Seedling Recognition Dataset
#object detection #object recognition #crop monitoring #plant growth analysis #agricultural automation
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The current agricultural industry faces challenges such as inefficient crop management and insufficient monitoring of pests and diseases. Traditional manual monitoring methods are not only time-consuming and labor-intensive, but also prone to errors. Existing solutions often rely on simple image recognition technology, which fails to meet the high-precision demands of real-world applications. This dataset aims to support more advanced object detection models by providing high-quality seedling images and their accurate annotations, thereby improving the automation of crop monitoring. The dataset is constructed using high-resolution cameras in a greenhouse environment to ensure image clarity and accuracy. We conducted multiple rounds of annotation and expert review to ensure the consistency and accuracy of data annotations. The data is stored in JPEG format with annotations organized in JSON format, facilitating processing and analysis.
Dataset Insights
Sample Examples
26751706**.jpg|3000*2000|1.43 MB
160f7cfe**.jpg|2000*3000|773.02 KB
d9721025**.jpg|2000*3000|936.45 KB
f69cab72**.jpg|5350*3567|3.21 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| species_label | string | The species label of the seedling. |
| health_status | string | The health status assessment of the seedling, such as healthy, diseased, or wilted. |
| growth_stage | string | The current growth stage of the seedling, such as the germination stage or seedling stage. |
| soil_condition | string | The soil condition where the seedling grows visible in the image, such as moist or dry. |
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 main purpose of the Seedling Recognition Dataset?
- The main purpose of the Seedling Recognition Dataset is to enhance the automation and accuracy of agricultural monitoring by assisting in the identification and differentiation of various types of seedlings.
- What agricultural applications is this dataset suitable for?
- The seedling recognition dataset is suitable for agricultural monitoring, vegetation classification, automated irrigation systems, and farmland health monitoring.
- What are the image size and format in the Seedling Recognition Dataset?
- The images in the dataset are typically high-resolution and in JPEG format to ensure accurate detail recognition.
- How is the accuracy and effectiveness of the Seedling Recognition Dataset evaluated?
- The accuracy and effectiveness of the dataset can be evaluated using metrics such as precision, recall, and F1 score on the seedling recognition task.
- What types of seedlings are included in the Seedling Recognition Dataset?
- The dataset includes various common crop seedlings such as corn, wheat, and rice.
- What advantages does the Seedling Recognition Dataset offer in agricultural automation?
- The dataset offers precise seedling image recognition, helping farmers manage crops more effectively, reducing errors, and increasing production efficiency.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Seedling Recognition Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/f7ea40f0aeea742c2227e8c2837751fd?dataset_scene_id=5},
urldate={2025-09-15},
keywords={seedling recognition, agricultural dataset, object detection, plant recognition, crop monitoring},
version={1.0}
}Using this in research? Please cite us.
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