Journal of Experimental Botany, Page 1 of 14

Imaging Stress Responses in Plants Special Issue

doi:10.1093/jxb/erl157

SPECIAL ISSUE PAPER

Intact plant MRI for the study of cell water relations,membrane permeability, cell-to-cell and long distancewater transport

Henk Van As*

Laboratory of Biophysics and Wageningen NMR Centre, Wageningen University, Dreijenlaan 3,6703 HA Wageningen, The Netherlands

Received 15 May 2006; Accepted 17 August 2006

Abstract

Water content and hydraulic conductivity, including

transport within cells, over membranes, cell-to-cell, and

long-distance xylem and phloem transport, are strongly

affected by plant water stress. By being able to measure

these transport processes non-invasely in the intact

plant situation in relation to the plant (cell) water balance,

it will be possible explicitly or implicitly to examine many

aspects of plant function, plant performance, and stress

responses. Nuclear magnetic resonance imaging (MRI)

techniques are now available that allow studying plant

hydraulics on different length scales within intact plants.

The information within MRI images can bemanipulated in

such a way that cell compartment size, water membrane

permeability, water cell-to-cell transport, and xylem and

phloem flow hydraulics are obtained in addition to anato-

mical information. These techniques are non-destructive

and non-invasive and can be used to study the dynamics

of plant water relations and water transport, for example,

as a function of environmental (stress) conditions. An

overview of NMR and MRI methods to measure such

information is presented and hardware solutions for

minimal invasive intact plant MRI are discussed.

Key words: Cell compartments, diffusion, flow conducting

area, hydraulic conductivity, phloem, stress imaging, T2

relaxation, xylem.

Introduction

Long-term growth and crop yield are considerably re-duced compared with maximum attainable yield due to

water stress. This topic is turning into an enormous socialand environmental problem due to the potential impacts ofclimate change on rainfall patterns and temperature ex-tremes. Several abiotic stresses are united by the fact thatat least part of their detrimental effects on plant perfor-mance is caused by disruption of plant water status(Verslues et al., 2006). Water content and hydraulic con-ductivity, including transport within cells, over mem-branes, from cell-to-cell, and long-distance xylem andphloem transport, is therefore key information in studyingthe effect of water stress. On the cell and tissue level, aqua-porins, water channel-forming proteins, are of eminentimportance in defining hydraulic conductivity (Verkman,2000; Javot and Maurel, 2002; Tyerman et al., 2002;Tournaire-Roux et al., 2003; Lee et al., 2005). In xylemand phloem the flow conducting area and the resistancewithin the vessel or tracheid connections determinehydraulics (Sperry et al., 2006).By being able to measure transport processes in relation

to the plant (cell) water balance it will be possible ex-plicitly or implicitly to examine many aspects of plantfunction and plant performance. This is key information tovalidate biophysical functional-structural plant modelsbased on integrated carbon and water allocation and func-tions. Such models are in use to address water stress-induced effects and growth limitations (Daudet et al.,2002; Tardieu, 2005). In addition, such models are used tocount for the contribution of plant evapotranspiration andcarbon exchange within global atmospheric circulationmodels (Sellers et al., 1997).Transport within intact plants is difficult to measure

because only a few techniques are suitable. In the phloem,but also in the xylem and the surrounding tissue, complex

* E-mail: henk.vanas@wur.nl

ª The Author [2006]. Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved.For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Journal of Experimental Botany Advance Access published December 14, 2006

and fragile gradients in pressure and osmotic potentialexist that are easily disturbed by invasive experimentation(Verkman, 2000; Steudle, 2001; Koch et al., 2004). Onthe cell level, the cell pressure probe has been proven tobe very valuable to measure water (and solute) membranepermeability, either diffusional (Pd) or under hydrostaticor osmotic pressure gradients (Pf) (Tomos and Leigh,1999; Verkman, 2000). On the tissue level, the pressurebomb and root pressure probe techniques allow waterpotential and tissue hydraulics to be measured (Henzleret al., 1999). These techniques have been applied to ex-cised roots, leaves, and other pieces of a plant and areclearly very informative but destructive. Hydraulic con-ductivity has been studied by the use of the high pressureflow meter (Tyree et al., 1995). That method can only beapplied to excised parts as well.For several decades heat tracer methods were used to

measure the mass flow in xylem. Up to now they havebeen used in several ecophysiological investigations, andhave led to acceptable results if precautions against poten-tial sources of errors are taken (Smith and Allen, 1996). Ageneral problem is that heat dissipation probes do nottruly integrate velocity along the probe length. Further-more, the placement of the sensor itself is a source oferrors, particularly for the heat-pulse method (Clearwateret al., 1999). Calculations of mass flow rates from sapvelocities obtained by heat pulse techniques require areliable estimate of sap-conducting surface area. Measure-ment of the active surface, in general, is very difficult. Inaddition, it is known that shrinking and swelling of thestem occur periodically (Sevanto et al., 2002), and thatday/night rhythm may be accompanied by changes in sap-conducting surface area (Windt et al., 2006). All thesefactors can result in substantial underestimation of theactual sap flow.A very promising and attractive method for providing

detailed, non-invasive, and quantitative information onwater transport and water balance in intact plants is Mag-netic Resonance Imaging (MRI). MRI was considered toinclude NMR Microscopy or MRM, the high spatial res-olution analogue of MRI. MRI is, in essence, spatiallyresolved Nuclear Magnetic Resonance (NMR). NMR isa non-invasive and non-destructive technique that has alarge number of anatomical and physiological applicationsto plant cells, plant organs, and living plants (Walteret al., 1992; Ratcliffe, 1994; Shachar-Hill and Pfeffer,1996; Chudek and Hunter, 1997; Ishida et al., 2000;Kockenberger, 2001; Ratcliffe et al., 2001). 1H NMR haslong been used for the characterization of the physicalstate of water in plant tissue and for the non-invasivemeasurement of molecular displacement such as flow anddiffusion in plants (MacFall and Van As, 1996).Although well known from (bio-)medical applications,

MRI in plant research is still far from being a routine tool.Dedicated hardware is required in order to image intact

plants or even trees. MRI systems that are used for plantstudies have often been developed for other purposes,such as medical imaging. As a result, many machineshave been used with horizontal bore superconductingmagnets with cylindrical geometry of the magnetic fieldgradient coils. In such systems plants have to be placedhorizontally instead of vertically. Fitting the shoot or rootsof a plant through the narrow cylindrical bore of a gradientset can be stressful and damaging for the plant. Bettersolutions for minimal invasive studies on intact plants,with a (potted) root system and extended shoot (leaves),require special hardware: open access magnets, open ac-cess gradient and detector coil systems, and climatecontrol. Dedicated MRI equipment and methods are nowavailable to study cell water balance, cell-to-cell, phloemand xylem transport in (large) potted plants. An overviewof NMR and MRI methods and hardware to measure suchinformation is presented here.

NMR and MRI basics related to plant (cell)structure

Some basics of NMR and MRI and the informationavailable by NMR directly related to water in plant(cell) structures is first briefly introduced. For more ex-tended descriptions of the NMR technique and MRI stra-tegies see one of the many excellent recent textbooks(Callaghan, 1993; Levitt, 2001) and the reviews cited inthe Introduction.Water molecules contain two protons (1H), which are

spin-bearing nuclei. In a strong magnetic field (created bya magnet) aligning the magnetic moments of such nucleiresults in a weak sample magnetization, which can bemanipulated by applying time-dependent magnetic fieldpulses at the proper frequency (radio frequency or rfpulses). The component of the sample magnetizationperpendicular to the main magnetic field induces a weakinduction voltage in a detector coil placed around thesample. The time-dependent induction signal can beanalysed into frequency components by Fourier trans-formation, resulting in a frequency spectrum. In a homo-geneous main magnetic field B0, equal spins (e.g. protonsof the water molecules) have identical Larmor precessionfrequency or resonance frequency, and a single resonanceline in the frequency spectrum is observed. When a well-defined constant magnetic field gradient G, G¼@B0/@r,is created within the magnet, identical spins at differentpositions along this gradient have different resonancefrequencies, because the resonance frequency is propor-tional to the local magnetic field experienced by the spins.G can be created in three independent directions x, y, or z,or combinations thereof. In this way spins can be uniquelyspatially encoded. This is the basis for NMR imaging.Position labelling by magnetic field gradients can be

performed in a variety of ways (Callaghan, 1993).

2 of 14 Van As

Depending on the actual method used, the process ofposition labelling will take some time and acquisition ofthe signal occurs at a certain time TE (echo-time) after theexcitation of the spin system. During that time, theobserved signal will decay according to the transverse orT2 relaxation process: S(TE)¼A0 exp(–TE/T2). A0 is thesignal amplitude directly after excitation, and is a directmeasure of the amount of spins under observation in thedetector coil. In imaging it is primarily a function of thespin density. In order to obtain a full two-dimensionalimage of N3N pixels, the sequence has to be repeated Ntimes for position encoding in the second direction. If therepetition time TR is long enough, the spin system hasrestored equilibrium along the magnetic field direction:TR >3T1, where T1 is the signal decay time in the longi-tudinal or main magnetic field direction. If TR <3T1, theeffective signal amplitude, Aeff, does not represent the spindensity in each pixel uniquely, but depends on a combina-tion of the spin density and the relaxation time T1: Aeff¼A0(1–exp(–TR/T1)). As a result, NMR image intensityusually depends on a combination of these parameters,reflecting spin density, T1, and T2. In addition to theseparameters, diffusion behaviour of the molecules can alsocontribute to the contrast (see below) (Duce et al., 1992;Callaghan et al., 1994a; Xia, 1995; Edzes et al., 1998).

Methods are available by means of which quantitativeimages are obtained that represent each of these param-eters separately. Multiple Spin-Echo (MSE) MRI (Edzeset al., 1998) and Inversion recovery (IR) MSE MRI(Donker et al., 1996) are examples of such sequences. InMSE a series of images is obtained during the decay ofthe signal after the first excitation rf pulse. Single param-eter images can now be processed from the MSE-experiment by assuming a mono-exponential relaxationdecay as a function of n3TE in each picture element orpixel. Here n is the image number acquired during thesignal decay. The resulting images are: signal amplitude(A0), T2, and T1 (the latter in the case of InversionRecovery (IR-)MSE MRI). In addition, images represent-ing the diffusion coefficient, D, and flow can be obtained(see below). In this way a combination of anatomical andphysiological (functional) information is obtained, referredto as functional imaging. Some examples of single param-eter images are presented in Fig. 1.

NMR relaxation times and compartments

A variety of interactions between the magnetic momentsof the observed spins and the surrounding nuclei and

Fig. 1. (A) Single parameter images of a 3 mm slice through the trunk of a poplar tree (1.8 m total length), obtained at 0.7 T. These images havebeen calculated based on a mono-exponential fit per pixel of the signal decay as a function of decay time n3TE. a: Signal amplitude or spin densityimage, b: T�1

2 image, c: T2 image. (B) Single parameter images from a slice of the stem of a Ricinus pant. a: Signal amplitude or spin density image,b: T1 image, c: T2 image. In-plane resolution is around 1003100 lm2. Both examples demonstrate the sensitivity of T2 to tissue structure or cell size.Amplitude images show water content times tissue density. Images by courtesy of C Windt.

MRI and water transport in plants 3 of 14

electrons contribute to the relaxation times T1 and T2.These interactions make it possible to probe the physico-chemical properties of the spin environment using NMRrelaxation measurements. The protons in water moleculesexperience an intramolecular dipolar interaction betweenthe two proton spins within one and the same watermolecule, as well as an intermolecular interaction withprotons of neighbouring water molecules. Both interac-tions fluctuate when the molecules rotate or translate.When the rotation correlation time of the molecules isshort, as is the case for free water molecules (sc~10

�12 s),both T1 and T2 are equal and relatively long (~2 s). Waterclose to macromolecules or to solid surfaces generallyhave slower tumbling rates (sc~10

�12–10�10 s), whichleads to a reduction in both relaxation times. In addition,exchange of protons between water and other molecules,such as sugars, proteins, and other macro-molecules, alsoinfluences (shortens) the relaxation times (Hills and Duce,1990).The signal from water in plant tissue, containing among

others vacuoles, cytoplasm, cell walls, and extracellularspaces, decays with different relaxation times. In bio-logical systems multi-exponential relaxation is thereforenormally observed and the different decay times (relaxa-tion times) observed could be used to obtain informationon the relative proportions of water in different environ-ments or compartments (Belton and Ratcliffe, 1985). Inplant tissue the different relaxation times can be assignedmore or less uniquely to either water in the vacuole(longest T1 and T2), cytoplasm (T1 >T2, both shorter thanvacuolar T1 and T2), or cell wall/extracellular space (T2depends strongly on the water content in this compart-ment, and ranges from about 5 ms up to hundreds of ms),respectively (Snaar and Van As, 1992; Van Dusschotenet al., 1995). In leaves, water in chloroplasts can be dis-criminated as well (McCain, 1995). Within these compart-ments diffusive exchange results in single exponentialbehaviour.Proton exchange over the plasmalemma and the

tonoplast membrane affects the observed relaxation times.Due to the effect of exchange, which depends on thedifference in the relaxation times of water in the exchang-ing compartments, T1 and T2 results are, in general,different, even for the number of observed exponentials.Differences in T1 for the different compartments arerelatively small, and exchange between the compartmentsresults in averaging over the compartments. Therefore T1values relate to water content more directly. Differences inT2 are more pronounced, and exchange over membranesonly results in partial averaging (depending on the size ofthe compartments and membrane water permeability). Cellcompartments, therefore, can best be discriminated basedon T2 values (Snaar and Van As, 1992; Van Dusschotenet al., 1995).

Because of the relatively poor spatial resolution,most pixels within an image will contain informationthat originates from different subcellular compartmentsor even different cells. This is called the partialvolume problem. In general, the low S/N per pixel inimaging (typically in the order of 10–50) does not allowmulti-exponential fitting, which might provide a way toresolve subcellular information. Such information isavailable from non-spatially resolved NMR measure-ments, with a much higher S/N (1000 or higher).Therefore the information presented in images mostly iscalled ‘apparent’: e.g. apparent T2, T2,app, or apparent D,Dapp. In images, the S/N can be enhanced by summingup the signal of pixels containing identical information(same tissue). In this way subcellular information of thattissue can be obtained (Scheenen et al., 2002).

T2, cell size, and (tonoplast) membranepermeability

Membrane permeability in plant cells (as well as in manyother systems, for example, red blood cells (Regan andKuchel, 2000, 2002)) has been determined using theNMR relaxation times of intracellular water protons basedon the Conlon–Outhred technique (Conlon and Outhred,1972; Stout et al., 1978; Ratkovic and Bacic, 1980; Snaarand Van As, 1992; Zhang and Jones, 1996; Donker et al.,1999). The disadvantage of this technique is that it needsthe introduction of paramagnetic ions (such as Mn2+,which can pass membranes, or other MRI contrast agentsthat cannot pass membranes) in high, non-physiologicalconcentrations. A non-invasive approach is based on theprinciple that the observed transverse relaxation time T2 ofwater in a confined compartment such as a vacuole can bedescribed as a function of the bulk T2, T2,bulk, of the waterand the probability that water molecules reach the mem-brane and lose magnetization at the membrane, eitherby a direct interaction with the membrane (acting as a sinkfor relaxation) or by passing the membrane and enteringa compartment with a (much) shorter relaxation time(Brownstein and Tarr, 1979; van der Weerd et al., 2001).The probability to reach the membrane is defined by thediffusion time and thus directly related to the compart-ment radii. No evidence has been found that membranesthemselves act as a relaxation sink (McCain, 1995; vander Weerd et al., 2002a). The net loss of magnetizationin a vacuole therefore depends on the membrane waterpermeability of the tonoplast and the effective relaxationin the cytoplasm (van der Weerd et al., 2002b; L van derWeerd, JEM Snaar, FJ Vergelt, H Van As, unpublisheddata). As a result the observed relaxation time depends,in addition to T2,bulk, to the radii of the compartmentalong the x, y, and z directions (Rx,y,z) and the netloss of magnetism at the compartment boundary, the

4 of 14 Van As

so-called magnetization sink strength (H) (van der Weerdet al., 2001):

1

T2;obs¼ H

ðRx þ Ry þ RzÞþ 1

T2;bulkð1Þ

H is linearly related to the actual membrane permeabil-ity (van der Weerd et al., 2002b; L van der Weerd, JEMSnaar, FJ Vergelt, H Van As, unpublished data). A simplecommon-sense approach is sufficient to explain the effectof compartment properties on relaxation. The intermem-brane distances (R) and the bulk diffusion coefficients (D)determine the average diffusion time of a water moleculeto cross a compartment (tdif¼R2/(2D)). The relaxation rateT�12;bulk in that compartment determines the chance that the

molecule still bears magnetization once it reaches themembrane. If that is the case (2D/R2)< T�1

2;bulk, the mem-brane permeability determines the exchange rate to thenext compartment, and thereby influences the relaxationrate; if the above condition does not apply, the membranepermeability is of no consequence for the NMR signal andequation 1 does not hold.An example of this relation based on MRI results is

shown in Fig. 2 for cells in the apex zone of the stem ofintact maize and pearl millet plants. In intact pearl milletplants, H in cells in this zone has been shown to changeduring osmotic stress experiments, in contrast to the samecells in maize plants where no changes were observed(van der Weerd et al., 2001, 2002a), pointing to a responseto stress most probably related to changes in aquaporinfunctioning.Some care must be taken into account by using T2,obs

from images. The observed T2 value in images withrespect to its value in non-imaging NMR depends on

a number of contributions that relates to details of theimage experiment and plant tissue characteristics (Rofeet al., 1995; Edzes et al., 1998):

1

T2;obs¼ 1

T2þ 1

Ti2

þ 1

Tii2

ð2Þ

Here T2 represents the original T2 of the liquid in thetissue, which is also observed in non-imaging mode ex-periments. Ti

2 and Tii2 originate from diffusion effects.

In plants, especially in leaves and woody tissue, smallair spaces in the order of a few lm up to 100 lm arepresent. Due to the difference in the magnetic permeabil-ity of air and tissue/water, local magnetic field gradients,gz, originate. Displacement through these local gradientsdue to diffusion results in a reduction of the observedT2 value:

1

Ti2

}c2Æg2zæTE2D ð3Þ

Here c is the gyromagnetic ratio, which is a constant foreach type of nuclear spin. D is the (self-)diffusion co-efficient of water in the tissue. The strength of these fieldinhomogeneities is proportional to the applied magneticfield (Ludecke et al., 1985). Minimizing this effect can beachieved by imaging at relatively low magnetic fieldstrength, B0, and at short TE values (Donker et al., 1996,1997, 1999). In non-spatially resolved T2 measurementsthis TE value can be chosen to be very short (in the orderof 200–400 ls) whereas in imaging mode TE is in theorder of a few ms or longer.In addition to the effect of local field gradients,

diffusion through the repeatedly applied position encodingmagnetic field gradients contributes to the observedrelaxation time:

1

Tii2

¼ c2G2d2�1� 4d

3TE

�D ð4Þ

Here 2d is the duration of the applied gradient. Inpractice, G and d are dictated by the choice of pixelresolution, image size, and actual TE. To image relaxationtimes in the order of 1 s, as a rule of thumb a lower limitof 100 lm for the pixel size for objects of 1–2 cmdiameter can be used (Edzes et al., 1998). At smaller pixelsizes the diffusive attenuation in the position-encodinggradient becomes the leading contribution to the observedtransverse relaxation time, and the information availablefrom the actual T2 is lost and mixed up with (restricted)diffusion information and equation 1 no longer holds.From equation 1 it is clear that, for a proper inter-

pretation of T2 measurements in terms of membranepermeability, it is necessary to know the cell dimensions,or more precisely the dimensions of the vacuole. Thisinformation can be obtained by NMR as well by

Fig. 2. Relation between the relaxation time T2 as observed by MRIand the cell dimensions for maize (filled triangles) and pearl millet(filled diamonds) cells of different internodes of the apex zone of thestem. Following the MRI measurements on the intact plants, the sameplants were used for microscopic sections to determine the celldimensions. After van der Weerd et al., 2001 (van der Weerd L,Claessens MMAE, Efde C, Van As H. 2002. Nuclear MagneticResonance imaging of membrane permeability changes in plants duringosmotic stress. Plant, Cell and Environment 25, 1538–1549) andreproduced by kind permission of Blackwell Publishing.

MRI and water transport in plants 5 of 14

(restricted) diffusion measurements, which, in addition,gives access to membrane permeability of water overlonger distances, resulting in cell-to-cell transport.

Diffusion, restricted diffusion, cell (compartment)dimension and cell-to-cell transport

All molecules in a fluid are subject to Brownian motion.The extent of this motion depends on the temperature andthe viscosity of the fluid, which are incorporated in thebulk diffusion coefficient of the fluid. When an ensembleof molecules is followed in time, the root mean squaredistance travelled, r, increases with time as long as noboundaries are encountered, according to the Einsteinrelation:

r ¼ffiffiffiffiffiffiffiffi2Dt

pð5Þ

D can be measured by NMR using a so-called pulsed fieldgradient (PFG) experiment. In this experiment a sequenceof two magnetic field gradient pulses of duration d andequal magnitude G but opposite sign (or equal sign butseparated by an inverting rf pulse) label the protons asa function of their position. If the spins remain at exactlythe same position the effect of the gradient pulses com-pensate each other. However, as soon as translational(displacement) motion occurs, the gradients do not exactlycompensate each other any more, resulting in attenuationof the signal amplitude. The amount of this attenuation isdetermined by d and G of the gradient pulses, and by themean translational distance travelled during the interval Dbetween the two pulses. The NMR-signal amplitude S(G)normalized to the signal amplitude S(0) at G¼0 for freediffusion at a given D is given by (Stejskal and Tanner,1965; Norris, 2001):

SðG;DÞSð0;DÞ ¼ exp

�� c2d2G2D

�D� d

3

��ð6Þ

By measuring S(G, D) as a function of G, D can beobtained. The distance travelled depends on the bulkdiffusion coefficient of the fluid in the compartment and D(equation 5 with t¼D). If water experiences a barrier todiffusion, for example, a cell membrane, the cell dimen-sions determine the maximum displacement (in case of animpermeable barrier) or to what extent it is hindered (semi-permeable membrane). For restricted diffusion equation 6no longer holds and becomes dependent on the geometryand size of the compartment and the permeability of thesurrounding membrane (Callaghan et al., 1999; Norris,2001; van der Weerd et al., 2002b; Regan and Kuchel,2000, 2002).To extract the information on size and membrane per-

meability, diffusion coefficients have to be measured asa function of the diffusion labelling time, or observation

time, D, the time between the two gradient pulses (fora tutorial on this subject see Sen, 2004). By varying D thedistance over which the spins can diffuse freely and towhat extend they can pass over the membrane, which re-stricts the diffusion process, are observed. The probabilityto pass the membrane is a direct measure of the waterpermeability of the surrounding membrane (Regan andKuchel, 2000). At longer values of D, water moleculescan even travel from cell to cell. An example ofa theoretical curve of D versus D for diffusion in a con-fined geometry is presented in Fig. 3 for a number ofdifferent values of the water membrane permeability. Inthe first region, at short diffusion times, free diffusion isobserved. In the next region the diffusion becomes re-stricted, but the averaging of local properties over a largeenough distance does not yet occur. In the last region, atlong diffusion times, hindered diffusion is observed,which is defined by the permeability of the system, andfor plants reflects cell-to-cell transport. The effective per-meability P can now be estimated. For diffusion througha geometry consisting of a series of semi-permeable mem-branes (thin walls) separated by a distance d, Crick (1970)obtained:

D�1inf ¼ D�1

0 þ ðPdÞ�1 ð7Þ

or

P ¼ ðDinfD0ÞðD0 � DinfÞd

ð8Þ

Dinf is the D value in the limit of D to infinity. If D0,Dinf, and d are known, P can be obtained. This is easilydone for D(D) information as presented in Fig. 3, whereDinf is reached. In practice, D(D) is obtained over a smaller

Fig. 3. Simulated behaviour of D(D) as a function of D in a systemwith a series of compartments separated by semi-permeable membranes(thin walls) at a distance of 10 lm, for different values of thepermeability coefficient P (in m s�1) of the membranes. For P¼0 fullyrestricted diffusion is observed. At increasing P values Dinf becomeshigher. Plot by courtesy of T Sibgatullin.

6 of 14 Van As

range of D values and a procedure is needed to extract thisinformation based on a limited range of D(D) values.In the limit of short D, D depends linearly on the square

root of the diffusion time. The slope of this dependence isdetermined by the surface-to-volume ratio (S/V) of thewater-containing compartment, irrespective of whetherthese compartments are connected or disconnected (Sen,2004), according to the equation

DðDÞD0

¼ 1� S

V

4

9ffiffiffip

pffiffiffiffiffiffiffiffiffiD0D

pð9Þ

For a sphere S/V¼3/R, where R is the radius of thesphere.In the limit of long diffusion time (D >>R2/D0) and fully

restricted diffusion (impermeable wall) the apparentdiffusion coefficient varies inversely with D according toEinstein’s equation

DðDÞ ¼ R2

2Dð10Þ

R can thus be obtained from the slope, the maximumvalue of r to be travelled in the confinement. However,semi-permeable membranes will result in deviations fromthis dependence (Fig. 3). If semi-permeable membranesare present D versus D curves can be described by thefollowing equation (Anisimov et al., 1998; Valiullin andSkirda, 2001)

DðDÞ ¼ Deff1ðDÞ�

D0 � Dinf

Deff1ðDÞ þ D0

�þ Dinf ð11Þ

where

Deff1ðDÞ ¼�

D0Deff2ðDÞD0 � Deff2ðDÞ

�ð12Þ

and

Deff2ðDÞ ¼�DðDÞ � Dinf

D0 � Dinf

�ð13Þ

An example of experimental data is given in Fig. 4.This figure also illustrates that the experimental range of Dvalues is limited by the relaxation times T2 and T1 andDinf is hard to obtain experimentally. Deff2(D) (equation13) behaves in much the same way as D(D) for the case ofa geometry enclosed by an impermeable membrane (cf.equation 10). The effect of the permeable wall is removedand it results in a good estimate of D0 at short D values(Fig. 4). However, due to the limited range of td thedependence D(D)~D�1 is not yet observed (Fig. 4, cir-cles). Rescaling according to equation 12 (Deff1) enlargesthe range of diffusion time (to the shorter D values) wherethe dependence according to equation 10 is observed. It isvery useful when the long diffusion times are unavailable

experimentally. As a result parameter R can be determined(cf. equation 10), and can be used to fit the experimentaldata D(D) versus D according to equation 11 resulting inD0 and Dinf. Alternatively, D0 can be estimated fromequation 9 at short D values, if experimentally available.P can now be calculated from D0, Dinf, and R (¼d, seeequation 8).P will include the permeability of the tonoplast,

plasmalemma, walls and plasmodesmata of neighbouringcells. At long observation times cell-to-cell transport be-comes visible. Therefore P is not identical to H asobtained from T2 measurements (equation 1). The valueof d as a result of the diffusion measurements can directlybe used to obtain H from the T2 measurements. A com-plication is the effect of the geometry of the confined com-partment. Equation 8 assumes plan-parallel membranes,which might be a good assumption for an array of cells inone dimension (the magnetic field gradient direction). Theresult of H from equation 1 depends on the actualgeometry of the compartment: for a sphere, the first termin equation 1 becomes 3H/R, for a cylindrical geometry itbecomes 2H/R. This problem can be overcome bymeasuring D in different directions, which is possible byapplying magnetic field gradients in different directions.Some first results are now available. By combining the

results of T2 and D measurements on water in appleparenchyma (Granny Smith) H was found to be around1310�5 m s�1 (T2,obs¼1.25 s and R¼86 lm). Under theassumption of parallel planes P¼2.9310�6 m s�1 (TASibgatullin, PA de Jager, FJ Vergeldt, AV Anisimov,E Gerkema, H Van As, unpublished results). For Coxapple parenchyma cells a tonoplast water membranepermeability of Pd¼2.44310�5 m s�1 was reported (Snaarand Van As, 1992) based on the Conlon–Outhred method.

Fig. 4. Experimental D(D) as a function of D as observed in rootsegments of maize plants. (Filled squares with open centre): Experi-mental D values; filled triangles, Deff1 (equation 12), from which R isobtained (dotted line); filled circles, Deff2 (equation 13), resulting in D0.A fit to the experimental data according to equation 11 (solid line)results in Dinf, in addition to D0 and R. This information is used tocalculate P (equation 8). Plot by courtesy of T Sibgatullin.

MRI and water transport in plants 7 of 14

In maize roots, Anisimov et al. (1998) found a highervalue of P: around 5310�5 m s�1. Recently values wereobtained of P in excised roots of normal and osmoticallystressed maize and pearl millet plants: P was found to bearound 3310�5 m s�1 for both normal and stressed maize,whereas P was around 9310�5 m s�1 for normal pearlmillet plants and 3310�5 m s�1 for stressed plants (TASibgatullin and H Van As, unpublished results). Ionenkoet al. (2006) recently reported P values for water in rootsof maize seedlings of 3310�5 m s�1, which decreased bya factor of 1.7 due to water stress or HgCl2 treatment. Thelatter clearly demonstrates the contribution of aquaporinfunctioning in P. Up to now H was found to be higherthan P, as expected.By time-dependent diffusion coefficient measurements

combined with MRI the size and the membrane perme-ability of, for example, the vacuoles in vacuolated planttissue have been measured, even spatially resolved withinsingle pixels of an image (TA Sibgatullin, FJ Vergeldt,E Gerkema, H Van As, unpublished results).As stated above, in imaging, Dapp is normally observed.

In tissue with (large) vacuolated cells Dapp will mainlyreflect D of vacuolar water. In other tissue it can becomemore complex (van der Toorn et al., 2000). Correlateddiffusion-T2 measurements have been developed thatallow unambiguously to relate D and T2 values ofdifferent water-containing cell compartments, even withinsingle pixels in images.

Correlated diffusion-T2 measurements

Water in different cell compartments can best be discrim-inated on the basis of the differences in relaxationbehaviour (T2) and (restricted) diffusion behaviour. Bycombined relaxation and diffusion measurements, togetherwith a recently developed efficient and stable two-dimensional fitting procedure based on a Fast LaplaceInversion algorithm (Venkataramanan et al., 2002;Hurlimann et al., 2002), two-dimensional correlation plotsbetween D and T2 can now be generated, which greatlyenhance the discrimination of different water pools insubcellular compartments. In this way, an unambiguouscorrelation between relaxation time and compartmentsize can be obtained, resulting in a general approach toquantify water in the different cell compartments. Thisapproach is very promising in non-spatially resolved mea-surements (Qiao et al., 2005), and has been shown toobtain sub-pixel information in images as well (VanDusschoten et al., 1996; for recent plant applications HVan As, FJ Vergeldt, CW Windt, unpublished data).

Flow, xylem and phloem hydraulics

The method that has been most successful in providingdetailed, non-invasive information on the characteristics of

water transport in the xylem, as well as in the phloem ofintact plants, is MRI [for overviews see MacFall and VanAs (1996) and Kockenberger (2001)]. Both non-imagingand imaging methods have been developed and applied toplants. Several groups have used different MRI methods.Most of them are based on (modified) Pulsed FieldGradient (PFG) methods, either by using a limited numberof PFG steps or by (difference) propagator approaches(Callaghan et al., 1994b, see below). Also flow measure-ments based on uptake and transport of (paramagnetic)tracers have been used (Link and Seelig, 1990; Clearwaterand Clark, 2003).The first (non-imaging) method to measure xylem water

transport in plants was presented some 20 years ago (VanAs and Schaafsma, 1984; Reinders et al., 1988a, b;Schaafsma et al., 1992). Based on that method a (trans)portable NMR bioflowmeter has been developed witha U-shaped permanent magnet (open access from oneside) and an openable, hinged, rf coil. It has been used ingreenhouse situations on intact plants (Van As et al.,1994). By the applied method averaged linear flowvelocity and flux (volume flow) are obtained, and the ratioresults in the effective flow conducting area. However, tointerpret the data in terms of averaged flow velocity,calibration is needed: the results depend on the actual flowprofile. Flow in a single xylem vessel, in general, isassumed to be laminar, but velocities within the differentxylem vessels in a stem will be different, depending onvessel diameter. So the flow profile within the total cross-section of a stem is therefore not known a priori. Inaddition, xylem and phloem flow can not be discriminatedby that method, the sum of both is observed.To quantify xylem and phloem flow accurately, one

needs to determine both the direction of the flow, and theactual flow profile, from which the flow velocity, the flux,and the flow conducting area can be obtained. At the sametime, diffusing water molecules (stationary water in cells)and flow have to be discriminated. These goals can bestbe obtained by the use of PFG techniques. To quantify theunknown displacement-behaviour of an observed ensem-ble of spins correctly, one has to measure the NMR-signalS(G) as a function of G. By applying a Fourier Transformon S(G) as a function of G, the propagator P(R, D) isobtained (cf. Fig. 5). P(R, D) presents the probability thata spin at any initial position is displaced by a distance R intime D. For flow, dividing the displacement axis R by Dresults in the flow profile P(v). This type of measurementis referred to as displacement or propagator imaging andhas been applied to measure flow in many porous systems,including plants (for some introductions and reviews seeCallaghan et al., 1999; Fukushima, 1999; Mantle andSedesman, 2003; Stapf and Han, 2005).The propagator for free, unhindered, diffusing water

has a Gaussian shape, centred around R¼0 (Fig. 5). Theroot mean square displacement, r, of diffusing protons,

8 of 14 Van As

observed by NMR, is proportional to the root of D timesD (equation 5). r is directly related to the width of theGaussian distribution (Fig. 5). By contrast, the meandisplacement r of flowing protons is linearly proportionalto D itself:

r ¼ mavD ð14Þ

where vav is the average flow velocity of the flowingprotons. The labelling time between the two PFGs has tobe long (in the order of 150 ms or longer) to discriminatebetween slow (phloem) flow and diffusion (D in the orderof 2310�9 m2 s�1) (Scheenen et al., 2001). At lowervelocities D has to be increased further (Fig. 5).A crucial step in the quantification of the flow is to

discriminate stationary and flowing water. The fact thatthe propagator for stationary water is symmetrical aroundzero is used to separate the stationary from the flowingwater. The signal in the non-flow direction is mirroredaround zero displacement and subtracted from the signalin the flow direction, to produce the displacement dis-tribution of the flowing and the stationary water. Becausethe signal amplitude is proportional to the density of themobile protons, the integral of the propagator providesa measure for the amount of water. The average velocityof the flowing water is then calculated by taking theamplitude weighted average of the velocity distribution.The volume flow rate or flux is calculated by taking theintegral of amplitude times displacement of the velocitydistribution. Using this approach, for each pixel in theimage the following flow characteristics are extracted ina model-free fashion, as described by Scheenen et al.(2000): total amount of water, amount of stationary water,amount of flowing water (or flow conducting area),average linear velocity (including the direction of flow),and volume flow per pixel. A propagator flow imagingmethod was developed that allowed the flow profile ofevery pixel in an image to be recorded quantitatively, with

a relatively high spatial resolution, while keeping measure-ment times down to 15–30 min (Scheenen et al., 2000,2001, 2002).Phloem transport in plants is particularly difficult to

measure quantitatively. The slow flow velocities and thevery small flowing volumes in the presence of largeamounts of stationary water make it difficult to distinguishthe slowly flowing phloem sap from freely diffusingwater. Windt et al. (2006) further optimized the propagator-fast imaging method to measure quantitatively, for thefirst time, detailed flow profiles of phloem flow in largeand fully developed plants. An example of xylem andphloem flow imaging in stem of a Ricinus plant is shownin Fig. 6. In this way the dynamics in phloem and xylemflow and flow conducting area were studied. The observeddifferences for day and night in flow conducting area,which directly relate to xylem and phloem hydraulics, areone of the most striking observations (Windt et al., 2006),which demonstrates the potential of the method to studyhydraulics in intact plants under normal and stress con-ditions. In addition, the phloem-to-xylem flux ratio reflectsthe fraction of xylem water that is used for phloemtransport, also known as Munch’s counter flow. This ratiowas surprisingly large at night (hardly any evaporation)for poplar (0.19), castor bean (0.37), and tobacco (0.55),but low in tomato (0.04) (Windt et al., 2006).

Hardware considerations

In many cases dedicated hardware is required in order toimage intact plants. Normally, only small parts of theplant (e.g. stem, a leaf, petioles, seed pots, fruit stalk, etc)will be chosen for study. If so, an optimal signal-to-noiseratio, S/N, is obtained by optimizing the radius of the rfcoil, r, with respect to that part of the plant to be meas-ured. The smaller r, the higher S/N. The best approach isto construct rf detector coils that closely fit that part of the

Fig. 5. Simulated propagators for a system consisting of 75% stationary water and 25% flowing water, with a laminar flow profile. D is 2.2310�9 m2

s�1. The mean linear average flow velocity is 0.2 mm s�1 (typical for phloem). (a) D¼15 ms (r¼8.1 lm, r¼3.0 lm); (b) D¼100 ms (r¼21 lm,r¼20 lm); (c) D¼1000 ms (r¼66 lm, r¼200 lm). The arrow indicates the signal of the flowing water, that emerges from the Gaussian shapedsignal centred on R¼0 of diffusing water. Reprinted from Scheenen TWJ, Vergeldt FJ, Windt CW, de Jager PA, Van As H. Microscopic imaging ofslow flow and diffusion: a pulsed field gradient stimulated echo sequence combined with turbo spin echo imaging. Journal of Magnetic Resonance151, 94–100, copyright 2001, with kind permission from Elsevier.

MRI and water transport in plants 9 of 14

plant or tree to be imaged (Scheenen et al., 2002, Windtet al., 2006).Also, when the distance between the magnetic field

gradient coils is made smaller, higher gradient strengthscan be obtained. This is important to obtain a high spatialresolution, fast switching of gradients, and to measure lowflow velocities: small displacements require a high Gvalue to be detected.Another way to increase S/N is to use higher field

strength, B0. However, for plant tissues with extracellularair spaces, this results in increased susceptibility artefacts,as discussed above. These artefacts can be overcome byincreasing maximum imaging gradients, but this wouldresult in a decrease in S/N and loss of T2 information (seeequations 3 and 4). At higher B0 the effective (and bulk)T2 is (much) shorter than at lower field strength, limitingthe number of measurable images during the signal decay,and resulting in a lower sensitivity to extract the per-meability information form T2 measurements (equation 1).Some hardware solutions for intact plant NMR and

MRI are presented in Figs 7 and 8. In Fig. 7a and b a lowfield (0.7 T) imaging system based on an open accesselectromagnet is shown. A comparable (permanent)magnet has been used by Utsuzawa et al. (2005) to studyxylem cavitation due to pine wilt disease. On top of themagnet a climate chamber for environmental control isplaced (Fig. 7b). Maximal access into the centre of themagnet is obtained by use of plan parallel gradient plates

(Fig. 7a). To maximize the filling factor a (solenoid) rfcoil is wrapped directly around the stem of the plants. Asolenoid coil results in about a factor 2 to 3 moresensitivity than Helmholtz or birdcage coils of the samediameter. This configuration allowed large plants, up to asize of two metres, to be placed upright easily in the NMR

Fig. 7. Magnet (a) and climate control unit on top of magnet (b) ofa 0.7 T imager based on an electromagnet. The two plan parallelgradient coils plates on top of the poles of the magnet (one is seen asa dark plate in the centre of the magnet, see arrow) results in maximumaccess to the centre of the magnet (a).

Fig. 6. Quantitative NMR flow images of xylem water moving upwards through the hypocotyl of Ricinus communis (a)–(d), and phloem watermoving downwards to the roots (e)–(h). Shown are the volume of stationary water per pixel (a, e), the flow conducting area per pixel (b, f), theaverage linear velocity per pixel (c, g), and the average volume flow per pixel (d, h). The xylem flow images were calculated from a single flowimaging measurement; the phloem flow images were constructed from seven consecutive individual flow imaging measurements. The differences inthe amounts of water per pixel shown in (a) and (e) are due to differences in image matrix size (1283128 versus 64364), slice thickness (3 mmversus 6 mm) and scaling. After Peuke et al., 2006 (Peuke AD, Windt C, Van As H. 2006. Effects of cold-girdling on flows in the transport phloemin Ricinus communis: is mass flow inhibited? Plant, Cell and Environment 25, 15–25) and reproduced by kind permission of Blackwell Publishing.

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magnet. Placement of plants can be undertaken withoutcausing much stress to the subject, other than the stressthat is caused by moving and handling it. Potentiallystressful actions like mounting an rf coil or, when nec-essary, the removal of a branch or leaf, can be undertakenwell in advance.In Fig. 8 part of a dedicated intact plant 3 T MRI sys-

tem is shown. The superconducting magnet has a 50 cmvertical free bore (Fig. 8a). One of the gradient coils isable to be opened. It consists of four parts and can easilybe mounted around the stem of a plant or trunk of a tree(Fig. 8b, c). An rf coil (4 cm inner diameter) that consistsof two parts completes the fully openable construction.Inside the bore of the magnet the climate is controlled byuse of a remote climate control unit. This 3 T MRI systemprovides an excellent and unique infrastructure for MRIon intact plants and trees.

Future of functional plant MRI

The combination of dedicated NMR/MRI equipment andT2, diffusion and propagator flow MRI methods is nowavailable to measure and quantify cell, tissue, phloem andxylem hydraulics routinely in intact plants up to a size ofseveral metres and over periods of weeks. Plant responsesin hydraulics and water content of the different tissues cannow be studied as a function of changes in environmentalconditions. The method has already been applied to studyday–night rhythms in flow and flow conducting area in thestem of large potted plants (Windt et al., 2006), dynamicsin phloem in response to stem cold girdling (Peuke et al.,2006), root cooling (inducing xylem air embolism, followrefilling and functionality of xylem; Scheenen, 2001), rootanoxia and long dark periods, and the flow (and changestherein) in the stalk of a tomato truss during a 5-weekperiod of fruit development (CW Windt et al., un-published results). Flow MRI has been proven to be

quantitative in terms of volume flow. The additionalinformation on effective flow conductive area is totallynew. First results demonstrate surprising, unexpected dy-namics in this parameter (Windt et al., 2006) which mayresult in a better understanding of the mechanism andregulation of long-distance transport. This information isvery difficult to measure, or cannot be measured at all, inintact plants using other techniques. Flow MRI can be ofhelp in understanding the results obtained by heat pulsemethods, which are routinely used in field situations. Firstcomparisons between flow MRI and (modified) heat pulsemethods have very recently been made in our laboratory.Clearly, flow MRI teaches us some striking lessons aboutsap flow of importance for the interpretation of othermethods, improving their reliability.By contrast to the measurement of long-distance trans-

port (xylem and phloem), MRI methods to study hydrau-lics on the membrane and tissue level based on diffusionmeasurements have not yet been demonstrated to be quan-titative. First results indicate that MRI can at least be usedto monitor changes in hydraulics within a single plant andthat these MRI methods are sensitive for aquaporinfunctioning. All tissues, independent of position, are acces-sible by MRI, in contrast to, for example, the pressureprobe technique. At the moment it has to be demonstratedthat both Pd and Pf can be obtained by MRI. In the nextstep it would be necessary to corroborate MRI results byresults obtained by more established and quantitativemethods for hydraulic conductivity, for example, by high-pressure flow meter or by cell pressure probe. For thispurpose, the development of MRI image guided cellpressure probe measurements will be of great interest, aswell as combining pressure bomb or high pressure flowmeter and MRI.Functional intact plant imaging by MRI offers exciting

new possibilities for the non-invasive physiologicalmapping of intact plants. Functional MRI is expected to

Fig. 8. (a) 50 cm diameter vertical free bore of the superconducting-magnet of an intact plant 3 T MRI system. Within this bore air temperature,humidity and gas composition and light intensity can be varied and controlled. (b, c) Gradient coil system consisting of four half-cylindrical parts thatcan be opened from one side (b), allowing the insertion of a plant. The closed gradient system containing the plant and placed on top of a supportsystem (c) has to be inserted in the 50 cm bore of the magnet (a).

MRI and water transport in plants 11 of 14

become a powerful tool to characterize functionality ofaquaporins to be studied. In this way it will contribute toresolve the role of aquaporins in plant water balance,hydraulics and stress tolerance (Verkman, 2000; Javot andMaurel, 2002; Tyerman et al., 2002; Tournaire-Rouxet al., 2003; Lee et al., 2005). Over-expression plants,knock-out plants or anti-sense plants show differentaquaporin gene expression patterns compared with wild-type plants and may be of great help in understanding therelationship between aquaporin gene expression andfunction. NMR imaging can elucidate in vivo gene func-tionality in tissue hydraulics at different levels and therebybridge the gap between gene expression and function.Currently MRI in plant science is still far from being

a routine tool. Some reasons for this could be the high costsof MRI equipment, the difficult theoretical fundamentalson which the technique is based, the horizontal orientationof most of the standard imaging set-ups, the limited acces-sibility (for large plants) of the magnetic field’s iso-centreof most set-ups, and the specific (climatic) requirementswhich have to be met when measuring intact plants. It is tobe expected, however, that relatively cheap imaging set-ups based on permanent magnet systems will soon becomeavailable (Rokitta et al., 2000; Haishi et al., 2001).For NMR flow and hydraulic measurements to be

applicable in situ (greenhouses, field situations), quantita-tive non-spatially resolved (non-imaging) methods withspecifically designed magnets are being developed. Thebasic principles and components are now available to de-velop (reasonably priced) NMR plant flow-meters, as arespecially designed magnets (Raich and Blumler, 2004).We can also think about small NMR or MRI detectors bymaking use of rather small magnets, as presented byBlumich and others (Blumich et al., 2002).

Acknowledgements

The research described in part herein was supported by the DutchTechnology Foundation (STW), Applied Science Division of theNetherlands Organization for Scientific Research (NWO) (projectsWAW07.0068, WBI 3493, and WBI 4803). The funding of thededicated intact plant 3 T MRI facility of Wageningen NMR Centreby NWO, the Dutch Ministry of Agriculture, Nature and FoodQuality (LNV), and the Wageningen University and ResearchCentre is greatly acknowledged. I acknowledge the contributionsand many stimulating discussions on the research topics presentedin this overview by my colleagues and coworkers Carel Windt,Timur Sibgatullin, Frank Vergeldt, Edo Gerkema, Tom Scheenen,and Louise van der Weerd. Financial support of the EU Trans-national Access to Research Infrastructure programs starting from1994 has stimulated Trans-European co-operation on this research.

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