute improved animal material to several continents to be farmed under diverse environments, and for very different market conditions. When establishing a global breeding program, there is a need to assess whether or not a single breeding objective satisfies the markets across different countries. It may be challenging to develop a single fish stock that performs well across all environments due to genotype-by-environment interaction (GxE). GxE is a phenomenon describing the possibility that different genotypes have a different sensitivity to changes in an environment. The objective of this thesis was to develop an optimized global breeding program for rainbow trout (Oncorhynchus mykiss) in terms of a balanced breeding goal that satisfies preferences of trout producers and maximized genetic gains across environments in the presence of GxE in production traits. Analytic hierarchy process (AHP) was used to estimate preferences, which can be aggregated to consensus preference values using weighted goal programming (WGP). The analysis revealed that the 6 most important traits were thermal growth coefficient (TGC), survival (Surv), feed conversion ratio (FCR), condition factor (CF), fillet percentage (FIL%), and late maturation (LMat). Individual trait preferences are different for farmers having different farming environments and producing different end-products. Calculating consensus preference values resulted in consensus desired genetic gains. To satisfy most farmers, consensus desired genetic gains can be taken into account in a global breeding strategy. Strong genotype re-ranking was found for all growth traits across environments. Based on simulation, re-location of breeding program led to highest total genetic gain for body weight at harvest. Alternatively, including sib performance into selection index increased genetic gain in all environments. Finally, environment-specific program can be used, but this is costly. There is a possibility of a conflict between 2 profits: from a breeding company and fish farmers and an optimum solution for that conflict can be found by using macroeconomics and cost-benefit analysis.
KW - regenboogforel
KW - dierveredeling
KW - veredelingsprogramma's
KW - genotype-milieu interactie
KW - optimalisatie
KW - kenmerken
KW - genetische winst
KW - selectief fokken
KW - simulatie
KW - visteelt
KW - aquacultuur
KW - rainbow trout
KW - animal breeding
KW - breeding programmes
KW - genotype environment interaction
KW - optimization
KW - traits
KW - genetic gain
KW - selective breeding
KW - simulation
KW - fish culture
KW - aquaculture
M3 - internal PhD, WU
SN - 9789461734648
PB - s.n.
CY - S.l.
ER -