Claim · model-written summary
Cubist, PLS, and SpikeSlab predicted wheat yield effectively at 55-60 days after sowing.
- Taxon
- wheat
Triticum aestivume0 - Organ / stage
- early stagee0
- Outcome
- predicting the wheat yielde0
- Value
- 55-60 days after sowinge0
Not reportedMaterialGeneCompoundInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Cubist, PLS, and SpikeSlab models were found to be effective in predicting the wheat yield at an early stage (55-60 days after sowing) of crop growth.”
Title
RN Singh; P. Krishnan; Vaibhav K. Singh; et al. Scientific Reports 2023. doi:10.1038/s41598-023-45682-3
Other claims from this paper (11)
- Association Canopy temperature increased as wheat rust increased.
- Observation Yellow rust significantly decreased wheat photosynthesis, transpiration, and stomatal conductance.
- Observation Yellow rust significantly decreased wheat leaf area index, membrane stability index, and relative leaf water content.
- Observation Yellow rust significantly decreased wheat normalized difference vegetation index.
- Association Reductions in wheat physiological traits were directly correlated with rust severity.
- Observation Moderately resistant cultivars lost 15.9-16.9% yield relative to resistant cultivars.
- Observation Low resistant cultivars lost 28.6-34.4% yield relative to resistant cultivars.
- Observation Susceptible cultivars lost 59-61.1% yield relative to resistant cultivars.
- Method / resource Machine learning yield estimates became more accurate nearer harvest.
- Method / resource KNN, Cubist, SLR, RF, SpikeSlab, XGB, GPR, and PLS were useful for wheat yield prediction at 70 days after sowing.
- Method / resource RF, SpikeSlab, KNN, Cubist, ELNET, GPR, SLR, XGB, and MARS predicted wheat yield well at 80 days after sowing.