Apple Leaf Diseases Image Dataset of ICAR-CITH

Published: 11 August 2025| Version 1 | DOI: 10.17632/gm6mfz8fz6.1
Contributors:
Sajad Un Nabi, RONIT JAISWAL

Description

This dataset, titled Apple Leaf Diseases Image Dataset of CITH, contains high-quality images of apple leaves affected by four major diseases: Alternaria leaf blotch, Apple scab, Powdery mildew, and Mosaic virus. • Alternaria leaf blotch, Powdery mildew, and Mosaic virus images were collected from the experimental fields of the ICAR–Central Institute of Temperate Horticulture (CITH), Srinagar, India under natural field conditions. • Apple scab images were sourced from publicly available data on the Kaggle platform to complement field-collected data. The dataset is intended to support research in plant disease diagnosis, computer vision, and precision horticulture, particularly in the development and evaluation of machine learning and deep learning models for disease classification and detection in apple crops. Each image is provided in its original resolution without preprocessing, allowing flexibility for various experimental setups. All images are categorized by disease type and stored in separate folders for easy accessibility. Potential Applications: • Automated apple leaf disease detection and classification • Deep learning model training and benchmarking • Comparative studies on disease detection under varying background conditions • Educational and extension activities in horticulture plant pathology Researchers and practitioners are encouraged to cite this dataset when used in publications or projects.

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Institutions

  • Central Institute of Temperate Horticulture

Categories

Machine Learning, Plant Pathology, Deep Learning

Licence