Claim · model-written summary
Univariate regression gave an R2 of 0.913 for moisture content, with RMSE 0.081.
- Taxon
- rice
Oryza sativat0 - Material
- Longqingdao 3e0
- Outcome
- moisture contente1
- Value
- 0.913e1
- Qualifier
- corresponding RMSE values of 0.122, 0.081, and 1.167e1
- Setting
- Suiling Water Conservancy Comprehensive Experimental Statione0
Not reportedGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rice Quality and Yield Prediction”
e0“Field experiments were conducted in 2018 at the Suiling Water Conservancy Comprehensive Experimental Station (47°27′ N, 127°06′ E), using Longqingdao 3 as the test variety”
e1“The results demonstrated that the optimal R2 values for brown rice rate, moisture content, and taste value were 0.866, 0.913, and 0.651, with corresponding RMSE values of 0.122, 0.081, and 1.167”
Title
Rice Quality and Yield Prediction Based on Multi-Source Indicators at Different Periods
Yufei Hou; Huiyu Bao; Tamanna Islam Rimi; et al. Plants 2025. doi:10.3390/plants14030424
Other claims from this paper (5)
- Method / resource Univariate regression gave an R2 of 0.866 for brown rice rate, with RMSE 0.122.
- Method / resource Univariate regression gave an R2 of 0.651 for taste value, with RMSE 1.167.
- Method / resource After model optimisation, the R2 for brown rice rate improved significantly to 0.95, with RMSE 0.075.
- Method / resource After model optimisation, the R2 for taste value improved significantly to 0.992, with RMSE 0.179.
- Method / resource The spectral index GM2 at the jointing stage gave the highest accuracy for yield prediction, with an R2 of 0.822.