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Zeitschrift für Naturforschung C

A Journal of Biosciences

Editor-in-Chief: Seibel, Jürgen

Editorial Board Member: Aigner , Achim / Boland, Wilhelm / Bornscheuer, Uwe / Hoffmann, Klaus

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Volume 71, Issue 9-10 (Sep 2016)


Picturing pathogen infection in plants

Matilde Barón
  • Corresponding author
  • Department of Biochemistry, Molecular and Cell Biology of Plants, Estación Experimental del Zaidín, Spanish Council of Scientific Research (CSIC), Profesor Albareda 1, 18008 Granada, Spain, Phone: +34 958 18 16 00 Ext. 213, Fax: +34 958 12 96 00
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Mónica Pineda
  • Department of Biochemistry, Molecular and Cell Biology of Plants, Estación Experimental del Zaidín, Spanish Council of Scientific Research (CSIC), Profesor Albareda 1, 18008 Granada, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ María Luisa Pérez-Bueno
  • Department of Biochemistry, Molecular and Cell Biology of Plants, Estación Experimental del Zaidín, Spanish Council of Scientific Research (CSIC), Profesor Albareda 1, 18008 Granada, Spain
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  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-09-14 | DOI: https://doi.org/10.1515/znc-2016-0134


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.

Abbreviations: BGF, blue-green fluorescence; Chl-F, chlorophyll fluorescence; Chl-FI, chlorophyll fluorescence imaging; F440, blue fluorescence; F520, green fluorescence; F680, red fluorescence; F740, far red fluorescence; FPSII, effective quantum yield of photosystem II; FV/FM, maximum quantum efficiency of photosystem II; GLRaV-3, Grapevine leafroll associated virus 3; HD, high dose; HR, hypersensitive response; LD, low dose; MCFI, multicolour fluorescence imaging; NIR, near infrared; ObPV, Obuda pepper virus; PAMPs, pathogen-associated molecular patterns; PMMoV, Pepper mild mottle virus; Pph, Pseudomonas syringae pv. phaseolicola; Psa, Pseudomonas syringae pv. actinidiae; PSII, photosystem II; Pto, Pseudomonas syringae pv. tomato; PVY, Potato virus Y; RFd, red chlorophyll fluorescence decrease ratio; TMV, Tobacco mosaic virus.

1 Imaging techniques for biotic stress detection

Plant diseases induced by pathogens such as viruses, bacteria and fungi are responsible for major economic losses in agriculture worldwide. Early detection of pathogens is essential to reduce disease spread and facilitate plant protection practices.

Non-invasive techniques to image the patterns of multispectral fluorescence or leaf temperature across infected leaves have greatly increased our understanding of plant responses to biotic stress [1], [2]. Visualization of the light signals emitted by plants can track the spreading of a pathogen through its host [3], [4], [5]. Furthermore, these techniques could be very useful for presymptomatic stress detection, depending on the extent in the changes in plants metabolism in response to pathogens. This early detection would allow appropriate measures at the right time, and can be used in the field, on the bench (microscopic or leaf level), as well as on canopy through remote sensing and in high-throughput plant phenotyping platforms [1], [2], [6], [7].

Available serological and PCR-based methods to confirm disease diagnosis, as well as visual rating procedures, are just some of the conventional methods for pathogen detection. These more common methods are effective, although they are labor-intensive, time-consuming and often result in delayed diagnosis. In contrast, novel analysis based on imaging sensors can effectively detect early infections directly in the field [8], [9]. In this context, imaging techniques are powerful non-destructive tools for precision agriculture, providing crucial information for decision-making and for determining the right timing for procedures to be applied [10]. These achievements are related both to the development of non-invasive, high-resolution optical sensors and of data analysis methods to deal with the large amount of data generated due to the high resolution, size and complexity rendered by these sensors [9]. Highly sophisticated and innovative methods of data analysis for complex plant-pathogen systems facilitate disease detection and expand the visual and/or molecular approaches for plant disease assessment [11].

2 Imaging kinetics of chlorophyll fluorescence

Kautsky and Hirsch [12] first described changes in red fluorescence (F680) after illumination of dark-adapted plants with photosynthetically active light. In simple words, this effect is due to the competition between photosystem II (PSII) photochemistry and processes of energy dissipation (as heat and fluorescence in the red region of the spectrum) for excitation energy in the pigment antenna of PSII. Therefore, the study of red chlorophyll fluorescence (Chl-F) kinetics provides information on the efficiency of PSII and indirectly on the CO2 assimilation rate [13]. It has been used for decades as an excellent technique for research on the light-dependent phase of photosynthesis. A great number of Chl-F parameters associated with photosynthetic activity are obtained by Chl-F induction kinetics and subsequent quenching analysis. Some coefficients are related to (i) photochemical processes, like FV/FM, the maximum quantum efficiency of PSII (FV/FM), and ΦPSII, which represents the effective quantum yield of PSII [14]; (ii) non-photochemical processes related to energy dissipation, estimated by non-photochemical quenching (NPQ) [15]. Also, the red chlorophyll fluorescence decrease ratio (RFd) is directly correlated to the net photosynthetic rates of leaves [16], [17]. Many other Chl-F parameters related to photosynthesis have been reviewed by several authors, e.g. [18], [19], [20]. Images of such Chl-F parameters could be good stress indicators to monitor pathogenesis [1]. A recent review by Murchie and Lawson [21] addresses important questions on how to measure Chl-F kinetics, paying special attention to field measurements and their application in plant phenotyping and remote sensing of crop management.

Imaging kinetics of chlorophyll fluorescence imaging (Chl-FI) is a useful tool to study the spatial and temporal heterogeneity of leaf photosynthesis under biotic stress. Thus, Chl-FI adds spatial resolution to the information obtained by conventional fluorometers. Changes in Chl-FI parameters could be related to physiological alterations in plants infected by viruses [4], [5], [22], [23], [24], [25], [26], [27], [28], bacteria [29], [30], [31], [32], [33], [34] and fungi [35], [36], [37], [38].

2.1 Chlorophyll fluorescence imaging to monitor plants infected with viruses

Work on the early responses of chloroplasts to viral infection demonstrate photoinhibitory damage in the infected plants [22], [23], [24], [25], [39]. Chl-FI measurements have been carried out in both inoculated and systemically-infected leaves during viral challenge, showing photosynthesis impairment in symptomatic and asymptomatic areas during pathogenesis [4], [5], [24], [25], [27]. In some cases, the rate of photosynthetic inhibition is associated to the severity of the symptoms; however, changes in some fluorescence parameters could precede the development of symptoms, allowing a presymptomatic detection of the disease [40]. Correlation between the pattern of Chl-FI quenching and virus distribution in leaves was found during the infection of pepper mild mottle virus (PMMoV) in Nicotiana benthamiana plants [4], [5] as well as in Abutilon mosaic virus-infected Abutilon striatum leaves [24], [25].

Asymptomatic leaves of N. benthamiana infected with PMMoV, showed low NPQ values around the invasion front, suggesting enhancement of the photosynthetic electron transport rate. In the areas already invaded by the pathogen, high NPQ values were detected. Thus, the leaf area showing higher NPQ values increased along the infection time, parallel to the spreading of the virus across the leaf. At the latest stages of infection, the leaves display the lowest NPQ values, denoting a loss in functionality in the chloroplast, presumably related to senescence (Figure 1). Virus-induced changes on the NPQ leaf pattern were visible before viral elements could be detected by either tissue print or Northern blot. The correlation found between the increase in NPQ and the location of the virus strongly supports the idea that the local rise of NPQ is associated with the presence of the pathogen in the area [4]. The discharge of the virus into the leaf has been proposed to produce an impairment of the photosynthetic electron transport chain (revealed as lower FV/FM and ΦPSII values). Then, the excess excitation energy would be dissipated (measured as higher NPQ values) to avoid photoinhibition. This effect takes place progressively in each downstream leaf invaded by the virus. Therefore, Chl-FI proved to be an excellent technique for real-time tracking of pathogen movement in the host plant, providing valuable images about the movement of the virus through the vascular system and its subsequent unloading from the phloem into the mesophyll and spreading across the leaves [5].

Images of non-photochemical quenching (NPQ) kinetics at 17 dpi of healthy and Pepper mild mottle virus Italian strain (PMMoV-I) infected Nicotiana benthamiana plants: kinetics during chlorophyll fluorescence induction from healthy (A) and asymptomatic leaves from infected plants (B) at 17 dpi. NPQ after 30 s of Kautsky induction kinetics (NPQ30) images at different dpi from healthy (C) and asymptomatic leaves of infected plants (D). Images of NPQ at steady state (300 s, NPQ300) from healthy (E) and asymptomatic leaves of PMMoV-I infected plants (F) during pathogenesis. The colour scale bar indicates the NPQ intensity of the leaf pixels given in false colors from high (white) to low (blue) values. Figure reproduced from Pérez-Bueno et al. [4] with permission.
Figure 1:

Images of non-photochemical quenching (NPQ) kinetics at 17 dpi of healthy and Pepper mild mottle virus Italian strain (PMMoV-I) infected Nicotiana benthamiana plants: kinetics during chlorophyll fluorescence induction from healthy (A) and asymptomatic leaves from infected plants (B) at 17 dpi. NPQ after 30 s of Kautsky induction kinetics (NPQ30) images at different dpi from healthy (C) and asymptomatic leaves of infected plants (D). Images of NPQ at steady state (300 s, NPQ300) from healthy (E) and asymptomatic leaves of PMMoV-I infected plants (F) during pathogenesis. The colour scale bar indicates the NPQ intensity of the leaf pixels given in false colors from high (white) to low (blue) values. Figure reproduced from Pérez-Bueno et al. [4] with permission.

Chl-FI was combined with metabolic profiling to study alterations in the primary metabolism of grapevine (Vitis vinifera ‘Malvasia de Banyalbufar’) upon infection with Grapevine leafroll associated virus 3 (GLRaV-3). The FV/FM, ΦPSII and NPQ parameters showed photoinhibition of PSII in infected plants, suggesting a loss of functionality in the chloroplast. The decrease in the accumulation of some photorespiratory intermediates found in infected plants correlated with their increase in NPQ [28].

Kyselákova et al. [41] investigated photosynthetic alterations in pea leaves infected systemically by Pea enation mosaic virus. Chl-FI revealed a decrease of ΦPSII and associated photoprotective responses, an increase in non-photochemical quenching and accumulation of de-epoxidized xanthophylls.

Spoustova et al. [42] used Chl-FI to study the impact of Potato virus Y (PVY) on the photosynthesis of non-transgenic and transgenic Pssu-ipt tobacco plants, overproducing endogenous cytokinins. Among the fluorescence parameters, NPQ proved to be most useful in assessing the differences between healthy transgenic and wild-type plants, as well as in the analysis of PVY infection in tobacco plants, although presymptomatic detection was not possible in this host-pathogen system.

Rys et al. [43] compared a compatible (PMMoV) with an incompatible [Obuda pepper virus (ObPV)] pepper-tobamovirus interaction by Chl-FI and other non-invasive techniques. After the appearance of necrotic lesions, due to inoculation with ObPV, strong inhibition of photochemical energy conversion was observed in these areas; however, leaf tissues adjacent to these inactive areas showed elevated ΦPSII and FV/FM values. PMMoV led to decreased PSII efficiency, but these responses were much weaker than in the case of infection by ObPV.

Standard Chl-F parameters do not always show clear differences between healthy and infected tissues. However, in some cases, combinatorial imaging methods could be used to map pathogen infection [30], [44]. Combinatorial imaging analysis is an advance statistical approach that renders new parameters with no physiological meaning, but offers the highest contrast between control and infected plants in the early stages of the infection. A similar approach was used by Pineda et al. [27] to follow the infection of two strains of PMMoV on N. benthamiana. In this case, combinatorial imaging revealed the infection earlier than any of the individual Chl-F parameters. Moreover, differences in detection time between the two PMMoV-strains correlated with the virulence of the strains. Detection of viral infection using combinatorial imaging preceded viral location in asymptomatic leaves by tissue printing.

2.2 Chlorophyll fluorescence imaging to monitor plants infected with bacteria

Imaging analysis of the changes of photosynthesis parameters during bacterial challenge in both compatible and incompatible interactions has been object of special attention [31], [33], [34], [45], [46]. An avirulent strain of Pseudomonas syringae pv. glycinea inducing hypersensitive response (HR) on soybean causes a decrease in ΦPSII, together with an increase in NPQ. Conversely, little changes were observed for a virulent strain able to establish a compatible interaction on the same host [45]. In contrast, Bonfig and collaborators [31] reported a decrease on maximum FV/FM, ΦPSII and NPQ in Arabidopsis plants infected with either virulent or avirulent P. syringae pv. tomato (Pto) strains. Meanwhile, combinatorial imaging and statistical analysis on Arabidopsis leaves infected with P. syringae can be used for the detection of the infection prior to the appearance of symptoms [30], and also to distinguish leaf tissues in the early or late phase of infection [44]. Rodríguez-Moreno et al. [46] reported differences between compatible and incompatible interactions in the case of asymptomatic leaf tissues of Phaseolus vulgaris plants inoculated with either P. syringae pv. phaseolicola (Pph) or Pto, respectively. A decrease in NPQ, apparent in both infiltrated and non-infiltrated leaf areas, was observed in Pph-infected plants with respect to mock-control and Pto-infected plants. Moreover, the combined analysis of leaf temperature, Chl-F and green fluorescence (F520) emitted by phenolics on such host-pathogen systems described the specific alterations on primary and secondary metabolism, making it possible to discriminate compatible from incompatible P. syringae-P. vulgaris interactions early in the presymptomatic phase of the infection process [34].

Pérez-Bueno et al. [33] imaged the host response of tissue invaded by the necrotrophic bacteria Dickeya dadantii, a causal agent of soft-rot disease, at low and high dosage of the bacterial inoculum. Inoculation with D. dadantii at a high dose (HD) seemed to overcome plant defense capacity, inducing maceration and tissue death, although it remained restricted to the infiltrated area. In contrast, the output of the defense response to low dose (LD) inoculation was the inhibition of tissue maceration and the limitation of bacterial growth. In this study, D. dadantii caused a decrease in ΦPSII and an increase in the capacity for energy dissipation or reversible NPQ on tissues in which the defense response was able to prevent tissue from maceration (Figure 2). The down-regulation of photosynthesis was suggested to be part of the plant defense program to limit carbon source availability for pathogens and/or to redirect carbon into secondary metabolism [47]. Meanwhile, Göhre et al. [48] proposed NPQ to be a positive regulator of pathogen-associated molecular patterns (PAMPs) triggered immunity. According to this model, PAMPs perception would cause a reduction of the PSII subunit PsbS, which would be partially responsible for the decrease in the NPQ capacity. This in turn would cause an increase in the production of reactive oxygen species which are known to play a role in the activation of plant defense.

Nicotiana benthamiana leaves inoculated with Dickeya dadantii at a concentration of 104 (LD) or 106 (HD) colony forming units per ml or mock-inoculated plants. Evolution of symptoms (A) and images at different post-infection times of: FV/FM (maximum quantum efficiency of photosystem II, B), non-photochemical quenching (NPQ) in the light-adapted steady state (C), quantum efficiency of photosystem II in the light-adapted steady state (ΦPSII, D), and fluorescence at 440 nm (E), and 520 nm (F). The infiltrated area was accurately outlined. The false colour-scale used in (B–F) is shown for each parameter. Figure reproduced from Pérez-Bueno et al. [33] with permission.
Figure 2:

Nicotiana benthamiana leaves inoculated with Dickeya dadantii at a concentration of 104 (LD) or 106 (HD) colony forming units per ml or mock-inoculated plants. Evolution of symptoms (A) and images at different post-infection times of: FV/FM (maximum quantum efficiency of photosystem II, B), non-photochemical quenching (NPQ) in the light-adapted steady state (C), quantum efficiency of photosystem II in the light-adapted steady state (ΦPSII, D), and fluorescence at 440 nm (E), and 520 nm (F). The infiltrated area was accurately outlined. The false colour-scale used in (B–F) is shown for each parameter. Figure reproduced from Pérez-Bueno et al. [33] with permission.

2.3 Chlorophyll fluorescence imaging to monitor plants infected with fungi

Alterations in the photosynthesis of fungi-infected plants mapped by Chl-FI are also spatially and temporally complex. Infected leaves consist of regions of cells directly invaded by the pathogen and regions that are remote from the fungal colony [24], [36], [37], [49]. The fluorescent parameter best suited for either evaluating damage or carrying out presymptomatic diagnosis depends on the type of infection.

Invasion of bean leaves by rust fungi (Uromyces appendiculatus) was revealed by changes in the fluorescence induction kinetics [50]. Cedar needles (Torreya taxifolia) infected by the fungus Pestaliopsis spp. were identified by an empirical estimate of quantum yield [51], which was also used by Bowyer et al. [52] to visualize the impact of fungal phytotoxins in hibiscus leaves (Hibiscus sabdariffa). Imaging of ΦPSII was also used to assess the impact of the fungal pathogen Ascochyta rabiei, which altered source-sink relationships in chickpea leaves [53]. Soukupová et al. [54] proposed an experimental algorithm to identify the combination of fluorescence parameters providing the highest contrast between affected and unaffected plants in canola (Brassica napus) and white mustard (Sinapis alba) leaves treated with phytotoxins produced by Alternaria brassicae. Changes in the photosynthetic parameters were also visualized during host resistance [38], [55]. A Chl-FI approach of pixel-wise analyses of FV/FM was capable of distinguishing resistant and susceptible butterhead and batavia lettuce lines against Bremia lactucae [56].

Muniz et al. [57] applied Chl-FI to cashew seedlings inoculated with the fungus Lasiodiplodia theobromae to assess any disturbances in the photosynthetic apparatus of the plants before the onset of visual symptoms. Early metabolic perturbations in the chloroplast caused by gummosis could be detected in FV/FM images of both whole plants and single leaves. The authors concluded that this parameter could be potentially used in larger-scale screening systems.

Csefalvay et al. [58] assessed the use of Chl-FI in the early stages of Plasmopara viticola infection on grapevine, under experimental conditions similar to those occurring in commercial vineyards. FV/FM and ΦPSII were identified as the most sensitive reporters of an infection. Heterogeneous distribution of FV/FM and ΦPSII in inoculated leaves was associated with the presence of developing mycelium before the appearance of symptoms and the release of spores.

The suitability of ΦPSII and other parameters calculated from the slow induction kinetics of Chl-F for monitoring the progression of a root disease was evaluated in ginseng plants (Panax quinquefolius L.) infected with Pythium irregulare Buisman. The results were compared to those obtained by the established methods of pathogen detection [59].

One of the most important soil-borne diseases affecting avocado (Persea americana Mill.) crops is white root rot, caused by the fungus Rosellinia necatrix. Symptoms in the aerial parts of the plants cannot be recognized in early stages of root infection. Granum et al. [35] found that some Chl-FI parameters (FM/F0, F’V/F’M and F’V/F’0) revealed significant differences between healthy and stressed plants at an earlier stage of the infection, suggesting that the photosynthetic apparatus was already affected in the pre-symptomatic phase. However, FV/FM decreased dramatically only when the first symptoms appeared (Figure 3). The decrease in this parameter is indicative of photodamage to PSII, probably due to the water deficit caused by the white root rot.

Chlorophyll fluorescence images of maximum quantum efficiency of photosystem II (FV/FM) in leaves of a Rosellinia necatrix-infected avocado plant (R) and a non-infected control plant (C) at 25 dpi and 28 dpi (A), and average non-photochemical quenching values throughout the infection (B). Figure adapted from Granum et al. [35] with permission.
Figure 3:

Chlorophyll fluorescence images of maximum quantum efficiency of photosystem II (FV/FM) in leaves of a Rosellinia necatrix-infected avocado plant (R) and a non-infected control plant (C) at 25 dpi and 28 dpi (A), and average non-photochemical quenching values throughout the infection (B). Figure adapted from Granum et al. [35] with permission.

3 Multicolor fluorescence imaging

The excitation of leaves with long-wavelength UV radiation (320–400 nm) resulted in four characteristic wide fluorescence bands with peaks around 440 nm (blue; F440), 520 nm (green; F520), 690 nm (red; F690) and 740 nm (far-red; F740) [60]. Imaging of fluorescence in those regions of the spectrum after UV excitation [the so-called multispectral or multicolor fluorescence imaging (MCFI)] increases the number of plant processes than can be simultaneously analyzed and provides a promising way to identify specific signatures for a particular stress [61].

The biosynthesis of many phenolic compounds, mainly through the phenylpropanoid pathway, is activated upon stress as part of the plant defense response. Under UV excitation, these compounds can emit blue-green fluorescence (BGF) [62], [63]. The main BGF emitters have been identified for some plant species and have been localized in healthy plants. Such was the case for ferulic acid [64], [65] or chlorogenic acid [66]. More recently, Talamond et al. [67] addressed the location of many phenolics using multiphoton microscopy. In leaves of healthy plants, the strongest BGF corresponds to the epidermis, vascular tissue and also mesophyll cell walls. Meanwhile, F690 and F740 are emitted by chlorophyll a [68]. However, red and far-red fluorescence (F740) are not strictly related to photosynthetic activity, since they are triggered by UV light, which is not photosynthetically active. In contrast to BGF, F690 and F740 are mainly emitted by the chloroplasts in the mesophyll and guard cells [62].

The fluorescence ratios F440/F520, F440/F690, F440/F740, and F690/F740 are often used in plant stress studies: F440/F690 and F440/F740 are frequently good as very early stress indicators, whereas F440/F520 reveals changes in plant metabolism after long stress exposure. Meanwhile, the F690/F740 ratio is inversely proportional to the chlorophyll content of a tissue [60], [63], [69].

3.1 MCFI to monitor plants infected with virus

MCFI has proved to be very useful in many experimental plant-virus systems. Pineda et al. [70] monitored a systemic viral infection in PMMoV-infected N. benthamiana and detected alterations in both red and BGF emission patterns in response to pathogenesis. It is worth noting here that N. benthamiana accumulates high levels of chlorogenic acid bound to the cell walls in response to viral infection [70]. Chinese cabbage infected with Turnip yellow mosaic virus showed an increase in the fluorescence ratios F440/F690, F440/F740, and F690/F740 [71]. For this system, the authors concluded that the increase in the intensity of F440 and F520 correlated with higher concentrations of phenylpropanoids in infected plants. Also, tobacco plants challenged with tobacco mosaic virus (TMV), triggering HR, showed an increase in BGF that was related to an increase in the accumulation of scopoletin [72]. During the infection of grapevine with GLRaV-3, the combination of NPQ images with those obtained by MCFI parameters could constitute disease signatures allowing the discrimination between GLRaV-3 infected and non-infected plants at a very early stage of infection, prior to the development of symptoms [28]. Meanwhile, the concentration of flavonols (represented by myricetin, kaempferol and quercetin derivatives) and hydroxycinnamic acids (which include derivatives of caffeic acid) increased following infection by the virus. These compounds could be responsible for the increase in multicolor fluorescence F440, F520 in the leaves, and for changes in the fluorescence ratios F440/F680, F440/F740, F520/F680 and F520/F740, but have little effect on the Chl-F ratio F680/F740.

3.2 MCFI to monitor plants infected with bacteria

Nicotiana benthamiana plants can be infected by D. dadantii, a necrotrophic bacterium producing soft rot in a wide range of hosts. Inoculated plants showed higher F440 and F520 than control plants in the early infection process, although F520 was more sensitive than F440 and could indicate infection at an earlier time (Figure 2). The localization of F440 and F520 emitters, first in the apoplast and later inside the vacuoles of mesophyll cells, pointed to an increase in the accumulation of soluble phenolic compounds, rather than bound to the cell walls. Moreover, ferulic acid and scopoletin, two well-known phytoalexins, were found to be increased in bacterial-challenged plants [33].

MCFI was used to test the response of tomato plants to Pto mutants in the multidrug resistance efflux pump MexAB-OprM. Images of F440 and F440/F690 could be used to classify them in terms of virulence [73].

Fluorescence signals were significantly higher in powdery mildew infected sugar beet (Beta vulgaris L.) plants compared to the controls, particularly F440, leading to higher F440/F690 in those plants [74]. The authors concluded that fluorescence indices might be used as single or combined indices of successful stress sensing.

3.3 MCFI to monitor plants infected with fungi

Effects of fungal root infection on host secondary metabolism were investigated using R. necatrix-infected avocado plants as a model [35]. F440 and F520 increased significantly in the leaves of infected plants, but were only observed at the late-symptomatic stage (32–36 dpi), which is probably caused by an alteration in the optical properties of the leaves due to loss of water from the leaves.

Meanwhile, Konanz et al. [75] used an advanced multicolor imaging system, based on Chl-F and BGF, in combination with an extended data analysis (shape descriptors). The authors found parameters by which they could identify different kinds of fungal symptoms (sugar beet leaf spot, grapevine black rot disease).

4 Thermal imaging

Stomata are pores in the epidermis of leaves. They are formed by two guard cells that determine the aperture of the pore, thereby controlling the gas exchange between the mesophyll of the leaves and the air. While CO2 necessary for photosynthesis enters the leaf, gaseous water leaves, serving both as driving force for water and nutrient intake in the roots and as cooling system for the leaves. Additionally, stomata are the main natural entry site for pathogens into leaves. Therefore, an accurate control of stomatal closure is essential as part of the plant defense responses triggered by pathogens [76]. Moreover, pathogens often have the ability of manipulating plant signaling pathways, thereby interfering with plant defense. As a result, some pathogens are able to prevent stomatal closure upon detection of pathogens or are even able to reopen them [48], [77], [78], [79].

The high resolution of actual thermal cameras allows to picture the behavior of stomata on the plant canopy and even on individual leaves related to biotic stress. Near infrared (NIR) cameras measure leaf and canopy temperature, which inversely correlates with transpiration and stomatal conductance [80], [81], [82], [83]. Thermal imaging of plants has been widely used in plant phenotyping mainly to characterize drought susceptibility [84]. Furthermore, thermal imaging combined with Chl-FI has enabled the analysis of spatial and temporal heterogeneity of leaf transpiration and to correlate it with photosynthetic activity. This combination of techniques can reveal presymptomatic responses to pathogens [33], [34], [40].

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

4.1 Thermal imaging to monitor plants infected with virus

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. on bean plants), obtaining contradictory effects regarding leaf temperature due to the different ways of infection of both pathogens [26]. In PMMoV-infected N. benthamiana plants, thermal imaging showed an increase in the temperature in asymptomatic leaves, before the virus unloaded from the phloem into the tissues [3]. It is concluded that this thermal pattern is due to the systemic invasion of PMMoV.

4.2 Thermal imaging to monitor plants infected with bacteria

Maes et al. [89] described the use of thermography for the detection of bacterial canker [caused by P. syringae pv. actinidiae (Psa)] in kiwifruit at leaf and orchard scale. At the leaf level, spots of lower temperature appeared shortly after Psa-infection, before any visual symptoms appeared. As the infection developed, spots of higher temperature were observed, partly associated with necrotic tissue. At the orchard level, authors could map the field based on canopy temperature, showing that Psa infects the outer canes rather than the central part of the canopy.

A comparative study was conducted on bean plants developing a compatible and incompatible interaction with two pathovars of P. syringae, i.e. Pph and Pto, respectively. An increase in temperature was detected at the infection sites during the first 5 h after infiltration. Pph caused an increase in temperature 1 h after the infiltration of bacteria, 1 h earlier than in those plants infiltrated with Pto; this differential behavior could be explained by the absence of a known toxin able to interfere with stomatal regulation in Pph [34].

The establishment of HR could also be monitored by thermal imaging in Nicotiana sylvestris plants inoculated with the bacterium Erwinia amylovora [88]. The authors linked the observed low temperature (which preceded the necrosis by several hours) with mitochondrial activity, since mutants in this organelle did not show such high transpiration rate. They proposed that mitochondria are the major source of energy required for stomatal activity, or alternatively, non-phosphorylating respiratory enzymes from this organelle could compensate for a slight temperature decrease by heat dissipation.

The effect of bacterial infection on stomatal regulation was also analyzed in the experimental system N. benthamiana – D. dadantii [33]. During the first hour of post-infiltration the temperature increased rapidly in infiltrated areas, probably as a response to wounding, followed by a second increase in temperature, this time dose-dependent (Figure 4). In this case, the stomatal closure would be triggered by PAMPs perception and controlled by abscisic and salicylic acid, the levels of which were found to be increased.

Infrared emission of Nicotiana benthamiana leaves inoculated with Dickeya dadantii at 104 (LD) or 106 (HD) colony forming units per ml, and mock-control, monitored by a thermal camera. False colour-scale thermal images of inoculated and control leaves during the first 6 days post infection. Figure adapted from Pérez-Bueno et al. [33] with permission.
Figure 4:

Infrared emission of Nicotiana benthamiana leaves inoculated with Dickeya dadantii at 104 (LD) or 106 (HD) colony forming units per ml, and mock-control, monitored by a thermal camera. False colour-scale thermal images of inoculated and control leaves during the first 6 days post infection. Figure adapted from Pérez-Bueno et al. [33] with permission.

4.3 Thermal imaging to monitor plants infected with fungi

Thermal imaging has been used in the analysis of many fungal infections attacking aerial parts of the plants. Downy mildew of cucumber, caused by Pseudoperonospora cubensis, has been reported to trigger changes in metabolic processes, including the transpiration rate, which could be visualized at an early stage by thermal imaging [90], [91].

Thermal imaging of leaves can also be an appropriate tool to detect soil-borne pathogens, as was the case with Fusarium wilt on cucumber plants, in which damage to leaf cells could be detected prior to the development of visible symptoms [92]. On the contrary, the presence of the white root rot – caused by R. necatrix – in avocado trees could not be detected presymptomatically by this technique [35]. This could be due to the characteristics of the different host-pathogen interactions.

In the literature, there are many examples of fungal infections on trees studied by thermal imaging. In a study on apple scab, thermal imaging was proven useful for describing the severity of the disease resulting from the disease stage, resistance of host tissue and differences in the virulence of Venturia inaequalis isolates infecting apple trees [93]. The infection by Phyllosticta of two conifer species induced a temperature rise in areas surrounding the inoculation site, suggesting a strong activation of stomata closure that would in turn be associated with the inhibition of ΦPSII and the increase in NPQ capacity [87].

Several authors have successfully addressed the application of thermal imaging to the detection of fungal diseases in crop fields. Stoll et al. [94] analyzed the infection caused by P. viticola in grapevine at different levels of the water status. The analysis of thermal images showed that pathogen development caused an increase in leaf temperature at the point of infection in irrigated vines. In contrast, the plants under severe water stress (non-irrigated) showed a lower temperature at the sites of inoculation. A recent study by Calderón et al. [95] describes an automatic procedure for the early detection of Verticillium wilt (VW) infection in olive trees to design focalized control strategies at a large scale. Considering that VW is related to physiological alterations shown by spectral changes, the procedure combined various vegetation indices obtained from thermal and high-resolution hyperspectral imagery. Indeed, thermal imaging appears a useful technique when combined with other imaging techniques. Oilseed rape (Brassica napus L.) is host for several species belonging to the genus Alternaria. Among all the imaging techniques employed in this study, the results obtained by thermography revealed significant changes in infected leaves. Differences in temperature, which depended on the Alternaria species, were observed in various stages of the infection [96]. Hellebrand et al. [97] studied the possibility of detecting wheat plants infected by powdery mildew (Blumeria graminis) using thermal and NIR imaging under laboratory and field conditions. The authors concluded that NIR imaging was not suitable for identification of infested plants while thermal imaging was useful under laboratory conditions.

5 Future prospects for imaging sensors in plant phenotyping and remote sensing

Besides possible alterations in leaf structure and morphology, plant pathogens usually affect plant transpiration rates, primary and secondary metabolism and interaction with sunlight. Sensors measuring fluorescence, temperature or even reflectance can be useful tools for the identification, detection and quantification of plant diseases. Using several imaging techniques in parallel could allow disease detection in the absence of visible symptoms and therefore the early identification of emerging diseases in crops [9].

Chl-FI has successfully been used in biotic stress detection in the laboratory, as indicated by the vast amount of information on this topic in the literature. Measuring photosynthesis by Chl-F at the canopy level is challenging because the technique implies the use of saturating light pulses. This limitation has been solved by the use of laser beams. Further improvements in the field include laser-induced fluorescence transients and sun-induced fluorescence (passive estimation of Chl-F from solar reflectance spectra) [7], [11], [98].

Thermal sensors detect early changes in transpiration due to both air- and soil-borne pathogens. However, thermography in crop fields is strongly affected by the microclimate of the plants. The data generated by thermal sensors require background soil corrections and reference temperatures of non-transpiring and/or fully transpiring neighbor canopies ([99] and references therein). The impact of environmental conditions, such as wind and transient cloudiness, has also to be taken into account to interpret plant temperature correctly.

Precision agriculture can make use of in-field imaging technologies to evaluate disease severity, as well as the incidence and progression of the disease. Based on this information, guidance is provided for decisions to further organize or direct protective activities in crop fields and greenhouses. The optical sensors can also be implemented in plant phenotyping programs designed to characterize the level of susceptibility and/or resistance of different genotypes to particular pathogens and to evaluate some plant defense reactions.

The quality, quantity and complexity of the data that can be obtained from sensors have dramatically increased in the last years, The high spectral, spatial and temporal resolution of these data require the use of advanced mathematical methods of data handling, analysis and interpretation [100], [101], [102].


This work was supported by a grant from Junta de Andalucía (P12-AGR-0370).


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A tree. Good. Yellow

of autumn. It opens up

to the sky brilliantly, eager

for more light. Screams its splendour

into the garden. And natural,

free, it scatters its colour

straight into the blue. It grows

like a flame, blazes, illuminates

its ancient blood. Dominates

all the air branch by branch.

All the air, branch by branch,

aglow with the yellow abundance

of the tree. Shines

that, only blue, lights

with a golden fire: oriflamme.

Not flag. Joyful fountain

of colour: It knocks up

its golden pole towards the sky.

Its eagerness of many centuries

reaches us. Light from the East.

Yellow. The wind does not

imagine yet, the flight

of its leaves, its brightness

already subdued. The gloomy

evening approaches. Not even foretells

its loneliness, that sorrow

of its branches.

It was certitude,

joy – autumn! - . Beacon

of open light.


afterwards. Where is your beau2ty?

Elena Martin Vivaldi

Source: The Ginkgo Pages http://kwanten.home.xs4all.nl/. The poem of Elena Martin Vivaldi has been translated into English by Eduardo Arancibia Diaz and Cor Kwant.

About the article

Received: 2016-06-30

Revised: 2016-07-21

Accepted: 2016-07-22

Published Online: 2016-09-14

Published in Print: 2016-09-01

Citation Information: Zeitschrift für Naturforschung C, ISSN (Online) 1865-7125, ISSN (Print) 0939-5075, DOI: https://doi.org/10.1515/znc-2016-0134.

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