Method / resourcemodel-written summary

VisLAI attained R2 0.84 at big trumpet.

A claim from Maize Leaf Area Index Estimation Based on Machine Learning Algorithm and Computer Vision · 2025

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

VisLAI attained R2 0.84 at big trumpet.

Taxon
MaizeZea mayst0
Organ / stage
big trumpete0
Outcome
R2e0
Value
0.84e0

Not reportedMaterialGeneCompoundInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Zea mays
Zea mays · TaxonAkwugo · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

t0

“Maize”

✓ located verbatim in the source · title, characters 0–5
e0

“The proposed LAI estimation model, named VisLAI, based solely on visible light imagery, demonstrated high accuracy, with R2 values of 0.84, 0.75, and 0.50, and RMSE values of 0.24, 0.35, and 0.44 across the big trumpet, tasseling–silking, and grain filling stages, respectively.”

✓ located verbatim in the source · abstract, characters 811–1089

Title

Maize Leaf Area Index Estimation Based on Machine Learning Algorithm and Computer Vision

Wanna Fu; Zhen Chen; Qian Cheng; et al. Agriculture 2025. doi:10.3390/agriculture15121272

Other claims from this paper (18)

Record rev-2b6a85a365b2c8ca158051bdbe76bc15c61fef47f359206108f4a9ab22c68634 · schema claims-v0.9 · position 1 in the model’s answer