Mobiusi

Fruit Tree Growth Stage Classification Dataset

#classification #recognition #detection #agricultural monitoring #crop management #precision agriculture
  • 5000 records
  • 1.5G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-02-04

AI Analysis & Value Prop

The current agricultural industry faces the challenge of accurately monitoring the growth stages of fruit trees. Traditional methods of manual observation are inefficient and prone to errors. Existing solutions often lack specificity and fail to provide real-time feedback on the growth of fruit trees. This dataset aims to use image classification technology to address the technical challenges of identifying fruit tree growth stages, assisting farmers and agricultural managers in optimizing management decisions. The dataset is constructed mainly through a combination of drone photography and ground collection methods, ensuring coverage of various growth environments. For quality control, multiple rounds of annotation and expert review are used to ensure data accuracy and consistency. The data is stored in JPEG format and organized by image ID for easy retrieval and use.

Dataset Insights

Sample Examples

c47eb26e**.jpg|6960*4640|9.92 MB

4ea4cfd6**.jpg|6960*4640|9.52 MB

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
fruit_tree_speciesstringIndicates the species of the fruit tree in the image.
growth_stagestringDescribes the growth stage of the fruit tree depicted in the image, such as budding, flowering, or fruiting.
leaf_colorstringRecords the color of the leaves in the fruit tree image to assess health status.
fruit_presencebooleanThis field indicates whether fruits are present in the image.
canopy_densitystringMeasures the density of the fruit tree canopy, categorized as sparse, medium, or dense.
disease_signsstringDetects and records any signs of disease in the fruit tree image, such as leaf spots or wilting.

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

In which fields can the Fruit Tree Growth Stage Classification Dataset be applied?
The Fruit Tree Growth Stage Classification Dataset is primarily applied in the agriculture sector, particularly in precision agriculture management. It helps farmers optimize planting and harvesting strategies by analyzing the growth stages of fruit trees.
What are the main features of the Fruit Tree Growth Stage Classification Dataset?
This dataset offers image classifications of different growth stages of fruit trees, which can be used to train models to identify and classify images of fruit trees at various growth stages, thus enhancing the efficiency of agricultural production management.
How can the Fruit Tree Growth Stage Classification Dataset be utilized to promote precision agriculture?
By using this dataset to train machine learning models, it is possible to accurately identify the growth stages of fruit trees, providing data support to improve agricultural management practices such as watering, fertilization, and pest control.
What impact does the Fruit Tree Growth Stage Classification Dataset have on agricultural research?
This dataset supports agricultural researchers by providing extensive imagery data on growth stages, enabling them to develop new algorithms and models for better understanding the growth process of fruit trees, which in turn can enhance agricultural productivity and resource use efficiency.

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Cite this Work

@dataset{Mobiusi2025,
  title={Fruit Tree Growth Stage Classification Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/7be76a39b88439544e3b56a9ab840508?dataset_scene_id=5},
  urldate={2025-09-15},
  keywords={fruit tree growth stage, agricultural dataset, image classification, precision agriculture},
  version={1.0}
}

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