Assessing the agronomic potential of sorghum B‐lines using genomic prediction

Abstract

In hybrid sorghum breeding, basic agronomic traits such as days to flowering and plant height of sorghum seed parents must be within a specific range for hybrid seed production. Because many sorghum programs select new B‐lines outside of commercial seed production environments, the purpose of this study was to determine if genomic prediction is effective to evaluate new lines for their agronomic potential for seed production. Two B‐line RIL populations were evaluated across several environments for days to mid anthesis (DY), plant height (PH), panicle length (PL) and grain yield (GY). Across environments and populations, average prediction accuracies were between 0.47 and 0.61 for DY, 0.24 and 0.60 for PH, 0.16 and 0.37 for GY, and 0.37 and 0.57 for PL. The effect of training set size was assessed by subsampling various amounts of data into the training set, ranging from 5% to 65%. Prediction accuracies generally improved as the proportion of the total data in the training set increased for both inter‐ and intra‐population predictions, but a relatively small portion (15%) of the total data still produced modest prediction accuracies. The effect of the marker density on genomic prediction accuracies was assessed by subsampling various numbers of SNPs. It was observed that as few as 500 markers were able to produce prediction accuracies similar to when all markers were used. The results of this study indicated that genomic prediction can be a useful and cost‐effective tool that sorghum breeding programs should incorporate into their pipeline.This article is protected by copyright. All rights reserved