Floral Health Status Monitoring Dataset

#Object Detection #Image Classification #Plant Health Monitoring #Agricultural Management #Intelligent Agriculture
  • 5000 records
  • 1.2G
  • JPG/PNG/JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-04-13

AI Analysis & Value Prop

In today's agricultural industry, as the area of flower cultivation expands, timely monitoring and evaluation of the floral health status becomes a challenge. Existing monitoring means primarily rely on manual observation, which is inefficient and prone to misjudgment. This dataset aims to provide an efficient and accurate solution for agricultural management by automatically identifying and evaluating floral health status through object detection technology. The dataset is collected using professional equipment under various environments and contains images of different types of flowers. We employ multi-round annotation and expert review quality control measures to ensure data accuracy and consistency. The data is stored in JPG format and organized by date and location, facilitating subsequent analysis and application.

Dataset Insights

Sample Examples

28a1e61b**.jpg|3024*4032|2.55 MB

3f845b9b**.jpg|4640*6960|4.89 MB

7ececc0c**.jpg|4184*6276|6.24 MB

0932f5d8**.jpg|3293*4939|2.99 MB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
flower_typestringIdentify the specific type of flower in the image.
disease_presencebooleanIndicates whether there are any signs of disease in the flower in the image.
disease_typestringIdentify the type of disease present in the flower, if any.
health_statusstringEvaluate the health status of the flower, such as healthy, infected, or wilting.
pest_presencebooleanIndicates whether the flower in the image is affected by pests.
pest_typestringIdentify the type of pest present in the flower, if any.
flower_colorstringIdentify the primary color of the flower in the image.
blossom_stagestringDescribe the blooming stage of the flower, such as bud, half-bloom, full-bloom, etc.
leaf_conditionstringAssess the condition of leaves associated with the flower.

Compliance Statement

Authorization TypeProprietary - Commercial AI Training License (No Redistribution)
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 agricultural intelligent projects can this dataset be used for?
The Flower Health Monitoring Dataset can be used for projects such as flower pest and disease detection, yield prediction, and smart greenhouse management.
What types of flowers' images are included in the dataset?
The dataset may contain images of various kinds and health statuses of flowers, such as roses, lilies, and tulips.
How to analyze this dataset using object detection algorithms?
You can train object detection models like Faster R-CNN or YOLO to recognize and analyze the health status of flowers.
Does this dataset help in increasing crop yield?
Yes, by accurately monitoring the health status of flowers, timely measures can be taken to increase overall crop yield and quality.
What is the significance of monitoring flower health status?
Monitoring flower health status helps in early detection of pests and diseases and optimizing nutrient supply, ensuring healthy growth and efficient management of flowers.

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Cite this Work

@dataset{Mobiusi2025,
  title={Floral Health Status Monitoring Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/e13742339f9f0e8c9f01e0cdc2bbbb62?dataset_scene_id=5},
  urldate={2025-09-15},
  keywords={Floral Health Monitoring, Object Detection Dataset, Agricultural Dataset},
  version={1.0}
}

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