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格木人工林节子的分布特征及预测模型(PDF/HTML)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2017年03期
Page:
100-104
Column:
研究论文
publishdate:
2017-05-31

Article Info:/Info

Title:
Distribution and statistical analysis of knots in Erythrophleum fordii plantations
Article ID:
1000-2006(2017)03-0100-05
Author(s):
HAO Jian12MENG Mingjun1HUANG Dewei1WEI Juling1LI Zhongguo1TANG Jixin1 XU Daping2*
1. Experimental Center of Tropical Forestry, Chinese Academy of Forestry, Pingxiang 532600, China;
2. Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou 510520, China
Keywords:
Erythrophleum fordii knot distribution characteristics predicting model
Classification number :
S796
DOI:
10.3969/j.issn.1000-2006.201603057
Document Code:
-
Abstract:
【Objective】 In order to investigate the formation and distribution characteristics of knots during the process of Erythrophleum fordii growth, and screen out the key factors to establish a multiple regression model to predict the effects on branch wood after forming knot by step wise regression analysis. 【Methods】 Thirty years old E. fordii plantation was researched by using a stem analysis method. 【Results】The results indicated that compared with geographical location, slope direction was the important factor influencing the distribution of E. fordii branches. Most knots were distributed on the highest utilization region of E. fordii trunks(2.0-8.0 m), which seriously reduced the wood utilization value. When branch angle was less than 60°, the knot diameter was greater than 2.5 cm. As the branch diameter increased, the length between dead knots and the span of knots in xylem was larger. Peak forming on branches occurred at 1-15 years. Branch wound healing was concentrated at 16-25 years, and most dead knots formed at 11-20 years, which was the critical period for the control of dead knot formation. Diameter of the branch(BD), insertion angle of the branch(IA), and year of birth of the branch(YB)were selected as key factors to establish a multiple regression model by step wise regression analysis, yRT = 1.634 4xBD + 0.067 8xIA + 0.164 8 xYB-1.611 4(F = 106.869 7, P = 0.000 1). 【Conclusions】The model was suitable to predict the effects on branch wood caused by knot formation.

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Last Update: 2017-05-20