Design and Implementation of a Web-Based Intelligent System for Kiwifruit Leaf Disease Detection Using Deep Learning

Hoseini Khotbeh Sara, Amirhossein; Sadeghzadeh, Mehdi

doi:10.22092/amsr.2026.372416.1534

Document Type : Original Article

Authors

¹ Master's Graduate in Computer Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran.

² Associate Professor, Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

10.22092/amsr.2026.372416.1534

Abstract

In this study, an intelligent web-based system is presented for diagnosing kiwifruit leaf diseases through image analysis. The proposed system is capable of identifying four conditions: healthy leaves, kiwifruit root infection caused by nematodes, Alternaria leaf infection, and Phytophthora leaf infection. The system was evaluated using the AgriVision-Kiwi benchmark dataset, which has been employed in previous studies on kiwifruit leaf disease diagnosis. In the first stage, the You Only Look Once version 11 (YOLOv11) algorithm was used to detect and localize leaf regions. Subsequently, the detected leaves were classified using the MobileNet-V3 deep learning architecture. The system was developed in Python using the FastAPI framework, while data management was implemented through a MySQL database. The evaluation results obtained on the AgriVision-Kiwi dataset using 10-fold cross-validation demonstrated an overall accuracy of 99. 703%, a macro-averaged precision of 99. 7119%, a macro-averaged recall of 99. 703%, and a macro-averaged F1-score of 99. 703%. These results demonstrate the system’s effectiveness in distinguishing among the four target conditions: healthy leaves, kiwifruit root infection caused by nematodes, Alternaria leaf infection, and Phytophthora leaf infection. The findings further indicate that the proposed system has considerable potential for application under real-world conditions in kiwifruit orchards. Moreover, the web-based nature of the system enhances its accessibility and enables users to employ it directly in orchard environments without requiring complex or specialized equipment.

Keywords

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Agricultural Mechanization and Systems Research

Design and Implementation of a Web-Based Intelligent System for Kiwifruit Leaf Disease Detection Using Deep Learning

References

References

Volume 25, Issue 91 - Serial Number 91
December 2024
Pages 87-104

Design and Implementation of a Web-Based Intelligent System for Kiwifruit Leaf Disease Detection Using Deep Learning

References

References

Volume 25, Issue 91 - Serial Number 91December 2024Pages 87-104

Volume 25, Issue 91 - Serial Number 91
December 2024
Pages 87-104