The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2025.0160616
PDF

Method for Tea Leaf Plucking Timing Prediction with High Resolution of Images Based on YOLO11

Author 1: Kohei Arai
Author 2: Yoho Kawaguchi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 6, 2025.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: As a method for estimating the time when tea leaves reach their peak quality (amino acid content) (optimum picking time), our previous study revealed that the optimum picking time is when the accumulated temperature from the detection of germination of new buds reaches 600°C. However, the accuracy of this germination detection was insufficient, so the estimation accuracy of the optimum picking time was also insufficient. Since annotation accuracy is extremely important for germination detection by YOLO11, strict attention is paid to annotation by hand and by increasing the number of training datasets. The detection accuracy has been improved compared to the germination detection by YOLOv8, which was previously proposed and used relatively low-resolution images. The conclusion of this study is that the estimation method of the optimum picking time based on the criterion that the optimum picking time (amino acid content reaches its peak) is effective when the accumulated temperature from germination detection meets the condition of 600°C. The effectiveness of this method has been confirmed by comparison with germination detection by experts. For tea farmers, being able to predict the optimum picking time, when the amino acid content in the new buds is at its peak, is important, and we are sure it will have a positive impact on agricultural researchers studying this subject.

Keywords: Tealeaf plucking; YOLO; budding detection; spatial resolution; optical image; annotation; germination rate

Kohei Arai and Yoho Kawaguchi, “Method for Tea Leaf Plucking Timing Prediction with High Resolution of Images Based on YOLO11” International Journal of Advanced Computer Science and Applications(IJACSA), 16(6), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160616

@article{Arai2025,
title = {Method for Tea Leaf Plucking Timing Prediction with High Resolution of Images Based on YOLO11},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160616},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160616},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {6},
author = {Kohei Arai and Yoho Kawaguchi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org