Corn Rust Disease Recognition Image Dataset

#image classification #target detection #data augmentation #agricultural pest and disease recognition #corn crop health management #intelligent agriculture monitoring
  • 500 records
  • 1.2G
  • JPG
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-16

AI Analysis & Value Prop

Currently in agricultural production, corn rust disease is one of the main diseases affecting yield and quality. Facing the challenges of outbreaks at different locations and rapid spread, precise identification and real-time monitoring have become urgent solutions. Existing methods rely on manual operations, which are not only inefficient but also limited in recognition accuracy, unable to meet the demands of large-scale production. This dataset focuses on improving the technical level of corn rust disease recognition, supporting the intelligent upgrade of crop health management systems. Data is collected using drones and ground-based camera equipment under various weather conditions, covering different growth stages and regions to ensure data diversity. Quality control involves multiple rounds of annotation, consistency checks, and review by plant pathology experts to improve annotation accuracy. The annotation team consists of professionals with an agricultural science background, involving a team of 10 people. During preprocessing, color correction, size normalization, and background interference filtering are performed, and data is stored in a folder structure organized by region and time.

Dataset Insights

Sample Examples

b4ca1a8c**.jpg|3072*4096|862.94 KB

af930715**.jpg|3072*4096|975.76 KB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
corn_disease_typestringThis field is used to label the specific type of rust disease affecting the corn in the image.
disease_severitystringThis field is used to label the severity of the corn disease, such as mild, moderate, or severe.
leaf_positionstringThis field is used to label the position of the affected leaf on the plant, such as upper, middle, or lower leaf.
rust_pustule_countintegerThis field is used to label the number of visible rust pustules in the image.
leaf_area_infectedfloatThis field is used to label the percentage of the leaf area that is infected.
color_change_presencebooleanThis field is used to indicate whether there is a color change in the leaf in the image.

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

What can this dataset be used for?
The Farmland Corn Rust Disease Identification Image Dataset can be used to accurately identify and monitor corn rust disease, thus improving crop health management efficiency.
Who would be interested in this dataset?
Agricultural researchers, plant pathologists, and smart agriculture system developers may be interested in this Farmland Corn Rust Disease Identification Image Dataset.
What are the practical applications of this dataset in agriculture?
The practical applications of this dataset in agriculture include assisting farmers and agricultural consultants in quickly identifying and monitoring corn rust disease to take timely measures to prevent its spread.
What are the advantages of using this dataset?
The advantages of using this dataset include improving the accuracy and efficiency of detecting corn rust disease, reducing the use of chemical agents, and promoting sustainable agriculture.
Can this dataset be applied through machine learning models?
Yes, this Farmland Corn Rust Disease Identification Image Dataset can be used to train machine learning models for automated detection and classification of corn rust disease.

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Cite this Work

@dataset{Mobiusi2026,
  title={Corn Rust Disease Recognition Image Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/b56d026c88e6bbc1d648e1a29fe12ede},
  urldate={2026-02-04},
  keywords={corn rust disease recognition, agricultural pest and disease dataset, intelligent agriculture monitoring data},
  version={1.0}
}

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