A comprehensive image dataset of plum leaf and fruit for disease classification

Plums, commonly known as Indian jujube, are economically important, valued for nutritional benefits and consumed by people from all over the world. The development of a comprehensive Plum leaf and fruit dataset is highly essential for advancing agricultural research and enabling effective disease management systems using machine learning techniques. This dataset serves as a foundational resource for machine learning based classification and bridges the gap between agricultural research and computer vision to support automated disease detection and fruit quality assessment. Researchers will be able to utilize this dataset to implement early disease detection which leads to improve crop management and supply quality and reduce the usage of chemicals. Proper utilization of this dataset can help farmers to reduce financial losses and encourage sustainable farming practices. The dataset was collected between December 2024 and February 2025 under various environmental conditions. It consists of 3,554 original images, an equal number of processed images and 18,000 augmented images generated from the original dataset. The dataset is categorized into six distinct classes: Shot Hole, Bacterial Spot, Wilted Leaf, Healthy Leaf, Unhealthy Plum, and Healthy Plum. This dataset contributes significantly to advance deep learning in agriculture enabling early disease detection and fruit quality monitoring.