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Table 4 Predictive accuracy and bias in cross-validation

From: Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size

  

CW

REA

RT

SFT

YI

BMS

Accuracya

Additivec model

0.630

0.541

0.449

0.550

0.546

0.596

Non-additived model

0.632

0.546

0.450

0.552

0.552

0.599

Biasb

Additive model

0.399

0.290

0.201

0.302

0.295

0.352

Non-additive model

0.401

0.294

0.203

0.303

0.299

0.354

  1. CW carcass weight, REA rib eye area, RT rib thickness, SFT subcutaneous fat thickness, YI yield rate, BMS beef marbling score
  2. aPearson’s correlation coefficient between adjusted phenotypic values and predicted total genotypic values
  3. bCoefficient obtained by regressing predicted total genotypic values on adjusted phenotypic values
  4. cModel A
  5. dModel AD for RT and Model AA2 for the other traits