Grass Maturity Detection Dataset
#Object Detection #Image Classification #Agricultural Monitoring #Crop Management #Precision Agriculture
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-13
AI Analysis & Value Prop
The current agricultural industry faces challenges such as insufficient crop growth monitoring and inaccurate maturity assessments, leading to unmet crop yield and quality assurance. Existing monitoring methods often rely on manual observation, which is inefficient and prone to errors. This dataset aims to address the shortcomings of object detection technology in agricultural applications by providing high-quality grass maturity images, meeting the needs of farmers and agricultural managers for precision agriculture. Data is primarily collected using high-resolution cameras in natural environments to ensure diversity and representativeness of the samples. Quality control measures such as multiple rounds of annotation, expert review, and consistency checks are implemented to ensure annotation accuracy. Data is stored in JPG format, organized by image ID and relevant annotation information.
Dataset Insights
Sample Examples
7948c41d**.jpg|4464*2976|2.59 MB
172679b7**.jpg|4000*2667|1.31 MB
79ea9827**.jpg|5184*3456|3.85 MB
65088787**.jpg|7360*4912|6.79 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| maturity_level | integer | The maturity level of the grass judged by visible characteristics. |
| color_index | float | The average color index of the grass, indicating its health and maturity. |
| leaf_count | integer | The count of identifiable grass leaves in the image. |
| disease_signs | boolean | Whether there are visible signs of pests or diseases on the grass in the image. |
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 agricultural applications can the Grass Maturity Detection Dataset be used for?
- The dataset is mainly used for assessing grass maturity to help optimize harvest timing and improve agricultural productivity.
- How is the object detection task performed on this dataset?
- Use image annotation tools to label grass images and train models to detect the maturity level of grass in the images.
- What are the advantages of grass maturity detection in agricultural production?
- Accurate detection of grass maturity can optimize harvest timing, reduce waste, and enhance economic benefits.
- What kind of image information is included in the dataset?
- The dataset includes high-quality images of grass with clearly annotated target areas of different maturity levels.
- How can the accuracy of grass maturity detection be improved?
- Improve detection accuracy by using larger and more diverse image datasets and more advanced deep learning models.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Grass Maturity Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/d8385dc1af7bc4ca641650321029f8af},
urldate={2025-09-15},
keywords={Grass Maturity, Object Detection Dataset, Agricultural Monitoring, Precision Agriculture},
version={1.0}
}Using this in research? Please cite us.
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