Phenotyping for drought tolerance of crops in the genomics era

26 Pages·2012·1.04 MB·English

by  Roberto Tuberosa

METHODSARTICLE
published:19September2012
doi:10.3389/fphys.2012.00347
Phenotyping for drought tolerance of crops in the
genomics era
RobertoTuberosa*
DepartmentofAgroenvironmentalScienceandTechnology,UniversityofBologna,Bologna,Italy
Editedby: Improving crops yield under water-limited conditions is the most daunting challenge
AntoniaOkono,CGIARGeneration faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly
ChallengeProgramme(GCP), pivotal role for the selection of drought-resilient genotypes and, more in general, for a
Mexico
meaningfuldissectionofthequantitativegeneticlandscapethatunderscorestheadaptive
Reviewedby:
response of crops to drought. A major and universally recognized obstacle to a more
BobCreelman,Mendel
Biotechnology,Inc.,USA effective translation of the results produced by drought-related studies into improved
PhilippeMonneveux,International cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to
PotatoCenter,Peru identifythequantitativetraitlocithatgovernyieldandrelatedtraitsacrossdifferentwater
*Correspondence: regimes. This review provides basic principles and a broad set of references useful for
RobertoTuberosa,Departmentof
themanagementofphenotypingpracticesforthestudyandgeneticdissectionofdrought
AgroenvironmentalScienceand
Technology,VialeFanin44, toleranceand,ultimately,forthereleaseofdrought-tolerant cultivars.
Bologna40127,Italy.
e-mail:[email protected] Keywords:droughttolerance,phenomics,genomics,QTL,breeding,yield,phenology,modeling
INTRODUCTION the deluge of molecular data produced in the past decade,
Crops are exposed to the ravages of drought in various ways the applicable results reported so far with non-conventional
and to different extents. Regrettably, global climate change will approaches have not met expectations (Edmeades et al., 2004;
increasetheoccurrenceandseverityofdroughtepisodes,notleast Araus et al., 2007, 2008; Collins et al., 2008; Xu and Crouch,
due to the higher evapotranspirative demand created by rising 2008;Heffneretal.,2009;Passioura,2010;Sinclair,2011),partly
temperatures.Altogether,thesechangeshavealreadybeenshown because the progress in high-throughput, quality phenotyping
to offset a significant portion of the increases in average yields haslaggedbehind.
that during the past three decades arose from technology, CO Before analyzing the factors that affect the quality of
2
fertilization and other factors (Lobell et al., 2011). Therefore, phenotypic data collected under water-limited conditions, it is
food security in the twenty-first century will rely increasingly important to define the nomenclatureand mechanisms of crop
on the release of cultivars with improved resistance to drought adaptation to drought and clarify their functional basis. Most
conditions and with high yield stability (Swaminathan, 2005; of the examples and references provided in this review refer to
Borlaug, 2007; Pennisi, 2008; Luo, 2010; Tester and Langridge, cereals,which,ascomparedtoothercrops,havebeenmoreexten-
2010; Reynolds et al., 2011; Serraj et al., 2011; Chapman et al., sivelyinvestigatedunderdroughtconditions.Nevertheless,most
2012). conceptspresentedhereinareequallyvalidforothercropsaswell.
Inthischallengingscenario,molecularapproachesoffernovel
opportunities for the dissection and more targeted manipula- DROUGHTADAPTATION:CONCEPTS,NOMENCLATURE,
tion of the genetic and functional basis of yield under drought ANDMECHANISMS
conditions (Forster et al., 2000; Sinclair et al., 2004; Bohnert Inagriculture,theterm“drought”referstoaconditioninwhich
etal.,2006;Mackill,2006;TuberosaandSalvi,2006;Jenksetal., theamountofwater availablethroughrainfalland/orirrigation
2007; Nelson et al., 2007; Ortiz et al., 2007a; Vij and Tyagi, is insufficient to meet the transpiration needs of the crop. The
2007; Leung, 2008; Xu and Crouch, 2008; Ashraf, 2010; Mittler examples presented in this review provide some general guide-
and Blumwald, 2010; Yadav et al., 2011; Deikman et al., 2012). linesonthedifferentmechanismsthatallowplantstowithstand
Additionally, the “-omics” platforms now allow for extensive and eventually mitigate the negative effects of water deficit. In
mining of the transcriptome (Rabbani et al., 2003; Poroyko general, a clear distinction should be made between traits that
et al., 2007; Degenkolbe et al., 2009; Ergen and Budak, 2009; helpplantstosurviveaseveredroughtstressandtraitsthatmit-
Sreenivasulu et al., 2010; Deokar et al., 2011; Hiremath et al., igateyieldlossesincropsexposedtoamildorintermediatelevel
2011), metabolome (Fernie and Schauer, 2009) and proteome ofwaterstress.Modernbreedingactivities, includingphenotyp-
(Timperio et al., 2008). Although, some may not consider ing conditions, have predominantly targeted the latter levels of
“-omics”dataasphenotypessensustricto,theyshouldbetreated stress.Although,yieldremainsanelusiveandneglectedconcept
assuch,consideringthattheyrepresentcrucialstepsthatarepro- in mostmolecular studies carriedout under water-limited con-
gressively removed from genes to their ultimate phenes (Houle ditions,itisanappropriatewaytogaugetheoverallphenotypic
et al., 2010; Furbank and Tester, 2011). Not with standing valueofanyaccession.
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Tuberosa Phenotypingfordroughttolerance
THEFUNCTIONALBASISOFDROUGHTRESISTANCE 2009a,b, 2012; Vikram et al., 2011; Dixit et al., 2012; Ghimire
Among the several definitions of drought resistance that have etal.,2012).
been provided during the past decades, the original one
formulatedbyLevitt(1972)retainsitsvalidityandoffersaratio- WATER-USEEFFICIENCYANDGRAINYIELDUNDER
nalapproachtoclassifythestrategiesthatallowplantstomitigate WATER-LIMITEDCONDITIONS
thenegativeeffectsofwaterdeficit.Levitt(1972)classifiedthedif- Water-use efficiency (WUE) is the amount of dry matter
ferent mechanisms or strategies of drought resistance into two produced [grain yield (GY) in the case of grain crops when
broad categories: dehydration avoidance anddehydration toler- consideringseasonalWUE]perunitofwaterlostthroughevap-
ance. In this respect, morpho-physiological features [e.g., deep otranspiration.Aclassicalformulathathighlightsthecriticalrole
roots, earlyflowering,deposition ofepicuticularwaxes,osmotic of WUE in determining GY in crops grown in water-limited
adjustment(OA),etc.]thatenabletheplant,orpartsthereof,to conditionswassuggestedbyPassioura(1977):
maintain hydration are classified under dehydration avoidance.
Conversely, features (e.g., remobilization of stem water-soluble GY=W×WUE×HI
carbohydrates (WSC), accumulation of molecular protectants,
etc.) that allow the plant to maintain, at least partially, proper where W is the total amount of water transpired by the crop
functionality in a severely dehydrated state are classified under and evaporated from the field and HI is the harvest index, i.e.,
dehydration (desiccation) tolerance. Carefully planned experi- the ratio between GY and total biomass. Salekdeh et al. (2009)
mentsconductedundercontrolledconditionsallowustoseparate identify phenotyping protocols that address each formula’s fac-
the action of loci imparting avoidance from those providing tors, describe their key features and illustrate their integration
tolerance to drought (Yue et al., 2006). Several reviews and with different molecular approaches. When using this formula,
dedicated volumes have addressed the mechanisms underlying oneshouldconsiderthepossibleinterdependence ofthese vari-
droughtresistanceandthestrategiesthatcanimproveyieldunder ables,withtheresultthatselectionforimprovingWUEinorder
such conditions (Blum, 1988, 1996, 2009, 2011; Ludlow and toincreaseGYmaybepartiallycounterbalancedbyareduction
Muchow, 1990; Ceccarelli and Grando, 1996; Passioura, 1996, intheamountofwaterextractedfromthesoil.Infact,anumber
2007, 2010; Richards, 1996; Turner,1997; Ribaut, 2006; Fischer oftraitsinfluencebothWandWUE.
et al., 2003; Boyer and Westgate, 2004; Chaves and Oliveira, Themostimportantfactorismatchingthephenologicaldevel-
2004; Tuberosa, 2004; Araus et al., 2008; Kumar et al., 2008; opment pattern of the crop and the seasonal rainfall pattern
Morisonetal.,2008;ReynoldsandTuberosa,2008;Farooqetal., (Richards,1996;Turner,1997;Arausetal.,2003;Morisonetal.,
2009; Passioura and Angus, 2010; Yang et al., 2010; Sadok and 2008;SoltaniandSinclair,2012).Earlyvigorpotentiallyimproves
Sinclair, 2011; Sinclair, 2011; Cairns et al., 2012; Mir et al., both W and WUE, while deep roots and/or osmoregulation
2012). underappropriateconditionsincreasewaterextractionfromthe
The first step is to define the population of environments soil (Blum, 1988, 2011; Ludlow and Muchow, 1990; Richards,
to be targeted, also identified as the TPE (target population 2006; Reynolds and Tuberosa, 2008; Sadok and Sinclair, 2011).
of environments). Differences in TPE are largely determined However,weshouldkeepinmindthatfarmerseventuallyharvest
by long-termpatterns of genotype-by-environment interactions grainandnotWUE,whichmeansthatalowerWUEmayactu-
(GEI). Theidentificationandcharacterizationof a TPEis facil- allybedesirablewhenWUEisnegatively associatedwithGY,as
itated by the use of crop simulation models based on historic iswell-knownincerealsdifferingintheirintrinsicWUE(Blum,
records of weather data. Simulation can describe a TPE by the 2005, 2006, 2009). Therefore, WUE should not be equated to
frequencyofoccurrenceofspecificabioticstresses andbebased drought tolerance. The best example is provided by a popula-
onthesoilmoistureprofilealongthecropcycle(Chapmanetal., tionofrelatedprogenysuchasrecombinantinbredlines(RILs)
2003). In Mediterranean environments, wheat and barley usu- thatdifferintheircapacitytoextractsoilmoistureduetodiffer-
ally experience terminal drought caused by high temperatures encesinrootdepth,andhencegreatercapacitytoaccessmoisture
duringthegrain-fillingperiod(Arausetal.,2008).Nevertheless, stored in deeper soil layers. Because, WUE is higher in geno-
within each TPE and GEI are frequently observed relating to typescharacterizedbylowstomatalconductance,oftenresulting
yearly fluctuations in environmental factors (e.g., rainfall, tem- from a lower water status, the genotypes that are more waste-
perature,etc.),diseases(e.g.,foliardisease),and/orparasites(e.g., ful (i.e., with a lower WUE) and able to extract more water
insects).Ideally,phenotypingfordroughttoleranceandyieldsta- from the soil (Merah, 2001; Rebetzke et al., 2002; Blum, 2006,
bilityshouldbecarriedoutacrossabroadrangeofenvironments 2009, 2011), whilst maintaining higher stomatal conductance,
presentwithintheTPE.Duringpastdecades,thesemultienviron- will have higher yield. Conversely, under conditions of limited
ment trials havebeen instrumental inincreasingyieldpotential soil moisture, low WUE resulting from excessive evapotranspi-
and also in maintaining yield stability under drought-stressed ration will not allow sustained accumulation of dry matter and
conditionsintemperatemaize(TollenaarandWu,1999;Duvick, itspartitioningtoreproductive organs(MonneveuxandRibaut,
2005; TollenaarandLee, 2006) aswell as inother crops (Lafitte 2006;Richards,2006;Tambussietal.,2007;Barnabasetal.,2008;
etal.,2006;Crossaetal.,2007;Acunaetal.,2008).Inafewcases, Sinclairetal.,2008).Thisfindingintroducesanessentialconcept
theyhavealsoallowedfortheidentificationofmajorQTLsconsis- forinterpretingcause–effectrelationshipsbetweenmorphophys-
tentlyaffectingyieldacrossarangeofwateravailability(Bernier iological traits and GY under drought conditions: the sign and
et al., 2007, 2009; Maccaferri et al., 2008; Venuprasad et al., magnitudeofthisrelationshipatthewhole-plantorQTLlevelare
FrontiersinPhysiology|PlantPhysiology September2012|Volume3|Article347|2
Tuberosa Phenotypingfordroughttolerance
notuniversalandcanchangewidely according tothe dynamics ratherthandrought-responsive traits (Blum,2005, 2006, 2011).
(i.e.,frequencyandtiming)andintensityofthedroughtepisode/s Inthisrespect, emphasisisincreasinglybeingplacedonpheno-
(Collinsetal.,2008;Sinclairetal.,2010;Tardieu,2012). typingtraitsthatconstitutivelyenhanceyieldperse(Blum,2009;
An alternative formula to address properly the factors influ- Passioura,2010),ratherthanoncharacteristicsthatenhanceplant
encingWUEincropsgrownunderwater-limitedconditionshas survivalunderextremedrought(Bartelsetal.,2006),inviewofa
beenproposedbyRichards(1991): possiblenegativetrade-offunderlessseverecircumstances(Blum,
1996,2005,2006;Passioura,2002,2007,2010;Sinclair,2011).
WUE(biomass)=TE/(1+E/T) The traits to be considered as potential selection targets
s
for improving yield under water-limited conditions must be
where TE is the transpiration efficiency (above ground dry genetically (i.e., causally) correlated with yield, and should
weight/transpiredwater),E isthewaterlostbyevaporationfrom have a greater heritability than yield itself (Blum, 1988, 2011;
s
thesoilsurfaceandT iswaterlostthroughtranspirationbythe MonneveuxandRibaut,2006).Additionaldesirablefeaturesare
crop. Analysisof the variables in this formula provides a useful the presence of sufficient genetic variability and lack of yield
framework for identifying the agronomic and breeding strate- penaltiesunderfavorableconditions.Ideally,measurementofthe
gies,andhencephenotypingtargets,mostsuitableforoptimizing targettraitshouldbenon-destructive,rapid,accurate,andinex-
WUEandmaximizingyieldinenvironmentsthatdifferinrainfall pensive. It should also be possible to measure the trait using a
distributionduringthecropcycle. smallnumber of plantsandwithoutlengthyprocedures to cali-
At the leaf level, “intrinsic WUE” indicates the ratio of the bratesensorsto individualplants.Finally,ratherthanreporting
instantaneous rates of CO assimilation and stomatal transpi- onshort-termfeaturesatthecellularlevel,thenatureofthesec-
2
ration. Condon et al. (2002) discussed the factors influencing ondarytraitshouldbeintegrativeacrossthegrowingcycle,orpart
intrinsic WUE and how an increased intrinsic WUE can be thereof,andrelatetohigherlevelsoffunctionalorganization(e.g.,
achievedthrougheitherlowerstomatalconductance,higherpho- the canopy level rather than the single leaf), thereby providing
tosyntheticcapacity,orboth.Thesameauthorscautionaboutthe information on the long-term ecophysiological performance of
possiblepenaltiesintermsofyieldthroughmanipulationofeach thecrop.Generalinformationandexamplesarenowprovidedon
variable.Theyconcludethattoachievemorewidespreadgainsin anumberoftraitsthathavebeeninvestigatedfortheirinfluence
cerealyieldderivedfromgreaterintrinsicWUE,itisnecessaryto ondroughtresistanceand/orWUE.
decouple intrinsic WUE and low crop growth rate. In practical
terms,WUEbecomesmoreimportantwhencropsgrowpredom- EARLYVIGOR
inantlyonstoredsoilmoisture(Condonetal.,2002),asreflected Earlyvigorunderconditionsoflowevapotranspirationmayallow
by the release of wheat cultivars Drysdale and Rees (Richards, annualcropstooptimizeWUEandlimitthelossofwaterdueto
2006),specificallyselectedfortargetareaswherewheatisgrown directevaporationfromthesoilsurface.Thisleavesmorestored
undersuchconditions. water available for later developmental stages when soil mois-
ture becomes progressively exhausted and increasingly limiting
WHICHTRAITSSHOULDBETARGETED? foryield(Slaferetal.,2005;Richards,2006;Rebetzkeetal.,2007;
Richardsetal.,2007).Earlyestablishmentalsoreducestheoccur-
The morphophysiological traits and the corresponding QTLs
renceofinhibitionofstomatalconductanceasaconsequenceof
that affect yield in drought conditions can be categorized as
root-bornesignalingsuchasfromABAthrough thexylemflow
constitutive (i.e., alsoexpressed under well-watered conditions)
(Daviesetal.,2000;Renetal.,2007)causedbyshallowandsuper-
or drought-responsive (i.e., expressed only under pronounced
ficial roots (Blum, 1996; Giuliani et al., 2005). As a trade-off,
watershortage;LafitteandEdmeades,1995;Blum,2006).While
excessivelyvigorouscanopydevelopmentmaycauseearlydeple-
drought-responsive traits/QTLs usually affect yield only under
tionofsoilmoisture.Theoptimaldegreeofvigorwillthusdepend
rather severe drought conditions, constitutive traits/QTLs can
ontheenvironmentalcharacteristicsoftheTPE.Earlyvigorhas
affect yield at low and intermediate levels of drought stress as
beenexploitedtoimproveWUEandyieldinwheat(Assengetal.,
well.TheresponseofQTLsfordrought-adaptivetraits(e.g.,accu-
2003;Richards,2006;Rebetzkeetal.,2007).QTLsforthegrowth
mulation of osmolytes, relocation of WSC, etc.) to drought is
rateofwheatseedlings(Spielmeyeretal.,2007)arebeingtargeted
probably due to regulation of the expression of the underlying
at CSIRO (Commonwealth Scientific and Industrial Research
structural genes in response to signaling cues such as abscisic
Organization,Australia)1.
acid(ABA)accumulation(Bray,2002)thatarereinforcedbycel-
lular dehydration. Under appropriate soil moisture conditions,
ROOTARCHITECTURE
the presence of QTLs for traits usually classified as constitu-
Roots exhibitanastoundinglevelof morphologicalplasticityin
tive but difficult to measure (e.g., root depth) can be revealed
response tosoilphysicalconditions(Passioura,1983; Bengough
by the collocation of QTLs for traits indicative of the water
etal.,2006;Geraldetal.,2006;Itoetal.,2006;Katoetal.,2007;
status of the plant such as ABA concentration, stomatal con-
Lynch, 2007; Forde, 2009; Siopongco et al., 2009), a peculiarity
ductance,canopytemperaturedepression(CTD),etc.,(Lebreton
that allows plants to adapt better to the chemical and physi-
etal.,1995; Tuberosa etal.,2002b; Reynoldsetal.,2009, 2011).
cal properties of the soil,particularlyunder drought conditions
Experimental evidence indicates that the progress achieved by
breedersduringthelastcenturycanmainlybeaccountedforby
changes in constitutive traits that affect dehydration avoidance 1http://www.csiro.au/files/files/p2ki.pdf
www.frontiersin.org September2012|Volume3|Article347|3
Tuberosa Phenotypingfordroughttolerance
(Baconetal.,2002;Yuetal.,2007).Theconceptofrootideotype Inmaize,afastnon-destructivemethodtoestimaterootmass
should be elaborated only after gaining a detailed understand- hasreliedontheuseofahand-heldcapacitancemeter(vanBeem
ing of: (1) the factors thatlimit the availabilityof soil moisture et al.,1998; McBrideet al.,2008). The accuracy of this method
to the crop; and (2) the metabolic cost sustained by the plant was tested by comparing the results with direct measurements
to develop andmaintain amore vigorous root system. Notably, taken on uprooted plants grown in the greenhouse and in the
recurrent selection for increased GY in drought-stressed tropi- field.Thesignificantcorrelation(rfrom0.56to0.73)betweenthe
cal maize was associated with a decrease in root mass (Bolaños methods suggests the feasibility of using capacitance meters for
and Edmeades, 1993). Accordingly, the effects of root size and routine,non-destructiveobservationsrepeatedovertime.Despite
architectureonfinalyieldwilldependonthedistributionofsoil thispossibility,themethodhasnotbeenwidelyapplied.
moistureandthelevelofcompetitionforwaterresourceswithin Heterogeneity in soil structure and composition hinders the
theplantcommunity(Kingetal.,2009). Therefore,whenaddi- acquisition of accurate values for root features in field-grown
tionalstoredmoistureisavailableindeepersoillayers,selection plants.Asanalternativetorootphenotypinginfieldexperiments,
forfastergrowinganddeeperrootscouldenhancewaterharvest anumberofstudieshavemeasuredrootsinplantsgrownunder
andhelpstabilizeyieldunderdroughtconditions. controlled conditions (Arihara and Crosbie, 1982; Price et al.,
Theimportanceofadeepandvigorousrootsystemforhigher 1997a,2002b,c;Landietal.,1998,2001a;Tuberosaetal.,2002b;
yieldhasbeen recognized in bean(Mohamed et al.,2002), soy- de Dorlodot et al.,2005, 2007; Kimurto et al., 2005; Zhu et al.,
bean(SadokandSinclair,2011),chickpea(Varshneyetal.,2011), 2006, 2011; Hochholdinger and Tuberosa, 2009; Zaman-Allah
lettuce(Johnsonetal.,2000),maize(Tuberosaetal.,2003,2007b, etal.,2011a;Renetal.,2012).Thisallowsmorerapidandaccurate
2011b;Hammeretal.,2009;Landietal.,2010;Hundetal.,2011), analysisofrootfeatures.Amajorshortcomingofthesestudiesis
barley(Forsteretal.,2005),wheat(Manschadietal.,2006,2010; the unnaturalenvironment in which the roots grow, suggesting
Wassonetal.,2012),andespecially,inrainfedrice(Nguyenetal., great caution in extrapolating the results to field-grown plants.
1997; PriceandTomos, 1997; Aliet al.,2000; Babuet al.,2003; Inmaize,asignificant,albeitweak,positiveassociationhasbeen
Courtois et al., 2003, 2009; Steele et al., 2006, 2007; Kamoshita reported between seminal root traits in hydroponics and root
et al., 2008; Witcombe et al., 2008; Bernier et al., 2009; Henry pullingresistanceinthefield(Landietal.,2001a;Tuberosaetal.,
et al., 2011). However, other experiments in rice have shown a 2002b). A reasonable compromise to avoid both the unnatural
lackofcorrelationbetween rootfeaturesanddroughtresistance conditionspresentinhydroponicsand/oraeroponicsandthedif-
(Pantuwanetal.,2002;Subashrietal.,2009). ficultyofstudyingrootsinthefieldisofferedbygrowingplants
The main drawback to the study of root features and their in pots, columns and/or observation chambers filled with soil
use as selection criteria relates to the difficulty of phenotyping (Azhiri-Sigarietal.,2000;Wadeetal.,2000;Zaman-Allahetal.,
field-grown plants (Richards, 2008). A number of techniques 2011a).Potexperimentsalsoallowforaprecisemeasurementof
allow for the estimation of root mass and its distribution in theamountofwaterprovidedtoeachplant,hencewateruseand
the soil profile. These techniques require different amounts of WUE(Priceetal.,2002b),andtoestimatethecapacityofrootsto
laborandplotdestructionforsamplecollection.Thefastestbut penetrateawaxlayerofhighmechanicalimpedancemimickinga
mostdestructivetechniquemeasurestheverticalpullingstrength soilhardpan,oftenthemainconstraintthatlimitsaccessofroots
requiredtouproottheplant,asaproxyforrootmassandarchi- to soil moisture in deeper soil layers (Cairns et al., 2004; Nhan
tecture (Lebreton et al., 1995; Sanguineti et al., 1998; Landi etal.,2006;Acunaetal.,2007).Inrice,anenhancedcapacityto
etal.,2002).Recently,ahigh-throughput,albeitequallydestruc- penetrateasoilhardpanisconsideredanessentialfeatureforthe
tiveapproachalsoknownas“shovelomics,”hasbeendeployedto development of deeper roots under rainfed lowland conditions
investigateseveralrootarchitecturalfeaturesinfield-grownmaize (Fukai and Cooper, 1995) and is a key factor in drought adap-
(Trachsel et al., 2011). Other less destructive but much more tation in areas where water supply is limited (Siopongco et al.,
time-consumingtechniquessuchasexcavationandcoringmeth- 2009).
ods have alsobeen used to estimate root mass and distribution Gel- or soil-filled chambers, soil sacs, pouches, paper rolls,
(Nissenetal.,2008). X-raymicrotomography,andmagneticresonanceimaging(MRI)
Minirhizotronsprovideanon-destructive,insitumethodfor have also been used to investigate bi- and tri-dimensional root
directly viewing and studying fine roots (Johnson et al., 2001; architecture (Bengough et al., 2004; Sanguineti et al., 2007;
SmitandGroenwold,2005).Tubeinstallationiscritical,andsteps Hargreavesetal.,2009;NortonandPrice,2009;Rutaetal.,2010;
must be taken to ensure good soil/tube contact without com- Tracyetal.,2010;Bovinaetal.,2011;Clarketal.,2011;Rascher
pacting the soil. Tube installation causes some degree of soil et al., 2011; Singh et al., 2011; Alhosein et al., 2012; De Smet
disturbanceandhasthepotentialtocreateartifacts inrootdata etal.,2012;Hamadaetal.,2012;Maceetal.,2012).Theseexper-
collection and analysis, resulting in biased values. Therefore, a iments are particularly suited to the discovery of QTLs that are
waiting period of a few months between tube installation and prevalentlyexpressedinaconstitutivefashionandwhich,assuch,
imagecollectionisrecommendedtoallowrootstorecolonizethe aremorelikelytoinfluencerootarchitecturalfeatures(e.g.,root
spacearoundthetubesandtopermitnutrientstoreturntopre- angle)acrossdifferentsoilconditions.
disturbancelevels(Johnsonetal.,2001).Thefrequencyofimage
collectiondependsupontherootparametersbeingmeasuredor FLOWERINGTIME
calculated, and the time and resources available for collecting Flowering time is recognized as the most critical factor to opti-
imagesandextractingdata. mizeadaptation,henceyield,inenvironmentsdifferinginwater
FrontiersinPhysiology|PlantPhysiology September2012|Volume3|Article347|4
Tuberosa Phenotypingfordroughttolerance
availabilityanddistributionduringthegrowingseason(Richards, allinintermediateconditions(Condonetal.,1993,2004).These
2006).Positiveassociationsbetween plasticityofyieldandflow- results can be interpreted based on the influenceof both stom-
ering time across different levels of water availabilityhave been atal conductance and photosynthetic activity on (cid:2)13C, and on
reported in different crops (Sadras et al., 2009). Therefore, in thefactthatbiomassproductionislimitedinwetyearsbyalower
addition to phenology per se (i.e., mean time to a phenological stomatal conductance—an advantageunder droughtconditions
stage), plasticity of phenological development merits consider- (Turner, 1997). (cid:2)13C measured in grains correlates positively
ation as a distinct trait influencing crop adaptation and the with growth cycle duration (Araus et al., 1997) and negatively
outcomeofanyQTLexperimentwheretheeffectsofphenology withleaftemperature(Richardsetal.,2002).Therefore,therela-
onyieldarenotdulyrecognizedandaccountedfor(Pintoetal., tionship between (cid:2)13C and GY depends on the environmental
2010;Sabadinetal.,2012). conditions,thephenologyofthecropandtheplantorgan(e.g.,
Many studies have investigated the genetic basis of flower- leaforgrain)fromwhichthesamplesarecollected(Arausetal.,
ing time, reflecting the economic importance of this trait. In 1997;Merahetal.,2001;Condonetal.,2004).
annualcrops,thegeneticbasisoffloweringtimeismorecomplex High genetic variation for grain (cid:2)13C has been reported in
in temperate species (e.g., barley, wheat, rye, etc.) as compared C species(Turner,1997;Chenetal.,2012),withhighheritabil-
3
to tropical species (e.g., rice, sorghum, maize, etc.), due to the ity(e.g., from0.76to 0.85indurumwheat; Merahetal.,2001)
presenceintheformer group of verbalizationgenes influencing andalowGEI(Richards,1996;Rebetzkeetal.,2008a).Forthese
flowering time in response to low temperatures. In cereals, the characteristics,(cid:2)13Cisanattractivebreedingtargetforimprov-
switchfromthevegetativetothereproductivephaseiscontrolled, ingWUEandyield,whilethehighcostrequiredtomeasureeach
accordingtothespecies,byseveralgenesresponsivetoverbaliza- samplemakesitaninterestingcandidateforMAS.
tionand/ordaylengthaswellasbylociforearlinessperse(Salvi
etal.,2002,2007,2011;Distelfeldetal.,2009). STOMATALCONDUCTANCE
In maize, a valuable selection target for improving drought Stomatalconductanceplaysapivotalroleinregulatingthewater
resistance is provided by the anthesis-silking interval (ASI), a balanceoftheplantanddetermining(cid:2)13CandWUE(Condon
traitof intermediate heritabilitythatisusuallynegatively corre- etal.,2002;Richardsetal.,2002,2007;Sinclairetal.,2008,2010).
latedwithGYunderdroughtconditions(BolañosandEdmeades, A retrospective study conducted by Fischer et al. (1998) on a
1996; Monneveux and Ribaut, 2006). Because ASI can be phe- historical series of successful bread wheat cultivars released by
notypedquiteeasilyandeffectivelyundertherightexperimental CIMMYTfrom1962to1988showedastrongpositivecorrelation
conditions, substantial breeding efforts have targeted this trait between stomatal conductance andGY (r=0.94; Fischer et al.,
throughconventionalbreeding(ChapmanandEdmeades,1999) 1998), indicating the possibility of raising the yield potential,
or,onceQTLshavebeenidentified(Ribautetal.,1996;Lietal., hencetheamountofwaterusedbythecrop,throughanindirect
2003a; Hao et al., 2008), with marker-assisted selection (MAS) selectionforstomatalconductanceand/orleaftemperature.
(Ribautetal.,2004;RibautandRagot,2007).Thenegativeassoci- Given the laborious nature of measuring stomatal conduc-
ationreportedbetweentheeffectsofQTLsthathavebeenshown tance, identifying the corresponding QTLs would allow for the
toinfluenceboth leafelongationandASIsuggests turgormain- implementationofMAS.Infact,itisdifficulttoaccuratelymea-
tenance as a possible common mechanism accounting for the surestomatalconductanceinareasonablylargenumberofplants
correlation(Welckeretal.,2007). while properly accounting for thefluctuation in the main envi-
ronmentalfactorsknowntoaffectstomatalconductanceduring
CARBONISOTOPEDISCRIMINATION theday(wind,solarradiation,humidity,etc.).Anumberofstud-
Carbonisotopediscrimination((cid:2)13C)measurestheratioofsta- ieshavereportedQTLsforstomatalconductance(Lebretonetal.,
blecarbonisotopes(13C/12C)intheplantdrymattercompared 1995;Priceetal.,1997b,2002a;Sanguinetietal.,1999;Ulloaetal.,
totheratiointheatmosphere(Condonetal.,1990).Becauseof 2000;Takaietal.,2006;KhowajaandPrice,2008).
differences inleaf anatomyandthemechanisms of carbonfixa- A more attractive and integrative way to indirectly monitor
tioninspecieswiththeC orC pathway,studieson(cid:2)13Chave stomatalconductancethroughanextendedtime-periodisbased
3 4
widerimplicationsforC specieswherethevariationin(cid:2)13Cis onthemeasurement ofthenaturaloxygenisotope composition
3
largerthaninC species andhasagreaterimpactoncropyield (d18O) in leaf and grain materials (Barbour et al., 2000; Ferrio
4
(Condonetal.,1990,2006).Commonly,butnotalways(Turner et al., 2007). Compared with stomatal conductance, measuring
et al., 2007), (cid:2)13C is negatively associated with WUE over the d18Oinplantmaterialoffersfouradvantages:(1)itprovidesan
period of dry mass accumulation (Condon et al., 1990, 2004; integrated measure of stomatal conductance and leaf tempera-
Arausetal.,2002;Rebetzkeetal.,2002;Xuetal.,2007;Royoetal., ture over the period that the analyzedtissue was formed; (2) it
2008). avoidsanumberofexperimentalproblemstypicalofmeasuring
Under drought stress, (cid:2)13C is a good predictor of stom- stomatal conductance; (3) it allows for the collection of a large
atal conductance (Condon et al., 2002) and WUE in different numberofsamples,and(4)requiresverylittlelaborinthefield.
crops (Turner, 1997; Tambussi et al.,2007). A number of stud- InthehistoricalseriesofCIMMYTwheatcultivarstestedunder
iesconductedinbreadwheatundervaryingconditionsofwater irrigatedconditions(seeabove),leafd18Owasstronglycorrelated
availability have shown that the correlation between (cid:2)13C and with stomatal conductance (r=−0.93; Barbour et al., 2000).
finalGYvariesfrompositive,whenamplewaterisavailabletothe In this case, GY was more strongly correlated with leaf d18O
crop, to negative in drought conditions, with no correlation at (r=−0.90)ascomparedtoleafd13C(r=−0.71).However,the
www.frontiersin.org September2012|Volume3|Article347|5
Tuberosa Phenotypingfordroughttolerance
authorscautionthatd18Oisaquestionableyieldpredictorwhen is a fundamental component of the mechanisms allowing the
stomatalconductanceandGYarenotstronglycorrelated. plantto match the water demandwith the water supply and to
optimizegrowthandsurvivalinresponsetobothdailyandmore
CANOPYTEMPERATUREDEPRESSION long-termenvironmentalfluctuations(ZhangandDavies,1990;
CTD as measured by thermal imaging is the difference in tem- Xiongetal.,2007).Indeed, anincreaseinABAconcentrationis
perature between the canopy surface and the surrounding air. auniversalresponseobservedinplantssubjectedtodroughtand
CTDisahighlyintegratingtraitresultingfromtheeffectsofsev- otherabioticstresses(Quarrie,1991;Setter,2006).Additionally,
eralbiochemicalandmorphophysiologicalfeaturesactingatthe ABAmodulatestheexpressionofalargenumberofgeneswhose
root,stomata,leaf,andcanopylevels.Inthefield,genotypeswith productsprotectthecellfromtheharmfuleffectsofdehydration
a cooler canopy temperature under drought stress, or a higher (Bray,2002;Sekietal.,2007).
CTD,usemoreoftheavailablewaterinthesoiltoavoidexcessive ABA has been shown to affect many of the traits that influ-
dehydration(Blum,1988;LudlowandMuchow,1990;Reynolds ence the water balance of the plant through both dehydration
etal.,2007,2009).Infraredthermometrycanreportsubtlediffer- avoidance and dehydration tolerance (Thompson et al., 2007).
encesinleaftemperatureinbothfieldandcontrolledconditions Inmaizeseedlingssubjectedtoartificiallyinducedconditionsof
(Blumet al.,1982; Jones et al.,2003, 2009; Chaerleet al.,2007; waterdeprivation,anincreasedABAconcentrationenhancedthe
Winterhalter et al.,2011a,b). Importantly, datacollection is fast root/shoot ratio (Spollen et al., 2000; Sharp, 2002; Sharp et al.,
andnon-destructive. 2004),anadaptivechangebeneficialforincreasingwateruptake.
CTDisusefulmainlyinhotanddryenvironmentstypicalof IthasalsobeenshownthatABAfacilitateswateruptakeintoroots
countries with a Mediterranean climate. Measurements should asthesoilbeginstodry,particularlyundernon-transpiringcon-
preferablybemadeonrecentlyirrigated cropsoncloudlessand ditions, when the apoplastic path of water transport is largely
windlessdayswithhighvaporpressuredeficits.Underthesecon- excluded (Hose et al., 2001). Under terminal drought, toler-
ditions andprovidedthatdataarecollected when thecanopyis antpearl millet [Pennisetum glaucum (L.)R. Br.]havehigh leaf
sufficientlyexpandedtocover thesoil,CTDcanbeagood pre- ABAandreducedtranspirationathighvapor pressuredeficit,a
dictor of wheat GY (r =0.6–0.8; Reynolds and Pfeiffer, 2000). feature that highlights the important role of constitutive water-
In bread wheat, yield progress was found to be associated with conservingmechanisms in maximizingyield under such condi-
coolercanopies(Fischeretal.,1998)andsignificantgeneticgains tions (Kholova et al., 2010a,b). The positive role on yield of a
inyieldhavebeenreportedinresponsetodirectselectionforCTD conservativewateruse,ratherthandeeporprofuserooting,has
(Reynoldsetal.,1999,2009;Brennanetal.,2007).Theaddition alsobeenhighlightedinchickpea(Zaman-Allahetal.,2011a,b).
ofCTDasaselection criterioninwheatnurseryimprovedcon- In cereals, an accumulation of ABA has been implicated as
siderablytheidentificationofthehighestyieldingmaterials(van oneofthefactorsthatinfluencereproductivefertility(Sainiand
GinkelandOgbonnaya,2007).Theseresultsareinkeepingwith Westgate,2000;Landietal.,2001b;Setteretal.,2001;Boyerand
theconclusionsofOlivares-Villegasetal.(2007):“Canopytemper- Westgate, 2004; McLaughlin andBoyer, 2007; Yanget al., 2007;
ature epitomises a mechanism of dehydrationavoidance expressed Tang et al., 2008; Zhang et al., 2009) and endosperm develop-
throughoutthecycleandacrosslatitudes,whichcanbeutilizedasa ment(Oberetal.,1991;Tuberosaetal.,1992;Setteretal.,1996;
selectioncriteriontoidentifyhigh-yieldingwheatgenotypesorasan Mambelli andSetter, 1998; Seiler et al.,2011). In rice, selection
importantpredictorofyieldperformanceunderdrought.” for reduced ABA root signaling has been advocated as a means
Grantetal.(2006)investigatedtherobustnessandsensitivity for better exploitation of subsoil water under mild or transient
ofthermalimagingfordetectingchangesinstomatalconductance waterdeficit(Siopongcoetal.,2008,2009).
andleafwaterstatusinarangeofplantspecies(grapevine,bean SensitivitytoABAisalsoofinterestforitsimplicationsonthe
andlupin)under greenhouseor controlled environmentcondi- adaptive response of plants to drought (Cominelli et al., 2005).
tions. In particular, they compared absolute leaf temperatures Genetic variability for sensitivity to ABA has been reported in
and thermal indices of plant stress with stomatal conductance maize (Frascaroli and Tuberosa, 1993). Gametophytic selection
andwaterpotential.Thermalimagingsuccessfullydistinguished carriedoutbysprayingmaizesilkswithanABAsolutionbefore
between irrigated and non-irrigated plants of different species, pollination led to significant effects on early vigor and other
with strong correlations between thermal indices and stomatal agronomictraits(FrascaroliandLandi,1996;Landietal.,2000).
conductanceasmeasuredwithaleafpyrometer.Theirresultsalso DuetotheavailabilityofABA-specificmonoclonalantibodies
highlighted factors such as leaf angle that should be addressed (Quarrie et al., 1988) that allow for the cost-effective measure-
whenusingthermalimagingforindirectmeasurementofthelevel ment of a large number of samples, several studies have been
ofdroughtstressofthetestedmaterials.Additionally,theseresults devotedtotheidentificationofQTLsforABAconcentrationand
are valuable for the design of protocols for application in crop the analysis of their associated effects on other drought-related
productionorecosystemmonitoring. traitsandyield(Lebretonetal.,1995;Tuberosaetal.,1998,2002a;
Sanguinetietal.,1999;Reymondetal.,2003;Giulianietal.,2005;
ABSCISICACIDCONCENTRATION Landiet al.,2005, 2007; Rahmanetal.,2011). Altogether, these
Oneofthemainfactorsinfluencingleaftemperatureviaaneffect studies do not provide a unifyingpicture of the role of ABA in
on transpiration through stomatal conductance is the concen- determiningyield,perhaps notunexpectedly in viewof thedif-
tration of ABA in the leaf tissue and, ultimately, in guard cells ferent species and genetic backgrounds involved. Nevertheless,
(Wasilewskaetal.,2008;Sirichandraetal.,2009).Therefore,ABA it is worth noting that the evaluation of an historical series of
FrontiersinPhysiology|PlantPhysiology September2012|Volume3|Article347|6
Tuberosa Phenotypingfordroughttolerance
maize hybridsreleased in the past60 years has shown a signifi- 2000;Shuklaetal.,2004).InUSCornBeltmaize,stay-greenhas
cantdecrease inthecapacity to accumulateABA in response to improvedsignificantlyandsteadilyduringthepastsixdecadesof
agivenlevelofwaterstress (Sanguinetietal.,2006)and,conse- breeding,particularlyunderfavorableconditions(Duvick,2005).
quently,anegativecorrelation(r=−0.62)betweenthecapacity Additionally,stay-greentraitsinmaizecorrelatecloselytoGY,and
toaccumulateABAattheseedlingstage(atraitneverselectedfor multiple intervals of stay-green QTLs overlap with yield QTLs
bybreeders)andGY. (Zhengetal.,2009). Although,stay-greeninmaizeseems more
likelytoberelatedtonitrogenuse,insorghumithasbeenrelated
OSMOTICADJUSTMENT tomaintenanceofamorefavorablewaterstatusasrelatedtoroot
OAisametabolicprocessentailinganetincreaseinintercellular features(GallaisandHirel,2004;Blum,2006;Maceetal.,2012).
solutes in response to water stress (Morgan, 1984; Zhanget al., In sorghum, four major QTLs that control stay-green and GY
1999; Serraj and Sinclair, 2002). As soil moisture declines, OA havebeenidentified(Harrisetal.,2007)andnearisogeniclines
favorsturgormaintenance,andhencetheintegrityofmetabolic (NILs)fortheseQTLshavebeenderived,providinganopportu-
functions.Importantly,OAcanbiasestimatesofthevalueofrela- nityforadetailedanalysisofstay-greenphysiologyandpositional
tivewatercontent,ashasbeenshowninwheatandbarley(Boyer cloningoftheunderlyinggenes(Vadezetal.,2011).
etal.,2008).
OAhasbeen implicatedinsustainingyieldunder conditions REMOBILIZATIONOFWATER-SOLUBLECARBOHYDRATES
of water deficit in oilseed Brassica species (Kumar and Singh, RemobilizationofWSCfromthestemandleavescanmitigatethe
1998),chickpea(Basuetal.,2007),cotton(Sarangaetal.,2001), negative effects ongrainfillingcausedbypost-anthesis drought
rice (Babu et al., 1999; Jongdee et al., 2002; Praba et al., 2009), tolerance(Blum, 1988, 1998; Araus et al.,2002; Reynoldset al.,
sorghum (Tangpremsri et al., 1995), maize (Chimenti et al., 2007;Rebetzkeetal.,2008b).QTLsforstem-reserveremobiliza-
2006),tef(Ayeleetal.,2001),barley(Gonzalezetal.,2008),and tionhavebeenreportedinbreadwheat(Salemetal.,2007;Snape
wheat (Ali et al., 1999; Blum et al., 1999; Salem et al., 2007; et al., 2007; Yang et al., 2007). Rebetzke et al. (2008b) pheno-
Ehdaie et al., 2008; Fan et al., 2008; Izanloo et al., 2008). Yet typedthreewheatmappingpopulationsforWSCconcentration
the value of OA as a desirable selection target from a breeding (WSC-C)andforWSCmassperunitarea(WSC-A).Genotypes
standpointhasbeenquestioned(Munns,1988;Paltaetal.,2007), with highWSC-C were commonly shorter, flowered earlier and
based on the notion that drought-tolerant genotypes endowed producedsignificantlyfewertillersthanthoseoflowWSC-C.This
withahighercapacitytoadjustosmoticallyarelikelytobechar- resulted in similar yields, lower final biomass, and fewer grains
acterizedbyslowgrowth,andhencebiomassproduction,dueto per m2, but greater dry weight partitioning to grain and kernel
themetabolicrequirementsofosmolytebiosynthesis.Undercon- weight in high versus low WSC-C genotypes. In contrast, lines
ditions of severe dehydration, a higher capacity to accumulate highforWSC-Aproducedmorefertiletillersassociatedwithsim-
osmolytes mayhelpplantswithstandaprolongeddrought spell ilarorgreateranthesisandmaturitybiomass,grainnumberand
andundergoamorepromptandcomplete recoveryuponrehy- yield,yetsimilarkernelweightorsizecomparedwithgenotypes
dration.Even though,the interpretation of osmotic relations in withlowWSC-A,thussuggestinganimportantroleforWSC-A
genetically engineered plants can be cumbersome (Blum et al., inassuringstableyieldandgrainsizeinwheat.
1996),transformationexperimentshaveshedlightonthemech- This overview of drought-adaptive traits, far from being
anismsby which plants maybenefitfroman alteredcapacity to exhaustive,indicatesthatgeneticvariabilityindroughttolerance
accumulateosmolytes(Umezawaetal.,2006).Similarlytoother andWUEcanbetracedtotheinteractionofamultitudeofquan-
drought-adaptive traits, the trade-off between the metabolic titatively inherited morphophysiological features, whose effects
requirementsofOAandthepotentialbenefitsforthecropvaries onyieldcanvarygreatlybothintermsofmagnitudeanddirec-
onacase-by-casebasisasafunctionofthecrop,andthedynamics tionaccordingtotheprevailingdroughtscenarioandotheryield
andseverityofthedroughtepisodes. constraints.Therefore,theadoptionofdrought-adaptivetraitsas
selectioncriteriaforyieldshouldbeexercisedcautiouslyandonly
CHLOROPHYLLCONCENTRATION,STAY-GREEN,ANDDELAYED afteracquiringaclearunderstandingofthefactorslimitingyield
LEAFSENESCENCE in the TPE. Identifying the QTLs underpinning such traits and
Awell-sustainedsourcecapacityisakeyfactortomaximizeyield interpretingtheircause–effect relationshipsallowus topartially
potentialduringbothvegetativeandreproductivephases,partic- disentanglethiscomplexitytoanextentand,eventually,makeit
ularly under source-limiting conditions that commonly charac- amenabletoamoredirectandeffectivemanipulationforbreed-
terizedrought-stressedcrops.Therefore,delayingleafsenescence ingpurposes.Inbothcases,goodphenotypicdataareessentialto
maintainstranspirationandincreasescumulativephotosynthesis success.
overthecroplifecycle(Borrelletal.,2001;Jiangetal.,2004;Vadez
etal.,2011).Thisisastrategythatisadequateforsoilswithappre- COLLECTINGGOODPHENOTYPICDATA
ciablewaterreservesbutmayotherwisecauseseverestressatthe Plantscientistsattemptingtoimproveresistancetodroughtface
endofthegrowthseasonduetoincreasedtranspiration. twocontrastingandapparentlyirreconcilablerequirements.The
Thetraitsthathavebeenmonitoredmostfrequentlytoobtain first is to simplify “the system” in order to facilitate elucida-
indirect estimates of photosynthetic potential are chlorophyll tion of the function of the relevant loci for the target traits
concentration, stay-green and delayed senescence, all of which (i.e., the reductionist approach). The second is to evaluate the
areinterconnected (Tuinstraetal.,1998;ThomasandHowarth, broader valueof such findings inabreeding andagronomically
www.frontiersin.org September2012|Volume3|Article347|7
Tuberosa Phenotypingfordroughttolerance
sound context (i.e., the holistic approach), where the physi- The basic attributes of good phenotyping carried out with
ology, epistatic interactions and pleiotropic effects of complex appropriategeneticmaterialsareaccuracyandprecisionofmea-
traits inevitably limit and blur the identification of the main surements, coupled with relevant experimental conditions that
factorsleadingtospecificphenotypes(e.g.,drought-resistantver- are representative of the TPE. Accuracy involves the degree of
sus drought-susceptible). In a way, the reductionist approach closenessofameasuredorcalculatedquantitytoitsactual(true)
is like trying to understand the subject of an entire puz- value.Accuracyiscloselyrelatedtoprecision,alsotermedrepro-
zle when only a few pieces are available. On the other hand, ducibilityorrepeatability,thedegree towhichfurther measure-
the holistic approach selecting, for example, for yield per se ments or calculations show the same or similar results. For a
will provide a complete picture of the puzzle (i.e., the phe- numberoftraitssuchasstomatalconductance,flowofxylemsap,
notype). However, it will often not allow us to tease the puz- etc., measured with mechanical or electronic devices, accuracy
zle apart to the extent that we would need to apply targeted andprecisioninmeasurementsrequirecalibrationoftheinstru-
approachessuchasMASand/orgeneticengineering,becauseof mentpriortodatacollection.Failuretosodowillproducebiased
our incomplete understanding of the number and function of resultswithadifferencebetweenthemeanofthemeasurements
the single pieces such are the QTLs for yield. Valuable oppor- andthetruereferencevalue.Afurthercomplexityofphenotyp-
tunities to begin to reconcile this conundrum are provided by ing a large number of genotypes (e.g., a mapping population
bioinformatics (Sawkins et al., 2004) and modeling (Hammer or an association mapping panel)for drought-adaptive features
et al., 2004, 2006; Cooper et al., 2009; Tardieu and Tuberosa, is exemplified by those traits such as stomatal conductance and
2010; Sinclair et al., 2010; Messina et al., 2011). Both mod- tissue water potential, the valueof which can vary considerably
eling and high-throughput phenotyping for drought-adaptive withinarathershorttimeframeduetochangingenvironmental
features are at the very core of DROPS (DROught-tolerant conditions.
yielding PlantS; www.drops-project.eu), an ongoing EU-funded An important distinction should be made between experi-
project aiming at improving our understanding and capac- ments aimed at (1) collecting data useful to dissect the genetic
ity to ameliorate yield and yield stability under water-limited basis of target traits or (2) breeding activities for the release of
conditions. improvedcultivars.Inbothcases,anadequatechoiceofmaterials
Yet the objective of this review is not to dwell on the mer- willbeessentialforsuccessfullymeetingthedesiredobjectives.A
its and pitfall of the reductionist and holistic approaches (see notablecasethatclearlyunderscorestheimportanceofgoodphe-
also Passioura, 2010). Rather, it seeks to introduce and discuss notypingisprovidedbyQTLcloning(SalviandTuberosa,2007).
a number of major issues on phenotyping that are relevant for Inthisrespect,theidealscenarioiswhenthealternativeQTLalle-
bothapproaches.Theseissuesshouldbeconsideredseriouslyin lescanbeunequivocallyscoredphenotypicallyandthetraititself
planningandmanagingexperiments underdroughtconditions, ismappedasoneofthemarkers.
collectingandanalyzingthedataand,eventually,ininterpreting
theresultsproperly. PHENOTYPINGISKINGANDHERITABILITYISQUEEN
Given the myriadof factors thatcan influencethe qualityof Good phenotyping means not only the collection of accurate
phenotypicdata,thisreview onlyaddresses themostimportant datatominimizetheexperimental“noise”introducedbyuncon-
ones.Although,itispossibletodefinegeneralrules,eachexper- trolled environmental andexperimental variability,but alsothe
imenthasitsown“phenotypingstory”andtheresultsshouldbe collectionofdatathatarerelevantandmeaningfulfromabiolog-
dealt with and interpreted accordingly. What follows is equally icalandagronomic standpoint, under the conditions prevailing
relevantfortheimprovementofcropperformanceunderwater- in farmers’ fields within the TPE. Although, hundreds of accu-
limited conditions and, more generally, for experiments in the rate studies reporting thousands of drought-responsive genes
fieldorundercontrolledconditionsaimedatdissectingthephys- andQTLs can be found in the literature, the relevance of these
iological and genetic basis of crop adaptation to water-limited data to “real” field conditions is often marginal andeven ques-
conditions. However, given the importance of field evaluation tionable; only seldom has it been appropriately addressed and
for breeding purposes, phenotyping under field conditions is discussed. In theearlystages followingtheir development, eval-
emphasized. uation of transgenic materials is limited to experiments carried
outingreenhouses,aconditionthatunderlinestheimportanceto
WHATDOES“GOODPHENOTYPING”MEAN? mimicascloseaspossiblethedroughtstressconditionsinfields
Good phenotyping is pivotal for reducing the genotype– (SaintPierreetal.,2012).
phenotype gap, especially for quantitative traits, which are the Collecting accurate phenotypic data that are relevant to the
majordeterminantsofdroughtresistance.Keepingagoodrecord TPE has always been a major challenge for the improvement
ofmeteorologicalparameters(rainfall,temperatures,wind,evap- of quantitative traits. The success of this endeavor is intimately
otranspiration, light intensity, etc.) allows for more meaningful connected with the heritability of the trait, namely the portion
interpretation of the results and identification of the environ- of the phenotypic variability accounted for by additive genetic
mental factors limitingyield (Sadras,2002). Equallyimportant, effects that can be inherited through sexually propagated gen-
though often neglected or ignored, are the physical-chemical erations (Falconer, 1981). Trait heritability varies greatly (from
propertiesofthesoil,particularlythoseinfluencingthewaterbal- 0 to 1) according to: (1) the genetic makeup of the materi-
ance of the crop under decreasing moisture conditions (Cairns alsunderinvestigation; (2)theenvironmentalconditionsunder
etal.,2011). which such materials are grown and evaluated; and (3) the
FrontiersinPhysiology|PlantPhysiology September2012|Volume3|Article347|8
Tuberosa Phenotypingfordroughttolerance
accuracyandprecision of thephenotypicdata.With onlya few analysisofQTL-by-environmentinteractions(vanEeuwijketal.,
notableexceptions (e.g.,floweringtimeandcarbon-isotopedis- 2005;Vargasetal.,2006;Burguenoetal.,2008)orbyidentifying
crimination), most of the traits determining the performance intrinsic characteristics of each genotype relating to its interac-
of crops under drought conditions usually have low (0.3–0.4) tionwithparticularenvironmentalconditions,whichrequiresthe
or, at best, intermediate (0.4–0.7) heritability. This impairs our developmentofmodelsabletoidentifythesevariablesandtosim-
capacitytodissecttheirgeneticbasisproperlyand,moreimpor- ulatethebehaviorofgenotypesinabroadrangeofenvironments
tantly,reducestheeffectivenessofphenotypicselection(Falconer, (Tardieu, 2003; Yin et al., 2003; Reymond et al., 2004; Cooper
1981). Despitethis,carefulevaluationandappropriatemanage- etal.,2009;Sinclairetal.,2010).
ment of the experimental factors that lower the heritability of A number of studies haveshown the importance of epistasis
traits,coupledwithawisechoiceofthegeneticmaterial,canpro- indeterminingthegeneticarchitectureofyieldandotherquanti-
videeffectivewaystoincreaseheritability,andhencetheresponse tativetraits(Lietal.,2003b; Maccaferrietal.,2008;Zhaoetal.,
tophenotypicselection. 2008; Frascaroli et al., 2009; Messmer et al., 2009; Ravi et al.,
Once a sound association has been established between a 2011).However,mappingtwo-wayepistaticinteractionsrequires
markerandalocusaffectingatargettrait,theproblemsencoun- adequatelylargemappingpopulation,anddetectinghigherorder
tered in the conventional selection of quantitative traits, par- epistasis is practically out of reach. Once different sets of NILs
ticularly the lowly-heritable ones, can been partially overcome becomeavailableforlocithatareknowntointeractepistatically,
through the use of markers linked to QTLs for the target trait. it will be possible to produce different combinations at will for
Thisenablesindividualstobescoredbasedontheirgeneticmake- furthertestingandcharacterizationoftheeffectsofsuchepistatic
up rather thantheir phenotypic features (Peleman andVander interactions.
Voort, 2003; Langridge, 2005). Paradoxically, the probability of
identifyingtherelevantchromosomalregionsandaccuratelyesti-
MONITORINGPLANT–SOILWATERRELATIONS
mating their effects relies on good phenotyping of the genetic
Asoundinterpretationoftheresultsofanexperimentconducted
materials originally used to establish the phenotype–genotype
underconditionsofwatershortagerequiresagoodcharacteriza-
associations. In other words, the effectiveness of marker-based
tionofthesoil–plant–atmospherecontinuum(SPAC),which,in
approachesintimatelydependsonhowwell andhowaccurately
turn,reliesonaccuratemonitoringofthewaterstatusofbothsoil
the target trait has been assessed phenotypically in mapping
andplant.Fromanexperimentalstandpoint,animportantissue
populations. In fact, a low heritability impairs the probability
istowhatextentgenotypicdifferencesindrought-adaptivetraits
of detecting the presence of QTLs (Bernardo, 2004), thereby
measured in phenotyping platforms at different water regimes
increasing Type II errors (i.e., false negatives). An accurate and
reflectgenotypeperformanceacrosswateringregimesunderfield
relevantphenotypingisofevengreaterimportancewhenapply-
conditions.Alongthisline,encouragingresultshaverecentlybeen
ing genome-wide selection, an approach that disregards QTL
reportedinmaize(Chapuisetal.,2012).
identificationandreliesonthemolecularprofilingandaccurate
Regrettably, a unique means of measuring water status that
phenotypingofeachprogeny(BernardoandYu,2007;Bernardo,
canbeappliedinallpossiblesituationsisnotavailable.Choosing
2008;Heffneretal.,2009).
the most appropriate method depends on the objective being
pursued, such as understanding drought-adaptive mechanisms,
EXPERIMENTALDESIGN,DEDICATEDSOFTWARE,AND selecting fordroughtresistance,investigatingwater movements,
STATISTICALAPPROACHES ormanagingirrigationtreatments(Boyer,1995;Kirkham,2004;
It is widely recognized that a substantial part of the increased Jones, 2007). At the plant level, greater emphasis has tradition-
efficiency of modern breeding is due to the accurate pheno- allybeendevotedtowaterpotentialratherthansustainedturgor,
typing of large numbers of plots, this scale-up being made theprimaryreasonforsustainedfunctionunderdrought(Blum,
possiblebymoresophisticatedandhigh-throughputexperimen- 2006,2009).Hence,examplesofsustainedfunctionatlowwater
tal machinery as well as the streamlining and automation of status as the main reason for drought tolerance are compara-
tediousmanualoperations.Thus,thelabelingofalargenumber tively few. Maintenance of high leaf water potential and turgor
of plots and samples, data collection and storage, and keep- under dry conditions indicates dehydration avoidance (Blum,
ing track of pedigrees, etc., are now facilitated by the use of 1988; Ludlow and Muchow, 1990). Similarly, the relative water
electronics(e.g.,bar-coding)anddedicatedsoftware(e.g.,spread- content of the leaf also provides important information on the
sheets, databases, etc.). Additionally, the effectiveness of field water status of the plant, offering the advantage of collecting a
experiments andthemanagementandinterpretation of pheno- highnumberofsamplesinashorttime(Sanguinetietal.,1999),
typicdatacanbeenhancedgreatlythroughtheutilizationofthe animportantprerequisiteforQTLstudiestryingtolinkvariation
most appropriate experimental designs to allow for better con- inphysiologicalparameterstovariationinyield.Theprecautions
trolofwithin-replicatevariabilityandtoreduceorremovespatial tobeadoptedformeasuringrelativewatercontenthavebeendis-
trends. Equally important are statistical approaches to analyz- cussedbyBlum2.Although,allcomponentsofleafwaterrelations
ingthedata,particularlyforinvestigatingtheeffectsofGEI(van change during the day as irradianceand temperatures vary, the
Eeuwijk et al., 2005; van Eeuwijk, 2006; Malosetti et al., 2008; changeissmallforabout2hatandaftersolarnoon.Therefore,
Mathewsetal.,2008;Messmeretal.,2009)andepistasis(Gaoand
Zhu,2007;Jannink,2007).Copingwiththetemporalvariability
ofdrought-adaptivefeaturescanbedealtwiththroughin-depth 2http://www.plantstress.com/methods/index.asp
www.frontiersin.org September2012|Volume3|Article347|9
Tuberosa Phenotypingfordroughttolerance
this is an appropriate time window for investigating leaf water approach has been adopted to identify QTLs for yield across a
relationsinalargenumberofgenotypes2. broadrangeofwateravailability(Malosettietal.,2008;Messmer
It is equally important to monitor changes in soil moisture, et al., 2009) and to develop superior hybrids in sub-Saharan
preferablyatdifferentdepthoftherhizosphere,duringthegrowth Africa(Bänzigeretal.,2006).
and reproductive cycle of the crop. Root water uptake is one Retrospective studies conducted with an historical series of
of thepivotal processes within theSPAC.Whilethegravimetric maize hybrids showed that screening in multiple sites at high
method (i.e.,weighingsamplesof soilcolumns beforeandafter plant densities provides substantial yield gains across a broad
ovendrying)providesaccurate,albeittime-consuming,measure- range of environments, although, rates of gain in well-watered
mentofsoilmoisture,othermethodssuchastheneutronprobe, conditionsaremorethantwiceashighasthoseinwater-stressed
the capacity method and the “I-sensor” allow for quicker and environments(Duvick,2005;Camposetal.,2006).Inwheat,four
lesslabor-intensivemeasurement(Nagyetal.,2008;Caycietal., decadesofbreedingatCIMMYThaveclearlyindicatedtheimpor-
2009). tance of selecting and managing key environments differing in
During recent decades, progress in microelectronics has their yield potential to identify the best performing genotypes
allowed the development of several dielectric-based soil water across a broad range of environments. The so-called “shuttle
monitoring techniques, namely time-domain reflectome- breeding” which was instrumental for the success of the Green
try (TDR), and single and multisensor capacitance probe Revolution(Borlaug andDowswell, 2005), remains a keyfactor
(SCP/MCP)systems(FaresandPolyakov,2006;Vereeckenetal., indevelopingmorebroadlyadaptedcultivars(Ortizetal.,2007b;
2008). These techniques have greatly simplified the real-time TrethowanandCrossa,2007).Recently,aQTLwithamajorand
determination of water content on a fine spatial and temporal consistent effect on GY in multiple elite genetic backgrounds
scale. Because of their relatively lowcost andease of operation, underbothwater-stressedandnon-stressedconditionshasbeen
MCP systems have met widespread acceptance as a means of described (Vikram et al., 2011). Consistency of the QTL effect
closely monitoring soil moisture by collecting high-resolution acrossdifferentgeneticbackgroundsmakesitasuitablecandidate
soil-watercontentdataintherhizosphere.Despitetheirsuccess, foruseinmarker-assistedbreeding.
MCPsystemshaveshownsometemperatureandsalinityeffects
indifferentsoiltypes,suggestingthatfurtherresearchisneeded PHENOTYPINGINTHEFIELD
to eliminate such effects for these capacitance systems to take Assumingthatboththetypeandthenumberoftreatments(geno-
theirplaceasleadingsoilwatermonitoringsensors. types, irrigation volumes, etc.) to be evaluated are adequate for
TDR has been one of the most widely used techniques to the specific objectives of each experiment, the following gen-
determine soil volumetric water content thanks to its high pre- eralfactorsshouldbeevaluatedcarefullytoensurethecollection
cision,non-ionizingradiationandlowinfluenceof soilsalinity, of meaningful phenotypic data in field experiments conducted
bulk density and texture (Noborio, 2001). However, compared underwater-limitedconditions:
to the neutron probe, most of the TDR equipment available
doesnotallowdetailedmeasurementalongthesoilprofile.Also, • Experimentaldesign
the use of conventional TDR probes requires drilling holes or • Heterogeneityofexperimentalconditionsbetweenandwithin
opening trenches in the soil to install the probes, limiting the experimentalunits
number of points measured in the soil profile (Manieri et al., • Sizeoftheexperimentalunitandnumberofreplicates
2007).Morerecently,two-dimensionalgeoelectricaltomography • Numberofsampledplantswithineachexperimentalunit
has been used for monitoring soil-water redistribution due to • Genotype-by-environment-by-managementinteraction.
water uptake by lupin roots (Werban et al., 2008). The result-
ing average water content from two-dimensional geoelectrical The relative impact of each factor on the quality of the phe-
tomographyagreedwellwiththevaluesdeterminedbytheTDR notypic data to be collected will vary greatly according to each
measurementsmodel. experiment. As an example, an excessive heterogeneity in soil
characteristics (depth, moisture, pH, etc.), and/or compaction
WHATSEVERITYOFWATERSHORTAGE? amongfieldplotswillinevitablyincreasetheexperimentalerror
Unlike yield under conditions of severe drought stress (>70% and will jeopardize an accurate evaluation of yield. Mapping
reductionfromyieldunderwell-wateredconditions)yieldunder thesoilinexperimentalnurseriesforenvironmentalfactorsthat
moremoderatewatershortage(uptoapproximately50%reduc- decrease phenotypic accuracy (Cairns et al., 2004, 2011; Rossel
tion) reflects more closely yield potential under favorable con- etal.,2006;Patzoldetal.,2008)andadoptingsuitableexperimen-
ditions (Blum, 2006). Therefore, drought resistance per se is taldesignscanpartiallymitigatethenegativeeffects ofhighsoil
expected to playa progressively more important rolethanyield heterogeneity.
potential as the severity of drought escalates, with genotype Forexperimental activities carriedoutunderdroughtcondi-
ranking for yield changing considerably once the mean yield tions, the additional factors discussed below should receive due
falls below 20–30% of yield potential (Blum, 2006) as a result attentionwhenplanningandconductingtheexperiments.
of water scarcity. Consequently, germplasm evaluation in areas
wheredroughtseverityfluctuateswidelyshouldpreferablybecar- VARIATIONINPHENOLOGY
ried out under well-watered conditions and at different levels In environments where escape is the predominant cause of
of drought stress (e.g., intermediate and severe). In maize, this droughtresistance,thepresenceoflargedifferencesinflowering
FrontiersinPhysiology|PlantPhysiology September2012|Volume3|Article347|10