Smartphone image dataset for radish plant leaf disease classification from Bangladesh

Radishes, which are common root vegetables, are rich in vitamins and minerals, and contain low calories. This vegetable is known for its rapid growth. Nevertheless, the variety of leaf diseases where leaves get affected by various bacterial and fungal diseases can hinder the healthy growth of radish. Furthermore, there is a high risk of inaccurate identification of diseases if the farmers try to use traditional methods in recognizing these diseases. With the purpose of precise identification of radish leaf diseases for the finest growth of this vegetable, total of 2801 images of the radish leaves are collected from vegetable field in Bangladesh. The collected dataset includes comprehensive images of healthy leaves as well as four types of leaf affected by various diseases such as Black Leaf Spot, Downey Mildew, Flea Beetle and Mosaic. Utilizing this robust dataset, deep learning models can be trained to identify the leaf diseases which helps to detect the diseases in order to reduce the harm of the cultivation of radish. By identifying the diseases on radish leaves accurat-ely and maintaining healthy production of radish, this dataset contributes to the broader sustainability in the agricultural sector.

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Publication Details

Journal
Data in Brief
Published
2024-12-27
DOI
https://doi.org/10.1016/j.dib.2024.111263
Citations
5
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
3.00
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article

Smartphone image dataset for radish plant leaf disease classification from Bangladesh

Mohammad Rifat Ahmmad Rashid, Maherun Nessa Isty, Mahamudul Hasan, Taslima Khan Tarin et al.
5 citations
Data in Brief
Smart Agriculture and AI
3.00
article

Smartphone image dataset for radish plant leaf disease classification from Bangladesh

Mohammad Rifat Ahmmad Rashid, Maherun Nessa Isty, Mahamudul Hasan, Taslima Khan Tarin, Raka Kamara, Raiyan Gani
article en
5 citations

Abstract

Radishes, which are common root vegetables, are rich in vitamins and minerals, and contain low calories. This vegetable is known for its rapid growth. Nevertheless, the variety of leaf diseases where leaves get affected by various bacterial and fungal diseases can hinder the healthy growth of radish. Furthermore, there is a high risk of inaccurate identification of diseases if the farmers try to use traditional methods in recognizing these diseases. With the purpose of precise identification of radish leaf diseases for the finest growth of this vegetable, total of 2801 images of the radish leaves are collected from vegetable field in Bangladesh. The collected dataset includes comprehensive images of healthy leaves as well as four types of leaf affected by various diseases such as Black Leaf Spot, Downey Mildew, Flea Beetle and Mosaic. Utilizing this robust dataset, deep learning models can be trained to identify the leaf diseases which helps to detect the diseases in order to reduce the harm of the cultivation of radish. By identifying the diseases on radish leaves accurat-ely and maintaining healthy production of radish, this dataset contributes to the broader sustainability in the agricultural sector.

Data in BriefVol. 58
East West University (BD)
Zero hunger
Openalex Percentile: Top 9%
Smart Agriculture and AI
3.00
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