The soybean simulation system ran as expected.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Taxon: Glycine Max (L) Merrillt0
Outcome: system has been running as expectede0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValueQualifier

Verbatim

e0
“Overall, the system has been running as expected.”
✓ located verbatim in the source · abstract, characters 1372–1421

t0
“Glycine Max (L) Merrill”
✓ located verbatim in the source · title, characters 84–107

Title

Machine Learning and Polynomial – L System Algorithm for Modeling and Simulation of Glycine Max (L) Merrill Growth

Rika Rokhana; Wiwiet Herulambang; Rarasmaya Indraswari 2020 International Electronics Symposium (IES) 2020. doi:10.1109/ies50839.2020.9231935

Other claims from this paper (5)

Method / resource The MLP model adapted to varying N, P and K values and estimated soybean growth traits.
Method / resource Mean prediction error for soybean trunk growth was 3.63%.
Method / resource Mean prediction error for soybean leaf width was 3.72%.
Method / resource Mean prediction error for soybean branching growth was 4.27%.
Method / resource Changing N, P and K composition altered the soybean Poly-L System frames.

Record rev-23e229c52b8d9beb05dcd42a9c96427e2a3023c5ca60658fe30c47b226de043c · schema claims-v0.9 · position 6 in the model’s answer