|Title||One size fits all? : optimization of rainbow trout breeding program under diverse preferences and genotype-by-environment interaction|
|Source||University. Promotor(en): Johan van Arendonk, co-promotor(en): Hans Komen; A. Kause. - S.l. : s.n. - ISBN 9789461734648 - 200|
Animal Breeding and Genetics
|Publication type||Dissertation, internally prepared|
|Keyword(s)||regenboogforel - dierveredeling - veredelingsprogramma's - genotype-milieu interactie - optimalisatie - kenmerken - genetische winst - selectief fokken - simulatie - visteelt - aquacultuur - rainbow trout - animal breeding - breeding programmes - genotype environment interaction - optimization - traits - genetic gain - selective breeding - simulation - fish culture - aquaculture|
|Categories||Cultured Fishes / Aquaculture Breeding, Reproduction and Genetics|
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.