| 基于自然光照反射光谱的温室黄瓜叶片含氮量预测 |
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| 引用本文： | 张喜杰,李民赞,张彦娥,赵朋,张建平.基于自然光照反射光谱的温室黄瓜叶片含氮量预测[J].农业工程学报,2004,20(6):11-14. |
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| 作者姓名： | 张喜杰 李民赞 张彦娥 赵朋 张建平 |
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| 作者单位： | 中国农业大学"现代精细农业系统集成研究"教育部重点实验室,北京,100083 |
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| 基金项目： | 北京市科技计划项目(H020720030530);上海市科技兴农项目(2001-2-8)资助 |
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| 摘 要： | 利用便携式光谱辐射仪测量了自然光照条件下温室黄瓜叶片的光谱反射率,并计算了反射率光谱的一次微分光谱。反射率光谱以及一次微分光谱与叶片含氮量的相关分析表明,温室内光谱特性与叶片含氮量相关性最大的敏感波段分别是505～664 nm和685～722 nm。当利用原始光谱进行分析时,通过变量筛选得到了4个敏感波长,分别是568、596、640和664 nm。偏最小二乘回归分析(PLSR)以及归一化颜色指数(NDCI)分析都表明,建模时的相关系数RC>0.800,模型验证时的相关系数RV>0.700。对微分光谱进行的相关分析结果表明,利用单一敏感波长520 nm就可获得理想模型,建模时的相关系数为0.880,模型验证时的相关系数为0.787。对比原始光谱的PLSR模型与一阶微分光谱的一元线性回归模型可以得知,原始光谱以及一阶微分光谱都可用于温室内叶片含氮量的预测,而且一阶微分光谱在一些特殊的波长处具有更高的预测能力,这些模型将成为开发便携式作物长势诊断仪器的技术基础。
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| 关 键 词： | 近地遥感 叶片氮元素含量 温室栽培 多元回归分析(MLR) 偏最小二乘回归分析(PLSR) |
| 文章编号： | 1002-6819(2004)06-0011-04 |
| 收稿时间： | 2/7/2004 12:00:00 AM |
| 修稿时间： | 2004年2月7日 |
Estimating nitrogen content of cucumber leaf based on solar irradiance spectral reflectance in greenhouse |
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| Zhang Xijie,Li Minzan,Zhang Yan'e,Zhao Peng,Zhang Jianping Ministry of Education,China Agricultural University,Beijing ,China.Estimating nitrogen content of cucumber leaf based on solar irradiance spectral reflectance in greenhouse[J].Transactions of the Chinese Society of Agricultural Engineering,2004,20(6):11-14. |
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| Authors: | Zhang Xijie Li Minzan Zhang Yan'e Zhao Peng Zhang Jianping Ministry of Education China Agricultural University Beijing China |
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| Institution: | Zhang Xijie,Li Minzan~,Zhang Yan'e,Zhao Peng,Zhang Jianping Ministry of Education,China Agricultural University,Beijing 100083,China) |
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| Abstract: | Spectral reflectance of cucumber leaves in growing status was measured using the ASD FieldSpec Pro VNIR spectrometer with natural illumination in greenhouse, and the first derivative of the spectral reflectance was also calculated. The results from both spectral reflectance and the first derivative show that higher correlation coefficients were obtained within wavelength range of 505~664 nm, and 685~722 nm. Four wavelengths of 568 nm, 596 nm, 640 nm and 664 nm were obtained when using spectral reflectance data. Partial least square regression(PLSR) and the single linear regression(SLR) of the normal difference color index(NDCI) of 527 nm and 762 nm were executed to spectral reflectance to avoid the harms from multicollinearity. The PLSR results show that square of the correlation coefficients were 0.819 and 0.727, respectively for calibration and validation. The SLR results of the NDCI show that squares of the correlation coefficients were 0.815 and 0.740, respectively for calibration and validation. But a linear model with single wavelength(520nm) was better when using the first derivative data. Squares of the correlation coefficients for calibration and validation were 0.880 and 0.787, respectively. These show that both spectral reflectance and the first derivative can be used to estimate cucumber leaf N-content in greenhouse, and both models will provide a basis for developing potable instrument to diagnose crop growth potential. |
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| Keywords: | ground-based remote sensing leaf nitrogen content greenhouse crop growing multiple linear regression partial least square regression |
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