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本文引用的文献

1
Satellite Remote Sensing of Wheat Infected by Wheat streak mosaic virus.小麦线条花叶病毒感染小麦的卫星遥感监测
Plant Dis. 2011 Jan;95(1):4-12. doi: 10.1094/PDIS-04-10-0256.
2
Detecting Sugarcane yellow leaf virus infection in asymptomatic leaves with hyperspectral remote sensing and associated leaf pigment changes.利用高光谱遥感技术和相关叶片色素变化检测无症状叶片中的甘蔗黄叶病毒感染。
J Virol Methods. 2010 Aug;167(2):140-5. doi: 10.1016/j.jviromet.2010.03.024. Epub 2010 Mar 31.
3
Quantifying wheat yield across the field as a function of wheat streak mosaic intensity: a state space approach.将田间小麦产量作为小麦条斑花叶病强度的函数进行量化:一种状态空间方法。
Phytopathology. 2009 Apr;99(4):432-40. doi: 10.1094/PHYTO-99-4-0432.
4
Remote sensing and image analysis in plant pathology.植物病理学中的遥感与图像分析。
Annu Rev Phytopathol. 1995;33:489-528. doi: 10.1146/annurev.py.33.090195.002421.
5
Promoters, transcripts, and regulatory proteins of Mungbean yellow mosaic geminivirus.绿豆黄花叶双生病毒的启动子、转录本和调控蛋白。
J Virol. 2005 Jul;79(13):8149-63. doi: 10.1128/JVI.79.13.8149-8163.2005.
6
The potential of optical canopy measurement for targeted control of field crop diseases.光学冠层测量在田间作物病害靶向防治中的潜力。
Annu Rev Phytopathol. 2003;41:593-614. doi: 10.1146/annurev.phyto.41.121702.103726. Epub 2003 Apr 18.
7
Evidence for expression level-dependent modulation of carbohydrate status and viral resistance by the potato leafroll virus movement protein in transgenic tobacco plants.转基因烟草植株中马铃薯卷叶病毒移动蛋白对碳水化合物状态和病毒抗性的表达水平依赖性调节的证据。
Plant J. 2001 Dec;28(5):529-43. doi: 10.1046/j.1365-313x.2001.01179.x.
8
Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration.高等植物叶片的光学特性:将光谱特征与胁迫和叶绿素浓度联系起来。
Am J Bot. 2001 Apr;88(4):677-84.

用于评估大豆黄花叶病的光谱反射模式。

Spectral reflectance pattern in soybean for assessing yellow mosaic disease.

作者信息

Gazala I F Saad, Sahoo R N, Pandey Rakesh, Mandal Bikash, Gupta V K, Singh Rajendra, Sinha P

机构信息

Division of Plant Pathology, Indian Agricultural Research Institute, New Delhi, 110012 India.

Division of Agricultural Physics, Indian Agricultural Research Institute, New Delhi, 110012 India.

出版信息

Indian J Virol. 2013 Sep;24(2):242-9. doi: 10.1007/s13337-013-0161-0. Epub 2013 Sep 19.

DOI:10.1007/s13337-013-0161-0
PMID:24426282
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3784907/
Abstract

Remote sensing technique is useful for monitoring large crop area at a single time point, which is otherwise not possible by visual observation alone. Yellow mosaic disease (YMD) is a serious constraint in soybean production in India. However, hardly any basic information is available for monitoring YMD by remote sensing. Present study examines spectral reflectance of soybean leaves due to Mungbean yellow mosaic India virus (MYMIV) infection in order to identify YMD sensitive spectral ratio or reflectance. Spectral reflectance measurement indicated significant (p < 0.001) change in reflectance in the infected soybean canopy as compared to the healthy one. In the infected canopy, reflectance increased in visible region and decreased in near infra-red region of spectrum. Reflectance sensitivity analysis indicated wavelength ~642, ~686 and ~750 nm were sensitive to YMD infection. Whereas, in yellow leaves induced due to nitrogen deficiency, the sensitive wavelength was ~589 nm. Due to viral infection, a shift occurred in red and infra-red slope (called red edge) on the left in comparison to healthy one. Red edge shift was a good indicator to discriminate yellow mosaic as chlorophyll gets degraded due to MYMIV infection. Correlation of reflectance at 688 nm (R688) and spectral reflectance ratio at 750 and 445 nm (R750/R445) with the weighted mosaic index indicated that detection of yellow mosaic is possible based on these sensitive bands. Our study for the first time identifies the yellow mosaic sensitive band as R688 and R750/R445, which could be utilized to scan satellite data for monitoring YMD affected soybean cropping regions.

摘要

遥感技术有助于在单个时间点监测大面积的农作物,而仅靠肉眼观察则无法做到这一点。黄花叶病(YMD)是印度大豆生产中的一个严重制约因素。然而,几乎没有任何关于通过遥感监测黄花叶病的基础信息。本研究检测了受印度绿豆黄花叶病毒(MYMIV)感染的大豆叶片的光谱反射率,以确定对黄花叶病敏感的光谱比或反射率。光谱反射率测量表明,与健康的大豆冠层相比,受感染的大豆冠层的反射率有显著变化(p < 0.001)。在受感染的冠层中,光谱的可见光区域反射率增加,近红外区域反射率降低。反射率敏感性分析表明,波长约642、686和750 nm对黄花叶病感染敏感。而在因氮缺乏导致的黄叶中,敏感波长为589 nm。由于病毒感染,与健康冠层相比,红色和红外斜率(称为红边)向左发生了偏移。红边偏移是区分黄花叶病的一个良好指标,因为叶绿素因MYMIV感染而降解。688 nm处的反射率(R688)以及750和445 nm处的光谱反射率比(R750/R445)与加权花叶指数的相关性表明,基于这些敏感波段可以检测黄花叶病。我们的研究首次确定了对黄花叶病敏感的波段为R688和R750/R445,可利用这些波段扫描卫星数据以监测受黄花叶病影响的大豆种植区域。