Asparagus Quality Grading Dataset
#object detection #classification #image recognition #agricultural detection #quality control #automatic grading
- Records
- 5000 records
- Size
- 1.5G
- Format
- JPG/PNG/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
AI Analysis & Value Prop
The current agricultural industry faces challenges in asparagus grading and quality control, such as low efficiency and poor accuracy in manual grading. Existing solutions often rely on manual experience and lack standardization, leading to inconsistent grading results. This dataset aims to improve the application of AI in agricultural detection by establishing an asparagus grading system based on freshness, thickness, and color. The structure of the dataset includes fields such as images, sample ID, freshness, thickness, and color. Data collection uses professional cameras in a greenhouse environment to ensure the captured images are clear and distinguishable. Our quality control measures include multiple rounds of annotation and expert review to enhance the consistency and accuracy of annotations. The data will be stored in JPG format, organized by sample ID to ensure easy retrieval and use.
Overview
Dataset Insights
Preview
Sample Examples
c3bc7ae8**.jpg|4433*5541|3.47 MB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| asparagus_color | string | The color of the asparagus, which helps in determining its maturity and quality. |
| asparagus_length | float | The length of the asparagus, measured in centimeters, used as a grading criterion. |
| asparagus_thickness | float | The thickness of the asparagus, measured in millimeters, can affect its classification grade. |
| surface_quality | string | The quality of the asparagus surface, such as the presence of damage or spots. |
| tip_compactness | string | The compactness of the asparagus tip, which helps evaluate the freshness of the asparagus. |
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 is the Asparagus Quality Grading Dataset?
- The Asparagus Quality Grading Dataset is an image dataset used for quality detection and grading of asparagus, aimed at supporting automation in agriculture.
- How to use the Asparagus Quality Grading Dataset for object detection?
- The Asparagus Quality Grading Dataset can be applied to object detection algorithms, by training models to identify and grade the quality of asparagus.
- How does the Asparagus Quality Grading Dataset help agriculture?
- This dataset offers an automated solution that can significantly improve the grading efficiency of asparagus, reduce labor costs, and enhance the accuracy of agricultural inspections.
- What are the industry applications of the Asparagus Quality Grading Dataset?
- It is mainly applied in the agriculture industry, specifically used in scenarios requiring asparagus quality inspection and automated grading.
- Why choose images as the data modality for Asparagus Quality Grading?
- Image modality provides high-resolution information, facilitating precise analysis and evaluation of asparagus quality, and offering a visual foundation for machine learning models.
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Cite this Work
@dataset{Mobiusi2025,
title={Asparagus Quality Grading Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/a8167648508c6b3066b1844c1966f972?dataset_scene_id=5},
urldate={2025-09-15},
keywords={asparagus dataset, object detection, agricultural quality control, AI grading, asparagus grading},
version={1.0}
}Using this in research? Please cite us.
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