文献类型：期刊文献

中文题名：毛竹材用林高产优化施肥与结构模型的建立

英文题名：The Optimal Models of High-Yields with Fertilization and the Structure of Moso Bamboo Stands for Culm-producing

作者：顾小平[1] 吴晓丽[1] 汪阳东[1]

第一作者：顾小平

机构：[1]中国林业科学研究院亚热带林业研究所

年份：2004

卷号：40

期号：3

起止页码：96-101

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;Scopus;北大核心:【北大核心2000】；CSCD:【CSCD2011_2012】；

基金："九五"国家科技攻关专题 ( 96-0 11-0 2 -0 7)项目研究内容之一

语种：中文

中文关键词：毛竹材用林;施肥;竹材产量;回归模型;经济效益;立竹密度

外文关键词：Moso bamboo stands, Fertilization, Density, Regression design, Model

分类号：S795.7

摘要：采用四因素二次回归最优设计建立氮、磷、钾施肥及留竹密度与毛竹林竹材产量间的回归模型 ,同时根据投入、产出价格建立施肥和留养立竹的经济效益方程。经F值检验 ,方程均拟合较好。进一步统计分析表明 :留养立竹密度和施用氮肥是影响竹林产量的主导因子 ,参试各因素对产量贡献率的排序为留竹密度 >氮肥 >钾肥 >磷肥。采用产量和效益两目标函数的双频分析 ,得到 95 %置信域的毛竹林优化施肥方案 :施尿素 4 88～ 6 0 7 6kg·hm- 2 ,平均 5 4 7 8kg·hm- 2 ;过磷酸钙 2 5 2 7～ 2 6 1 2kg·hm- 2 ,平均 2 5 7kg·hm- 2 ;氯化钾 4 3 3～ 12 3 2kg·hm- 2 ,平均83 3kg·hm- 2 ;对平均胸径 10cm左右的毛竹林 ,优化的立竹留养密度 2 36 3～ 2 5 82株·hm- 2 ,平均 2 4 72株·hm- 2 。
By the optimum design of quadratic regression for 4 factors, the regression model between fertilization, the living bamboo density and the bamboo timber output of moso bamboo stands, was established in this paper. Meanwhile, the economic benefit equations of the fertilization and the standing culm based on the prices of input and output, which were tested by %F%_value in goodness of fit. Further statistical analysis showed that the leading factors enfluencing bamboo timber output were the standing culm density and the application of introgen. The order of the contribution rate of the tested factors to yield of bamboo timber was the standing culm density>N fertilizer>K fertilizer>P fertilizer. By bi_frequency analysis of yield and the economic benefit, the optimal fertilization and culms density scheme were obtained within the confidence interval of 95% as follows:urea 488～607.6 kg·hm -2(average 547.8 kg·hm -2), superphosphate 252.7～261.2 kg·hm -2(average 257 kg·hm -2), potassium chloride 43.3～123.2 kg·hm -2(average 83.3 kg·hm -2), and culms density 2 363～2 582 culms·hm -2(average 2 472 culms ·hm -2).