湿地松产脂量与生长及树冠性状多点遗传相关及通径分析

为研究湿地松生长及树冠性状与产脂量之间的遗传相关关系及其对产脂量的控制途径,以赣北、赣中和赣南等多种典型立地条件下的28年生湿地松家系试验林为研究对象,对112个湿地松家系进行产脂量、生长及树冠性状全林调查,并对测定数据进行分析。结果表明,除枝下高外,产脂量与生长及树冠性状均呈显著或极显著遗传正相关关系,遗传相关系数排名前四的性状分别为胸径(R=0.93)、树冠表面积(R=0.83)、冠长(R=0.78)和冠幅(R=0.73);通径分析中,胸径、树高、树冠表面积和冠幅通过直接和间接作用成为影响产脂量的主导因素,其决定系数贡献率分别为0.557、0.507、0.424和0.240;产脂量与生长、树冠性状的线性回归方程为:y=-0.255+0.040x_(DBH)+0.004x_(HGT)+0.006x_(CSA)+0.036x_(CW)(F=955.907^**, R²=0.559),模型的预估精度为99.64%。本试验结果明确了湿地松生长及树冠性状与产脂量之间的关系,其中,树高、胸径、冠幅和树冠表面积对产脂量影响较大;建立的产脂量多元回归模型具有一定的现实意义,实现了对树高、胸径和树冠表面积等性状的快速测定预估产脂量,为湿地松产脂量的科学、准确与高效预测提供了依据。

Multipoint Genetic Correlation and Path Analysis of Resin Yield and Growth Traits and Crown Traits in Slash pine

In order to provide indirect evaluation factors for high-yielding slash pine (Pinus elliottii) breeding, genetic correlations among growth traits, crown traits and resin yield (RY), and the control the RY, growth traits and crown traits were investigated in 112 families of slash pine (28 years old) experimental forests located in northern, southern and middle parts of Jiangxi province, China. The results showed that the RY positively correlated with the growth and crown traits (excluded HLC). The top four genetic correlation coefficients were DBH (0.93), CSA (0.83), CL (0.78) and CW (0.73). In the genetic path analysis, the direct and indirect effects of each trait on RY were different. The main factors influencing RY were DBH, HGT, CSA and CW, of which of R-square were 0.557, 0.507, 0.424 and 0.240, respectively. The linear regression equation between RY and growth and crown traits was y=-0.255+0.040 x_(DBH)+0.004 x_(HGT)+0.006 x_(CSA)+0.036 x_(CW)(F=955.907^**, R²=0.559), and the estimated accuracy of the model is 99.64%. The results of this experiment clarified the relationship between the growth traits, crown traits and RY of slash pine, among which, the HGT, DBH, CW and CSA had a great influence on RY. The established multiple regression model of RY had a certain practical significance, and it could achieve the purpose of estimating the RY through the rapid determination of HGT, DBH, CW and CSA. Therefore, it provided a basis for scientific, accurate and efficient prediction of the RY of slash pine.