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    Guo Qi, Sun Yuhan, Zhang Yuanshuai, Chen Xiaoyang, Li Yun. Phenotypic variation analysis on leaf traits and selection of optimal forage clones of Robinia pseudoacacia clones in Shandong Province of eastern China[J]. Journal of Beijing Forestry University, 2021, 43(11): 62-70. DOI: 10.12171/j.1000-1522.20200305
    Citation: Guo Qi, Sun Yuhan, Zhang Yuanshuai, Chen Xiaoyang, Li Yun. Phenotypic variation analysis on leaf traits and selection of optimal forage clones of Robinia pseudoacacia clones in Shandong Province of eastern China[J]. Journal of Beijing Forestry University, 2021, 43(11): 62-70. DOI: 10.12171/j.1000-1522.20200305

    Phenotypic variation analysis on leaf traits and selection of optimal forage clones of Robinia pseudoacacia clones in Shandong Province of eastern China

    •   Objective  The objective of this experiment was to systematically understand the phenotypic variation rule of Robinia pseudoacacia clones in Feixian County State Owned Daqingshan Forest Farm of Shandong Province, eastern China and selection of optimal forage varieties.
        Method  Diversity, subordinate function, correlation and cluster analysis were performed on 13 leaf phenotypic traits of 332 R. pseudoacacia clones, and on the basis of cluster analysis, the differences among groups were analyzed for different traits.
        Result  The total coefficient of variation of the 13 traits was 14.883%, of which the coefficients of variation of the 4 compound leaves and 9 leaflets were 16.062% and 14.360%, respectively. The subordinate function value of this R. pseudoacacia was between 0.196 and 0.717, in which SD328 clone had the maximum value (0.717) and obvious advantages in the three characteristics of compound leaf width, leaflet area and petiole angle. The phenotype and genetic correlation showed that the leaflet pairs had the largest positive correlation coefficient with the leaflet numbers, and the leaflet length/width had the largest negative correlation coefficient with the leaflet circularity. Principal component analysis showed that the four principal component factors could represent 86.447% of the original data information of R. pseudoacacia clones. When the squared euclidean distance was 8, cluster analysis was performed, and 332 clones of R. pseudoacacia were divided into 5 categories.
        Conclusion  The phenotypic diversity of the R. pseudoacacia germplasm resources was systematically analyzed, seventy-two accessions were selected based on the breeding of ornamental and forage tree species, in order to lay the foundation for the research of breeding and germplasm preservation of R. pseudoacacia.
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