Preharvest sprouting (PHS) can severely damage barley (Hordeum vulgare L.) malting quality and is of particular concern in locations with a high frequency of precipitation around harvest. Malting quality and PHS resistance are often negatively correlated, and the SD2 locus on chromosome 5H has been associated with both traits. Using three spring barley populations, PHS, seed dormancy, and germination rate were mapped over six time points to identify changes in genetic control of these traits during the after‐ripening period. HvAlaAT1 at the SD1 locus was associated with long‐term dormancy and reduced germination rate. Ninety lines were Sanger sequenced for HvGA20ox1, but variants were not associated with PHS or germination traits. The allelic state of HvMKK3 was strongly associated with genetic PHS susceptibility in North American spring two‐row barley germplasm and interactions between HvAlaAT1 and HvMKK3 were associated with changes in seed dormancy and germination rate over time. Several malting quality traits were associated with HvMKK3 alleles. Kompetitive allele‐specific polymerase chain reaction (KASP) markers were developed for the causal mutations in HvAlaAT1 and HvMKK3 and a diagnostic mutation in HvGA20ox1. Haplotypes with PHS resistance, short primary dormancy, and a high germination rate were identified that could be useful for breeding for PHS resistance and malting quality.

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Preharvest sprouting (PHS) resistance is essential in malting barley (Hordeum vulgare L.) production to prevent damage caused by late season moisture but may be negatively correlated with malting quality traits. The germination percentage and germination rate (GI) in malting barley are measures of both PHS resistance and suitability for malting. Functional principal component analysis (FPCA) and logistic regression on time series spring malting barley GE and GI were performed to identify genetic regions associated with germination trait changes from 0 to 22 wk after maturity. Both analysis methods identified the SD1 and SD2 regions known to affect germination traits, as well as one novel locus on chromosome 6H at 473 Mbp. Several other associations were detected with a single analysis method. Genomic prediction (GP) was used in conjunction with the time series models to test GE and GI predictability over time. Germination traits of unobserved lines at unobserved times were predicted with high accuracy using ridge regression GP coupled with FPCA or logistic regression. The results demonstrate applicability of time series data analysis in determining genetics of germination trait changes in malting barley and that time series germination is predictable. Threshold traits calculated with these time series models, such as the after‐ripening time needed until a line achieves a GE of 95%, can be used as an estimate for dormancy duration, which will be useful in breeding for combined PHS resistance and malting quality.

New breeding programs are faced with many challenges including evaluation of unknown germplasm, initiation of breeding populations that will satisfy short-and long-term breeding goals, and implementation of efficient phenotyping strategies for multiple traits. Genomic selection (GS) is a potentially valuable tool for recently established breeding programs to quickly accelerate genetic gain. Genomic selection on selection index (SI) values may increase gain over phenotypic selection but empirical studies remain limited. We compared gain in overall SI value for height, heading date, preharvest sprouting (PHS) resistance, and spot blotch resistance and component traits in two cycles of GS with one round of phenotypic selection (PS) in two-row spring malting barley (Hordeum vulgare L.). Higher realized gain for SI value, height, and PHS was observed with GS compared with PS but GS did not result in significant gain for heading date and spot blotch. Genetic variances for height and heading date, which had small index weights, were not reduced with GS but variances were substantially reduced for heavily weighted PHS and correlated seed germination traits. Inbreeding was increased by GS compared with PS but restricted mating of high breeding value individuals limited potential inbreeding. Our results indicate GS is a useful method to improve selection on index values with different weights.

Prediction of trait values in plant breeding populations typically relies on assumptions about marker effect homogeneity across populations. Evidence is presented for winter malting barley (Hordeum vulgare L.) germination traits that a single, causative, largeeffect gene in the Seed dormancy 1 region on Chromosome 5H, HvAlaAT1 (Qsd1), leads to heterogeneous estimated marker effects genome wide between groups of otherwise related individuals carrying different Qsd1 alleles. This led to reduced prediction accuracy across alleles when a model was trained either on individuals carrying both alleles or one allele. Several genomic prediction models were tested to increase prediction accuracy within the Qsd1 allele groups. Small gains (5-12%) in prediction accuracy were realized using structured genomic best linear unbiased predictor models when information about the Qsd1 allele was used to stratify the population. We concluded that a single large-effect locus can lead to heterogeneous marker effects in the same breeding family. Variance partitioning based on largeeffect loci can be used to inform best practices in designing genomic prediction models; however, there are likely few cases for which it may be practical to do this.For malting barley, if germination traits are highly associated with malting quality traits, then similar steps should be considered for malting quality trait prediction.