Literature DB >> 24426282

Spectral reflectance pattern in soybean for assessing yellow mosaic disease.

I F Saad Gazala1, R N Sahoo2, Rakesh Pandey3, Bikash Mandal1, V K Gupta2, Rajendra Singh4, P Sinha1.   

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.

Entities:  

Keywords:  Mungbean yellow India mosaic virus; Red edge; Remote sensing; Soybean yellow mosaic; Spectral indices

Year:  2013        PMID: 24426282      PMCID: PMC3784907          DOI: 10.1007/s13337-013-0161-0

Source DB:  PubMed          Journal:  Indian J Virol        ISSN: 0970-2822


  7 in total

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Journal:  Am J Bot       Date:  2001-04       Impact factor: 3.844

Review 2.  The potential of optical canopy measurement for targeted control of field crop diseases.

Authors:  Jonathan S West; Cedric Bravo; Roberto Oberti; Dimitri Lemaire; Dimitrios Moshou; H Alastair McCartney
Journal:  Annu Rev Phytopathol       Date:  2003-04-18       Impact factor: 13.078

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Journal:  Annu Rev Phytopathol       Date:  1995       Impact factor: 13.078

4.  Evidence for expression level-dependent modulation of carbohydrate status and viral resistance by the potato leafroll virus movement protein in transgenic tobacco plants.

Authors:  D Hofius; K Herbers; M Melzer; A Omid; E Tacke; S Wolf; U Sonnewald
Journal:  Plant J       Date:  2001-12       Impact factor: 6.417

5.  Detecting Sugarcane yellow leaf virus infection in asymptomatic leaves with hyperspectral remote sensing and associated leaf pigment changes.

Authors:  Michael P Grisham; Richard M Johnson; Paul V Zimba
Journal:  J Virol Methods       Date:  2010-03-31       Impact factor: 2.014

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Journal:  J Virol       Date:  2005-07       Impact factor: 5.103

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Authors:  F Workneh; D C Jones; C M Rush
Journal:  Phytopathology       Date:  2009-04       Impact factor: 4.025

  7 in total
  2 in total

Review 1.  Breeding for disease resistance in soybean: a global perspective.

Authors:  Feng Lin; Sushil Satish Chhapekar; Caio Canella Vieira; Marcos Paulo Da Silva; Alejandro Rojas; Dongho Lee; Nianxi Liu; Esteban Mariano Pardo; Yi-Chen Lee; Zhimin Dong; Jose Baldin Pinheiro; Leonardo Daniel Ploper; John Rupe; Pengyin Chen; Dechun Wang; Henry T Nguyen
Journal:  Theor Appl Genet       Date:  2022-07-05       Impact factor: 5.699

2.  Leaf and canopy reflectance spectrometry applied to the estimation of angular leaf spot disease severity of common bean crops.

Authors:  Víctor Martínez-Martínez; Jaime Gomez-Gil; Marley L Machado; Francisco A C Pinto
Journal:  PLoS One       Date:  2018-04-26       Impact factor: 3.240

  2 in total

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