Method / resourcemodel-written summary

The proposed CNN model reached an accuracy of 97% in classifying orange fruit diseases.

A claim from Automatic classification of orange fruit diseases using deep neural network model · 2026

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The proposed CNN model reached an accuracy of 97% in classifying orange fruit diseases.

Taxon
oranget0
Outcome
accuracye0
Value
97%e0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

Verbatim

t0

“orange fruit diseases”

✓ located verbatim in the source · title, characters 28–49
e0

“The proposed model reached an accuracy of 97%”

✓ located verbatim in the source · abstract, characters 1257–1302

Title

Automatic classification of orange fruit diseases using deep neural network model

Silvia Sifath; Sajeeb Saha; Sohely Jahan Journal of Agriculture and Food Research 2026. doi:10.1016/j.jafr.2026.102712

Other claims from this paper (1)

Record rev-70fb9a04e577ca51aa0a28e6d678d9c48b6983af0dc7dcd7a474a79f368ce44b · schema claims-v0.9 · position 2 in the model’s answer