Organic Fertilizer and Soil Environment Identification Dataset
#target detection #classification #segmentation #agricultural monitoring #soil quality assessment #organic fertilizer usage
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-13
AI Analysis & Value Prop
Challenges faced by the current agricultural industry include declining soil quality and excessive use of chemical fertilizers, leading to sustainability issues. Existing solutions often lack efficient soil monitoring methods and cannot timely assess soil health status. This dataset aims to help researchers and farmers better identify and evaluate soil environments and the use of organic fertilizers by providing high-quality image data and accurate annotation information. During the construction of the dataset, high-resolution cameras were used to capture images in various natural environments, followed by multiple rounds of annotation and expert review to ensure data accuracy and reliability. Data storage is in JPEG format, and annotation information is stored in JSON format, facilitating subsequent machine learning and data analysis.
Dataset Insights
Sample Examples
8ce7b66c**.jpg|3000*2000|1.43 MB
ba0216b6**.jpg|2000*3000|773.02 KB
b7c8bf58**.jpg|5350*3567|3.21 MB
ea28f3cf**.jpg|4000*2000|1.72 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| soil_type | string | Identifies the type of soil, such as sandy soil, loam, clay, etc. |
| fertilizer_presence | boolean | Indicates whether organic fertilizer is present in the image. |
| crop_health_status | string | Assesses and describes crop health, such as healthy, dehydrated, diseased, etc. |
| soil_moisture_level | float | Estimates and records the soil moisture level, expressed as a percentage. |
| organic_matter_content | float | Evaluates the proportion of organic matter content in the soil, expressed as a percentage. |
| vegetation_cover_density | float | Evaluates the density of vegetation cover in the image, expressed as a percentage. |
| ambient_light_condition | string | Describes and categorizes the ambient light conditions at the time of the photo, such as sunny, cloudy, overcast, etc. |
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 |
Frequently Asked Questions
- What is the purpose of the Organic Fertilizer and Soil Environment Recognition Dataset?
- This dataset is used to identify and detect organic fertilizers and soil in the agricultural environment to support agricultural monitoring and assessment.
- How does the Organic Fertilizer and Soil Environment Recognition Dataset help the agricultural sector?
- By using object detection technology, this dataset can help improve the accuracy of soil analysis and optimize fertilization strategies, thereby increasing agricultural production efficiency.
- What data modalities are included in the Organic Fertilizer and Soil Environment Recognition Dataset?
- This dataset primarily includes image modalities for target detection and identification.
- What techniques can be used to analyze the Organic Fertilizer and Soil Environment Recognition Dataset?
- You can use object detection algorithms in deep learning, such as YOLO and Faster R-CNN, to analyze this dataset.
- What is the industrial application value of the Organic Fertilizer and Soil Environment Recognition Dataset?
- Its application value lies in helping agricultural producers better manage soil health, increase crop yields, and improve resource use efficiency.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Organic Fertilizer and Soil Environment Identification Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/8cd5153a58508308e1bfd3fed094f70b?dataset_scene_id=5},
urldate={2025-09-15},
keywords={organic fertilizer, soil identification, agricultural dataset, target detection, environmental monitoring},
version={1.0}
}Using this in research? Please cite us.
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