| 9个阔叶树种叶绿素估测模型 |
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| 引用本文： | 朱旭珍,丁丽霞,李 梦,金雨菲,邹红玉,程 乾.9个阔叶树种叶绿素估测模型[J].浙江农林大学学报,2014,31(4):577-582. |
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| 作者姓名： | 朱旭珍 丁丽霞 李 梦 金雨菲 邹红玉 程 乾 |
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| 作者单位： | 1. 浙江农林大学 浙江省森林生态系统碳循环与固体减排重点实验室，浙江 临安 311300； 2. 浙江农林大学 天目学院，浙江 诸暨 311800；3. 浙江工商大学 区域生态环境与空间信息技术研究所, 浙江 杭州 310018 |
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| 基金项目： | 国家自然科学基金资助项目(4127417);浙江农林大学科研发展基金资助项目(2009FK30,2009FK69) |
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| 摘 要： | 为了方便快速准确地测量树木叶片的叶绿素质量分数,对9个阔叶树种的叶片采样,利用CCM-200测得的叶绿素指数(CCI值)和叶片厚度因子建立叶绿素的估算模型,将估算结果与萃取法测量叶绿素质量分数比较,分析发现:仅利用CCM-200测得的叶绿素指数估算叶绿素a,叶绿素b和总叶绿素质量分数的线性模型误差较大,叶绿素指数与叶绿素a,叶绿素b和总叶绿素质量分数的决定系数(R2)均在0.610左右,相关性不是很显著。当用比叶质量(SLW)来反映叶片厚度,与叶绿素指数一起作为自变量,分别建立估算叶绿素a,叶绿素b以及总叶绿素质量分数的线性回归方程,发现叶绿素指数及比叶质量与叶绿素a,叶绿素b和总叶绿素质量分数之间的决定系数(R2)分别为0.678,0.707和0.689,相关性得到较大提高。而如果采用比叶面积(SLA),即比叶质量的倒数来反映叶片厚度,与叶绿素指数一起作为自变量,分别建立估算叶绿素a,叶绿素b以及总叶绿素质量分数的线性回归方程,各决定系数分别为0.869,0.893和0.881,相关性得到显著提高。由此得到结论:利用叶绿素指数与比叶面积建立的叶绿素质量分数估算模型精度较高,且适用于多种不同树种叶绿素质量分数估算,具有普适性。
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| 关 键 词： | 植物生理学 叶绿素指数 回归分析 比叶质量 比叶面积 |
| 收稿时间： | 2013-09-27; |
Chlorophyll content modeling for nine species of broadleaf trees |
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| ZHU Xuzhen,DING Lixia,LI Meng,JIN Yufei,ZOU Hongyu,CHENG Qian.Chlorophyll content modeling for nine species of broadleaf trees[J].Journal of Zhejiang A&F University,2014,31(4):577-582. |
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| Authors: | ZHU Xuzhen DING Lixia LI Meng JIN Yufei ZOU Hongyu CHENG Qian |
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| Affiliation: | 1. Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration, Zhejiang A & F University, Lin’an 311300, Zhejiang, China; 2. School of Tianmu, Zhejiang A & F University, Zhuji 311800, Zhejiang, China; 3. Research on Regional Ecological Environment and Space Information, Zhejiang Gongshang University, Hangzhou 310018, Zhejiang, China |
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| Abstract: | Chlorophyll is the main pigment of plant photosynthesis, and chlorophyll content is used as an important indicator to evaluate photosynthetic efficiency, mutation, environmental stress and nutritional status for plants. To determine the best way to measure chlorophyll content easily, quickly and accurately, nine species of broadleaf trees were sampled and measured. The nine species of broadleaf trees were Cyclobalanopsis glauca, Castanopsis sclerophylla, Cinnamomum camphora, Magnolia grandiflora，Koelreuteria integrifoliola, Magnolia heptapeta, Sapindus mukorossi, Liriodendron chinensis and Prunus serrulata. The purpose of this paper was to explore the relationship between chlorophyll content index （CCI） and absolute chlorophyll content, so that just by CCI to obtain the absolute chlorophyll content in leaves. The absolute chlorophyll content meant the quality of chlorophyll in leaves which was obtained by solution extraction method. The Chlorophyll Meter CCM-200 was used to determine the chlorophyll content index （CCI） of leaves. And then CCI and leaf thickness were used to simulate models of chlorophyll content. Comparison of simulated and measured data were extracted to show the error from 1） linear models which were only based on chlorophyll content index （CCI ） to estimate chlorophyll a, chlorophyll b, and total chlorophyll; 2） models with CCI and specific leaf weight （SLW）; 3） models with CCI and specific leaf area （SLA）, using a regression analysis. A regression analysis showed models only using CCI had an R2 = 0.610. With CCI and SLW, R2 improved, but R2 was better still with SLA and CCI, R2 between CCI and the content of chlorophyll a （R2 = 0.869）, chlorophyll b （R2 = 0.893）, and total chlorophyll （R2 = 0.881）. Overall, the simulated model with CCI and SLA as variables was more accurate and universal for estimating chlorophyll content of selected broadleaf tree species. ［Ch, 3 fig. 3 tab. 12 ref.］ |
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| Keywords: | plant phsiology chlorophyll content index（CCI） regression analysis specific leaf weight （SLW） specific leaf area （SLA） |
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