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用于孟加拉国蔬菜田植物叶片疾病检测和新鲜度评估的综合智能手机图像数据集。

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

作者信息

Hasan Mahamudul, Gani Raiyan, Rashid Dr Mohammad Rifat Ahmmad, Tarin Taslima Khan, Kamara Raka, Mou Mahbuba Yasmin, Rabbi Sheikh Fajlay

机构信息

Department of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.

出版信息

Data Brief. 2024 Aug 2;56:110775. doi: 10.1016/j.dib.2024.110775. eCollection 2024 Oct.


DOI:10.1016/j.dib.2024.110775
PMID:39221011
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11363486/
Abstract

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.

摘要

孟加拉国的农业格局受到蔬菜种植的显著影响,蔬菜种植极大地提升了该国的营养水平、经济状况和粮食安全。数百万人依靠蔬菜生产维持生计,为众多农民带来了可观的收入。然而,叶部病害经常影响蔬菜作物的产量和品质。植物病害是全球农业生产力的常见阻碍,对作物质量和产量产生不利影响,给农民造成巨大经济损失。早期发现植物叶部病害对于改善种植和蔬菜生产至关重要。诸如细菌性叶斑病、花叶病毒病和霜霉病等常见病害常常减少蔬菜种植,并严重影响蔬菜生产和粮食经济。因此,孟加拉国的许多农民难以识别具体病害,遭受了重大损失。该数据集包含12643张孟加拉国广泛种植作物的图像,便于对比健康叶片识别不健康叶片。数据集中包括苦瓜(2223张图像)、葫芦(1803张图像)、茄子(2944张图像)、花椰菜(1598张图像)、黄瓜(1626张图像)和西红柿(2449张图像)等蔬菜叶片的图像。每个蔬菜类别都包含几种影响种植的常见病害。通过识别早期叶部病害,该数据集对农民和农业研究人员都将非常宝贵。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/f424941636ef/gr23.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/d32dd8327d0c/gr1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/2acf6747b9eb/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/3d833395cd15/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/568c74b3a419/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/6825b13c79c5/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/b8a5ba9957ff/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/f4653bce7c28/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/8828730f7a9f/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/70be7be69cde/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/b1fc5c55bedd/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/11f126e9ec06/gr13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/9b8d85b6459c/gr14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/cdf2b4eef5c2/gr15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/1868d46ffa3e/gr16.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/7615a339786d/gr17.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/d1167f2e1af0/gr18.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/715369e5cc76/gr19.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/77f80ac03fff/gr20.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/45ff2d0e8505/gr21.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/0fe953d42533/gr22.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/f424941636ef/gr23.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/d32dd8327d0c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/5d7b89f9c986/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/d6e6e5c7b6a3/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/2acf6747b9eb/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/3d833395cd15/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/568c74b3a419/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/6825b13c79c5/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/b8a5ba9957ff/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/f4653bce7c28/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/8828730f7a9f/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/70be7be69cde/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/b1fc5c55bedd/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/11f126e9ec06/gr13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/9b8d85b6459c/gr14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/cdf2b4eef5c2/gr15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/1868d46ffa3e/gr16.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/7615a339786d/gr17.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/d1167f2e1af0/gr18.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/715369e5cc76/gr19.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/77f80ac03fff/gr20.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/45ff2d0e8505/gr21.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/0fe953d42533/gr22.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e74d/11363486/f424941636ef/gr23.jpg

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[2]
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本文引用的文献

[1]
Smartphone image dataset to distinguish healthy and unhealthy leaves in papaya orchards in Bangladesh.

Data Brief. 2024-6-6

[2]
A dataset for successful recognition of cucumber diseases.

Data Brief. 2023-6-16

[3]
Seed Transmission of Begomoviruses: A Potential Threat for Bitter Gourd Cultivation.

Plants (Basel). 2023-3-21

[4]
Molecular Breeding Strategy and Challenges Towards Improvement of Downy Mildew Resistance in Cauliflower ( var. L.).

Front Plant Sci. 2021-7-20

[5]
Suppression of Verticillium Wilt of Eggplant by Earthworms.

Plant Dis. 2009-5

[6]
Tomato yellow leaf curl virus, an emerging virus complex causing epidemics worldwide.

Virus Res. 2000-11

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