Genomic Selection for Small Grain Improvement



In this chapter we present an overview of genomic selection (GS) research in the small grain cereals and interpret some of the results across studies where there is a growing body of information. We also provide the reader with approaches to implementation of GS in applied breeding programs and how various scenarios affect gain from selection and cost relative to conventional breeding. Training population optimization is discussed as well as the factors that affect prediction accuracy. We conclude with comments on future research directions required to improve the efficiency of GS.


Genomic selection Wheat Oats Barley Rye Triticale Inbreeding crops Breeding strategy Gain from selection Marker-assisted selection Training population Whole-genome genotyping 





Bayesian ridge regression


International Maize and Wheat Improvement Center


Diversity Array Technology


Doubled haploids




Environmental covariates


Fusarium head blight


Genotyping by sequencing


Genomic estimated breeding value


Genomic selection


Genotype-by-environment interaction




High-throughput phenotyping


Linkage disequilibrium


Marker-assisted selection




Multi-environment trials


Marker-by-environment interaction


Phenotypic selection


Quantitative trait loci, RR-BLUP, ridge-regression best linear unbiased prediction


Single nucleotide polymorphism


Target population of environments


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.International Programs, College of Agriculture and Life SciencesCornell UniversityIthacaUSA
  2. 2.Department of Plant PathologyKansas State UniversityManhattanUSA
  3. 3.Department of Plant Breeding and GeneticsCornell UniversityNew YorkUSA

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