Content area

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.

Details

1009240
Business indexing term
Location
Title
Method for Tea Leaf Plucking Timing Prediction with High Resolution of Images Based on YOLO11
Author
Volume
16
Issue
6
Number of pages
11
Publication year
2025
Publication date
2025
Publisher
Science and Information (SAI) Organization Limited
Place of publication
West Yorkshire
Country of publication
United Kingdom
ISSN
2158107X
e-ISSN
21565570
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
ProQuest document ID
3231644716
Document URL
https://www.proquest.com/scholarly-journals/method-tea-leaf-plucking-timing-prediction-with/docview/3231644716/se-2?accountid=208611
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-07-28
Database
ProQuest One Academic