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    文浩雨, 张杰, 李慧玉, 高彩球, 王超, 张庆祝, 姜静, 刘桂丰. 基于BLUP-GGE双标图的白桦子代多地点速生性及稳定性分析[J]. 北京林业大学学报. DOI: 10.12171/j.1000-1522.20240010
    引用本文: 文浩雨, 张杰, 李慧玉, 高彩球, 王超, 张庆祝, 姜静, 刘桂丰. 基于BLUP-GGE双标图的白桦子代多地点速生性及稳定性分析[J]. 北京林业大学学报. DOI: 10.12171/j.1000-1522.20240010
    Wen Haoyu, Zhang Jie, Li Huiyu, Gao Caiqiu, Wang Chao, Zhang Qingzhu, Jiang Jing, Liu Guifeng. Analysis of fast-growing and stability characteristics of Betula platyphylla progeny at multiple locations based on BLUP-GGE biplot[J]. Journal of Beijing Forestry University. DOI: 10.12171/j.1000-1522.20240010
    Citation: Wen Haoyu, Zhang Jie, Li Huiyu, Gao Caiqiu, Wang Chao, Zhang Qingzhu, Jiang Jing, Liu Guifeng. Analysis of fast-growing and stability characteristics of Betula platyphylla progeny at multiple locations based on BLUP-GGE biplot[J]. Journal of Beijing Forestry University. DOI: 10.12171/j.1000-1522.20240010

    基于BLUP-GGE双标图的白桦子代多地点速生性及稳定性分析

    Analysis of fast-growing and stability characteristics of Betula platyphylla progeny at multiple locations based on BLUP-GGE biplot

    • 摘要:
      目的 通过白桦子代多地点试验,分析其速生性和稳定性,筛选出优良家系,为种子园的改建和重建提供科学依据。
      方法 以3个试验点的8年生白桦半同胞家系子代试验林为研究对象,调查其树高、胸径、材积、通直度、保存率性状,采用R语言中的ASReml-R4.0软件包,拟合具有异质方差的混合线性模型,通过最佳线性无偏预测法(BLUP)获得不同试验点各家系的综合育种值,并结合GGE双标图对各参试点和家系进行综合评价及选择。
      结果 (1)以地点为固定效应的混合线性模型分析中,白桦半同胞家系子代的5个性状在地点间、家系间、以及地点 × 家系的互作间的差异均达到显著水平(P < 0.05,Z ratio > 1.5)。(2)基于各家系综合育种值的GGE双标图显示,尚志试验点的区分度和代表性均最优,庆安和尚志试验点的相关性最强,永吉与尚志试验点几乎不相关、与庆安试验点负相关。(3)16号和15号白桦家系的速生性最优,4号和32号白桦家系的稳定性最强。基于各家系速生性和稳定性的综合性状排序,按20%的入选率共选出16号、40号、15号和38号4个优良家系。
      结论 白桦半同胞家系在不同试验地点的生长表现存在显著差异,同一试验地点内不同家系之间的生长表现也存在差异。基因型(家系)与环境(地点)的交互作用对白桦的生长有显著影响。依据各家系速生性及稳定性综合性状,选出16号、40号、15号和38号为白桦半同胞优良家系。

       

      Abstract:
      Objective  Through multi-location trials of birch progeny, this paper analyzes their fast-growth and stability, selects excellent genotypes, and provides a scientific basis for the renovation and reconstruction of seed orchard.
      Method The study focused on the progeny test forest of 8-year-old half-sibling families of birch at three experimental sites. Traits such as tree height, diameter at breast height, wood volume, straightness, and survival rate were investigated. The ASReml-R4.0 software package in the R language was employed to fit a mixed linear model with heterogeneous variance. Breeding values for each family at different trial locations were obtained through best linear unbiased prediction (BLUP). Additionally, a comprehensive evaluation and selection of trial sites and families were conducted using the GGE biplot method.
      Result (1) In the mixed linear model analysis with location as a fixed effect, differences in the offspring of half-sib family lines of birch reached significant levels (P < 0.05, Z ratio > 1.5) for all five traits among locations, among family lines, and among location × family line interactions. (2) Based on BLUP values of each trait, the GGE biplot revealed that Shangzhi trial site had the optimal discrimination and representativeness. Qing’an and Shangzhi trial sites showed the strongest correlation, while Yongji was almost uncorrelated with Shangzhi and negatively correlated with Qing’an. (3) Progeny from birch family 16 and 15 exhibited the best fast-growth characteristics, and families 4 and 32 demonstrated the highest stability. Considering a comprehensive ranking based on stability and fast-growth characteristics of each family, four excellent families, including family 16, 40, 15, and 38, were selected with a 20% inclusion rate.
      Conclusion There are significant differences in the growth performance of birch half-sibling families at different trial locations, and growth performance also varies among different families within the same trial location. The interaction between genotype (family) and environment (site) significantly influences the growth of birch. Based on the comprehensive traits of stability and fast-growth for each family, families 16, 40, 15, and 38 have been selected as excellent half-sibling families of birch.

       

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