Tomato Diseases and Pests Identification Dataset
#Object Detection #Image Classification #Agricultural Monitoring #Disease and Pest Identification #Crop Management
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The current agricultural field faces significant losses caused by diseases and pests, especially in tomato cultivation, where the occurrence of diseases and pests directly affects yield and quality. Existing monitoring methods largely rely on manual inspection, which is inefficient and prone to missing critical information. This dataset aims to provide high-quality image data support for the automatic identification of agricultural diseases and pests, improving the accuracy and efficiency of disease and pest identification through object detection technology. Data collection is conducted using high-resolution cameras in natural environments to ensure the authenticity and diversity of the images. We implement multiple rounds of annotation and consistency checks, with professional agricultural experts reviewing the annotation results to ensure data quality. The data is stored in JPEG format, organized by image ID for quick retrieval and use.
Dataset Insights
Sample Examples
93a1cb38**.jpg|3024*4032|2.08 MB
d57c071e**.jpg|3456*5184|1.53 MB
7da20d84**.jpg|4640*6960|5.18 MB
18783cec**.jpg|3456*5184|1.23 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| disease_type | string | The identified type of disease or pest, such as leaf spot disease, powdery mildew, or pest infestation. |
| disease_severity | string | The severity level of the disease or pest, such as mild, moderate, or severe. |
| plant_part_affected | string | The part of the plant affected by the disease or pest, such as leaf, stem, or fruit. |
| symptom_color | string | The color of the symptoms caused by the disease or pest, such as yellow, brown, or black. |
| symptom_shape | string | The shape of the symptoms caused by the disease or pest, such as circular, spotted, or irregular shapes. |
| damage_extent | string | Description of the extent of damage on the plant due to the disease or pest, such as all leaves, most leaves, or few leaves. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 |
Frequently Asked Questions
- What is the Tomato Pest and Disease Recognition Dataset?
- The Tomato Pest and Disease Recognition Dataset is a collection of high-quality images of tomato pests and diseases, designed for object detection tasks to support agricultural automation.
- What are the application areas of the Tomato Pest and Disease Recognition Dataset?
- This dataset is primarily used in the agricultural field to identify and detect various pests and diseases on tomatoes, supporting smart agriculture management and pest prevention.
- What is the image quality of the Tomato Pest and Disease Recognition Dataset?
- The dataset provides high-quality images to ensure the accuracy and effectiveness of object detection tasks.
- How does the Tomato Pest and Disease Recognition Dataset assist in agricultural automation?
- By providing precise pest and disease recognition, this dataset can help improve the efficiency of agricultural automation management and reduce the impact of pests on crops.
- What types of models can be trained using the Tomato Pest and Disease Recognition Dataset?
- The dataset can be used to train object detection models, helping machine learning systems to identify and detect pests and diseases on tomatoes.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Tomato Diseases and Pests Identification Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/00338711fccbdf68753ef614b8384f1b?dataset_scene_id=5},
urldate={2025-09-15},
keywords={Tomato Diseases and Pests Identification, Agricultural Dataset, Object Detection Dataset, Image Recognition, Agricultural Monitoring},
version={1.0}
}Using this in research? Please cite us.
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