BDRubberLeaf: A Comprehensive Dataset of Rubber Tree Leaf Diseases from Bangladesh for Agricultural Research
Description
The Rubber Leaf Disease Dataset is a comprehensive collection of high-quality images of rubber tree leaves, systematically gathered from a Rubber Garden in Sreemangal Upazila, Moulvibazar District, Bangladesh, between December 23, 2024, and July 10, 2025. The dataset consists of eight distinct classes: Abnormal, Anthracnose, Black_Spot, Dry_Leaf, Healthy_Leaf, Leaf_Blight, Leaf_Spot and Powdery_Mildew which represent various stages of both diseased and healthy conditions in rubber tree leaves. The total dataset contains 4,066 images, with class-wise distribution as follows: Abnormal (561 images), Anthracnose (300 images), Healthy Leaf (506 images), Dry Leaf (450 images), Leaf_Blight(414 images), Powdery_Mildew (480 images), Black_Spot (450 images), and Leaf Spot (595 images). The images were captured using the Realme 6i smartphone in natural lighting conditions, ensuring high resolution and clarity. The original images were captured in jpg format at a resolution of 4000 × 3000 pixels, later resized to 480 × 640 pixels with a resolution of 72 dpi to standardize the dataset. Although the dataset does not include annotations, it serves as a valuable resource for researchers and machine learning practitioners focused on plant disease classification and early disease detection in rubber trees. This dataset is particularly relevant for applications in precision agriculture and automated plant pathology analysis, where understanding leaf conditions can play a critical role in improving crop health management strategies.