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The aim of this study was to identify quantitative trait locus (QTL) associated with grain yield (GY) in a recombinant inbred line (RIL) population from a cross between two elite soft red winter wheat (SRWW) cultivars ('Pioneer 26R61' and 'AGS2000'). The RIL population was grown from 2011 to 2014 in 12 site-year combinations throughout the southeastern US. Overall, AGS2000 was the higher yielding parental line, out-performing 26R61 in seven of the 12 environments. Mean GY for the RILs ranged from 3.39 to 7.16 t ha -1 with significant genotype, environment and genotype by environmental interaction effects. Nine stable QTL were detected for yield, explaining up to 53 % of the phenotypic variation when fit into a multiple-QTL model. The QTL with the largest effect was detected at the Vrn-B1 locus with the short vernalization winter allele from AGS2000 favorable for yield. In addition, vrn-B1 acted additively with a region on chromosome 2B near the Ppd-B1 locus, indicating that a shorter vernalization requirement combined with the Ppd-B1b allele for photoperiod sensitivity may play a key role in adaptation of SRWW to the southern US. Single nucleotide polymorphism markers linked to additional QTL on chromosomes 3A and 3B were in agreement with a previous genome-wide association study in spring wheat, confirming the importance of these regions for yield across environments and germplasm pools. Overall the stable QTL were more predictive of GY compared to individual site-year QTL, indicating that a targeted QTL approach can be utilized by breeding programs to enrich for favorable loci.Electronic supplementary material The online version of this article (

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The objective of this study was to identify quantitative trait loci (QTL) associated with normalized difference vegetation index (NDVI) measured across different growth stages in a wheat (Triticum aestivum L.) recombinant inbred line (RIL) population and to determine the predictability of NDVI and grain yield (GY) using a genomic selection (GS) approach. The RILs were grown over three seasons in 12 total site‐years and NDVI was measured in seven site‐years. Measurements of NDVI from tillering to physiological maturity showed low to moderate heritability (h2 = 0.06–0.68). Positive correlations were observed among NDVI, GY, and biomass, particularly in low‐yielding site‐years. Quantitative trait loci analysis found 18 genomic regions associated with NDVI, with most pleiotropic across multiple growth stages. The QTL were detected near markers for Ppd‐B1, Ppd‐D1, vrn‐A1, and vrn‐B1, with Ppd‐D1 having the largest effect. Multiple QTL models showed that epistatic interactions between Ppd and Vrn loci also significantly influenced NDVI. Genomic selection accuracy ranged from r = −0.10 to 0.54 for NDVI across growth stages. However, the inclusion of Vrn and Ppd loci as fixed effect covariates increased GS accuracy for NDVI and GY in site‐year groupings with the lowest heritability. The highest accuracy for GY (r = 0.58–0.59) was observed in the site‐year grouping with the highest heritability (h2 = 0.85). Overall, these results will aid in future selection of optimal plant growth for target environments using both phenotypic and GS approaches.