作 者 ：冯伟,朱艳,田永超,马吉锋,庄森,曹卫星*
期 刊 ：生态学报 2008年 28卷 10期 页码：4902~4911
关键词：小麦；高光谱遥感；叶绿素密度；类胡萝卜素密度；监测模型；
Keywords:wheat, hyperspectral remote sensing, chlorophyll density, carotenoid density, monitoring model,
摘 要 ：作物叶片色素状况是评价植株光合效率和营养胁迫的重要指标，冠层叶片色素密度(单位土地面积叶片色素总量)的实时无损监测对作物生长诊断、产量估算及氮素管理具有重要意义。以包括不同品质类型（高蛋白、中蛋白和低蛋白）的多个小麦品种在不同施氮水平下的连续2a大田试验为基础，研究了小麦叶片色素密度与冠层高光谱参数的定量关系。结果表明，叶片色素（叶绿素a、叶绿素b、叶绿素a+b和类胡萝卜素）密度随施氮水平增加而提高，不施氮处理的叶片色素密度随生育进程而下降，施氮处理的叶片色素密度呈单峰曲线，品种间存在明显差异。群体叶片色素密度的敏感波段主要分布在可见光区，而红边区域导数光谱表现更显著。光谱参数VOG2、VOG3、RVI(810,560)、SRE/SBE和SDr/SDb等与叶绿素密度关系较为密切，线性方程决定系数R2均在0.858以上，而与类胡萝卜素密度关系减弱，决定系数R2低于0.780，且参数间差异较小。经独立试验资料的检验表明，VOG2、VOG3、SRE/SBE和SDr/SDb对不同色素的估测结果较好，预测相对误差RE低于17.6%，虽然对叶绿素b的准确性稍低。总体上，光谱参数VOG2、VOG3、SRE/SBE和SDr/SDb与小麦群体叶片色素密度关系密切，特别是对叶片叶绿素a和叶绿素a+b的密度可以进行准确可靠的实时监测。
Abstract:Canopy leaf pigment status is a key index for evaluating crop potential photosynthetic efficiency and nutritional stress. Leaf pigment density per unit ground area provides a rapid and non-destructive method to evaluate yield predictions and management of nitrogen applications. This study investigated the quantitative relationships of leaf pigment density to canopy hyperspectral reflectance in wheat (Tritium aestivum L.) with two field experiments consisting of different cultivars and nitrogen levels in two growing seasons. On the basis of measured protein content, the cultivars, Yumai 34, Yangmai 12 and Ningmai 9 were considered as high, medium and low protein types, respectively. Four nitrogen rates were applied as 0, 75, 150, 225 kg N hm-2 in the form of urea in 2004-2005, and 0, 90, 180, 270 kg N hm-2 in the form of urea in 2005-2006. Canopy hyperspectral reflectance over 350-2500 nm was measured, and the density of chlorophyll a (Chl a), chlorophyll b (Chl b), chlorophyll a+b (Chl a+b), and carotenoid (Car) were determined for leaves in the wheat canopies. The densities of the different pigments (Chl a, Chl b, Chl a+b, Car) in wheat leaves increased with increasing nitrogen application rates. With respect to plant development, the densities of the different pigments (Chl a, Chl b, Chl a+b, Car) initially increased and then decreased after jointing with differences between the cultivars, while gradually decreasing in the non-nitrogen treatment. The sensitive wavebands for pigment density occurred mostly within the visible light range, and a close correlation existed between the first derivatives of reflectance in the red-edge region (680-760 nm) and leaf pigment density. The analyses between 21 vegetation indices and leaf pigment density indicated that the pigment densities were highly correlated to all these 21 vegetation indices. The correlations of leaf chlorophyll density to the following five vegetation indices, were higher than for the other spectral parameters, with the coefficients of determination (R2) for linear correlations above 0.858. These five vegetation indices were Vogelmann indices 2 (Vog2), Vogelmann indices 3 (Vog3), the ratio vegetation index of 810 to 560 nm (RVI(810,560)), the ratio of the red-edge (680-760 nm) slope to the blue-edge (490-530 nm) slope (SRE/SBE), and the ratio of the integral of the first derivative on the red-edge region to that on the blue-edge region (SDr/SDb). All the values of R2 between Car density and the different spectral indices were below 0.780. Testing of the derived regression equations with independent datasets indicated that Vog2, Vog3, SRE/SBE and SDr/SDb were the best to predict leaf pigment density with a relative error (RE, (simulated value - observed value)/observed value) below 17.6%. The R2 associated with the Chl b density was below 0.804, lower than that of other pigment densities. The overall results suggested that the Vog2, Vog3, SRE/SBE and SDr/SDb indices have stable relationships with the pigment density in wheat leaves, especially the densities of leaf Chl a and Chl a+b.
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