Claim · model-written summary
In five-year forecasting the model reduced RMSE by 3.2914% relative to leading models such as AMAP on US soybean county data.
- Taxon
- soybean
Glycine maxe1 - Outcome
- RMSEe0
- Direction
- reducese0
- Value
- 3.2914%e0
- Comparator
- leading models like AMAPe2
- Setting
- major U.S. soybean-producing statese1
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Verbatim
e0“For five-year long-term forecasting, it reduces the RMSE by 3.2914% and increases the R2 by 4.7537%”
e1“major U.S. soybean-producing states”
e2“compared with leading models like AMAP”
Title
Fengling Li; Chengjun Xu; Ronghua Jin Sustainability 2026. doi:10.3390/su18052418
Other claims from this paper (3)
- Method / resource In single-year forecasting the model reduced RMSE by 4.1762% relative to leading models such as AMAP on US soybean county data.
- Method / resource In single-year forecasting the model raised R2 by 3.4458% relative to leading models such as AMAP on US soybean county data.
- Method / resource In five-year forecasting the model increased R2 by 4.7537% relative to leading models such as AMAP on US soybean county data.