GENOMIC SELECTION MODELS SUBSTANTIALLY IMPROVE THE ACCURACY OF GENETIC MERIT PREDICTIONS FOR FILLET YIELD AND BODY WEIGHT IN RAINBOW TROUT USING A MULTI-TRAIT MODEL AND MULTI-GENERATION PROGENY TESTING

Genomic selection models substantially improve the accuracy of genetic merit predictions for fillet yield and body weight in rainbow trout using a multi-trait model and multi-generation progeny testing

Abstract Background In aquaculture, the proportion of edible meat (FY = fillet yield) is of major economic importance, and breeding animals of superior genetic merit for this trait can improve efficiency and profitability.Achieving genetic gains for fillet yield is possible using a pedigree-based best linear unbiased prediction (PBLUP) model with d

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