Genomic prediction of UAV-phenotyped ground cover in organic spring Wheat and Oat (original) (raw)

Mahmood, Khalid; Oertelt, Lukas; Orabi, Jihad; Jørgensen, Janni Hedensvang; Haldrup, Hans; Jahoor, Ahmed and Sarup, Pernille (2025) Genomic prediction of UAV-phenotyped ground cover in organic spring Wheat and Oat. [Genomic prediction of UAV-phenotyped ground cover in organic spring Wheat and Oat.] Working paper, Grindsnabevej 25 8300 Odder, Denmark, Nordic Seed
Kornamrken 1
8464 Galten
Denmark . [Completed]

Summary

This study demonstrates the potential of integrating UAV-based phenotyping with genomic prediction to enhance selection for ground cover in organic spring oat and wheat breeding. UAV-derived measurements of canopy development effectively captured meaningful phenotypic variation, particularly at early growth stages, when differences among genotypes were most pronounced. The moderate to high heritability estimates indicate that ground cover is under genetic control and can be improved through selection. Genomic prediction models achieved substantial accuracy, especially for early-season ground cover, confirming that genetics can reliably predict complex canopy traits even in diverse organic populations. The positive genetic and phenotypic correlations between early ground cover, late ground cover, and grain yield further suggest that selection for rapid canopy establishment will indirectly enhance yield potential and weed competitiveness, two key objectives in organic cereal production. By enabling early and objective assessment of canopy development, this approach can accelerate genetic gain for both agronomic performance and ecological resilience in organically managed systems. Future work should focus on multi-environment and multi-year validation, as well as integration with other UAV-derived traits such as canopy temperature and spectral indices, to further refine genomic selection models and support holistic improvement of organic cereal crops.

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