Comprehensive smart smartphone image dataset for plant leaf disease detection and freshness assessment from Bangladesh vegetable fields.

Autor:	Hasan M; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh., Gani R; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh., Rashid DMRA; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh., Tarin TK; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh., Kamara R; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh., Mou MY; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh., Rabbi SF; Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Jazyk:	angličtina
Zdroj:	Data in brief [Data Brief] 2024 Aug 02; Vol. 56, pp. 110775. Date of Electronic Publication: 2024 Aug 02 (Print Publication: 2024).
DOI:	10.1016/j.dib.2024.110775
Abstrakt:	Bangladesh's agricultural landscape is significantly influenced by vegetable cultivation, which substantially enhances nutrition, the economy, and food security in the nation. Millions of people rely on vegetable production for their daily sustenance, generating considerable income for numerous farmers. However, leaf diseases frequently compromise the yield and quality of vegetable crops. Plant diseases are a common impediment to global agricultural productivity, adversely affecting crop quality and yield, leading to substantial economic losses for farmers. Early detection of plant leaf diseases is crucial for improving cultivation and vegetable production. Common diseases such as Bacterial Spot, Mosaic Virus, and Downy Mildew often reduce vegetable plant cultivation and severely impact vegetable production and the food economy. Consequently, many farmers in Bangladesh struggle to identify the specific diseases, incurring significant losses. This dataset contains 12,643 images of widely grown crops in Bangladesh, facilitating the identification of unhealthy leaves compared to healthy ones. The dataset includes images of vegetable leaves such as Bitter Gourd (2223 images), Bottle Gourd (1803 images), Eggplants (2944 images), Cauliflowers (1598 images), Cucumbers (1626 images), and Tomatoes (2449 images). Each vegetable class encompasses several common diseases that affect cultivation. By identifying early leaf diseases, this dataset will be invaluable for farmers and agricultural researchers alike. (© 2024 The Author(s).)
Databáze:	MEDLINE
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