Genomic Selection for Antioxidant Production in a Panel of and Lines.

The purpose of this work was to assess the performance of four genomic selection (GS) models (GBLUP, BRR, Bayesian LASSO and BayesB) in 4 sorghum grain antioxidant traits (phenols, flavonoids, total antioxidant capacity and condensed tannins) using whole-genome SNP markers in a novel diversity panel of lines and landraces and recombinant inbred lines. One key breeding problem modelled was predicting the performance in the antioxidant production of new and unphenotyped sorghum genotypes (validation set). The population was weakly structured (analysis of molecular variance, AMOVA R = 9%), showed a significant genetic diversity and expressed antioxidant traits with a good level of variability and high correlation. The lines outperformed populations for all the antioxidants. The four GS models implemented in this work performed comparably across traits, with accuracy ranging from 0.49 to 0.58, and are considered high enough to sustain sorghum breeding for antioxidants production and allow important genetic gains per unit of time and cost. The results presented in this work are expected to contribute to GS implementation and the genetic improvement of sorghum grain antioxidants for different purposes, including the manufacture of health-promoting and specialty foods.