Imaging techniques in plant physiology: from simple to multispectral approaches
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Time-lapse imaging and continuous video-capture have been extensively applied for long-term monitoring of plant growth. To study growth responses in the absence of light, near infrared illumination, which is generally regarded as physiologically inactive, is used. Near infrared radiation (NIR) illumination and imaging under natural light conditions visualises plant leaves with higher contrast compared to visual spectrum imaging. This fact has been exploited to calculate the local speed of leaf growth from time sequences of near infrared images (Schmundt et al., 1998). The resulting data are graphically represented as a displacement map. This a pseudocolour representation of the leaf, where light colours indicate high growth rate, and darker colours slower growth rate The technique was subsequently applied to monitor the effect of drought stress on diurnal variations in leaf growth rate (Schurr et al., 2000). Under field conditions, NIR permits to discern leaf cover from soil (Marchant et al., 1998), what could be applied in multispectral systems to guide leaf-cover-specific extraction of information in other spectral bands with low soil-crop contrast (see 7). To extend the range of imaging applications, systems can be mounted on autonomous vehicles for field applications or on robotic installations in laboratory and nursery environments. In addition, multiple cameras can be monitored from a central computer system. Multi-site monitoring of the activity of predators on plants infested with insect pests was achieved by the use of 16 multiplexed videocameras equipped with IR-illumination to allow night time measurements as well (Meyhofer, 2001). On the field scale, simple optical visual spectrum observation was used to quantify herbicide phytotoxicity with vehicle-mounted optical sensing (Bell et al., 2000). This technique was found to be as reliable as conventional visual assessment by an experienced person. Remote sensing techniques are well suited for site-specific crop management and yield prediction, since from the combination of image sets taken at different growth stages of the crop, both spatial and temporal information can be extracted (Shanahan et al., 2001). In the classical 'manual' approach to investigate growth of field crops, repetitive and intensive measurements representative for the whole crop, need to be carried out in the field at regular intervals. Remote sensing provides an accurate alternative on which crop management decisions can be based (Flowers et al., 2001). Importantly, field measurements should be conducted according to standardised protocols to avoid the influence of sun zenith angle (Dymond et al., 2001) and leaf wetness (Guan and Nutter, 2001). Laboratory measurements are less prone to such influences as a result of controlled environmental conditions.
Plants contain compounds that fluoresce upon excitation with short-wavelength light. Upon excitation with UV or blue light, light of longer wavelength is emitted. The choice of an appropriate filter set on the light source and on the detector allows the light emitted from the target fluorochrome present in the leaf to be imaged only. In addition, the introduction of artificial fluorochromes by loading into cells or by transformation of the plant permits to visualise a whole array of physiological changes. Endogenous and artificial fluorophores can be excited by illumination and visualised microscopically at the cellular level. On the macroscopic scale, autofluorescence or fluorescence from expressed fluorophores can be captured from plant organs, whole plants or canopies. Possible applications of fluorescence imaging range from analysis of photosynthesis and metabolism to cell biology, gene expression, signalling research and studies of plant-microbe interactions.
By using specific fluorescence probes, the dynamics of cellular substances can be visualised. Fluorescence ion imaging permits to monitor the transport of ions, a mechanism implicated in a multitude of signalling processes in plants (Roos, 2000). Microscopic observation of cellular processes has been greatly improved by techniques to express fluorochromes in plants under the control of specific promoters, or as fusion proteins. The green fluorescent protein (GFP), isolated from the jellyfish Aequorea victoria, emits green light when excited by blue or ultraviolet (UV) light, and is by far the most popular fluorochrome used for these applications. Three dimensional (3D) visualisation of gene expression or protein transport in intact specimens has been made possible by the development of confocal and two-photon microscopy (Gilroy, 1997; König, 2000). These microscopic techniques have a bigger depth of visualisation compared with conventional microscopy. Several reviews are available that provide a detailed overview of recent research in the field of GFP imaging (Haseloff, 1999; Köhler, 1998). GFP imaging does not always allow efficient visualisation. To avoid problems with high background autofluorescence, double reporter systems could be used, for instance by combining luciferase (see 3.2) and GFP (Mantis and Tague, 2000). A recent development with high-throughput potential for in-vivo screening of protein-protein interactions is the protein fragment complementation assay (PCA). The principle of this assay is based on the reconstitution of the 3D structure of native murine dihydrofolate reductase (mDHFR) from two separate but complementary parts of the enzyme, each fused to one of a pair of interacting proteins. Upon interaction of the selected pair of proteins the mDHFR inhibitor methotrexate (MTX), linked to a fluorescent probe, specifically binds to the reconstituted mDHFR. Protoplasts were transformed by electroporation with plasmid DNA carrying gene fusions encoding the selected interacting proteins, each linked with a fragment of mDHFR. The effect of (putative) resistance-inducing compounds, added together with MTX to the protoplasts, can be studied at the protein level in vivo, also enabling to elucidate the subcellular location of the interaction (Subramaniam et al., 2001). In addition to the use of fluorescence imaging (see 5.2) and thermography (see 2.6), confocal microscopy can be used for characterisation of surface and subsurface fruit characteristics in quality assessment. Repeated non-destructive visualisation of the evolution of apple fruit wax layer thickness was recently achieved. The apple cuticular layer prevents water evaporation from the fruit and determines storage time (Veraverbeke et al., 2001) (see also 5.3).
All plant material that contains chlorophyll pigments will emit red fluorescence upon illumination. This chlorophyll fluorescence has an enormous potential as a non-destructive probe to investigate the physiology and structure of the photosynthetic apparatus (Krause and Weiss, 1991). By use of portable fluorimeters, this simple non-invasive means of studying photosynthetic electron transfer reactions has been applied in several fields, as an efficient tool in basic photosynthesis research, to describe and investigate the photosynthetic light processes and quantum conversion at physiological conditions (Govindjee, 1995; Strasser et al., 1995; Stirbet et al., 1998), as well as to detect stress and senescence in the photosynthetic apparatus (Lichtenthaler and Rinderle, 1988; Mohammed et al., 1995; van Kooten and Snel, 1990; Strasser and Tsimilli-Michael, 1998). However, these instruments have an important limitation. Portable fluorimeters are equipped with small-sized sensors, which deliver measurements of fluorescence intensity averaged over the area of the sensor. The information obtained is limited to a small spot, which is rarely representative for the situation in the whole leaf (Ciscato and Valcke, 1998, Figure 4). Information about the spatial distribution of fluorescence emission can be obtained by performing series of measurements, regularly distributed over the surface to be analysed; this approach however is tedious and inefficient. Over the last decade, high-resolution fluorescence-imaging techniques have been developed. In a sense, the very first experiment about fluorescence imaging can be ascribed to Kautsky and Hirsch (1931) who used their own eyes to visually observe chlorophyll fluorescence changes. The first images of chlorophyll fluorescence were obtained photographically by a technique called phytoluminography (Sundbom and Björn, 1977). The advent of CCD technology and digital imaging techniques allow qualitative and quantitative analysis of fluorescence images. High resolution imaging of chlorophyll fluorescence from intact leaves has enabled the production of images of the relative quantum efficiency of photosynthetic electron transport in tissues, individual cells and even chloroplasts in situ (Oxborough and Baker, 1997; Baker et al., 2001). This technique offers the possibility to study the distribution and irregularities of chlorophyll fluorescence over the whole leaf area (Buschmann and Lichtenthaler, 1998) and enables the analysis of the progressive loss of photosynthetic activity of leaves under stress conditions (Lichtenthaler and Miehé, 1997). Fluorescence imaging systems have also been used to investigate the role of stomatal conductance in the regulation of photosynthesis (Cardon et al., 1994; Meyer and Genty, 1999), to study the effect of fungal pathogens on photosynthesis (Peterson and Aylor, 1995; Scholes and Rolfe, 1996; Meyer et al., 2001) and to demonstrate photosynthetic oscillations in leaves (Siebke and Weiss, 1995). The use of chlorophyll imaging in agriculture and horticulture has still been very limited (Abbott, 1999). Only a few attempts have been made to correlate chlorophyll fluorescence emission to physiological properties of fruits in order to estimate maturity and senescence (Song et al., 1997), to predict development of diseases (DeEll et al., 1996) or to detect stress conditions during storage (DeEll et al., 1995). However, these studies used the conventional portable instrumentation and not the fluorescence imaging as such.
I Figure 4. Chlorophyll fluorescence imaging of the dynamic evolution of abiotic photosynthetic stress induced by the heavy metal copper. A tobacco leaf was dark-adapted and subsequently submitted to continuous light. An image of maximum fluorescence (Fm) was captured immediately after this induction. Images of steady state fluorescence (Fs) were captured after induction reached an equilibrium state. The treatment consisted in injecting a copper-sulphate solution in the mid-vein at the base of the leaf, after a control image of the leaf (left panel) was taken. The depicted fluorescence parameter, called ratio of fluorescence decay (Rfd, also variable chlorophyll fluorescence ratio), indicates photosynthetic efficiency and is obtained by the following formula: Rfd=(Fm-Fs)/Fs. Low values (red as indicated on the scale bar) result from a lack of photosynthetic activity. As copper is transported through the vascular system, Rfd values drop, indicating inhibition of photosynthesis (see second panel, 30 min. after treatment and right panel, 60 min after treatment). The left panel shows the distribution of Rfd for a typical untreated leaf region. Figure reproduced with permission from Ciscato and Valcke, 1998. lluminating plant material (e.g. leaves, fruit) with UV-A laser light results in a fluorescence emission spectrum characterised by four emission bands: a blue (440 nm), a green (520 nm) and the well known red (690 nm) and far-red (740 nm) chlorophyll fluorescence emission bands (Chapelle et al., 1984). The blue-green emission, although not yet very well established, relates to secondary metabolites (Goulas et al., 1990) (see also 5.3). High spatial resolution imaging systems have been developed, which allow a fast and large-scale screening of fluorescence gradients and local disturbances in fluorescence emission over the whole leaf surface at the four characteristic emission bands (Chappelle and Williams, 1987; Lang et al., 1994). Such a system has been used to evaluate nitrogen fertilisation in apple orchards (Sowinska et al., 1998), to detect physiological disorders during storage of apples (Ciscato et al., 2001), to study the dynamic evolution of heavy metal stress (Valcke et al., 1999) and as a diagnostic tool for plant stress (Lichtenthaler and Miehé, 1997).
In response to biotic and abiotic stresses, plants accumulate secondary metabolites. In order to analyse these compounds, new spectroscopic methods, which are non-destructive, rapid and environmentally friendly, compared to the traditional and slower physico-chemical methods have been developed during the last decades. Practically all substances will give rise to substantial absorption and scattering effects when illuminated and can be analysed using vibrational spectroscopies such as near infrared, mid-infrared and Raman. Information on trace substances, present in complex samples such as food, and on their detailed conformation is hidden in their spectra. A limited number of trace substances, which contain one or more fluorophores, can be detected and measured using fluorescence emission spectra. Most naturally occurring products do not fluoresce, so emission spectra can be measured against a black background. Important fluorophores include the amino acids tryptophan, tyrosine and phenylalanine as protein constituents, coenzymes and nucleotides of the energetic metabolism (NADH, NADPH and FAD), vitamins (A, B1, B2, B6, B12, D2, E and folic acid), chlorophyll, and secondary metabolites such as caffeine, polyphenols, flavonoids and aflatoxins. Fingerprinting with fluorescence spectroscopy becomes a powerful technique. In this technique, two-dimensional fluorescence landscapes are obtained by measuring the fluorescence spectra as a function of two variables, the excitation wavelength and the emission wavelength (Engelsen, 1997). Employing ‘Partial Least Square Regression (PLSR)’ techniques, a number of fat- and oil-related quality attributes such as anisidine value, oligomer content, iodine value and vitamine E content can be predicted or measured in complex food samples (Munck et al, 1998). In most cases, endogenous fluorophores require excitation with UV light (see also 5.2). Long-term UV irradiation during continuous microscopic observation often leads to photodamage (Cheng et al, 2001) (see also 5.1). To overcome this problem, time-resolved fluorescence microscopy using two-photon excitation offers new opportunities to investigate excited-state dynamics. In fluorescence lifetime imaging (FLIM), the far-field fluorescence decay is recorded with a scanning microscope and an image is constructed from the fluorescence lifetime values obtained for each voxel (volume pixel - picture element) of the scanned field (Draajer et al, 1995). Using FLIM, heterogeneity in the aggregation of LHCII was demonstrated (Barzda et al, 2001). In food analysis, such as quality assessment of fruit, this kind of non-destructive analysis of secondary metabolites seems to be very promising (vande Ven et al., 2001).
Environmental control of vegetation requires the development of rapid screening techniques, which can be applied on a large scale. Until 1995, remote sensing was almost exclusively carried out by measuring the reflectance signals and images via aircraft and satellites (Nilsson, 1995). On a large scale, fluorescence imaging offers fast and remote measurements from a leaf to a canopy. Nevertheless, since the intensity of actively induced fluorescence is ten fold lower when compared to the reflectance signal, fluorescence images of plants can only be taken from short distances. Moreover, more sophisticated instruments than those for reflectance measurements are needed: a strong source of radiation for exciting the fluorescence and synchronised amplification to discriminate the low-intensity fluorescence from the background of high-intensity daylight reflectance. An overview of the possibilities and limitations in multi-colour fluorescence imaging of plants is given by Buschmann and Lichtenthaler (1998). Their extension to remote sensing is covered by Cerovic et al. (1999) (see also 7). The effect of temporal changes in the physical environment of plant communities has been monitored remotely by changes in surface chlorophyll concentration in the oceans and in the Normalized Difference Vegetation Index (NVDI) on land. The consequences of the El Niño – Southern Oscillations (ENSO) on the biospheric primary production has recently been studied using the Sea-viewing Wide Field-of-view Sensor (SeaWifs) measuring fluorescence at four different wavelengths (Behrenfeld et al., 2001). Using a newly developed infrared fast repetition rate fluorimeter (IRFRR), the distribution of aerobic bacterial photosynthesis in tropical surface waters and in temperate coastal waters was mapped in a biophysical way (Kolber et al., 2000). The spatial distribution of photosynthetic bacteria and oxygenic phytoplankton was obtained by measuring the fluorescence emission signals at 880 nm and 685 nm, respectively.
In plant physiology, quantitative analysis of metabolites and modelling of metabolic pathways is still in progress. Firstly, the continuing advances in molecular biology provide tools for dissecting the operation of metabolic pathways and secondly, advances in mathematical modelling and computer programming made analyses of metabolic fluxes more efficient. Another versatile technique to investigate plant metabolism is nuclear magnetic resonance (NMR) spectroscopy (Ratcliffe and Shachar Hill, 2001). Recording and interpretation of NMR spectra of plant tissue has been described extensively (Roberts and Xia, 1995; Shachar-Hill and Pfeffer, 1996). Two-dimensional phosphorus NMR exchange spectroscopy has been used to monitor several reactions of central plant metabolism (Bligny and Douce, 2001). Spatial information from NMR signals can be extracted using NMR imaging (generally referred to as magnetic resonance imaging - MRI). The strongest signal that can be detected in vivo is the 3H NMR water signal, allowing visualisation of water movement in plants (Ratcliffe, 1994; Velikanov et al., 2001). Besides describing tissue anatomy and water movement, MRI is also capable of generating physiologically important information (Köckenberger et al., 1997; Köckenberger, 2001). More abundant primary and secondary metabolites have been successfully mapped using imaging methods (Koizumi et al., 1995; Ishida et al., 1996). The tissue distribution of carbohydrates and amino acids has been mapped simultaneously in hypocotyls of castor bean seedlings using the technique of correlation peak imaging (Ziegler et al., 1996) which allows the detection of the metabolites present at concentrations as low as 10 mM and in a voxel volume of 0.56 µl (Metzler et al., 1995). Although the in vivo histochemistry is still limited by the sensitivity, long-term measurements of both xylem and phloem sap has been performed (Peuke et al., 2001) and chemical shift imaging can generate physiologically important information about the translocation of sucrose, for instance in the phloem (Verscht et al., 1998). Recently, a positron emitting tracer (PET) imaging system, which has already been widely applied in medical diagnosis, was used to visualise real time translocation of nitrogen (13N labelled) and water (15O labelled) in living rice plants (Kiyomiya et al., 2001). NMR and PET imaging visualise transport phenomena inside plants with sufficient spatial and temporal resolution to study influences of stress factors.
The term multispectral is generally used to indicate systems that measure reflectance in narrow regions of the visible and near infrared (up to 2000 nm) spectrum (e.g. with 10-nm spectral resolution). The term hyperspectral imaging is also used for such systems. Depending on the wavelength, leaves absorb and reflect more of the captured light. Deterioration of photosynthetic pigments, accumulation of secondary compounds upon a(biotic) stress and structural changes at the leaf surface influence the spectral characteristics of the leaves (Peñuelas and Filella, 1998). To determine at which wavelength(s) a given (a)biotic stress is most effectively detected, a multispectral imager, which captures data from separate regions of the spectrum (down to 10 nm), is very appropriate. Kobayashi et al. (2001) applied an airborne multispectral scanner to setup a detection methodology for rice panicle blast. Ratios of the signal in different wavelength bands are generally adopted as stress indicators. Airborne digital imagery is one of the key technologies in precision agriculture. Yang et al. (2000) showed that growth data extracted from near infrared images taken during development of a field crop correlated well with the ultimate crop yield. The imaging data thus provides a precision tool to correct for heterogeneity in growth by selective application of fertiliser. The hyperspectral compact airborne spectrographic imager (CASI) was used to estimate chlorophyll content in closed forest canopies (Zarco Tejada et al., 2001). At growth stages when soil is still visible as background, the image data corresponding to plant leaves needs to be extracted from the different spectral images (Marchant et al., 2001) (see also 4). Mutispectral imaging is also applied in machine vision systems for fruit quality control purposes. The imaging system, which combined visual and near infrared radiation (NIR - see also 4) detection with 40nm resolution, was used in conjunction with neural networks for classification of fruit depending on their type and extent of damage (Guyer and Yang, 2000).
Combination of multispectral reflectance imaging, chlorophyll and blue/green fluorescence imaging and thermography would provide a platform for the simultaneous non-invasive assessment of multiple physiological parameters. Applications include quantification of the efficiency of developed phytoprotective products or resistance-inducing compounds (for instance acibenzolar-S-methyl). This would complement molecular data, such as those obtained from microarrays (Reymond, 2001) and biochemical information on the influence of these treatments on plant-pathogen systems. A shortening of the necessary monitoring time by presymptomatic quantification of the stress response would be a major contribution to efficient screening programs. Also transgenic plants manipulated for increased stress resistance could be assessed in a more detailed way by simultaneous imaging of multiple characteristics. Multispectral monitoring systems have the potential for early detection of infected plants. Early assessment of emerging fungal, bacterial or viral infections should prevent further expansion of disease by taking appropriate measures. Identification of the type of stress causing the visualised symptoms would at a first level be derived from the information available from different spectral bands. In the case of biotic stress, a final characterisation by polymerase chain reaction (PCR) of marker genes (Verdier et al., 2001) may be needed for appropriate treatment. Epidemics of soil-borne plant disease could likely be detected in fields, as they appear in because of limited spreading via the soil (Truscott and Gilligan, 2001).
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