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Fig. 4 | BMC Genomics

Fig. 4

From: Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat

Fig. 4

Cross-validation schemes employed. ST-CV1: single-trait cross-validation scheme where a training set of 70% of random genotypes are phenotyped and genotyped and a testing set of remaining 30% of genotypes are genotyped, not phenotyped; MT-CV1: multi-trait cross-validation scheme where a training set of 70% of random genotypes are phenotyped (primary + secondary traits) and genotyped and remaining 30% of genotypes are genotyped only, not phenotyped; MT-CV2: multi-trait cross-validation scheme where 100% information from secondary traits, a training set of 70% of random genotypes are phenotyped for primary traits and remaining 30% of genotypes as testing set (phenotyped for correlated traits but not primary traits and genotyped)

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