High-Resolution Images of Lychee and Jackfruit Plant Diseases for Classification and Detection
Description
This dataset consists of high-resolution images of lychee (Litchi chinensis) and jackfruit (Artocarpus heterophyllus) plants collected from Biral, Dinajpur, Bangladesh, a region renowned for its lychee and jackfruit production. The dataset was captured between 7th and 12th November 2025 and includes a total of 8,000 images. The collection comprises 3,856 images of lychee leaves, which after augmentation, total 6,000 images, and 628 images of jackfruit leaves, which after augmentation, total 2,000 images. The dataset is categorized into eight distinct disease types and plant conditions: Lychee Leaves: Anthracnose Cloudy: 971 images Algal Spot Indirect: 697 images Dry Leaves: 477 images Entomosporium Spot: 407 images Leaf Mites Direct: 657 images Mayetiola PostRain: 647 images Jackfruit Leaves: Mature Jackfruit Leaf: 127 images Young Jackfruit Leaf: 501 images Augmented Dataset (After Augmentation): Lychee Leaves (Augmented to 6,000 images): Anthracnose Cloudy: 1,000 images Algal Spot Indirect: 1,000 images Dry Leaves: 1,000 images Entomosporium Spot: 1,000 images Leaf Mites Direct: 1,000 images Mayetiola PostRain: 1,000 images Jackfruit Leaves (Augmented to 2,000 images): Mature Jackfruit Leaf: 1,000 images Young Jackfruit Leaf: 1,000 images Data Collection Process: The images were captured using smartphones (Poco F5 and Google Pixel 7) from various angles and under different lighting conditions, ensuring a variety of perspectives and environmental factors. Image Resolution: Original Resolution: 3024 × 4032 pixels Processed Resolution: 512 × 512 pixels for efficient processing Primary Goal of the Dataset: This dataset is designed to assist in the development of machine learning and deep learning models for: Classification of disease types in lychee and jackfruit plants Detection of disease symptoms at various stages Monitoring plant health and growth conditions Use Cases: Agricultural Disease Management: Facilitating early detection and monitoring of diseases in crops. Precision Farming: Enhancing crop health monitoring for better yield prediction and resource allocation. Plant Pathology: Advancing the study and understanding of plant diseases in lychee and jackfruit. This dataset serves as a valuable resource for researchers and agricultural professionals focused on improving disease management and precision farming practices. With its diversity of plant conditions and disease types, it aids in the development of advanced systems for crop health monitoring, disease detection, and the enhancement of agricultural practices for lychee and jackfruit plants.
Files
Institutions
- Daffodil International University