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Selection of Elite Tree of Evergreen Oaks and the Growth Characteristics of Selected IndividualsSelection of Elite Tree of Evergreen Oaks and the Growth Characteristics of Selected Individuals

Other Titles
Selection of Elite Tree of Evergreen Oaks and the Growth Characteristics of Selected Individuals
Authors
용성현김도현박관빈박동진송현진김학곤최명석
Issue Date
2022
Publisher
경상국립대학교 농업생명과학연구원
Keywords
Cluster analysis; Correlation analysis; Evergreen oaks; Principal component analysis; Selection factors
Citation
농업생명과학연구, v.56, no.2, pp.25 - 34
Indexed
KCI
Journal Title
농업생명과학연구
Volume
56
Number
2
Start Page
25
End Page
34
URI
https://scholarworks.bwise.kr/gnu/handle/sw.gnu/2378
ISSN
1598-5504
Abstract
Elite trees of evergreen oaks (Quercus glauca, Quercus acuta, Quercus salicina, and Quercus gilva) were selected from Jeju Island and Wando Island. Elite trees were carried out by modifying the tree selection criteria. Elite trees were selected by height, DBH, clear length, crown diameter, leaf length, and leaf depth. Regarding height, Q. acuta was the highest, and the other three tree species were similar. Clear length showed the same trend as height. In the case of Q. glauca, height showed a positive correlation with DBH, crown diameter and leaf depth. In the case of Q. acuta, positive correlations were shown with all characteristics of DBH, and correlation analysis between DBH and crown diameter, and leaf length and leaf depth also showed positive correlations. In the Pearson correlation coefficient of Q. salicina, height showed a positive correlation with DBH. In the case of Q. gilva, height showed a positive correlation with DBH (0.539). As a result of analyzing the principal components for each of the six growth characteristics, the four species were divided into two principal components with an eigenvalue of 1 or higher, and the cumulative explanatory power was 57% or more. Based on the principal component results, it was possible to confirm the relationship between growth and trait characteristics by species. Still, it was not easy to understand the relationship among each selection tree, so a cluster analysis was performed using the principal component score. Based on the distance levels 5.0 and 6.0 of the selection tree of each species, they were classified into 4-5 clusters. It is judged that the above results can be used as data for the selection of elite trees of evergreen oaks.
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Choi, Myung Suk
농업생명과학대학 (환경산림과학부)
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