Multivariate models improve accuracy of genomic prediction for spring frost tolerance in Norway spruce

Documenti analoghi

• Hybrid kernels integrating genomic and multispectral data improve wheat genomic prediction accuracy
  di: Osval A. Montesinos‐López, et al.
  Pubblicazione: (2025)
• Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield
  di: Guillermo García‐Barrios, et al.
  Pubblicazione: (2025)
• Effects of SNP marker density and training population size on prediction accuracy in alfalfa ( Medicago sativa L.) genomic selection
  di: Hu Wang, et al.
  Pubblicazione: (2024)
• Enhancing prediction accuracy of key biomass partitioning traits in wheat using multi‐kernel genomic prediction models integrating secondary traits and environmental covariates
  di: Sudip Kunwar, et al.
  Pubblicazione: (2025)
• Leveraging unmanned aerial vehicle derived multispectral data for improved genomic prediction in potato ( Solanum tuberosum )
  di: Muyideen Yusuf, et al.
  Pubblicazione: (2025)