Aloe Vera Leaf Disease Detection Dataset

Published: 13 November 2024| Version 1 | DOI: 10.17632/7w6t4zx33n.1
Contributors:
,
, Mayen Uddin Mojumdar

Description

#Description: This dataset contains 2,500 images of Aloe vera leaves under various health conditions, including four specific diseases and a healthy state. It supports the development of machine learning models for automatic detection and classification of Aloe vera health conditions, aiding researchers, farmers, and agricultural technology specialists in enhancing plant health monitoring and early disease detection. #Dataset Content: The dataset includes images captured under varied conditions (lighting, backgrounds, growth stages) to enhance model accuracy. It is organized as follows: Aloe Rust: 210 images Anthracnose: 500 images Leaf Spot: 500 images SunBurn: 510 images Healthy: 780 images #Purpose: This dataset is intended to support the development of machine learning models that can: Automatically identify and classify Aloe vera leaf conditions, aiding in disease detection and plant health monitoring. Assist farmers in reducing chemical use and improving crop yields through early disease detection. Promote sustainable and efficient farming practices by improving resource management in Aloe vera cultivation.

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Institutions

Daffodil International University

Categories

Agricultural Plant

Licence