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小麦叶片色素含量的高光谱监测

冯伟;朱艳;姚霞;田永超;姚鑫峰;曹卫星   

  1. 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
  • 收稿日期:2007-06-01 修回日期:1900-01-01 出版日期:2008-05-20 发布日期:2008-05-20

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   

  1. Hi-Tech Key Laboratory of Information Agriculture of Jiangsu Province & Ministry of Agriculture Key Laboratory of Crop Growth Regulation, Nanjing Agricultural University, Nanjing 210095, China
  • Received:2007-06-01 Revised:1900-01-01 Online:2008-05-20 Published:2008-05-20

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REPLEREPIG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R2RE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: 大兴安岭, 兴安落叶松, 土壤有机碳, 碳密度, 碳汇, 人工林经营

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 REPLE were better than to REPIG, 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 REPLE and REPIG were the best to predict leaf pigment concentrations. The R2 of chlorophyll a, chlorophyll a+b, and Car for REPLE 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 REPIG 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 oncentrations in wheat leaves, and especially, REPLE could be used to reliably estimate the concentrations of leaf chlorophyll a and chlorophyll a+b.

Key words: Great Xing’an Mountains, Larix gmelinii, soil organic carbon, carbon density, carbon sink, plantation management.