Presymptomatic visualization of plant–virus interactions by thermography

Chaerle, Laury; Caeneghem, [No Value] Van; Messens, Eric; Lambers, Hans; Montagu, Marc Van; Straeten, Dominique Van Der

doi:10.1038/11765

Cited by 163 publications

(84 citation statements)

References 27 publications

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“…Nilsson (1991) reported significant correlations between spectral reflectance data and cereal plant growth, green biomass, yield, and symptoms of net blotch in barley, glume blotch in winter wheat, and take-all in spring wheat [10]. The existing techniques for disease detection can be applied on scales ranging from microscopic observation to airborne remote sensing and have recently been reviewed by Chaerle et al (1999Chaerle et al ( , 2001 [11,12].…”

Section: Introductionmentioning

confidence: 99%

Identification of powdery mildew (Erysiphe graminis sp. tritici) and take-all disease (Gaeumannomyces graminis sp. tritici) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements

2006

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Identification of powdery mildew (Erysiphe graminis sp. tritici ) and take-all disease (Gaeumannomyces graminis sp. tritici ) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements Abstract: The ability to identify diseases in an early infection stage and to accurately quantify the severity of infection is crucial in plant disease assessment and management. A greenhouse study was conducted to assess changes in leaf spectral reflectance of wheat plants during infection by powdery mildew and take-all disease to evaluate leaf reflectance measurements as a tool to identify and quantify disease severity and to discriminate between different diseases. Wheat plants were inoculated under controlled conditions in different intensities either with powdery mildew or take-all. Leaf reflectance was measured with a digital imager (Leica S1 Pro, Leica, Germany) under controlled light conditions in various wavelength ranges covering the visible and the near-infrared spectra (380 -1300 nm). Leaf scans were evaluated by means of L*a*b*-color system. Visual estimates of disease severity were made for each of the epidemics daily from the onset of visible symptoms to maximum disease severity. Reflectance within the ranges of 490 780 nm (r 2 = 0.69), 510 780 nm (r 2 = 0.74), 516 1300 nm (r 2 = 0.62) and 540 1300 nm (r 2 = 0.60) exhibited the strongest relationship with infection levels of both powdery mildew and take-all disease. Among the evaluated spectra the range of 490 780 nm showed most sensitive response to damage caused by powdery mildew and take-all infestation. The results of this study indicated that disease detection and discrimination by means of reflectance measurements may be realized by the use of specific wavelength ranges. Further studies have to be carried out, to discriminate powdery mildew and take-all infection from other plant stress factors in order to develop suitable decision support systems for site-specific fungicide application.

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Section: Introductionmentioning

confidence: 99%

Identification of powdery mildew (Erysiphe graminis sp. tritici) and take-all disease (Gaeumannomyces graminis sp. tritici) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements

2006

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“…Presymptomatic increases in temperature were visualized on TMV infection sites on tobacco plants, related to HR [85,88]. Moreover, the same authors compared a viral-induced HR (on a TMV-resistant tobacco line) with an infection by a necrotrophic fungus (Cercospora spp.…”

Section: Thermal Imaging To Monitor Plants Infected With Virusmentioning

confidence: 99%

“…Thermal imaging has been used to monitor plant stress caused by viruses [3,85,86], bacteria [33,34] and fungi [26,35,87].…”

Section: Thermal Imagingmentioning

confidence: 99%

Picturing pathogen infection in plants

Barón

Pineda

Pérez-Bueno

2016

Zeitschrift Für Naturforschung C

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Several imaging techniques have provided valuable tools to evaluate the impact of biotic stress on host plants. The use of these techniques enables the study of plant-pathogen interactions by analysing the spatial and temporal heterogeneity of foliar metabolism during pathogenesis. In this work we review the use of imaging techniques based on chlorophyll fluorescence, multicolour fluorescence and thermography for the study of virus, bacteria and fungi-infected plants. These studies have revealed the impact of pathogen challenge on photosynthetic performance, secondary metabolism, as well as leaf transpiration as a promising tool for field and greenhouse management of diseases. Images of standard chlorophyll fluorescence (Chl-F) parameters obtained during Chl-F induction kinetics related to photochemical processes and those involved in energy dissipation, could be good stress indicators to monitor pathogenesis. Changes on UV-induced blue (F440) and green fluorescence (F520) measured by multicolour fluorescence imaging in pathogen-challenged plants seem to be related with the up-regulation of the plant secondary metabolism and with an increase in phenolic compounds involved in plant defence, such as scopoletin, chlorogenic or ferulic acids. Thermal imaging visualizes the leaf transpiration map during pathogenesis and emphasizes the key role of stomata on innate plant immunity. Using several imaging techniques in parallel could allow obtaining disease signatures for a specific pathogen. These techniques have also turned out to be very useful for presymptomatic pathogen detection, and powerful non-destructive tools for precision agriculture. Their applicability at lab-scale, in the field by remote sensing, and in high-throughput plant phenotyping, makes them particularly useful. Thermal sensors are widely used in crop fields to detect early changes in leaf transpiration induced by both air-borne and soil-borne pathogens. The limitations of measuring photosynthesis by Chl-F at the canopy level are being solved, while the use of multispectral fluorescence imaging is very challenging due to the type of light excitation that is used.Keywords: biotic stress; chlorophyll fluorescence imaging; multicolor fluorescence imaging; plant pathogens; thermography. Dedication: This work is dedicated to the memory of Professor Peter Böger. He will always bring to my heart (M. B.) the best memories of my postdoc at Lake Constance.

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“…The closure of stomatal apertures is a defence mechanism which not only helps reduce water losses, but also prevents the entry of microbes and host tissue colonisation. It was also found to cause an increase in leaf and canopy temperature (Moshou, 2012); a change that can often be detected by thermal imaging at the leaf level at an early stage of infection (Chaerle, 1999;Lindenthal, 2005).…”

Section: Introductionmentioning

confidence: 99%

Uav-Borne Thermal Imaging for Forest Health Monitoring: Detection of Disease-Induced Canopy Temperature Increase

Śmigaj

Gaulton

Barr

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VI/4KEY WORDS: Stress detection, unmanned aerial vehicle, unmanned aerial system, UAV, UAS, camera calibration. ABSTRACT:Climate change has a major influence on forest health and growth, by indirectly affecting the distribution and abundance of forest pathogens, as well as the severity of tree diseases. Temperature rise and changes in precipitation may also allow the ranges of some species to expand, resulting in the introduction of non-native invasive species, which pose a significant risk to forests worldwide. The detection and robust monitoring of affected forest stands is therefore crucial for allowing management interventions to reduce the spread of infections. This paper investigates the use of a low-cost fixed-wing UAV-borne thermal system for monitoring disease-induced canopy temperature rise. Initially, camera calibration was performed revealing a significant overestimation (by over 1 K) of the temperature readings and a non-uniformity (exceeding 1 K) across the imagery. These effects have been minimised with a two-point calibration technique ensuring the offsets of mean image temperature readings from blackbody temperature did not exceed ± 0.23 K, whilst 95.4% of all the image pixels fell within ± 0.14 K (average) of mean temperature reading.The derived calibration parameters were applied to a test data set of UAV-borne imagery acquired over a Scots pine stand, representing a range of Red Band Needle Blight infection levels. At canopy level, the comparison of tree crown temperature recorded by a UAV-borne infrared camera suggests a small temperature increase related to disease progression (R = 0.527, p = 0.001); indicating that UAV-borne cameras might be able to detect sub-degree temperature differences induced by disease onset.

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Presymptomatic visualization of plant–virus interactions by thermography

Cited by 163 publications

References 27 publications

Identification of powdery mildew (Erysiphe graminis sp. tritici) and take-all disease (Gaeumannomyces graminis sp. tritici) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements

Identification of powdery mildew (Erysiphe graminis sp. tritici) and take-all disease (Gaeumannomyces graminis sp. tritici) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements

Picturing pathogen infection in plants

Uav-Borne Thermal Imaging for Forest Health Monitoring: Detection of Disease-Induced Canopy Temperature Increase

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