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小麦叶片色素含量的高光谱监测
引用本文:冯伟,朱艳,姚霞,田永超,姚鑫峰,曹卫星.小麦叶片色素含量的高光谱监测[J].应用生态学报,2008,19(5):992-999.
作者姓名:冯伟  朱艳  姚霞  田永超  姚鑫峰  曹卫星
作者单位:南京农业大学/江苏省信息农业高技术研究重点实验室/农业部作物生长调控重点开放实验室,南京,210095
基金项目:国家自然科学基金 , 江苏省自然科学基金
摘    要:连续两年采用不同小麦品种在不同施氮水平下进行大田试验,建立了小麦叶片色素含量的光谱定量监测模型.结果表明,叶片色素含量随着施氮水平的增加而提高,品种间存在差异,叶绿素(Chl) a+b相对含量随生育时期的变化较Chl b和类胡萝卜素(Car)更为明显.群体叶片色素含量的敏感波段主要存在于可见光区,其中,红边区域表现显著.红边位置参数REPLE和REPIG与叶绿素关系较为密切,REPLE的表现较好.以REPLE为变量对Chl a、Chl b和Chl a+b进行方程拟合,决定系数R2分别为0.835、0.841和0.840;对Car含量进行方程拟合,其R2显著下降,且光谱参数间差异较小.经独立数据的检验表明,红边位置的估算结果较好,以REPIG为变量对Chl b进行预测,模型测试的R2和RE分别为0.632和18.2%;以REPLE为变量对Chl a、Chl a+b和Car含量进行预测,R2分别为0.805、0.744和0.588,RE分别为9.0%、9.7%和14.6%.表明红边位置与叶片色素含量关系密切且表现稳定,利用REPLE可以对小麦叶片Chl a和Chl a+b含量进行可靠的监测.

关 键 词:小麦  高光谱遥感  叶片色素含量  监测模型  小麦叶片  色素含量  光谱监测  remote  sensing  concentration  pigment  leaf  wheat  利用  稳定  测试  模型  预测  估算  红边位置  检验  数据  光谱参数  决定系数  方程拟合
文章编号:1001-9332(2008)05-0992-08
收稿时间:2007-06-01
修稿时间:2007年6月1日

Monitoring of wheat leaf pigment concentration with hyper-spectral remote sensing.
FENG Wei,ZHU Yan,YAO Xia,TIAN Yong-chao,YAO Xin-feng,CAO Wei-xing.Monitoring of wheat leaf pigment concentration with hyper-spectral remote sensing.[J].Chinese Journal of Applied Ecology,2008,19(5):992-999.
Authors:FENG Wei  ZHU Yan  YAO Xia  TIAN Yong-chao  YAO Xin-feng  CAO Wei-xing
Institution:Hi-Tech Key Laboratory of Information Agriculture of Jiangsu Province, Nanjing Agricultural University, Nanjing 210095, China. Feng-wei78@126.com
Abstract:In a two-year field experiment with wheat cultivars under different application rates of fertilizer N, the wheat leaf pigment concentrations were monitored with hyper-spectral remote sensing, and quantitative monitoring models were established. The results showed that the pigment concentrations in wheat leaves increased with increasing N application rate, and differed significantly among test cultivars. With the growth of wheat, the relative concentration of chlorophyll a + b varied more obviously than those of chlorophyll b and carotenoid (Car), and the sensitive bands of the pigments occurred mostly within visible light range, especially in red-edge district. The analyses on the relationships between eight existing vegetation indices and leaf pigment concentrations indicated that the concentrations of chlorophyll a, chlorophyll b, and chlorophyll a + b were highly correlated with red edge position, and the relationships to REP(LE) were better than to REP(IG), giving the determination coefficient R2 as 0.835, 0.841 and 0.840, and standard error SE as 0.264, 0.095 and 0.353, respectively. However, the R2 values between Car and different spectral indices decreased significantly, and the differences among the spectrum indices were very small. The tests of the monitoring models with independent datasets indicated that REP(LE) and REP(IG) were the best to predict leaf pigment concentrations. The R2 of chlorophyll a, chlorophyll a + b, and Car for REP(LE) were 0.805, 0.744 and 0.588, with the RE being 9.0%, 9.7% and 14.6%, respectively, and the R2 and RE of chlorophyll b for REP(IG) were 0.632 and 18.2%, respectively. It was suggested that the red-edge parameters of hyper-spectral reflectance had stable relationships with the pigment concentrations in wheat leaves, and especially, REP(LE) could be used to reliably estimate the concentrations of leaf chlorophyll a and chlorophyll a + b.
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