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All Journal Zero : Jurnal Sains, Matematika, dan Terapan
Surono, Sugiyarto
Department of Mathematics, Ahmad Dahlan University, Yogyakarta 55191, Indonesia
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics

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ResNet-18 Citrus Classification with Augmentation: Peel Color Associations with pH and Vitamin C Dewi, Titin Afrina Priani; Surono, Sugiyarto; Thobirin, Aris
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i3.27199

Abstract

Limes and lemons are widely consumed, but field quality assessment is often subjective. This study built a ResNet-18 citrus classifier using transfer learning and data augmentation, and evaluated it with stratified 5-fold cross-validation on 80 images (40 limes, 40 lemons). All analyses were conducted per fold to reduce optimistic bias. The model reached 98.75% mean validation accuracy, misclassifying one lime image while correctly recognizing all lemons. For interpretation, peel regions were quantified using NDYI and CIELab (L*, a*, b*), and related to pH and vitamin C using Spearman correlation. Uncertainty was quantified with bootstrap-based 95% confidence intervals for each correlation. Peel color features were more consistently associated with pH (especially in limes), whereas correlations with vitamin C were weak and non-significant for both fruits. Results indicate strong performance under controlled imaging, but using peel color as a vitamin C proxy requires broader data and external validation across cameras and lighting.
Co-Authors Dewi, Titin Afrina Priani Thobirin, Aris