Classical and genomic prediction of synthetic open‐pollinated sweet corn performance in organic environments

Open-pollinated cultivars provide a number of benefits for organic and smallholder farmers, allowing them to save seed, conduct on-farm selection, maintain crop genetic diversity. Synthetic open-pollinated advantages over traditional such farmers. The objective this research was determine the usefulness marker-based prediction models relative structured mating design-based predictions selecting untested sweet corn synthetic production systems. This study used marker data phenotypic collected in 2015 2016 11 trials across six locations on 40 (Zea mays L.) inbreds 100 hybrid progeny formed from four disconnected North Carolina Design II (NC DII) blocks predict performance populations. In 2017, validation 26 previously populations were grown five environments assess correlations between actual predicted by genomic best linear unbiased (GBLUP) or NC DII general combining abilities (GCAs). Correlations values measured 2017 complete dataset ranged 0.28 0.68 GCA-based predictions, 0.25 0.67 additive GBLUP model, plus dominance model. general, neither model with solely effects nor both demonstrated consistent increases accuracy population above based ability. However, could be that shared alleles training set, even if parents never included which is not possible ability models.