Multi-Crop Field Crop Recognition Dataset
#object detection #image classification #crop monitoring #agricultural automation #precision agriculture
- 20000 records
- 3.5G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-10
AI Analysis & Value Prop
The current agricultural industry faces challenges such as inaccurate crop recognition, low monitoring efficiency, and high labor costs. Existing crop recognition solutions perform poorly in multi-crop environments, making it difficult for farmers to obtain accurate information in crop management decisions. This dataset aims to help agricultural technology companies and research institutions by providing high-quality field crop recognition data to enhance the accuracy and efficiency of crop monitoring. The dataset includes 20,000 images covering different growth stages of crops and supports object detection tasks. Data collection uses high-resolution cameras under various lighting and climate conditions to ensure diversity and representativeness of samples. Quality control measures include multiple rounds of annotation and expert review to ensure the accuracy and consistency of data annotations. The data is stored in JPG format, with metadata records corresponding to each image.
Dataset Insights
Sample Examples
f43b0de2**.jpg|3840*2560|2.32 MB
c2d3d8e1**.jpg|7728*5152|13.73 MB
28094b8c**.jpg|5526*3110|3.67 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| crop_type | string | The identified crop category name, such as wheat, corn, etc. |
| growth_stage | string | The growth stage of the crop, such as seeding, seedling, mature. |
| health_status | string | The health condition of the crop, such as healthy, diseased, or water-deprived. |
| weed_presence | boolean | Whether weeds can be observed in the image. |
| soil_condition | string | The surface condition of the soil, such as moist, dry, barren. |
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 purpose of the multi-crop field crop recognition dataset?
- This dataset is used in the agricultural field for crop monitoring, helping farmers better manage crops by increasing recognition accuracy and efficiency.
- What type of data does this dataset include?
- This dataset includes image data, focusing on object detection in agricultural scenarios.
- How can this dataset be used to improve agricultural production efficiency?
- By applying machine learning algorithms, automated crop recognition and monitoring can be achieved, reducing manual intervention and thus enhancing agricultural production efficiency.
- What machine learning tasks is the multi-crop field crop recognition dataset suitable for?
- This dataset is suitable for object detection related machine learning tasks, especially in agricultural applications.
- Which industry can benefit the most from this dataset?
- The agricultural industry can benefit the most from this dataset as it improves accuracy and efficiency in crop monitoring.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Multi-Crop Field Crop Recognition Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/f93343e8d0df3f4b0e92ca79999005ed},
urldate={2025-10-23},
keywords={crop recognition dataset, multi-crop detection, agricultural dataset, object detection data, precision agriculture},
version={1.0}
}Using this in research? Please cite us.
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