Cabbage Yield Prediction Dataset
#Target Detection #Image Recognition #Crop Yield Prediction #Agricultural Intelligence #Precision Agriculture
- 15000 records
- 2.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-17
AI Analysis & Value Prop
Current agricultural production faces challenges such as inaccurate yield predictions and resource wastage, especially in crop growth monitoring. Most existing solutions rely on human experience and lack scientific quantitative data support, leading to decision errors. This dataset aims to solve the issue of cabbage yield prediction through high-quality images and precise annotations to meet the needs of smart agriculture. Data collection is conducted using high-resolution cameras in real farmland environments, covering different growth stages of cabbage. We have implemented multiple rounds of annotation and expert review as part of our quality control measures to ensure the accuracy and consistency of the data. Data storage is in JPG format, with each image corresponding to a metadata file, facilitating subsequent analysis and model training.
Dataset Insights
Sample Examples
e7586b1e**.jpg|8368*5584|6.83 MB
f1abb55b**.jpg|4196*5067|3.86 MB
5af57f8e**.jpg|3840*2560|1.89 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| cabbage_size | float | The average size of the cabbages in the image, measured in centimeters. |
| cabbage_maturity | string | The maturity level of the cabbages, such as 'unripe', 'ripe', etc. |
| leaf_color | string | The color of the cabbage leaves, such as 'green', 'yellow-green', etc. |
| damage_presence | boolean | Indicates whether there is any damage on the cabbages, such as pest infestation or mechanical damage. |
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 Cabbage Yield Prediction Dataset?
- The Cabbage Yield Prediction Dataset is used to develop accurate agricultural yield prediction models to enhance crop management and yield.
- What is the image format of the Cabbage Yield Prediction Dataset?
- The dataset images are usually provided in high-resolution formats to facilitate target detection model training.
- How can the Cabbage Yield Prediction Dataset be used for model training?
- By using the images from the dataset to train target detection models, it is possible to predict cabbage yield and thus optimize agricultural production.
- Who needs to use the Cabbage Yield Prediction Dataset?
- This dataset is suitable for researchers and engineers engaged in agricultural technology development, crop management, and agricultural production optimization research.
- What information does the Cabbage Yield Prediction Dataset contain?
- The dataset mainly includes images of cabbage, each possibly accompanied by label information for training target detection models.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Cabbage Yield Prediction Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/3528d2a2250f763617084ee30e28bd40},
urldate={2025-09-15},
keywords={Cabbage Yield Prediction, Agricultural Dataset, Target Detection Dataset, Precision Agriculture},
version={1.0}
}Using this in research? Please cite us.
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