Rice pest dataset supports the construction of smart farming systems

Rice holds a significant position in the global food supply chain, particularly in Asian, African, and Latin American countries. However, rice pests and diseases cause significant damage to the supply and growth of the rice cultivation industry. Therefore, this article provides a high-quality datase...

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Bibliographic Details
Published in:Data in brief 2024-02, Vol.52, p.110046-110046, Article 110046
Main Authors: Quach, Luyl-Da, Nguyen, Quoc Khang, Nguyen, Quynh Anh, Lan, Le Thi Thu
Format: Article
Language:English
Subjects:
Computer vision
Data
Deep learning
Image segmentation
Machine learning
Rice disease
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Summary:Rice holds a significant position in the global food supply chain, particularly in Asian, African, and Latin American countries. However, rice pests and diseases cause significant damage to the supply and growth of the rice cultivation industry. Therefore, this article provides a high-quality dataset that has been reviewed by agricultural experts. The dataset is well-suited to support the development of automation systems and smart farming practices. It plays a vital role in facilitating the automatic construction, detection, and classification of rice diseases. However, challenges arise due to the diversity of the dataset collected from various sources, varying in terms of disease types and sizes. This necessitates support for upgrading and enhancing the dataset through various operations in data processing, preprocessing, and statistical analysis. The dataset is provided completely free of charge and has been rigorously evaluated by agricultural experts, making it a reliable resource for system development, research, and communication needs.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2024.110046