Claim · model-written summary
Classification rules for eggplant fruit shape reached an accuracy of 92.59%.
- Taxon
- eggplant
Solanum melongenat0 - Outcome
- accuracye1
- Value
- 92.59%e1
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“eggplant”
e1“high accuracy (92.59%) classification rules were generated”
Title
Qiang Li; Shuangxia Luo; Huimin Du; et al. Journal of Integrative Agriculture 2026. doi:10.1016/j.jia.2026.03.027
Other claims from this paper (6)
- Method / resource A decision tree model with Gini index-based variable selection identified thirteen fruit shape categories in eggplant.
- Method / resource Ten key attributes that largely determine eggplant fruit shape were identified.
- Method / resource Five other methods (random forest, XGBoost, SVM, K-means and GMM) were less robust for fruit shape classification than the decision tree.
- Observation Four QTLs controlling Fruit Shape Index (FSI) and Proximal Angle Micro (PAMi) were detected in eggplant using GWAS and QTL-seq.
- Intervention effect Overexpression of the candidate gene SmFSI3.1 / SmFL in tomato resulted in elongated fruits.
- Mechanism The authors interpret the tomato result as indicating a positive role of SmFSI3.1 / SmFL in regulating fruit elongation in eggplant.