Grape Growth Monitoring Dataset
#Target Detection #Image Recognition #Precision Agriculture #Crop Monitoring #Agricultural Management
- 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 sector faces the challenge of effectively monitoring crop growth conditions. Traditional monitoring methods often rely on manpower, resulting in inefficiency and errors. Existing solutions lack real-time data acquisition and accuracy, failing to meet the needs of precise agricultural management. This dataset aims to record the state of grapevines at different growth stages through high-quality field images, addressing the issue of precise growth identification. Data collection is conducted using high-resolution cameras in natural environments, ensuring the authenticity and diversity of the images. Multiple rounds of annotation and expert-reviewed quality control measures ensure data accuracy and consistency. The data is stored in JPEG format, organized structurally for easy subsequent processing and analysis.
Dataset Insights
Sample Examples
a8ba9352**.jpg|5616*3744|4.08 MB
7f062b09**.jpg|4000*6000|2.99 MB
c8e8afbd**.jpg|5616*3744|3.77 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| growth_stage | string | The growth stage of the grapevine at the time the image was taken, such as bud stage, flowering stage, or fruit setting stage. |
| grape_variety | string | The variety of the grapevine shown in the image, such as Cabernet Sauvignon or Pinot Noir. |
| disease_presence | boolean | Indicates whether there are any visible signs of grapevine diseases in the image. |
| leaf_color | string | Describes the color of the grape leaves in the image, such as green, yellow, or brown, which may indicate health status. |
| fruit_load | string | Indicates the level of grape fruit load visible in the image, such as low, medium, or high. |
| canopy_density | string | The density level of the grapevine canopy, such as sparse, medium, or dense. |
| soil_condition | string | Describes the soil condition visible in the image, such as dry, moist, or covered. |
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
- How does this dataset help improve grape yield?
- By recording the state of grapevines at different growth stages, farmers can more accurately adjust their planting strategies and management measures to improve grape yield.
- How does the object detection work in the grape growth monitoring dataset?
- Object detection algorithms identify and label grapevines and grapes in images, providing information that helps monitor growth conditions.
- What precision agriculture applications can this dataset be used for?
- This dataset can be used for precision agriculture applications such as pest detection, yield prediction, and precision irrigation.
- What are the potential challenges of using this dataset for research?
- Potential challenges may include handling the volume of data, image quality under different lighting conditions, and the accuracy of algorithms.
- How can this dataset be used to improve crop health management?
- By analyzing grape growth data at different stages, farmers and researchers can develop more effective health management plans, identifying and addressing issues proactively.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Grape Growth Monitoring Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/a88ae47cedf93cec5bef85987c0c3ec5},
urldate={2025-09-15},
keywords={Grape Growth Monitoring, Agricultural Dataset, Target Detection Dataset, Precision Agriculture},
version={1.0}
}Using this in research? Please cite us.
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