| 引用本文: | 王 勇, 杜晓军, 招礼军, 焦志华, 安明态.五种火棘属植物的叶面积回归分析[J].广西植物,2013,(6):756-762.[点击复制] |
| WANG Yong, DU Xiao-Jun, ZHAO Li-Jun,
JIAO Zhi-Hua, AN Ming-Tai.Leaf area regression analysis of five Pyracantha species[J].Guihaia,2013,(6):756-762.[点击复制] |
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| 五种火棘属植物的叶面积回归分析 |
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王 勇1,2, 杜晓军1*, 招礼军2, 焦志华3, 安明态4
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1. 中国科学院植物研究所 植被与环境变化国家重点实验室, 北京 100093;2. 广西大学 林学院, 南宁 530004;3. 中国矿业大学 化学与环境工程学院, 北京 100083;4. 贵州大学 林学院, 贵阳 550025
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| 摘要: |
| 以采集于贵州、云南、广西、湖南等地的火棘、密花火棘、全缘火棘、细圆齿火棘和窄叶火棘共5种火棘属植物26 401个成熟叶样为材料,利用WinFOLIA软件测量叶的多项形态指标并与叶面积进行11种模拟方程回归分析。结果表明:五种火棘属植物的叶面积(LA)与叶长×叶宽(LW)相关性最高,幂函数方程、三次方程、二次方程和线性方程能较好拟合其关系,且均以幂函数方程的解释程度最高(R2均大于0.970),5个物种的幂函数方程分别为LA=0.743(LW)0.936、LA=0.748(LW)0.936、LA=0.742(LW)0.955、LA=0.732(LW)0.952、LA=0.766(LW)0.954。这说明基于叶长×叶宽的叶面积幂函数方程能很好地来模拟五种火棘属植物的叶面积。 |
| 关键词: 火棘属 叶面积 叶形 回归分析 幂函数方程 |
| DOI：10.3969/j.issn.1000-3142.2013.06.007 |
| 分类号:Q948.1 |
| 基金项目: |
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| Leaf area regression analysis of five Pyracantha species |
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WANG Yong1,2, DU Xiao-Jun1*, ZHAO Li-Jun2,
JIAO Zhi-Hua3, AN Ming-Tai4
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1. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences,
Beijing 100093, China;2. College of Forestry, Guangxi University, Nanning 530004, China;3. School of
Chemical and Environmental Engineering, China University of Mining and Technology-Beijing,
Beijing 100083, China;4. Forestry College of Guizhou University, Guiyang 550025, China
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| Abstract: |
| Leaf is an important plant organ for transpiration and photosynthesis. Accurate and non-destructive methods for estimating leaf area are critical to many related studies. In order to get the accurate regression functions to estimate leaf area of Pyracantha species,26401 mature leaf samples,from five species(Pyracantha fortuneana,P. densiflora,P. atalantioides,P. crenulata,P. angustifolia)in Guizhou,Yunnan,Guangxi,Hunan provinces in China,were collected in 2010 and 2011. Leaf analysis software of WinFOLIA was used to measure leaf indices such as leaf area(LA),leaf blade length(L),leaf horizontal width(W),leaf perimeter(LP),leaf vertical length(VL); then LW,L/W,LL and WW were also obtained. Regression analyses between LA and these leaf shape indices of these five species were carried out by using 11 models including power,cubic,quadratic,linear,logarithmic,inverse,compound,S,growth,exponential,logistic model. The results were as follows: leaf area can be modeled better with LW than other indices; leaf area can be modeled better with LW by power,cubic,quadratic and linear models,and power function is the fittest model(R2>0.970); Power models for five Pyracantha species were LA=0.743(LW)0.936,LA=0.748(LW)0.936,LA=0.742(LW)0.955,LA=0.732(LW)0.952 and LA=0.766(LW)0.954 respectively. This study highlight that power model of leaf area based on L×W can be better used to non-destructively estimate leaf area of five Pyracantha species. |
| Key words: Pyracantha leaf area leaf shape regression analysis power function |
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