Claim · model-written summary
A gradient boosting model was appropriate for predicting from the measured data.
- Taxon
- Rice
Oryza sativat0
- Outcome
- appropriate for predicting the modellinge0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The gradient‐boosting machine‐learning model was appropriate for predicting the modelling based on the measured data.”
t0“Rice”
Title
Binoy Kumar Show; Suraj Panja; Richik GhoshThakur; et al. Sustainability 2023. doi:10.3390/su151813706
Other claims from this paper (4)
- Intervention effect CW–BF:NPK (3:1:1) produced the highest grain yield of 7521 kg/hectare.
- Intervention effect CW–BF:NPK (3:1:1) increased panicle length, test weight and filled grains relative to other combinations.
- Observation PCA placed NPK first with high loading values.
- Observation PCA placed digestate as the second principal component.