Durian Plantation Disease Identification Blackhead Disease Image Dataset

#Image classification #disease identification #pattern recognition #Crop disease detection #durian plantation management #smart agriculture diagnostics
  • 500 records
  • 1.4G
  • JPG
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-02-04

AI Analysis & Value Prop

In modern agriculture, durian is a crop with high economic value, but its cultivation is vulnerable to diseases such as blackhead disease. Existing disease identification methods often rely on manual experience, resulting in inefficiency and lack of high accuracy. This dataset provides high-quality images of durian leaf blackhead disease, aiming to address technical issues like data scarcity and low precision in automated detection. The data is collected using high-resolution cameras under different lighting and humidity conditions. Quality control is ensured through multiple rounds of annotation and review by professional fruit tree pathologists, ensuring accuracy and consistency. The annotation team has a plant pathology background, with a total of 20 experts involved. Data preprocessing includes image denoising, normalization, enhancement, and other steps, stored in JPG format and classified by the severity level of the disease.

Dataset Insights

Sample Examples

e0f2b0c8**.jpg|3024*4032|3.10 MB

2bc15039**.jpg|3024*4032|2.94 MB

800acf80**.jpg|3024*4032|2.94 MB

5148bed6**.jpg|3024*4032|2.91 MB

80d98e84**.jpg|3024*4032|3.01 MB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
disease_severitystringIndicates the severity level of the disease on durian trees, such as mild, moderate, or severe.
affected_area_percentagefloatPercentage of the area affected by blackhead disease in the photo compared to the overall area.
disease_spot_countintNumber of visible blackhead disease spots in the image.
leaf_colorstringThe color variation of durian leaves showing symptoms of blackhead disease, such as yellow-green, brown, or black.
symptom_spreadstringExtent of disease symptoms spread within the image, e.g., leaves, twigs, fruit.

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

Who is this dataset suitable for?
The Durian Plantation Disease Recognition Blackhead Disease Image Dataset is suitable for agricultural researchers, agronomists, and machine learning engineers.
How can this dataset be used to improve disease recognition accuracy?
Researchers can use the images in the dataset to train machine learning algorithms, thus improving the accuracy of durian disease recognition.
How does this dataset help in controlling durian blackhead disease?
By accurately recognizing the disease, farmers can promptly take appropriate control measures to prevent the spread of durian blackhead disease.
What is the source of the images in the dataset?
The images in the dataset are sourced from diseased samples collected in actual durian plantations.
Why does durian cultivation need to pay special attention to blackhead disease?
Blackhead disease is a common disease that affects durian yield and quality, hence it requires special attention.

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Cite this Work

@dataset{Mobiusi2026,
  title={Durian Plantation Disease Identification Blackhead Disease Image Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/2ca268c31a67029130c7c1c11cabead5?dataset_task_cate_id=2},
  urldate={2026-02-04},
  keywords={Durian disease identification, blackhead disease detection, agricultural image dataset},
  version={1.0}
}

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