Claim · model-written summary
Vegetation index values at greenup, dormancy and peak of season were the most important yield prediction covariates.
Zea maysNot reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Vegetation index values at greenup, dormancy and POS were the most important covariates for the prediction”
e1“machine learning prediction of maize yield”
Title
Dorijan Radočaj; Ivan Plaščak; Željko Barač; et al. OTO 2025 2026. doi:10.3390/engproc2026125001
Other claims from this paper (3)
- Method / resource SVM with NDVI phenology metrics had the highest maize yield prediction accuracy.
- Method / resource Occurrence day of year of the vegetation index metrics had only a minor effect on yield prediction accuracy.
- Method / resource NDVI outperformed NDVI3RE for maize yield prediction when combined with phenology metrics.