Fig. 1: The prediction accuracies and standard errors of scenario 1.
From: Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods

(a Fivefold cross validation; and b 50-fold cross validation). Methods under evaluation were Bayesian genomic best linear unbiased predictor (BG-BLUP), Bayesian LASSO, Bayes C, Bayesian additive regression tree (BART), and these four models further adding pedigree or structure information as random effects. Traits being analysed included fibre length (LEN), uniformity (UNI), short fibre index (SFI), fibre strength (STR), fibre elongation (EL), fibre micronaire (MIC), lint yield (LY) and lint percentage (LP).