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2025 Vol.43, Issue 6 Preview Page

Research Article

A Pruning Criterion for Dormant ‘Niitaka’ Pear Trees that Uses a Decision Tree Model Based on the Basal Diameter of Bearing Branches
Ju Eun Kim12
,
So-Yeon Park3
,
Ung Yang4
,
Seung Gon Wi5
,
Min Soo Kim6
,
Sun Woo Chung1
,
Sang-Hyun Lee125*
1Department of Horticulture, Chonnam National University, Gwangju 61186, Korea
2Interdisciplinary Program in IT-Bio Convergence System, Chonnam National University, Gwangju 61186, Korea
3Department of Mathematics and Statistics, Chonnam National University, Gwangju 61186, Korea
4Pear Research Center, National Institute of Horticultural & Herbal Science, Rural Development Administration, Naju 58216, Korea
5Digital Agriculture Research Institute for Horticultural Fruit, Chonnam National University, Gwangju 61186, Korea
6Department of Statistics, Chonnam National University, Gwangju 61186, Korea
*Corresponding Author
31 December 2025. pp. 673-684
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Abstract

Criteria for the selective pruning of pear trees are required at this time as the number of experienced pruning workers continues to decline. The present study aimed to analyze the occurrence of water sprouts and fruit yields according to bearing branch basal diameters and establish pruning criteria for pear trees. During a three-year dormancy period, the lengths and diameters of water sprouts and bearing branches on ‘Niitaka’ pear trees were measured, and the data were analyzed with Python and R. Bearing branch thickness and sprouting vigor increased with age. Fruit yield initially increased with the bearing branch basal diameter and remained constant thereafter. A correlation analysis of water sprout occurrences and variations in the bearing branch basal diameters identified the explanatory variables used to build a decision tree and establish pruning criteria. A feature importance analysis revealed that the bearing branch basal diameter had the greatest impact on the output of the decision tree. The latter recommended pruning when the bearing branch central and basal diameters exceeded 26.2 mm and 42.3 mm, respectively. We believe that the results of the present study provide guidelines for improving pruning accuracy and efficiency through model-based decision-making.

Keywords
fruit yield
regression
selective pruning
thickness
water sprout
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Information
  • Publisher :KOREAN SOCIETY FOR HORTICULTURAL SCIENCE
  • Publisher(Ko) :한국원예학회
  • Journal Title :Horticultural Science and Technology
  • Journal Title(Ko) :원예과학기술지
  • Volume : 43
  • No :6
  • Pages :673-684
  • Received Date : 2025-03-10
  • Revised Date : 2025-07-22
  • Accepted Date : 2025-07-24
  • DOI :https://doi.org/10.7235/HORT.20250059
Journal Informaiton Horticultural Science and Technology Horticultural Science and Technology
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