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Multivariate analysis of Quercus castaneifolia C.A. Mey based on morphological characterizations
Mehdi Rezaei1, Mohammad Sahebi2, Ali Khadivi3
1Department of Horticultural Sciences, Faculty of Agriculture, Shahrood University of Technology, Shahrood, Iran.
Scientific Reports
|July 21, 2026
Summary
This study reveals significant phenotypic diversity in Iranian Quercus castaneifolia oak populations. Fruit and kernel traits are most valuable for characterizing and selecting superior Q. castaneifolia germplasm for breeding programs.
Area of Science:
- Botany
- Ecology
- Genetics
Background:
- Quercus castaneifolia (Iranian oak) is ecologically vital in Hyrcanian forests.
- Limited large-scale morphological studies exist for this species.
- Understanding phenotypic diversity is crucial for conservation and breeding.
Purpose of the Study:
- Evaluate phenotypic diversity in 51 Q. castaneifolia accessions.
- Identify informative traits for characterization and selection.
- Assess trait variability and interrelationships using multivariate analyses.
Main Methods:
- Collected 51 Q. castaneifolia accessions from three natural populations.
- Assessed 52 morphological and pomological traits (tree, leaf, nut, cupule, kernel).
- Applied ANOVA, Pearson correlation, Hierarchical Cluster Analysis (HCA), and Multiple Regression Analysis (MRA).
Main Results:
- Substantial phenotypic diversity observed; 75% of traits had >20% coefficient of variation.
- Reproductive traits (nut/kernel dimensions, weights) were most informative.
- Strong positive correlations among nut/kernel size and weight; negative correlation with nut cover/kernel ratio.
Conclusions:
- Multivariate analyses revealed structured phenotypic differentiation among accessions.
- Fruit and kernel traits are key for germplasm characterization and selection in Q. castaneifolia.
- 'Olang-5', 'Olang-11', 'Tooskestan-1', 'Tooskestan-15', and 'Tooskestan-10' identified as promising accessions.
