Monitoring Cereal Rust Development With A Spectral Radiometer

Abd, S O El; Cr, Perry; Al, Scharen; Go, B. H.; Dc, Sands; Lf, Lautenschlager; Cm, Yahyaoui; Fw, Ravet

doi:10.1094/phyto-75-936

Cited by 28 publications

(14 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Characteristic changes in reflectance spectrum has been observed due to Grapevine leafroll associated virus-3 in grape [23], Sugarcane yellow leaf virus in sugarcane [8], Potato yellow vein virus infection in potato [7] and viral infection in Nicotiana debneyi [26]. Though, commonly used broadband have been shown to detect differences between healthy and diseased plants [16,24,32], but discrimination of healthy plants from those showing mild symptom is not very sharp. However, measurement of reflectance contiguously (hyperspectral remote sensing) as a series of narrow wavelength band provides pertinent information for discrimination of disease and other plant stresses.…”

Section: Introductionmentioning

confidence: 99%

Spectral reflectance pattern in soybean for assessing yellow mosaic disease

et al. 2013

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Spectral reflectance pattern in soybean for assessing yellow mosaic disease

et al. 2013

View full text Add to dashboard Cite

show abstract

“…More recently, researchers have investigated the link between chlorophyll-related wavebands and crop plant diseases. For example, Sharp et al (1985) researched the monitoring of cereal rust development with a spectral radiometer. Changes in leaf spectral properties induced in barley leaves by cereal powdery mildew were studied by Lorenzen et al (1989).…”

Section: Introductionmentioning

confidence: 99%

Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging

et al. 2007

View full text Add to dashboard Cite

The aim of this study was to evaluate the accuracy of the spectro-optical, photochemical reflectance index (PRI) for quantifying the disease index (DI) of yellow rust (Biotroph Puccinia striiformis) in wheat (Triticum aestivum L.), and its applicability in the detection of the disease using hyperspectral imagery. Over two successive seasons, canopy reflectance spectra and disease index (DI) were measured five times during the growth of wheat plants (3 varieties) infected with varying amounts of yellow rust. Airborne hyperspectral images of the field site were also acquired in the second season. The PRI exhibited a significant, negative, linear, relationship with DI in the first season (r 2 = 0.91, n = 64), which was insensitive to both variety and stage of crop development from Zadoks stage 3-9. Application of the PRI regression equation to measured spectral data in the second season yielded a coefficient of determination of r 2 = 0.97 (n = 80). Application of the same PRI regression equation to airborne hyperspectral imagery in the second season also yielded a coefficient of determination of DI of r 2 = 0.91 (n = 120). The results show clearly the potential of PRI for quantifying yellow rust levels in winter wheat, and as the basis for developing a proximal, or airborne/spaceborne imaging sensor of yellow rust in fields of winter wheat.

show abstract

“…Since these pigments are destroyed and foliar physiological activity decreases following inoculation by the rust epiphyte, recent developments in ground-based optical sensor technology and remote sensing techniques may provide for an objective, time-and cost-effective method of recording and/or mapping disease intensity for large crop areas Moshou et al 2005;Qin and Zhang 2005;Sharp et al 1985;Steddom et al 2005;Zhang et al 2003).…”

mentioning

confidence: 99%

“…In one of the earliest experiments reported, Sharp et al (1985) monitored the onset of stripe and stem rust using a radiometer and four VIs based on broad Multi Spectral Scanner (MSS) channels (Perry and Lautenschlager 1984). Out of the four channels, channels 4 (0.5-0.6 lm) and 5 (0.6-0.7 lm) were in the visible wavelength range and the remaining two channels 6 (0.7-0.8 lm) and 7 (0.8-l.1 lm) were in the near-infrared range.…”

mentioning

confidence: 99%

Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves

et al. 2008

View full text Add to dashboard Cite

Ten, widely-used vegetation indices (VIs), based on mathematical combinations of narrow-band optical reflectance measurements in the visible/near infrared wavelength range were evaluated for their ability to discriminate leaves of 1 month old wheat plants infected with yellow (stripe), leaf and stem rust. Narrow band indices representing changes in non-chlorophyll pigment concentration and the ratio of nonchlorophyll to chlorophyll pigments proved more reliable in discriminating rust infected leaves from healthy plant tissue. Yellow rust produced the strongest response in all the calculated indices when compared to healthy leaves. No single index was capable of discriminating all three rust species from each other. However the sequential application of the Anthocyanin Reflectance Index to separate healthy, yellow and mixed stem rust/leaf rust classes followed by the Transformed Chlorophyll Absorption and Reflectance Index to separate leaf and stem rust classes would provide for the required species discrimination under laboratory conditions and thus could form the basis of rust species discrimination in wheat under field conditions.

show abstract

Monitoring Cereal Rust Development With A Spectral Radiometer

Cited by 28 publications

References 6 publications

Spectral reflectance pattern in soybean for assessing yellow mosaic disease

Spectral reflectance pattern in soybean for assessing yellow mosaic disease

Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging

Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves

Contact Info

Product

Resources

About