Rice Leaf Disease and Pest Dataset Overview

Published: 11 November 2024| Version 1 | DOI: 10.17632/vwv3nry3wr.1
Contributors:
,
,
, Mayen Uddin Mojumdar

Description

This dataset, tailored for training machine learning models in rice disease and pest detection, supports precision agriculture, crop management, and automated rice plant health monitoring. It contains 2,769 original images from various field conditions, expanded to 19,128 images through augmentation techniques for robust model training. #Purpose: Automatic identification of rice diseases and pests. #Original and Augmented Data: 2,769 original images, augmented to 19,128 with rotation, flipping, cropping, scaling, and color adjustments. #Categories: Tungro: Yellowed, stunted leaves due to Tungro virus. Leaf Stripes: Stripe patterns from possible nutrient issues or stress. Leaffolder: Leaf damage by Leaffolder pest (Cnaphalocrocis medinalis). Healthy: Disease-free rice leaves. Rice: General rice leaf images. Leaf Blast: Necrotic lesions from fungal disease Pyricularia oryzae. Insect: Damage from insects other than Leaffolder. #Applications: Enhances precision agriculture, aids in early disease detection, and supports mobile and IoT-based monitoring systems for rice farming.

Files

Institutions

Daffodil International University

Categories

Asian Rice, Agriculture

Licence