Fennel Crop Growth Monitoring Dataset

#Object Detection #Image Recognition #Crop Monitoring #Agricultural Research #Precision Agriculture
  • 5000 records
  • 1.2G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-14

AI Analysis & Value Prop

Currently, the agricultural sector faces challenges such as the lack of high-precision data and real-time monitoring in crop growth monitoring. Traditional monitoring methods often rely on manual observation, which is inefficient and prone to errors. Existing solutions are limited in terms of data update speed and accuracy, failing to meet the precision and timeliness demands of modern agriculture. The construction of this dataset aims to solve the problems of image recognition and classification in object detection by providing high-quality fennel crop growth monitoring data, meeting the data needs in agricultural production. Data collection uses drone aerial photography techniques with high-resolution cameras, capturing images at different growth stages and under different environmental conditions. To ensure data quality, multiple rounds of annotation and consistency checks were implemented, and the data was reviewed by agricultural experts. The data is stored in JPG format, organized by time and growth stage, to facilitate subsequent analysis and model training.

Dataset Insights

Sample Examples

9e047de9**.jpg|6960*4640|9.80 MB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
fenugreek_plant_stagestringIndicates the growth stage of the fenugreek plant, such as seedling stage, flowering stage, etc.
leaf_health_statusstringDescribes the health condition of the leaf, such as healthy, diseased, pest damage, etc.
plant_heightfloatMeasures the vertical height of the plant from the base to the top (in centimeters).
plant_densityintegerThe number of plants per unit area visible in the image.
flower_countintegerThe total number of flowers visible in the image.
soil_conditionstringDescribes the condition of the soil surface, such as dry, moist, muddy, etc.
weather_conditionsstringThe weather conditions at the time of image capture, such as sunny, overcast, rainy, etc.
light_intensityfloatThe light intensity at the time of capturing, usually measured in lumens (lux).

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What is the Fennel Crop Growth Monitoring Dataset?
The Fennel Crop Growth Monitoring Dataset is a high-quality image dataset specifically designed for monitoring the growth status of fennel crops, supporting object detection research in the agricultural field.
What research can the Fennel Crop Growth Monitoring Dataset be used for?
This dataset can be used for agricultural object detection research, such as monitoring the growth of fennel crops, identifying pests and diseases, and optimizing agricultural production management.
What data modalities are included in the Fennel Crop Growth Monitoring Dataset?
The Fennel Crop Growth Monitoring Dataset mainly includes image data modality.
Why choose the Fennel Crop Growth Monitoring Dataset for agricultural research?
Choosing the Fennel Crop Growth Monitoring Dataset for agricultural research can leverage its high-quality image data to improve the accuracy and efficiency of crop detection, providing reliable data support for agricultural research and management.
Is the Fennel Crop Growth Monitoring Dataset suitable for machine learning research?
Yes, the Fennel Crop Growth Monitoring Dataset is very suitable for research in the field of machine learning, especially in image recognition and object detection.

Can't find the data you need?

Post a request and let data providers reach out to you.

Get this Dataset

Verified for Enterprise Use

Cite this Work

@dataset{Mobiusi2025,
  title={Fennel Crop Growth Monitoring Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/95394537065b082a7c02306c5da2a294},
  urldate={2025-09-15},
  keywords={Fennel Monitoring Dataset, Agricultural Object Detection, Crop Growth Monitoring, Image Dataset},
  version={1.0}
}

Using this in research? Please cite us.

placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder

Popular Dataset Searches