Strawberry Harvest Traceability Dataset
#Target Detection #Image Classification #Intelligent Traceability #Supply Chain Management #Agricultural Monitoring
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
AI Analysis & Value Prop
In modern agriculture, the strawberry harvesting process faces issues with inaccurate traceability and low efficiency. Existing traceability systems often rely on manual input, resulting in data inconsistencies and frequent errors. This dataset aims to provide accurate images and tracking labels to support intelligent traceability systems, enhancing supply chain transparency and traceability capabilities. The dataset contains a large number of images from the strawberry harvest process, captured with high-resolution cameras under natural light conditions to ensure image quality. During the data collection process, multiple rounds of annotation and consistency checks are implemented to ensure data accuracy and completeness. All data is stored in JPG format, accompanied by labels in JSON files, facilitating subsequent data processing and analysis.
Dataset Insights
Sample Examples
1b6a1aca**.jpg|4032*3024|2.82 MB
44e8e04c**.jpg|3456*4608|3.24 MB
edf87b8f**.jpg|4032*3024|757.52 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| ripeness_level | string | The ripeness level of the strawberries in the image, such as: unripe, semi-ripe, ripe. |
| defect_presence | boolean | Whether there are visible defects on strawberries in the image. |
| defect_type | string | The type of defects on strawberries in the image, such as: pest damage, rot, bruising. |
| leaf_inclusion | boolean | Whether the image includes strawberry leaves. |
| plant_part_covered | string | Information on the plant parts covered in the image, such as fruit, leaves, stem, etc. |
| weather_condition | string | The weather condition when the image was taken, such as: sunny, cloudy, rainy. |
| lighting_condition | string | The lighting condition when the image was taken, such as: daylight, artificial light, shadow. |
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 Strawberry Harvest Traceability Dataset?
- The Strawberry Harvest Traceability Dataset is an image dataset designed to support intelligent traceability in agriculture, primarily applied in object detection.
- What data types are included in the Strawberry Harvest Traceability Dataset?
- The dataset primarily includes image data, which is used for object detection applications.
- How does the Strawberry Harvest Traceability Dataset support applications in agriculture?
- The dataset aids in intelligent traceability and better production management in agriculture by providing visual information about strawberry harvesting.
- What are the benefits of using the Strawberry Harvest Traceability Dataset?
- Using this dataset can enhance efficiency and accuracy in agricultural production processes, particularly in strawberry picking and traceability.
- What is the role of object detection in the Strawberry Harvest Traceability Dataset?
- Object detection technology is used in this dataset to identify and track the position and status of strawberries during the harvest process.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Strawberry Harvest Traceability Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/d98da34efd23cf740cff555af46756bc?dataset_scene_id=5},
urldate={2025-09-15},
keywords={Strawberry Harvest Dataset, Agricultural Traceability, Target Detection Dataset, Intelligent Agriculture},
version={1.0}
}Using this in research? Please cite us.
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