Method / resourcemodel-written summary

MobileNetV2 and DenseNet121 achieved 96.25% accuracy in chili pepper disease classification.

A claim from Deep learning enables precision agriculture for sustainable chili pepper disease detection in Benin · 2025

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

MobileNetV2 and DenseNet121 achieved 96.25% accuracy in chili pepper disease classification.

Taxon
chili pepperCapsicumt0
Treatment
MobileNetV2 and DenseNet121e4
Outcome
accuracye4
Value
96.25%e4

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleComparatorSettingDirectionQualifier

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

Capsicum
Capsicum · Taxon · picture of the genus (one of its species)Public domain · Wikimedia Commons ↗

Verbatim

t0

“chili pepper disease detection”

✓ located verbatim in the source · title, characters 60–90
e4

“MobileNetV2 and DenseNet121 achieved 96.25% accuracy”

✓ located verbatim in the source · abstract, characters 1559–1611

Title

Deep learning enables precision agriculture for sustainable chili pepper disease detection in Benin

Mireille Gloria Founmilayo Odounfa; Castro Gbêmêmali Hounmenou; Valère Kolawolé Salako; et al. Discover Artificial Intelligence 2025. doi:10.1007/s44163-025-00583-4

Other claims from this paper (4)

Record rev-96dc32a63c6a8a55956e25cc8162dde9b69472de267b9761c5a7edab63f199c6 · schema claims-v0.9 · position 5 in the model’s answer