利用高光谱无图像测量技术评估甜菜冠层斑叶病的病情发展

Ahmed Ameen Heba M.
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引用次数: 0

摘要

甜菜(Beta vulgaris)在埃及是第二重要的糖源。在埃及,甜菜受到由甜菜斑孢菌引起的斑孢叶斑病(CLS)的侵袭。在本研究中使用遥感和GIS代表光谱特征和植被指数来确定这些技术在植物病理学领域的能力。利用高光谱无图像测量技术SpectraPen SP100研究甜菜CLS病侵染的光谱特征和植被指数。取决于选择波长值(R490, R560, R655, R705, R740和R775)与甜菜植株冠层的反应。利用光谱特征和植被指数(NDVI、SR、OSAVI、AR1和AR2),成功测定了甜菜CLS病引起的植物侵染冠层变化。结果表明,光谱反射率在选择波长上能够区分健康植株和患病植株,以可见光、红边和近红外为代表,对CLS的检测效果最好,且与CLS的病情严重程度有较高的相关性。结果表明。结果表明,植被指数NDVI相关性最高,AR1和AR2次之。
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Utilizing Hyper-Spectral No-Image Measurement to Assess the Development of disease severity of Cercospora Leaf Spot disease in sugar beet canopy
: Sugar beet ( Beta vulgaris ) in Egypt is second important source sugar. In Egypt sugar beet is attacked by Cercospora leaf spot (CLS) caused by Cercospora beticola fungus. Remote sensing and GIS represent spectral signature and vegetation indices were used in the present study to determine the ability of these technique in the plant pathology sector.spectral signature and vegetation indices associated with infection of sugar beet crops by CLS disease using Hyperspectral No-image measurements SpectraPen SP100. Depend on the reaction between selecting wavelength values (R490, R560, R655, R705, R740 and R775) with canopy of sugar beet plants. Using spectral signature and vegetation indices (NDVI, SR, OSAVI, AR1 and AR2) result revealed that succeeded in determining the change in plant infected canopy causing by CLS disease of sugar beet. The result showed that spectral reflectance in selecting wavelength can discriminating between healthy and infected plant which represented (visible, red-edge and near-infrared) which have the best result to detect CLS and high correlation with disease severity of CLS. Result showed that. Result showed that vegetation indices NDVI have the highest correlation followed by AR1 and AR2.
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