PaddyPulse-SLNR

The PaddyPulse-SLNR is a newly constructed dataset developed to support research in automated rice leaf disease classification. It consists of 2,256 high-resolution images (2592×3456 pixels) covering four major rice leaf diseases: brown spot, rice blast, Bacterial leaf streak, and sheath blight. The images were captured under a controlled white background to ensure consistency and to highlight disease characteristics at multiple scales. Data collection was carried out across key rice-growing regions in Northern Province of Sri Lanka, including Mannar, Jaffna, Mullaitivu, and Kilinochchi, incorporating diverse environmental conditions. The dataset includes images from commonly cultivated rice varieties such as Aattakkari, Bg300, Bg406, and Bg360. Image acquisition was performed using multiple devices, including Canon EOS 60D, Canon R6, Nikon D750, and iPhone 14, to ensure variability in imaging conditions. All images were manually annotated and verified by agricultural officers to ensure labeling accuracy.