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Journal of Cereal Science 52 (2010) 303e309

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Journal of Cereal Science

journal homepage: www.elsevier .com/locate/ jcs

Development of wheat kernels with contrasting endosperm texturecharacteristics as determined by magnetic resonance imaging and timedomain-nuclear magnetic resonance

Cecilia Castro a,1, Laura Gazza b, Roberto Ciccoritti a, Norberto Pogna b, Cesare Oliviero Rossi c,Cesare Manetti a,*aDipartimento di Chimica, Universitá degli Studi di Roma “La Sapienza”, Piazzale Aldo Moro 5, Roma 00185, ItalybCRA-QCE, Via Cassia 176, Roma, ItalycDipartimento di Chimica, Università della Calabria, Cubo 12C Via P. Bucci, Arcavacata di Rende (CS), Italy

a r t i c l e i n f o

Article history:Received 5 January 2010Received in revised form17 June 2010Accepted 21 June 2010

Keywords:TD-NMRMRIMulti-way analysisTexture characteristicsWheat

Abbreviations: MRI, Magnetic Resonance ImaginNuclear Magnetic Resonance.* Corresponding author. Tel.: þ39 06 49913058; fax

E-mail address: c.manetti@caspur.it (C. Manetti).1 Present address: Department of Biochemistry, Un

bridge, UK.

0733-5210/$ e see front matter � 2010 Elsevier Ltd.doi:10.1016/j.jcs.2010.06.012

a b s t r a c t

Spikes and seeds from diploid ‘einkorn’ wheat Triticum monococcum and two near-isogenic hard and softcommon wheat (Triticum aestivum) lines were harvested at regular intervals from 7 days post-anthesis(dpa) and analysed by non-destructive magnetic resonance imaging (MRI) and time domain-nuclearmagnetic resonance (TD-NMR). A large amount of free water occurred in rachises, glumes and awns ofspikes collected at 7 dpa, and accumulated in the physiologically active cells of the endosperm at 21 dpa.In the final stages of kernel development, awns and seed embryos exhibited a high MR signal due to thepresence of free water likely associated with biological activities. TD-NMR relaxation time distributionsobtained by discrete exponential fitting, distributed exponential fitting and SLICING multivariate analysisoffered detailed information on mobility behaviour of water molecules in developing seeds and wereable to differentiate two soft and hard isolines from common wheat cv. Enesco at early stages of seeddevelopment.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

In the last decades, cereals have been investigated by emergingtechniques belonging to complementary fields such as genomics(Xu et al., 2005), proteomics (Skylas et al., 2005), and metabolomics(Castro and Manetti, 2007; Castro et al., 2008; Cho et al., 2008;Winning et al., 2009).

During the last 30 years, magnetic resonance imaging (MRI)asserted itself in human diagnostics and gained increasing impor-tance in many scientific areas to reveal sample characteristicsunavailable by traditional invasive techniques. In plant physiology,MRI was applied to investigate caryopsis development (Glidewell,2006; Horigane et al., 2001; Ruan et al., 1999), dormancy

g; TD-NMR, Time Domain-

: þ39 06 4455278.

iversity of Cambridge, Cam-

All rights reserved.

(Himmelsbach and Gamble, 1996), cooking (Horigane et al., 1999;Horigane et al., 2000; Takeuchi et al., 1997) as well as sugardistribution (Ishida et al., 1996) in rice (Oryza sativa), wheat (Triti-cum spp.) or barley (Hordeum vulgare).

Time domain-nuclear magnetic resonance (TD-NMR) has beenapplied to simultaneously determine oil, water and proteincontents in oilseeds and oilseed residues (AOCS, 1995; ISO, 1993;Todt et al., 2006; Pedersen et al., 2000). Furthermore, TD-NMR hasbeen extensively used to investigate molecular mobility in bananaand wheat starch (Thygesen et al., 2003; Choi and Kerr, 2003).

In this work, developing spikes of common wheat (Triticumaestivum L.) and ‘monococcum’ wheat (Triticum monococcum sspmonococcum) have been analysed by MRI from anthesis to matu-rity. Kernels were removed from the developing spikes and ana-lysed by TD-NMR. In particular, kernels of biotypes ES and EH ofcommon wheat cv. Enesco have been compared for their NMRspectra. ES (Enesco Soft, with soft kernels) and EH (Enesco Hard,with hard kernels) are two near-isogenic lines indistinguishablefrom each other in their morpho-physiological traits except kerneltexture (Gazza et al., 2004). Kernel texture is a main determinant offlour quality because it strongly affects flour yield, starch granule

Fig. 1. (a) Longitudinal section of commonwheat ears at 7 dpa; (b) cross-section of commonwheat ears at 7 dpa; (c) longitudinal sections of einkorn ears at 7 dpa; (d) cross-sectionof einkorn ears at 7 dpa; (e) longitudinal section of einkorn ears at 21 dpa; (f) longitudinal section of common wheat ears at 60 dpa; (g) longitudinal section of common wheat earsat 60 dpa; and (h) longitudinal section of einkorn ears at 60 dpa. The arrows indicate the position of embryos, while the arrow heads indicate awns.

C. Castro et al. / Journal of Cereal Science 52 (2010) 303e309304

integrity and viscoelastic properties of wheat dough (Pomeranzand Williams, 1990; Morris, 2002).

2. Materials and methods

2.1. Plant material

‘Monococcum’ wheat accession SAL 98-38 and biotypes ES andEH from common wheat cv. Enesco were grown in 2008 at Mon-telibretti (Rome, Italy) in 10 m2 plots with three replicationsaccording to the standard agronomical procedures. Developingspikes of each wheat genotype were removed from the threereplicated plots to the laboratory at 7, 14, 21, 28, 35, 42 and 60 dayspost-anthesis (dpa) and analysed immediately by MRI. Kernelsfrom these spikes were then analysed by LF-NMR.

2.2. MRI measurements

MRI experiments were performed on a Bruker Avance 300wide-bore spectrometer equipped with a standard microimaging probe,operating at a proton resonance frequency of 300 MHz. Themaximum gradient strength in the x, y, and z directions was 100 G/cm. The gradient coils were actively shielded. The proton signal,acquired with a 25 mm (inner diameter) radio frequency bird-cagecoil, was processed and reconstructed by an image processingsoftware (Paravision, Bruker Analytiche Messtechnik GmbH,Germany).

The MR images were acquired by gradient echo (GEFI) and spin-echo techniques (MSME). Field of view was 20� 20 mm witha matrix 128� 128 and slice thickness was 1.0 mm. These param-eters are related to the image resolution and voxel (volumeelement) dimension.

T2 (T2WIs) (MSME) and T2* (T2*WIs) (GEFI) weighted imageswere acquired onwheat ears at seven developmental stages duringthe grain-filling period. All experiments were performed at thetemperature of 25 �C.

2.3. TD-NMR measurements

The TD-NMR relaxation measurements in developing kernelswere performed on a MiniSpec NMS120 Pulse NMR Spectrometer(Bruker BioSpin), with a proton resonance frequency of 20 MHz.Measurements were performed at 25.0� 0.1 �C. Transverse relax-ation, T2, was measured using the CarrePurcelleMeiboomeGillsequence (CPMG) (Meiboom and Gill, 1958):

90�x �

hs�

�180

�y � 2s

�k�180

�y � s� acq

in

The T2 measurements were performed with a s value of 0.05 ms.The repetition time between consecutive scans was 15 s. Data from4000 echoes were acquired and 128 experiments were accumu-lated in the absence of signal saturation.

Each sample (10e15 kernels) was placed in a 1 cm sample tubeand maintained for 15 min before analysis. De-hulled grains of‘monococcum’ wheat were used. Two samples for each genotype/stage of maturation were analysed.

2.4. Analysis of TD-NMR data

The NMR data were analysed by distributed exponential fittingand SLICING.

2.4.1. Distributed exponential fittingThis analysis was performed by the CONTIN algorithm

(Provencher, 1982), a widely applied method to analyse NMR data.

7 dpa

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Fig. 2. Relaxation curves obtained for ES (in black) and “monococcum” wheat (in gray)at 7, 21 and 42 dpa. (a.u.: arbitrary units).

C. Castro et al. / Journal of Cereal Science 52 (2010) 303e309 305

This is a general-purposeprogram for inverting noisy linear algebraicand integral equationsbymeansof inverse Laplace transform, suchas

yðtkÞ ¼Zb

a

Gðtk;sÞsðsÞdsþ bi

where s(s) is the unknown function to be solved, y(tk) is the knownfunction or the measurable relationship, and G(s, tk) is a known

kernel function depending on the physical meaning of the specificquestion, and bi is a constant term. This analysis resulted in a plot ofrelaxation amplitude for individual relaxation processes versusrelaxation time.

2.4.2. SLICINGThis multi-way generalization of principal component analysis

(Pedersen et al., 2002) was used to obtain the optimal dimensionreduction of data, implemented on the particular version Power-Slicing (Engelsen and Bro, 2003). Applying this method to a datasetformed by the relaxation curves acquired at all the developingstages it is possible to follow the evolution of the system throughtime.

3. Results and discussion

3.1. Magnetic resonance imaging (MRI)

Regional differences in physical, chemical and structural prop-erties of a developing wheat ear analysed by MRI resulted in ananatomical gray-scale image due to variation in proton density,proton self-diffusion, T1 and T2.

Depending upon the MRI pulse sequence employed in moni-toring the proton signal, the intensity of pixel images can bedirectly proportional to the proton content or, alternatively,‘weighted’ for the local transverse relaxation times T2, GEFI andMSME experiments, respectively (Bernstein et al., 2004). In GEFImeasurements the acquired echoes for reconstructing the imagesare generated only by gradient pulses, while in MSME experimentsthe echoes arise from a spin-echo based pulse sequence. Morpho-logical details of the sample can be revealed with both classes ofmeasurements, while spin relaxation information can be deter-mined only with MSME experiments.

Because of the predominant role played by water protons, MRIproduced the map water distribution or of water organization inthe different living tissues of a wheat spike.

In the T2*WIs (GEFI), the signal intensity in the different areas ofthe sample is directly proportional only to the water moleculecontent, i.e. spin density, whilst in the T2WIs, the ear regions withhigh water proton mobility appeared as bright areas in the MRimage, whereas those with slowly re-orientating water moleculesproduced dark voxels (volume elements).

The T2* weighted anatomical images of both common and“monococcum” wheat samples revealed that a large amount ofwater in ears collected at 7 dpa occurred in rachises, glumes, awnsand along the sieve tubes in the vascular bundles (Fig. 1aed). Therewas a remarkable change in the water distribution map in ears atthe middle stage of growth (21 dpa). A large amount of wateraccumulated in the physiologically active cells in the endosperm,whereas water bound to stored materials appeared as dark areas inthe internal part of the endosperm (Fig. 1e). At 35 dpa, most of thewater was bound by stored materials in the dark endosperm,whereas the embryo region exhibited a high MR signal due to thepresence of water likely associated with biological activity (Fig. 1fand g). Interestingly, free water was also detected in awns, whichlikely maintained physiological connections with seeds until thefinal stage of maturation (Fig. 1h). The present finding is in accor-dance with early MR images of developing barley grains by Kanoet al. (1990) and Glidewell (2006). In this context it is noteworthythat wheat awns were found to increase plant water-use efficiencyand grain yield under moderate and severe droughts (Evans et al.,1972; Foulkes et al., 2007). Moreover, transpiration ratio (carbonexchange rate/transpiration) in awns of hexaploidwheat, tetraploidwheat and barley was shown to be higher by several orders ofmagnitude than that of glumes and flag leaves (Blum,1985). Finally,

ES 7dpa

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Fig. 3. Distributed fitting obtained by Contin on relaxation curves of ES, monococcum and EH seeds at 7, 21 and 42 dpa. The straight line and the dotted line represent two samplesanalysed for each stage of development.

C. Castro et al. / Journal of Cereal Science 52 (2010) 303e309306

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Fig. 4. Representation in the space spanned by (A) Score 1 vs. Score 2; and (B) Score 2vs. Score 3 of seeds belonging to the genotype Monococcum at different stages ofdeveloping.

C. Castro et al. / Journal of Cereal Science 52 (2010) 303e309 307

soft-textured ES and hard-textured EH from common wheat cv.Enesco did not differ significantly from each other in the waterdistribution maps of their developing spikes (data not shown).

3.2. TD-NMR measurements

Localization of specific voxels by TD-NMR is hampered by thelow resolution of this technique. However, TD-NMR provideddetailed information on mobility behaviour of molecules such aswater, starch and lipid compounds in seeds, olives, nuts, chocolate,milk powder and cheese (Todt et al., 2001). The upper limit of watercontent for lipid determination by TD-NMR without pre-drying ofthe sample is about 15% (ISO, 1993) water content, far lower thanthat measured in the developing wheat kernels analysed here. Forthis reason, it was not possible to isolate the lipid contribution tothe signal.

The relaxation curves of the soft kernels of line ES were clearlydistinguishable from those of the soft kernels of “monococcum”

wheat at all the developmental stages during the grain-fillingperiod except complete maturity (60 dpa) (Fig. 2).

TD-NMR data obtained from developing kernels of ‘mono-coccum’ wheat and common wheat isolines ES and EH were ana-lysed by distributed exponential fitting and SLICING.

NMR datawere analysed by distributed exponential fitting usingthe CONTIN algorithm (Provencher, 1982), which takes into accountthe heterogeneity of the chemicalephysical characteristics of thedeveloping seeds and the distribution of disperse signal carriers.The bimodal response obtained in the plots meant that there weremainly two groups of water molecules in the samples: one hadstrong interactions with the other species (tightly bound water)and was characterised by shorter relaxation times, while the otherhad weak interactions (loosely boundwater) and was characterisedby longer relaxation times (Fig. 3). It was noted that there weresignificant differences in the mobile water/structured water ratio ateach stage of kernel development amongst the three genotypesunder analysis. Not only were the relaxation times important todifferentiate the behaviour of the three lines, the ratio betweenintensity of the component characterised by a long relaxation time(Fig. 3, arrow) and that of the component with a short relaxationtimewas found to decrease in the course of the grain-filling processin the threewheat genotypes analysed, suggesting that both looselybound water and tightly bound water increased during seeddevelopment.

The ratio between mobile protons and bound protons in eachkernel sample throughout the grain-filling period can be used asa descriptor of the developing trajectory. Therefore, the relaxationcurves obtained by TD-NMR measurement for the developingkernels of each genotype were collected in the same dataset andsubmitted to SLICING (Pedersen et al., 2002). According to thismethod of multi-way analysis, the relaxation curves describing themotion characteristics of the different water molecule ‘families’contained in the seed samples were projected in a space spannedby the loading curves and compared. SLICING has beenwidely usedto fit data characterized by common characteristic relaxation time(but individual amplitudes) for a set of samples (Povlsen et al.,2003; Andersen and Rinnan, 2002; Manetti et al., 2005). More-over, the method has been used to characterise the single relaxa-tion curve (Manetti et al., 2004; Andrade et al., 2007).

Fig. 4 shows the developing trajectories of ‘monococcum’

kernels in a space spanned by three coordinates (Scores 1, 2 and 3)corresponding to three proton families with distinct mobilities. Inparticular, contribution of the middle component (Score 2, Fig. 4A)was high from 7 dpa to 21 dpa and decreased afterwards, whereasthat of the shortest component (Score 1) increased from 7 dpa to35 dpa and came back to initial values in the final stages of seed

development. The longest component (Score 3, Fig. 4B), whichcorresponds to molecules with high mobility, was important at7e14 dpa and decreased afterwards as a consequence of theinteraction of water molecules with macromolecular compoundssuch as starch and proteins stored in the developing endosperm.

The developing trajectories of the three proton families in near-isogenic lines ES and EH (Fig. 5) followed the general trendobserved in ‘monococcum’ wheat.

Common wheat cultivars can be classified into three classesbased on kernel hardness as determined by the Single KernelCharacterization System (SKCS), i.e. soft (mean SKCSindex¼ 15e40), medium hard (55e70) and hard (71e95) (Coronaet al., 2001). Amongst the wheat cultivars grown in Italy, cv.Enesco was found to be quite unique in showing a bimodal distri-bution of its SKCS values because of the presence of two near-isogenic lines with contrasting endosperm texture characteristics(Gazza et al., 2004). In particular, ES is a soft line (average SKCSindex¼ 26) that accumulates relatively high amounts of pur-oindolines A and B on the starch granules in the developingendosperm, whereas EH is a hard-textured genotype (average SKCSindex¼ 82) that lacks puroindoline A and accumulates very lowamounts of puroindoline B. Puroindoline accumulation on starchgranules was found to be the casual factor for grain softness (Girouxand Morris, 1998; Corona et al., 2001).

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Fig. 5. Representation in the space spanned by (A) Score 1 vs. Score 2; and (B) Score 2vs. Score 3 of seeds belonging to the biotypes ES (in black) and EH (in gray) at differentstages of developing.

C. Castro et al. / Journal of Cereal Science 52 (2010) 303e309308

Differences in developing trajectories between ES and EH werevisible from as early as 7 dpa and persevered until 35 dpa. Duringthe first three weeks post-anthesis, there was a remarkablecontribution of themiddle component (Score 2) in line ES. Thus, therelaxation values of this genotype gathered together in a separatecluster with respect to those of line EH (Fig. 5A and B). In addition,at 28e35 dpa, contribution of the shortest component (Score 1) inline ES was high compared with that in line EH (Fig. 5A). Thesefindings suggest that variation in grain hardness in lines ES and EHis associated with differences in water mobility during kerneldevelopment. Moreover, they indicate that endosperm texture inwheat is expressed in the very early stages of grain developmentand that differences in water mobility between soft and hardkernels can be detected by non-destructive TD-NMR. According toTurnbull et al. (2003) near-isogenic soft and hard lines fromcommon wheat cv. Heron can be differentiated by scanning elec-tron microscopy of their developing kernels from 5 dpa to 32 dpa,the Heron hard kernels having a more compact endosperm struc-ture than its soft counterpart. More recently, Finnie et al. (2010)demonstrated that endosperm hardness is associated with theamount of polar lipids accumulated on the surface of wheat starchgranules. Therefore, the mechanism of endosperm hardness seemsto involve starch granules, puroindolines, polar lipids and proteinsin the endosperm matrix. Interactions between these components

could affect the mobility of water molecules in the developingseeds. As a consequence, ES and EH isolines would exhibit con-trasting patterns of molecular mobility as determined by TD-NMR.Further investigations are required to clarify the exact relationshipbetween endosperm texture and water mobility.

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