Study on Hyperspectral Estimation of Pigment Contents in Leaves of Cotton Under Disease Stress
Study on Hyperspectral Estimation of Pigment Contents in Leaves of Cotton Under Disease Stress
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DOI：
10.3964/j.issn.1000-0593(2010)02-0421-05
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发表时间：
2010-02-01
影响因子：
0.7
通讯作者：
Pan Wen-chao
中科院分区：
文献类型：
--
作者：
Chen Bing;Li Shao-kun;Pan Wen-chao
在病圃和大田条件下，测定了不同生育期棉花黄萎病叶片的光谱反射率和色素含量，并调查了棉花黄萎病的严重程度。分析了棉花黄萎病叶片色素含量与光谱反射率、反射率一阶导数和光谱特征参数的相关性。建立了病害棉花叶片色素含量的估测模型，并进行了检验。结果表明，叶片叶绿素a、B和a+B含量与可见光波段的光谱反射率、蓝边、黄边和红边波长区的一阶导数光谱以及除红边摆幅Dr外的所有光谱特征参数之间的相关性均达到极显著水平。转换叶绿素吸收/反射指数（TCAR）模型和归一化植被指数（NDVI [702，758]）新模型的估算精度最高，平均相对误差在1. 5%以内。百分之三NDVI模型[702，758]简单实用，可作为估算病害棉花叶绿素a、B和a+B含量的最佳模型。这项研究表明，叶超光谱。数据可用于定量估计棉花叶片色素含量。该结论对利用高光谱遥感技术监测棉花生长状况和病害影响评价也具有重要的实践和应用价值。
The spectrum reflectance and pigment contents of cotton leaves infected with Verticillium wilt were measured in cotton disease nursery and field in different growth phases, and severity level of Verticillium wilt was investigated. The correlation between pigment contents of cotton leaves with Verticillium wilt and spectra reflectance, the first derivative of reflectance and spectral characteristic parameters were analyzed respectively. The estimation models about leaves pigment contents of disease cotton were established and tested. The results indicated that the correlations were best significant between chlorophyll a, b and a+b contents of leaves and spectral reflectance in visible wave bands, the first derivative spectrum at the wavelength regions of blue edge, yellow edge and red edge, and all spectral characteristic parameters (excluding red edge swing Dr). The models of transformed chlorophyll absorption in reflectance index (TCAR) and the new model of normalized difference vegetation index (NDVI [702,758]) had best estimated precision, and the relative errors were in average within 1. 3%. Given that the model of NDVI [702,758] is very simple and practical, it was commended as a best model to estimate chlorophyll a, b and a+b contents of disease cotton. This study shows that leaves hyperspectra. data can be used to estimate the pigment contents of cotton leaves quantitatively. This conclusion has also great practice and application value for monitoring the growth state and disease influence evaluation on cotton by using hyperspectral remote sensing.