棉花冠层高光谱参数与叶片氮含量的定量关系

建立棉花(Gossypium hirsutum)氮素状况的光谱监测技术对于棉花营养诊断和长势估测具有重要意义。该研究利用冠层高光谱反射率及演变的多种高光谱参数,分析了不同施氮水平下不同棉花品种叶片氮含量与冠层反射光谱的定量关系,建立了棉花叶片氮含量的敏感光谱参数及预测方程。结果显示,棉花叶片氮含量和冠层高光谱反射率随不同施氮水平呈显著变化。棉花叶片氮含量的敏感光谱波段为600~700 nm的可见光波段和750~900 nm的近红外波段,且叶片氮含量与比值植被指数RVI average (760~850), 700]有密切的定量关系,4个品种的平均决定系数在0.70左右。进一步分析表明,可以用统一的回归方程来描述不同品种、不同生育时期和不同氮素水平下棉花叶片氮含量随反射光谱参数的变化模式,从而为棉花氮素营养的监测诊断与精确施肥提供技术依据。

RELATIONSHIP BETWEEN CANOPY HYPERSPECTRA PARAMETER AND LEAF NITROGEN CONCENTRATION IN COTTON

Aims It is very important to develop a nondestructive method for estimating nitrogen status and growth characters in cotton. We carried out two experiments to investigate the quantitative relationship between leaf nitrogen concentration and the canopy hyperspectral parameter in cotton.  Methods Based on the canopy hyperspectral reflectance and derived hyperspectral parameter, we investigated the quantitative relationship between leaf nitrogen concentration and canopy reflectance spectra in different cotton cultivars under different N rates and put forward the sensitive parameters and monitoring equations for leaf nitrogen concentration. Experiment 1 was conducted with two cultivars ( Sumian12 and Zhongmian29) and four N application levels (0, 150, 300 and 450 kg•hm^-2) in 2004. Experiment 2 included two cultivars (Kemian1 and Meimian33B) with three nitrogen levels (0, 240 and 480 kg•hm^-2) in 2005. Important findings Leaf nitrogen concentration and canopy hyperspectral reflectance significantly changed with levels of nitrogen fertilization. The sensitive bands of leaf nitrogen concentration were 600－700 nm of visible light and 750－900 nm of near infrared light, and the quantitative relationships between leaf nitrogen concentration and ratio vegetation index (RVI) ［average (760-850), 700］ of canopy were significant with an average R2 of 0.70 in four cultivars. An integrated regression equation could be used for describing the dynamic change pattern of leaf nitrogen concentration with hyperspectral parameters in different varieties, growing stages and nitrogen levels in cotton. These results provide a technical approach for monitoring plant nitrogen status and guiding precision nitrogen management in cotton production.