Annals of Applied Biology ISSN 0003-4746

RESEARCH ARTICLE

Photosynthesis light curves: a method for screening waterdeficit resistance in the model legume Medicago truncatulaC. Nunes1,2, S.S Araujo3, J.M. Silva1,2, P. Fevereiro1,3 & A.B. Silva1,2

1 Universidade de Lisboa, Faculdade de Ciencias, Departamento de Biologia Vegetal, Campo Grande, 1749-016 Lisbon, Portugal

2 Universidade de Lisboa, Faculdade de Ciencias, Centro de Engenharia Biologica, Campo Grande, 1749-016 Lisbon, Portugal

3 Instituto de Tecnologia Quımica e Biologica, Laboratorio de Biotecnologia de Celulas Vegetais, Universidade Nova de Lisboa, Apartado 127, 2781-901

Oeiras, Portugal

Keywords

Adc; Dsp22; Medicago truncatula;

photosynthesis light curves; recovery;

transgenic lines; water deficit screening.

Correspondence

C. Nunes, Universidade de Lisboa, Faculdade

de Ciencias, Departamento de Biologia

Vegetal, Campo Grande, 1749-016 Lisbon,

Portugal; Universidade de Lisboa, Faculdade

de Ciencias, Centro de Engenharia Biologica,

Campo Grande, 1749-016 Lisbon, Portugal.

Email: catiamaria@gmail.com

Received: 13 May 2008; revised version

accepted: 22 April 2009.

doi:10.1111/j.1744-7348.2009.00341.x

Abstract

The photosynthetic performance of two transgenic Medicago truncatula linesengineered for water deficit (WD) resistance and a non-transformed linewas assessed in a growth chamber experiment in well-watered, WD andstress recovery conditions. Direct gas exchange measurements showed thatthe transgenic plants had lower photosynthetic rates under well-hydratedconditions when compared to the non-transformed line. Photosynthesis lightcurves confirmed this difference but more importantly showed a progressivechange in photosynthetic behaviour with intensity of dehydration. Dehydrationled to sharp decreases of maximum photosynthesis (Amax), photosyntheticapparent quantum yield (�) and apparent light compensation point. Therecovery rates showed that all plant lines had a similar capacity to regaincontrol photosynthetic values. Furthermore, results suggested that light wasmore limiting for photosynthesis than atmospheric CO2 concentration. Theresults are discussed in terms of the use of photosynthesis light responsecurves as a non-destructive and expeditious approach to select M. truncatulatransformants with improved WD resistance.

Introduction

The effects of global warming, such as extreme weather

events and changed precipitation patterns, are increasing

the extent of arid and semi-arid areas around the

globe (IPCC, 2001, 2007). In addition, the rapid growth

of the human population requires increased crop

productivity (Altman, 1999). An adequate plant water

status is needed for plant growth and crop production, but

this requirement is denied by the decreased availability

of water caused by drought, salinity, freezing (Verslues

et al., 2006) and chilling. Photosynthesis is one of the

first physiological processes to be affected by water

shortage (Chaves, 1991). The induced stomatal closure

decreases water loss but causes a decline in leaf

CO2 uptake leading to slower photosynthetic rates,

altered responses to light and eventually to metabolic

impairment (Lawlor & Cornic, 2002). The concomitant

loss in crop yield (Boyer, 1982) makes the understandingof adverse plant responses towards abiotic stressesimportant and plant improvement to overcome theseresponses a major target for increased agriculturalproductivity (Chaves et al., 2003; Vinocur & Altman,2005; Tuberosa & Salvi, 2006). Therefore, great effortshave been made to improve plant adaptation to droughtby both classical breeding and genetic engineering (Zhanget al., 1999; Wang et al., 2003; Chaves & Oliveira, 2004).

Not only do legumes have a high protein content,valuable in human diet and livestock feed, but they alsohave major impacts on agriculture and the environmentby contributing to nitrogen cycle stability. Their inclusionin crop rotations breaks cycles of cereal diseases anddecreases soil erosion (Graham & Vance, 2003; Younget al., 2003; Dita et al., 2006). Therefore, improvedresistance of legumes to water stress not only benefitstheir productivity but also benefits the productivity of

Ann Appl Biol 155 (2009) 321–332 © 2009 The Authors 321Journal compilation © 2009 Association of Applied Biologists

A/I curves for screening water deficit resistance in M. truncatula C. Nunes et al.

other crops. In the past years, great improvements havebeen achieved in cereals such as wheat, rice, maize andbarley but less improvement in legumes (Christou, 1997).It seems that effective water stress resistance in legumesremains a worthwhile target (Christou, 1997; Graham &Vance, 2003). Besides shortages of funding, there arepractical issues that constrain legume engineering. Theirrecalcitrant behaviour towards tissue culture (Chandra &Pental, 2003), the limited success of transformation usingbiolistic techniques and Agrobacterium vectors (Chandra& Pental, 2003) and difficulties in screening fortransformants (Stoddard et al., 2006) are problems yetto be overcome. However, the use of model legumes,Medicago truncatula Gaertn. and Lotus japonicus, has focussedefforts and may lead to a quicker progress on theconstruction of enhanced genotypes (Young et al., 2005).

When transformation for increased water deficit (WD)resistance is achieved, a large number of lines may needto be evaluated for physiological performance underlow water availability, preferably without destructionof the plant material (Wery et al., 1994). This isan essential phase in the identification of usefultransformants and in the rejection of lines with collateralgenetic damage (Birch, 1997). Breeding material can bescreened for drought tolerance under field conditionsby measuring grain yield, water use efficiency, carbonisotope discrimination, leaf water potential, stomatalcharacteristics and osmotic adjustment (Stoddard et al.,2006). However, collecting such information in thefield is usually time-consuming, expensive and oftenproduces variable results (Longenberger et al., 2006).Greenhouse and growth chamber experiments canprovide a preliminary mass screening method, whichis less expensive.

The aim of this work was to determine the photo-synthetic capacity of two M. truncatula lines geneticallymodified to express proteins related to water stress resis-tance in a growth chamber experiment (lines Dsp22 andAdc). The line Dsp22 expresses constitutively the earlylight inducible protein, DSP22, from Craterostigma plan-

tagineum (Araujo et al., 2004). The expressed protein isknown to accumulate rapidly in the chloroplast duringWD, and this enhances survival and recovery processesthrough pigment binding or the maintenance of photo-synthetic structures (Bartels et al., 1992). The Adc lineconstitutively expresses the arginine decarboxylase fromAvena sativa (Araujo et al., 2004), which was chosen forits involvement in the metabolic pathway of polyaminesynthesis. Polyamines are thought to contribute to waterstress resistance through reactive oxygen species inacti-vation and the stabilization of cellular structures such asthylakoid membranes (Tiburcio et al., 1994). The consti-tutive expression of the two proteins (DSP22 and ADC)

was expected to improve plant photosynthetic perfor-mance under imposed water stress conditions. As aresult, water stress-induced susceptibility to photoinhi-bition should be avoided or decreased in both transgeniclines. Prior to the physiological evaluation, the transcriptaccumulation of the inserted transgenes was confirmedby reverse transcriptase-polymerase chain reaction (RT-PCR). The DSP22 protein accumulation was detectedby Western blots and polyamine accumulation in theAdc line was measured by high-performance liquid chro-matography (HPLC) (A. S., Duque, unpublished data).The photosynthesis of two transgenic plant lines and thatof a control was studied both under WD and subse-quent recovery. The use of photosynthetic light responsecurves (Bjorkman, 1981) allowed the establishment of auseful non-destructive and expeditious screening tech-nique for genotypes derived from the model legume M.truncatula.

Material and methods

Plant material and growth conditions

The experiment was conducted using three different M.

truncatula cv. Jemalong plant lines, a non-transformedline (M9–10a) and two lines transformed for improvedWD resistance (Dsp22 and Adc). All seeds werescarified in concentrated anhydrous sulphuric acidaccording to Araujo et al. (2004) and sterilised in sodiumhypochlorite solution (10% Cl) diluted 1:1 with H2O.They were then immersed in 70% (v/v) ethanol for2 min, rinsed with distilled water and placed in Petridishes on wet filter paper. After 3 days at 4◦C in darkconditions, the Petri dishes were transferred to the growthchamber (thermoperiod of 25◦C day/18◦C night) wherethe seeds germinated within 2–3 days still in the dark.Germinated seeds were maintained for another week inthe Petri dishes at the same temperature of 25◦C day/18◦Cnight, but under light conditions (photoperiod of 16 h)at an irradiance of 300–400 μmol m−2 s−1 obtained fromwhite fluorescent and incandescent lamps (TLD58W/77,Halo Star 64476, L30W/77 and L58W/77). Afterwards,seedlings were individually transferred each to a 0.5 Lpot containing a mixture of 2:1:1 of standard ’terra deMontemor’ commercial soil (Horto do Campo Grande,Lisbon, Portugal), sand (Higium, Cartaxo, Portugal)and organic compost (Humais, Santarem, Portugal),respectively. The plants were maintained in the growthchamber under the same conditions (photoperiod of16 h at an irradiance of 300–400 μmol m−2 s−1 andthermoperiod of 25◦C day/18◦C night) and at a relativehumidity (RH) of approximately 40% through the entireexperiment.

322 Ann Appl Biol 155 (2009) 321–332 © 2009 The AuthorsJournal compilation © 2009 Association of Applied Biologists

C. Nunes et al. A/I curves for screening water deficit resistance in M. truncatula

Experimental design

A completely randomised factorial design was used. Theplants were irrigated every other day using tap waterto the maximum soil capacity. For each of the threelines, WD treatment began when the plants were 8 weeksold. Plants of each line were divided into three groups.One group of plants was fully irrigated throughout theexperiment (control), a second group was subjectedto WD through soil water content (SWC) decrease bywithholding water for 4 and 5 days (WD) and the thirdgroup, for study during the 3 days of water recovery(WR), was subjected to the WD treatment for 5 daysbefore irrigation to restore full soil water. After 3 daysof WD, there were no changes in relative water content(RWC) and after 6 days the plants no longer recoveredthrough rehydration of the existing leaves but by theformation of new ones. Therefore, the measurements onthe fourth and fifth days of WD were during the phase ofrapid decrease in RWC.

The youngest fully expanded leaf on the main branchof 8- to 9-week-old plants was used for all themeasurements. For evaluating the effects of WD on leafRWC and stomatal conductance, four to five plants ofeach line were used (Figs 1 and 2). To establish thecurves of photosynthesis (assimilation of CO2) (A) inresponse to different incident irradiances (I), the A/Icurves, 4 plants of each line were used for the controlgroup (Fig. 3A) and for the WD group 8 to 10 plantswere assayed (Fig.3B–Fig. 3D) to obtain a range of RWCvalues as wide as possible. In the recovery experiment,unequal replication of eight, six and four plants were usedfor M9–10a, Dsp22 and Adc plant lines, respectively, ateach time point (Fig. 7) because of reduced availability oftransgenic plants.

Water status

The soil water status was evaluated through the SWC,expressed as a weight fraction (Coombs et al., 1987).The following equation was used: SWC(%) = 100*(FW −DW)/DW, where FW was the weight of a soil portion fromthe internal region of the bulk soil in each pot and DWwas the dry weight of the same soil portion after it hadbeen oven-dried at 105◦C for 4 days. Plant water statuswas evaluated by the leaf RWC, determined accordingto Catsky (1960).

Gas exchange analysis

Photosynthetic gas exchange measurements were per-formed in non-detached young fully expanded leaves

using a portable infrared gas analyser (IRGA, LCpro+Adc BioScientific Ltd, Great Amwell, Hertfordshire, UK).Enclosed leaves were kept under controlled atmosphere.A constant gas flow into the leaf chamber maintainedthe RH at 60–70% and the leaf temperature at 25 ± 2◦Cmonitored by a thermocouple placed under the leaf.

The net photosynthesis rate (A) and stomatal conduc-tance (gs) were registered in control and stressed plantsafter steady-state was achieved at a CO2 concentrationadjusted to 370 μmol mol−1 and saturating photosyn-thetic photon flux density (PPFD) of 800 μmol m−2 s−1

supplied by an external cold light source (Schott, KL2500 LCD, Walz, Effeltrich, Germany).

Photosynthetic recovery was monitored in the 3 daysfollowing rewatering. Gas exchanges were recordedunder controlled RH (60–70%) and temperature (25 ±2◦C) after an adaptation period of 10 min to three dif-ferent conditions of irradiance and CO2: (a) irradiance of300 μmol m−2 s−1, similar to the growing conditions and370 μmol mol−1 CO2; (b) irradiance of 800 μmol m−2 s−1,saturating to the well-watered, non-transgenic line(established in preliminary tests, results not shown) and370 μmol mol−1 CO2; (c) irradiance of 800 μmol m−2 s−1

and CO2 concentration of 800 μmol mol−1, saturatingto the well-watered non-transgenic line (established inpreliminary tests, results not shown). Gas exchange mea-surements were registered every 60 s at each conditionto ensure stable measurements and values were cor-rected to the effective leaf area enclosed in the leafchamber.

Light response curves of photosynthesis

The A/I curves were also determined at a CO2 concen-tration of 370 μmol mol−1. Leaves were preadapted for10 min to darkness and then subjected to a sequenceof increasing light intensity, rising stepwise from 50 to100, 200, 300, 500, 800, 1100 and 1300 μmol m−2 s−1 for4 min at each intensity. Intensity was set by an externalcontrollable LED light unit (Adc BioScientific Ltd). Gasexchange measurements were registered every 60 s ateach irradiance to assure that the steady-state of A wasachieved after 4 min and the last value was correctedto the effective leaf area enclosed in the leaf cham-ber. Because of considerable variation in the responsefor plants within each RWC group by line combina-tions and some combinations only having one plant, inFig. 3B–Fig. 3D the response over increasing irradiancefor a single plant within the RWC range is displayed.This plant represents the median response observed. A/Icurves were then analysed according to Lambers et al.(1998). The photosynthetic apparent quantum yield (�)

Ann Appl Biol 155 (2009) 321–332 © 2009 The Authors 323Journal compilation © 2009 Association of Applied Biologists

A/I curves for screening water deficit resistance in M. truncatula C. Nunes et al.

0 25 50 75 100

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

gs (

mol

m-2

s-1

)

C

WD

RWC (%)

Figure 1 Effect of decreasing leaf relative water content (RWC) on

the stomatal conductance (gs) determined at a CO2 concentration of

370 μmol mol−1 and saturating irradiance of 800 μmol m−2 s−1 in leaves

of Medicago truncatula non-transgenic line M9–10a (black squares, �),

transgenic line Dsp22 (grey diamonds, ♦) and transgenic line Adc (white

triangles, �) . Each point corresponds to an independent measurement

and represented groups correspond to control (C) and water deficit (WD)

plants.

was calculated as the initial slope of the curve, the appar-ent light compensation point (LCP) as the light valueat which the rate of CO2 fixation by photosynthesis issimilar to the rate of CO2 release by respiration and pho-torespiration, and maximum photosynthesis (Amax) ratewas given as the asymptotic A value as irradiance tendsto infinity.

Statistical analysis

The relationship between different parameters obtainedfor the three plant lines subjected to different wateravailability was tested using regression analysis. The

regression model that best fitted the data, evaluatedby an F-test, was chosen. This type of analysiswas performed using GraphPad Prism4 for Windows(GraphPad Software, San Diego, CA, USA). Data obtainedduring recovery from WD were submitted to the analysisof variance [two-way analysis of variance (ANOVA)] toassess line and time effects and the interaction betweenthese two factors. This analysis was also performed usingthe software programme GraphPad Prism4 for Windows(GraphPad Software).

Results

WD plants evaluation

The three M. truncatula plant lines under study, thenon-transgenic M9–10a and both transgenic Dsp22 andAdc, responded similarly to WD imposition (Fig. 1). Themidday RWC values were about 80% in well-irrigatedplants (C) and decreased to values ranging from 30%to 60% after 4–5 days of withholding water (WD). Gasexchange measurements showed that gs was decreasedwith the WD imposition in a similar manner for the threeplant lines under study (Fig. 1). Fully hydrated leavespresented similar RWC but scattered gs values, rangingbetween 0.68 and 0.25 mol m−2 s−1. At the end of the WDperiod, RWC and gs values were consistently lower thanin well watered plants but with more scatter in values forRWC than for gs.

No morphological differences were observed in theshoots between the plant lines either under control orWD conditions. After 5 days of WD, all plants presentedwith slightly closed leaflets and wilted leaves with a morepubescent appearance, probably because of increasedtrichome density.

0 20 40 60 80 100

0

10

20

30

RWC (%)

A (

μmol

m-2

s-1

)

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0

10

20

30

gs (mol m-2 s-1)

A BA B

Figure 2 Effect of decreasing leaf relative water content (RWC) (A) and stomatal conductance (gs) (B) on the net photosynthetic rate (A) measured at

a CO2 concentration of 370 μmol mol−1 and saturating irradiance of 800 μmol m−2 s−1 in leaves of Medicago truncatula non-transgenic line M9–10a

(black squares, �), transgenic line Dsp22 (grey diamonds, ♦) and transgenic line Adc (white triangles, �). Each point corresponds to an independent

measurement each from a different plant and the presented regressions in (B) (M9–10a, solid line: A = 8.52Ln(gs) + 27.41, R2 = 0.9385; Dsp22,

long-dashed line: A = 6.18Ln(gs) + 21.85, R2 = 0.9005; Adc, short-dashed line: A = 3.89Ln(gs) + 17.11, R2 = 0.9222) are the best fit for the data groups

(three Medicago lines) (P < 0.05).

324 Ann Appl Biol 155 (2009) 321–332 © 2009 The AuthorsJournal compilation © 2009 Association of Applied Biologists

C. Nunes et al. A/I curves for screening water deficit resistance in M. truncatula

0

5

10

15

20

25

30

0

5

10

15

20

25

30

A (

μmol

m-2

s-1

)

0

5

10

15

20

25

30

A (

μmol

m-2

s-1

)

Irradiance (μmol m-2 s-1) Irradiance (μmol m-2 s-1)

0

5

10

15

20

25

30

BA

C

RWC 85 -80% RWC 70 -50%

RWC 50 -40%

250 500 750 1000 12500

250 500 750 1000 12500

250 500 750 1000 12500

250 500 750 1000 12500

D RWC 40 -30%

Figure 3 Relationship between net photosynthetic rate (A) and light irradiance determined at a CO2 concentration of 370 μmol mol−1 in control (A) and

successively lower relative water content (RWC) range of values (B, C and D) in leaves of Medicago truncatula non-transgenic line M9–10a (black

squares, �), transgenic line Dsp22 (grey diamonds, ♦) and transgenic line Adc (white triangles, �). In (A) points represent mean values ± SE of four

independent measurements and in (B), (C) and (D) median relationships are presented. In (B), it was not possible to obtain Adc plants at the 70–50% RWC

range of values.

Under WD conditions, the net photosynthetic rate(A) determined at a CO2 concentration of 370 μmol mol−1

and saturating irradiance of 800 μmol m−2 s−1, decreasedfor all M. truncatula plant lines under study (Fig. 2A). Dif-ferences of the photosynthetic capacity among the threeplant lines are better perceived when A is plotted againstgs (Fig. 2B). This last relationship confirmed that the non-transgenic M9–10a plants presented higher A values,approaching 25 μmol m−2 s−1, under control conditionswhereas the Adc line did not exceed 15 μmol m−2 s−1

and transgenic Dsp22 line attained an intermediate value(Fig. 2B). These differences however, were no longerfound at the end of the WD period, when all three plantlines presented A values around 5 μmol m−2 s−1.

Photosynthesis light curves

A/I curves confirmed the differences found between theplant lines (Fig. 3). Under control conditions, the non-transgenic line M9–10a had a better photosyntheticperformance than either transgenic line. The Dsp22tended to present higher A values than the Adc line.This difference, however, only showed at irradianceabove 200 μmol m−2 s−1 and was more evident as lightintensities increased (Fig.3A). A/I curves also showeddecreased A with leaf dehydration for all incident light

intensities in the three plant lines (Fig. 3B–Fig. 3D). Thebetter performance of M9–10a line was less evident at

lower RWC values and lower incident light. The differentcurve shapes observed in plants with different RWC

values highlight the effect of WD on photosynthesis, not

only through variation of A but also through an evidentincrease in the apparent LCP with RWC decrease.

In fact, estimates obtained using the model describedby Lambers et al. (1998) showed that Amax, � and LCP

changed markedly with WD in the three M. truncatula

lines. Amax was always higher in fully hydrated leavesthan in dehydrated ones (Fig. 4A). Under fully irrigated

conditions, the non-transgenic line M9–10a reached

Amax values above 30 μmol m−2 s−1, whereas for thetransgenic line Dsp22 values ranged between 30 and

20 μmol m−2 s−1, and for the Adc line values werelower than 20 μmol m−2 s−1. Under WD conditions,

line M9–10a maintained higher Amax values of about

16 μmol m−2 s−1 and both transgenic lines decreasedto around 5 μmol m−2 s−1. This parameter shows a

significant linear relation (P < 0.05) with gs. The rates

of decrease in Amax values are not significantly different(P > 0.05) for the two transgenic lines, but differ from

the M9–10a line (Fig. 4A).Photosynthetic apparent quantum yield (�) decreased

with WD (decreased gs) in all three M. truncatula lines

Ann Appl Biol 155 (2009) 321–332 © 2009 The Authors 325Journal compilation © 2009 Association of Applied Biologists

A/I curves for screening water deficit resistance in M. truncatula C. Nunes et al.

0.0 0.1 0.2 0.3 0.4

0.0 0.1 0.2 0.3 0.4

0.0 0.1 0.2 0.3 0.4

0

10

20

30

40

Am

ax (

μmol

m-2

s-1

)

A

0.00

0.02

0.04

0.06

0.08

0.10

0.12

φ

B

C

0

100

200

300

400

gs (mol m-2 s-1)

LCP

(μm

ol m

-2 s

-1)

Figure 4 Effect of decreasing leaf stomatal conductance (gs) on the

maximum net photosynthetic rate (Amax) (A), photosynthetic apparent

quantum yield (�) (B) and apparent light compensation point (LCP)

(C) determined from A/I curves in leaves of Medicago truncatula non-

transgenic line M9–10a (black squares, �), transgenic line Dsp22 (grey

diamonds, ♦) and transgenic line Adc (white triangles, �). Each point

corresponds to an independent measurement each on a different plant.

The presented linear regressions in (A) (M9–10a, solid line: Amax = 49.99

gs + 16.14, R2 = 0.7490; Dsp22 and Adc, dashed line: Amax = 68.75 gs +5.293, R2 = 0.7860) are significantly different and are the best fit for the

data groups (three Medicago lines) (P < 0.05). In (B) (M9–10a, Dsp22 and

Adc: � = 0.2785gs + 0.00779, R2 = 0.7888) and (C) (M9–10a, Dsp22

and Adc: LCP = 16.61exp(–1.614gs), R2 = 0.8792) the presented linear

regressions are the best fit for the data groups (three Medicago lines)

(P < 0.05).

(Fig. 4B). Statistical analysis revealed that when plottedas a function of gs, the decrease of � with decreasedgs was not statistically different (P > 0.05) between thethree plant lines.

When plotted against gs, the apparent LCP presentedan exponential increase as gs decreased but this was notstatistically different (P > 0.05) between the three plantlines (Fig. 4C). Its values increased from close to zero incontrol conditions to higher than 300 μmol m−2 s−1 inplants of around 40% RWC (Fig. 5). The sharp increaseof the apparent LCP with the decrease of RWC, easilyperceived by an observation of A/I curves (Fig. 3), wasnot statistically different (P > 0.05) for the three plantlines under study (Fig. 5).

Photosynthesis recovery from WD

Plant water status and A were measured at two CO2

concentrations and two light intensities during the 3 daysfollowing the rewatering after 5 days of WD. Recoverywas assessed relative to the control mean values of therespective M. truncatula line and its evolution throughthe time points was analysed applying a two-wayANOVA. For each of the three combinations of CO2

and light intensity, there was no significant main effectof lines (P > 0.05), but there was a significant effectof time (P < 0.05). There was no significant interaction(P > 0.05) between these two factors.

Water status, evaluated through RWC, reached thevalues of control plants in the first day after rewatering inall three plant lines and was maintained in the following

0 20 40 60 80 100

0

100

200

300

400

RWC (%)

LCP

(μm

ol m

-2 s

-1)

Figure 5 Effect of decreasing leaf relative water content (RWC) on the

apparent light compensation point (LCP) determined from A/I curves

in leaves of Medicago truncatula non-transgenic line M9–10a (black

squares, �), transgenic line Dsp22 (grey diamonds, ♦) and transgenic

line Adc (white triangles, �). Each point corresponds to an independent

measurement and the regression equation (LCP = −6.86RWC + 527.1;

R2 = 0.8612) is the best fit for the data groups (three Medicago lines)

(P < 0.05).

326 Ann Appl Biol 155 (2009) 321–332 © 2009 The AuthorsJournal compilation © 2009 Association of Applied Biologists

C. Nunes et al. A/I curves for screening water deficit resistance in M. truncatula

0 1 2 3

0

20

40

60

80

100

120

Time (days)

RW

C (

reco

very

%)

Figure 6 Relative water content (RWC) recovery in 3 days following

rewatering. The mean values of RWC obtained for each line of Medicago

truncatula in 3 recovery days were normalised (100%) to the corresponding

control RWC values. The recovery percentages are presented for the non-

transgenic line M9–10a (black squares with solid line, �), transgenic

line Dsp22 (grey diamonds with long-dashed line, ♦) and transgenic line

Adc (white triangles with short-dashed line, �). The points represent

mean values ± S.E of eight, six and four independent measurements for

M9–10a, Dsp22 and Adc plant lines, respectively.

days (Fig. 6). No significant differences (P > 0.05) wereobtained in the recovery rates between the three plantlines.

In the three M. truncatula lines, the A measured at a CO2

concentration of 370 μmol mol−1 and an irradiance of300 μmol m−2 s−1 reached 30–60% of the control meanvalue in the first recovery day and 60–80% in the secondday (Fig. 7A). In the third day, the change in mean valuesfor lines compared to previous days suggests that someplants needed more time to reach 100% recovery orcould not completely recover from the WD treatment. Nosignificant differences (P > 0.05) were obtained betweenlines. The photosynthetic recovery determined at aCO2 concentration of 370 μmol mol−1 was faster at anirradiance of 800 than at 300 μmol m−2 s−1 (compareFig 7B with Fig. 7A). There was a faster recovery rate inthe first day at 800 μmol m−2 s−1 when, on average, theplants recovered 55–75%. In the following day, therewas a slight improvement towards full recovery andplants attained 70–85% recovery, but there was littlefurther recovery by the third day (Fig. 7B). These valueswere similar to those obtained in the third day andagain no significant differences (P > 0.05) were foundbetween lines during the recovery period. Under elevatedCO2 (800 μmol mol−1) and elevated light intensity(800 μmol m−2 s−1) photosynthesis recovery was slightlyhigher in the first day (Fig. 7C) than that obtained at370 μmol mol−1 CO2 at an irradiance of 800 μmol s−1m−2

but identical in the next 2 days (compare Fig. 7C with

Time (days)

C

0 1 2 3

0

20

40

60

80

100

120

A (

reco

very

%)

0 1 2 3

0

20

40

60

80

100

120

A (

reco

very

%)

0 1 2 3

0

20

40

60

80

100

120

A (

reco

very

%)

A

B

Figure 7 Net photosynthetic rate (A) recovery in the 3 days following

rewatering. The mean values of A measured for each line of Medicago

truncatula under different conditions (at a CO2 concentration of

370 μmol mol−1 and a photosynthetic photon flux density (PPFD)

of 300 μmol m−2 s−1 (A); at a CO2 concentration of 370 μmol mol−1

and a PPFD of 800 μmol m−2 s−1 (B) and at a CO2 concentration of

800 μmol m−2 s−1 and a PPFD of 800 μmol m−2 s−1 (C)) in 3 recovery

days were normalised (100%) to the corresponding control A values. The

recovery percentages are presented for the non-transgenic line M9–10a

(black squares with solid line, �), transgenic line Dsp22 (grey diamonds

with long-dashed line, ♦) and transgenic line Adc (white triangles with

short-dashed line, �). The points represent mean values ± SE of eight,

six and four independent measurements each on a different plant for

M9–10a, Dsp22 and Adc plant lines, respectively.

Fig. 7B). Also under these conditions, there were nosignificant differences (P > 0.05) between the three lines.

Ann Appl Biol 155 (2009) 321–332 © 2009 The Authors 327Journal compilation © 2009 Association of Applied Biologists

A/I curves for screening water deficit resistance in M. truncatula C. Nunes et al.

Discussion

Pot experiments have already proven to be useful inlegume WD evaluation (Antolın et al, 1995; Amede et al.,1999) and to produce results strongly correlated withresults obtained in field trials (Khan et al., 2007). In Fig. 1,the variation of gs with RWC is of the same magnitude asthat described for Phaseolus vulgaris (Castrillo et al., 2001)and Vicia faba (Khan et al., 2007) in pot experiments andas those found for Medicago arborea and Medicago citrina

in field experiments carried out during 1 year (Lefi et al.,2004). The decrease in gs was similar for the three M.

truncatula plant lines (Fig. 1) and almost total for the mostsevere WD, ranging between 0.68 mol m−2 s−1 in fullyirrigated conditions and 0.05 mol m−2 s−1 in dehydratedplants. Medrano et al. (2002) suggested that gs is a betterleaf WD indicator than RWC. In fact, Fig. 1 shows thata large variation in gs could occur without significantchanges in RWC. Also, Fig. 2 shows a clear relation of Awith gs not found for A in relation to RWC. Similar resultswere reported for cultivars of Phaseolus vulgaris and Vigna

unguiculata (Cruz de Carvalho et al., 1998).The A values were similar to those obtained in the field

for M. arborea and M. citrina (Lefi et al., 2004) and in potexperiments in M. sativa (Antolın & Sanchez-Diaz, 1993),but there were significant differences (P < 0.05) betweenthe three plant lines (Fig. 2B). Under fully hydrated con-ditions, the transgenic lines showed lower photosyntheticcapacity. This suggests that both transgenic lines haveimpaired metabolism, such as higher photorespirationand/or dark respiration rates, or morphological differ-ences that reduce mesophyll conductance to CO2.

Photosynthesis light curves confirmed that the non-transgenic line M9–10a had a better photosyntheticcapacity than either transgenic lines, but more impor-tantly, these curves reveal through their different shapes,a distinctive photosynthetic pattern for plants withsuccessively lower RWC values. Besides the expecteddecrease in Amax with WD (Fig. 4A), as reported forEncelia farinosa (Ehleringher & Cook, 1984) and Medicago

sativa (Antolın & Sanchez-Diaz, 1993), a decrease wasobserved in � (Fig. 4B), and an unpredicted extremerise of the apparent LCP, reaching up to and above300 μmol m−2 s−1 (Fig. 4C and Fig. 5), elsewhere foundin three cultivars of Eragrostis curvula, a C4 plant (Colom& Vazzana, 2001).

Because Amax is attained as saturating irradianceis reached and carboxylation capacity of the CalvinCycle is limited (Bjorkman, 1981), an Amax decreaseis expected in drought-stressed plants because of alower stomatal conductance. In M. truncatula plants,Amax showed a significant linear decline (P < 0.05)with gs for the three plant lines (Fig. 4A) supporting

the importance of stomatal limitations under saturatingirradiance. However, at a given gs value, the transgeniclines had lower Amax than the non-transgenic lineshowing that non-stomatal limitations are also presentunder saturating irradiance in the transformed plants.Furthermore, these limitations increased with WD asshown by the higher rate for transgenic plants. Possibly,light energy dissipation in metabolic processes wereoccurring that did not result in carbon fixation, suchas fluorescence, thermal dissipation, Mehler-ascorbateperoxidase reactions and photorespiration. Of theseprocesses, only photorespiration could significantly alterthe net gas exchange balance and lead to the observedAmax variation (Long et al., 1994; Bjorkman & Demmig-Adams, 1995). The decline of � with gs for the threeM. truncatula lines studied (Fig. 4B) suggests that at lowirradiance photorespiration was increased with drought.The same decline for all plant lines indicates that atlow irradiance the proportion of the exciting energydissipated by photosynthesis and photorespiration wassimilar. In M. sativa, � also decreased in water-stressedleaves but was similar despite the WD severity (Antolın& Sanchez-Diaz, 1993).

There is still disagreement whether moderate WDhas an influence in CO2 fixation by Rubisco. Severalworks show a weak correlation between dehydrationand Rubisco activity (Gimenez et al., 1992; Gunasekera& Berkowitz, 1993), whereas others suggest the con-trary. Majumdar et al. (1991) showed a clear and rapidloss of Rubisco activity in soybean plants under WD.Under more severe WD, opinions tend to converge andboth loss of activity and decreased protein quantity aredescribed (Tezara & Lawlor, 1995 and Kicheva et al.,1994, respectively). A strong decline in Rubisco activ-ity was also reported in Medicago sativa plants subjectedto cycles of moderate or severe drought stress (Antolin &Sanchez-Diaz, 1993). Decreased Rubisco activity can berelated to the binding inhibitors under WD, such as 2-carboxy-D-arabinitol 1-phosphate (CA1P), which slowlyappears under darkness and low light, and D-glycero-2,3-diulose-1,5-bisphosphate (PdBP) that appears in thelight. Both inhibitors can be involved in Rubisco protec-tion under stressful conditions, including WD, avoidingits degradation (Khan et al.,1999; Parry et al., 2002). If thisis the case, the lower � found for the three M. truncatulalines under WD can be a consequence of adenosinetriphosphate (ATP) deficiency essential to release the tightinhibitors from the active sites of Rubisco through acti-vation of Rubisco activase (Parry et al., 2008; Portis et al.,2008). Nevertheless, the differences found for controland WD A/I curves can be related to diurnal inhibitors.The decreased Amax in dehydrated plants (Fig. 4A) isprobably because of both CO2 diffusion limitations and

328 Ann Appl Biol 155 (2009) 321–332 © 2009 The AuthorsJournal compilation © 2009 Association of Applied Biologists

C. Nunes et al. A/I curves for screening water deficit resistance in M. truncatula

metabolic impairment, as described for M. truncatula cv.Jemalong (Nunes et al., 2008), contributing to a loweredphotosynthesis yield (Fig. 4B). The lower Amax valuesof both transgenic lines indicate that the photosyntheticlimitations observed under growth conditions (Fig. 2) arenot overcome under saturating light.

A higher LCP could result from a higher respiration rate,a higher photorespiration rate and/or a lower Rubiscocarboxylase activity. If the photorespiration increaseand/or Rubisco carboxylase activity decrease were themain cause for the rise of the apparent LCP with gs inM. truncatula, the � would have changed accordingly.However, because the observed sharp increase in theapparent LCP was different from the linear decline of �

with gs, it cannot be related to significant variation of thephotorespiration rate and/or Rubisco carboxylase activity.In Medicago sativa, respiration and photorespiration wereless affected by drought than net photosynthesis (Antolın& Sanchez-Diaz, 1993) and apparent LCP was notaffected. One possible explanation could be the needof dehydrated plants to be exposed for a longer periodof time to low light to attain a steady-state valueof the photosynthetic rate. If this was the case, alonger exposure to low light, more than 4 min, woulddecrease the apparent LCP. However, recovery of Aafter 10 min under an irradiance of 300 μmol m−2 s−1

also showed null values of A. Another hypothesis couldbe a lower light absorption by the leaves because of anotable rise in trichome density in dehydrated plants.Although we have no data concerning trichome densityon leaves of plants subjected to the WD treatment,the leaves appeared to be paler (whiter) under theseconditions. Ehleringer and Bjorkman (1978) studied theE. farinosa leaf reflectance properties and proposed thatpubescence becomes reflective only after the leaf hairshave dried out and become air-filled. In this context, itseems possible that an increase in the reflectance of M.truncatula leaf can be related to a higher proportion ofair-filled trichomes induced by WD. Galmes et al. (2007)showed that a trichome layer can significantly alterthe internal leaf radiation state and be an importantprotection factor against damaging irradiance in someMediterranean species. As far as we know, a sharpincrease in the apparent LCP with drought was onlyfound in three cultivars of E. curvula, a C4 plant (Colom &Vazzana, 2001). Because photorespiration rate is lower inC4 plants than in C3 plants and only a slight increase wasfound in C4 plants under WD conditions (Carmo-Silvaet al., 2008), the higher apparent LCP of E. curvula cannotbe related to a significant increase in photorespiration.

The recovery process, evaluated in terms of RWC(Fig. 6) and photosynthesis (Fig. 7A–Fig. 7C), measuredunder different CO2 concentrations and light intensities,

showed an equal recovery capacity of all three plantlines towards control values. The progress in the increasein A during the recovery process was different intwo light intensities. The photosynthetic apparatus,when affected by the imposed WD, responded morerapidly to higher incident light intensities. One possibleexplanation could be related to the leaf reflectance.Increase in this factor that can be reducing light reachingthe chloroplasts did not alter CO2 diffusion to thecarboxylating site because the higher atmospheric CO2

concentration (800 μmol m−2 s−1) did not lead to muchdifferent recovery rate.

Plant genetic engineering has already proven useful indeveloping plants resistant to biotic stresses. However,its contribution to protection from abiotic constraints isproving more difficult to achieve because many genesare simultaneously involved (Shinozaki & Yamaguchi-Shinozaki, 2000). The work presented is further evidenceof the difficulty because the constitutive expressionof two water stress-related genes did not lead toexpected improvements in photosynthetic performanceunder the conditions used. Several explanations arepossible for the lack of improvement. For example,polyamine accumulation under well-irrigated conditionscan have toxic effects in plants (Tiburcio et al., 1994).Therefore, the constitutive expression of ADC could bethe cause for the poorer performance of the Adc lineunder control conditions. Pyramiding traits to neutralisepotential negative effects of individual traits (Condonet al., 2002) and driving the expression of genes usinga stress inducible promoter could lead to better results.Finally, it is possible that the transgenic lines may show abetter performance under more prolonged periods of WDthan those employed.

This work shows that photosynthesis light curves arean appropriate method to screen M. truncatula lines forimproved WD resistance. Through the establishment ofthe typical A/I curves for genotype under study in well-watered and in WD, the magnitude of the variationin apparent LCP for the genotypes can be studied tocompare their responses. A lower apparent LCP underWD conditions could indicate higher Amax and � andtherefore improved productivity under these conditions.This method can have special interest when a largenumber of improved lines are obtained and a fast methodis needed. We believe that the protocol can be adapted tothe plant under study to minimise the time required forevaluation. Once the curve patterns are established forspecific RWC ranges, the use of fewer measurements, forexample at only four light intensities, may be sufficientto extract the relevant information (differences betweenplants and lines) and could decrease to around 16 minthe time needed for each plant. However, the four light

Ann Appl Biol 155 (2009) 321–332 © 2009 The Authors 329Journal compilation © 2009 Association of Applied Biologists

A/I curves for screening water deficit resistance in M. truncatula C. Nunes et al.

intensities would need to be chosen strategically, so thatthe curve is well defined. In the present case, 0, 250, 500and 1000 μmol m−2 s−1 could have been used. For routineuse, it would be worth assembling a system with camerasconnected to the same analyser to process as many plantsa day as possible. A non-destructive technique may beadvantageous where few plants are available, for examplein T1 transgenic lines. The technique can constitute apreliminary test for plant productivity and behaviourtowards WD conditions in the field.

In conclusion, no improvement in photosynthetic per-formance under water stress induced by rapid dehydra-tion was found in two M. truncatula transgenic lines.Photosynthesis light curves were found to be an expedi-tious and non-destructive approach to discriminate plantphotosynthesis performances and to screen and selectwater stress resistant or non-resistant M. truncatula lines.

Acknowledgements

This work was supported by research and equipmentgrants from Fundacao para a Ciencia e Tecnologia andFEDER through POSC (POCTI/BIO/56659/2004). Theauthors thank the anonymous reviewers for their helpfulcomments.

References

Altman A. (1999) Plant biotechnology in the 21s century:

the challenges ahead. Electronic Journal of Biotechnology, 2,

51–55.

Amede T., Kittlitz E.V., Schubert S. (1999) Differential

drought responses of faba bean (Vicia faba L.) inbred

lines. Journal of Agronomy and Crop Science, 183, 35–45.

Antolın M.C., Sanchez-Diaz M. (1993) Effects of temporary

droughts on photosynthesis of alfalfa plants. Journal of

Experimental Botany, 44, 1341–1349.

Antolın M.C., Yoller J., Sanchez-Diaz M. (1995) Effects of

temporary drought on nitrate-fed and nitrogen-fixing

alfalfa plants. Plant Science, 107, 159–165.

Araujo S.S., Duque A.S.R.L.A., Santos D.M.M.F.,

Fevereiro M.P.S. (2004) An efficient transformation

method to regenerate a high number of transgenic plants

using a new embryogenic line of Medicago truncatula cv.

Jemalong. Plant Cell, Tissue and Organ Culture, 78,

123–131.

Bartels D., Hanke C., Schneider K., Michel D., Salamini F.

(1992) A desiccation-related Elip-like gene from the

resurrection plant Craterostigma plantagineum is regulated

by light and ABA. The EMBO Journal, 11, 2771–2778.

Birch R.G. (1997) Plant transformation: problems and

strategies for practical application. Annual Review of Plant

Physiology and Plant Molecular Biology, 48, 297–326.

Bjorkman O. (1981) Response to different quantum flux

densities. In Encyclopedia of Plant Physiology, New Series,Vol. 12A, pp. 57–107. Eds O.L. Lange, P.S. Nobel,

C.B. Osmond and H. Zeigler. Berlin: Springer.

Bjorkman O., Demmig-Adams B. (1995) Regulation of

photosynthesis light energy capture, conversion, and

dissipation in leaves of higher plants. In Ecophysiology of

Photosynthesis, pp. 17–47. Eds E.-D. Schulze and

M.M. Caldwell. Berlin: Springer.Boyer J.S. (1982) Plant productivity and environment

potential for increasing crop plant productivity, genotypic

selection. Science, 218, 443–448.

Carmo-Silva A.E., Powers S.J., Keys A.J., Arrabaca M.C.,

Parry M.A.J. (2008) Photorespiration in C4 grasses

remains slow under drought conditions. Plant, Cell and

Environment, 31, 925–940.Castrillo M., Fernandez D., Calcagno A.M., Trujillo I.,

Guenni L. (2001) Responses of ribulose-1,5-bisphosphate

carboxylase, protein content, and stomatal conductance

to water deficit in maize, tomato and bean.

Photosynthetica, 39, 221–226.

Catsky J. (1960) Determination of water deficit in discs cut

out from leaf blades. Biologia Plantarum, 2, 76–77.Chandra A., Pental D. (2003) Regeneration and genetic

transformation of grain legumes: an overview. Current

Science, 84, 381–387.

Chaves M.M. (1991) Effects of water deficit on carbon

assimilation. Journal of Experimental Botany, 42, 1–16.

Chaves M.M., Oliveira M.M. (2004) Mechanisms

underlying plant resilience to water deficits: prospects forwater-saving agriculture. Journal of Experimental Botany,

55, 2365–2384.

Chaves M.M., Maroco J.P., Pereira J.S. (2003)

Understanding plant responses to drought – from genes

to the whole plant. Functional Plant Biology, 30, 239–264.

Christou P. (1997) Biotechnology applied to grain legumes.

Field Crops Research, 53, 83–97.Colom M.R., Vazzana C. (2001) Drought stress effects on

three cultivars of Eragrostis curvula: photosynthesis and

water relations. Plant Growth Regulation, 34, 195–202.

Condon A.G., Richards R.A. Rebetzke G.J. Farquhar G.D.

(2002) Improving intrinsic water use efficiency and crop

yield. Crop Science, 42, 122–131.

Coombs J., Hall D.O., Long S.P., Scurlock J.M.O. (1987)Techniques in Bioproductivity and Photosynthesis. Oxford:

Pergamon Press.

Cruz de Carvalho M.H., Laffray D., Louguet P. (1998)

Comparison of the physiological responses of Phaseolus

vulgaris and Vigna unguiculata cultivars when submitted to

drought conditions. Environmental and Experimental

Botany, 40, 197–207.Dita M.A., Rispail N., Prats E., Rubiales D., Singh K.B.

(2006) Biotechnology approaches to overcome biotic

and abiotic stress constraints in legumes. Euphytica, 147,

1–24.

330 Ann Appl Biol 155 (2009) 321–332 © 2009 The AuthorsJournal compilation © 2009 Association of Applied Biologists

C. Nunes et al. A/I curves for screening water deficit resistance in M. truncatula

Ehleringer J.R., Bjorkman O. (1978) A comparison of

photosynthetic characteristics of Encelia species possessing

glabrous and pubescent leaves. Plant Physiology, 62,

185–190.

Ehleringer J.R., Cook C.S. (1984) Photosynthesis in Encelia

farinosa Gray in response to decreasing leaf water

potential. Plant Physiology, 75, 688–693.

Galmes J., Medrano H., Flexas J. (2007) Photosynthesis and

photoinhibition in response to drought in a pubescent

(var. minor) and glabrous (var. palaui) variety of Digitalis

minor. Environmental and Experimental Botany, 60,

105–111.

Gimenez C., Mitchell V.J., Lawlor D.W. (1992) Regulation

of photosynthesis rate of two sunflower hybrids under

water stress. Plant Physiology, 98, 516–524.

Graham P.H., Vance C.P. (2003) Legumes: importance

and constraints to greater use. Plant Physiology, 131,

872–877.

Gunasekera D., Berkowitz G.A. (1993) Use of transgenic

plants with ribulose-1,5-bisphosphate carboxylase

oxygenase antisense DNA to evaluate the rate limitation

of photosynthesis under water-stress. Plant Physiology,

103, 629–635.

IPCC. (2001) Climate change 2001: the scientific basis. In

Contribution of Working Group I to the Third Assessment Report

of the Intergovernmental Panel on Climate Change (IPCC)

pp. 944. Eds J.T. Houghton, Y. Ding, D.J. Griggs,

M. Noguer, P.J. van Der Linden, X. Dai. Cambridge, UK:

Cambridge University Press, UK.

IPCC. (2007) Contribution of working group I to the fourth

assessment report of the Intergovernmental Panel on

Climate Change (IPCC): The Physical Science Basis,

Summary for Policymakers.

Khan H.R., Link W., Hocking T.J., Stoddard F.L. (2007)

Evaluation of physiological traits for improving drought

tolerance in faba bean (Vicia faba L.) Plant and Soil, 292,

205–217.

Khan S., Andralojc P.J., Lea P.J., Parry M.A.J. (1999)

2’-Carboxy-D-arabitol 1-phosphate protects

ribulose-1,5-bisphosphate carboxylase/oxygenase against

proteolytic breakdown. European Journal of Biochemistry,

266, 840–847.

Kicheva M.I., Tsonev T.D., Popova L.P. (1994) Stomatal and

non-stomatal limitations to photosynthesis in two wheat

cultivars subjected to water stress. Photosynthetica, 30,

107–116.

Lambers H., Chapin III F.S., Pons T.L. (1998) Plant

Physiological Ecology, pp. 154–209. Dordrecht, The

Netherlands: Springer.

Lawlor D.W., Cornic G. (2002) Photosynthetic carbon

assimilation and associated metabolism in relation to

water deficits in higher plants. Plant, Cell and Environment,25, 275–294.

Lefi E., Medrano H., Cifre J. (2004) Water uptake dynamics,photosynthesis and water use efficiency in field-grownMedicago arborea and Medicago citrina under prolongedMediterranean drought conditions. Annals of AppliedBiology, 144, 299–307.

Long S.P., Humphries S., Falkowski P.G. (1994)Photoinhibition of photosynthesis in nature. AnnualReview of Plant Physiology and Plant Molecular Biology, 45,633–662.

Longenberger P.S., Smith C.W., Thaxton P.S.,McMichael B.L. (2006) Development of a screeningmethod for drought tolerance in cotton seedlings. CropScience, 46, 2104–2110.

Majumdar S., Ghosh S., Glick B.R., Dumbroff E.B. (1991)Activities of chlorophyllase, phosphoenolpyruvatecarboxylase and ribulose-1,5-bisphosphate carboxylase inthe primary leaves of soybean during senescence anddrought. Physiologia Plantarum, 81, 473–480.

Medrano H., Escalona J.M., Bota J., Gulias J., Flexas J.(2002) Regulation of photosynthesis of C3 plants inresponse to progressive drought: stomatal conductance asa reference parameter. Annals of Botany, 89, 895–905.

Nunes C., Araujo S.S., Marques da Silva J.,Fevereiro M.P.S., Bernardes da Silva A. (2008)Physiological responses of the legume model Medicago

truncatula cv. Jemalong to water deficit. Environmental andExperimental Botany, 63, 289–296.

Parry M.A.J., Keys A.J., Madgwick P.J., Carmo-Silva A.E.,Andralojc P.J. (2008) Rubisco regulation: a role forinhibitors. Journal of Experimental Botany, 59, 1569–1580;online doi:10.1093/jxb/ern084.

Parry M.A.J., Andralojc P.J., Shahnaz K., Lea P.J., Keys A.J.(2002) Rubisco activity: effect of drought stress. Annals of

Botany, 89, 833–839.Portis A.R. Jr., Li C., Wang D., Salvucci M.E. (2008)

Regulation of Rubisco activase and its interaction withRubisco. Journal of Experimental Botany, 59, 1597–1604;doi:10.1093/jxb/erm240.

Shinozaki K., Yamaguchi-Shinozaki K. (2000) Molecularresponses to dehydration and low temperature:differences and cross-talk between two stress signallingpathways. Current Opinion in Plant Biology, 3, 217–223.

Stoddard F.L., Balko C., Erskine W., Khan H.R., Link W.,Sarker A. (2006) Screening techniques and sources ofresistance to abiotic stresses in cool-season food legumes.Euphytica, 147, 167–186.

Tezara W., Lawlor D.W. (1995) Effects of water stress on thebiochemistry and physiology of photosynthesis insunflower. In Photosynthesis: From Light to Biosphere IV,pp. 625–628. Ed. P. Mathis. Dordrecht: Kluwer AcademicPublishers.

Tiburcio A.F., Besford R.T., Capell T., Borrell A.,Testillano P.S., Risueno M.C. (1994) Mechanisms ofpolyamine action during senescence responses induced

Ann Appl Biol 155 (2009) 321–332 © 2009 The Authors 331Journal compilation © 2009 Association of Applied Biologists

A/I curves for screening water deficit resistance in M. truncatula C. Nunes et al.

by osmotic stress. Journal of Experimental Botany, 45,1789–1800.

Tuberosa R., Salvi S. (2006) Genomics-based approaches toimprove drought tolerance of crops. Trends in Plant Science,

11, 405–412.Verslues P.E., Agarwal M., Katiyar-Agarwal S., Zhu J.,

Zhu J-K. (2006) Methods and concepts in quantifyingresistance to drought, salt and freezing, abiotic stressesthat affect plant water status. The Plant Journal, 45,523–539.

Vinocur B., Altman A. (2005) Recent advances inengineering plant tolerance to abiotic stress:achievements and limitations. Current Opinion in

Biotechnology, 16, 123–132.Wang W., Vinocur B., Altman A. (2003) Plant response to

drought, salinity and extreme temperatures: towards

genetic engineering for stress tolerance. Planta, 218,1–14.

Wery J., Silim S.N., Knights E.J., Malhotra R.S., Cousin R.(1994) Screening techniques and sources and toleranceto extremes of moisture and air temperature in coolseason food legumes. Euphytica, 73, 73–83.

Young N.D., Cannon S.B., Sato S., Kim D., Cook D.R.,Town C.D., Roe B.A., Tabata S. (2005) Sequencing thegenespaces of Medicago truncatula and Lotus japonicus. Plant

Physiology, 137, 1174–1181.Young N.D., Mudge J., Ellis T.N. (2003) Legume genomes:

more than peas in a pod. Current Opinion in Plant Biology,

6, 199–204.Zhang J., Nguyen H., Blum A. (1999) Genetic analysis of

osmotic adjustment in crop plants. Journal of Experimental

Botany, 50, 291–302.

332 Ann Appl Biol 155 (2009) 321–332 © 2009 The AuthorsJournal compilation © 2009 Association of Applied Biologists