Claim · model-written summary
Multivariate genomic selection models with the robust, reproducible 3K array SNP markers have great potential for improving genetic gains of dry matter yield in oat breeding.
- Taxon
- oat
Avena sativat0 - Outcome
- genetic gains of DMYe0
Verbatim
e0“the great potential of multivariate GS models incorporating the more robust and easily reproducible 3K array SNP markers for improving the genetic gains of DMY in breeding programs”
t0“biomass yield in oat”
Title
Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179
Other claims from this paper (4)
- Method / resource The 3K array and GBS-based SNPs performed similarly for training population optimization, forward prediction, and univariate and multivariate genomic prediction of forage yield in oat.
- Method / resource GBLUP, Bayes-B and random forest models gave similar predictive ability for dry matter yield across harvest-year combinations and both marker platforms.
- Method / resource Multivariate models with secondary traits gave more than twofold higher predictive abilities than univariate models.
- Method / resource The overlap between top 25% observed and predicted genotypes was higher for multivariate GBLUP models (30.10%-66.99%) than univariate models (27.18%-51.46%).