Claim · model-written summary
Calibration accuracy was 95.52%.
- Taxon
- barley seeds
Hordeum vulgaret0 - Outcome
- accuracy of the calibration sete0
- Value
- 95.52%e0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
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Verbatim
e0“The accuracy of the calibration set and the prediction set were 95.52% and 93.71%”
t0“barley seeds varieties using hyperspectral data”
Title
Heng Sun; Liu Zhang; Hao Li; et al. Journal of Food Process Engineering 2021. doi:10.1111/jfpe.13769
Other claims from this paper (7)
- Method / resource Reverse spectra with multivariate scatter correction gave the best modeling results.
- Method / resource Ventral spectra with Savitzky–Golay first derivative gave the best modeling results.
- Method / resource K nearest neighbors with successive projections on reverse spectra was selected as the best model.
- Method / resource Prediction accuracy was 93.71%.
- Method / resource Calibration Kappa was 0.9424.
- Method / resource Prediction Kappa was 0.9156.
- Method / resource Mixed reverse and ventral spectral data gave satisfactory results.