Durian Plantation Disease Identification Algal Spot Disease Image Dataset

#Image classification #Object detection #Disease identification #Agricultural pest and disease detection #Smart agriculture management #Crop health monitoring
Records
500 records
Size
1.5G
Format
JPG
Provider
MOBIUSI INCMOBIUSI INC
Updated
v1.02026-11-05
AI Analysis & Value Prop
Currently, the durian plantation industry faces crop yield reduction and economic loss due to untimely disease identification. Traditional disease management relies on manual experience, but due to lack of precision and efficiency, technological upgrades are urgently needed. This dataset aims to provide high-quality disease samples to support the application of robotic vision in agricultural disease detection. Data collection was completed using professional photography equipment under various lighting and weather conditions to ensure sample diversity. During the data annotation stage, multiple rounds of expert review and consistency checks were employed to enhance annotation accuracy. The annotation team comprised plant pathology experts with extensive industry experience. The data preprocessing process includes image denoising, normalization, and data augmentation to improve the effectiveness of model training. Data storage adopts a hierarchical folder structure for ease of management and access.

Overview

Dataset Insights

Preview

Sample Examples

d9d5dda6**.jpg|3024*4032|1.10 MB

1b91b0bc**.jpg|1920*2560|462.98 KB

89000bb0**.jpg|1920*2560|578.21 KB

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Schema

Technical Specifications

file_namestringFile name
qualitystringResolution
disease_severitystringThe classification of the severity of algal spot disease, such as mild, moderate, or severe.
affected_area_percentagefloatThe percentage of the leaf surface area affected by algal spot disease.
leaf_health_statusstringThe overall health status of the leaf, with possible values like healthy, damaged, severely damaged, etc.
disease_spot_countintThe number of visible algal spots on the leaf.
leaf_color_variationstringThe changes in the color of the leaf, such as yellow, brown, or greenish-brown.
disease_spot_size_rangestringThe size range of the disease spots on the leaf, such as small, medium, large, etc.
leaf_texture_changesstringThe changes in the texture of the leaf due to the disease.
visual_symptomsstringThe description of symptoms observed visually on the leaf.

Trust

Compliance Statement

Authorization Type

Proprietary - Commercial AI Training License (No Redistribution)

Commercial Use

Requires exclusive subscription or authorization contract (monthly or per-invocation charging)

Privacy and Anonymization

No PII, no real company names, simulated scenarios follow industry standards

Compliance System

Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

FAQ

Frequently Asked Questions

What does the Durian Cultivation Disease Identification Algal Spot Image Dataset include?
This dataset includes multiple images used for identifying durian disease, specifically algal spot, aimed at enhancing the recognition capability of robotic vision systems.
How does this dataset help improve robotic vision technology?
By providing specific visual samples of durian diseases, this dataset helps in training and testing visual recognition algorithms, improving the accuracy of disease identification by robots.
Who can benefit from the Durian Cultivation Disease Identification Dataset?
Agricultural technology developers, robotic vision engineers, and durian plantation managers can benefit from it to improve crop management and disease control.
What are the common symptoms of durian algal spot disease?
Common symptoms of algal spot disease include small brown spots on the leaves, which expand and merge over time.
How to use this dataset for algorithm training?
The dataset can be loaded through a machine learning framework, using image labels to train visual recognition algorithms, supporting automatic detection of durian diseases.

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Cite this Work

@dataset{Mobiusi2026,
  title={Durian Plantation Disease Identification Algal Spot Disease Image Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/0b4711777e863e8715ceee81a23a3d23?dataset_task_cate_id=2},
  urldate={2026-02-04},
  keywords={Durian disease identification, Algal spot disease image dataset, Smart agriculture dataset},
  version={1.0}
}

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