Evaluation of agronomic traits and spectral reflectance in Pacific Northwest winter wheat under rain-fed and irrigated conditions

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ContentslistsavailableatScienceDirect

Field

Crops

Research

j o ur na l h o me pa g e :w w w . e l s e v i e r . c o m / l o c a t e / f c r

Evaluation

of

agronomic

traits

and

spectral

reﬂectance

in

Paciﬁc

Northwest

winter

wheat

under

rain-fed

and

irrigated

conditions

Shiferaw

A. Gizaw

a

_,

_Kimberly

_{Garland-Campbell}

b

_,

_Arron

_H.

_Carter

a,∗

a_Department_of_Crop_and_Soil_Sciences,_Washington_State_University_Pullman,_WA_99164-6420,_USA

b_US_Department_of_Agriculture,_Agricultural_Research_Service,_Wheat_Genetics,_Quality,_Physiology_and_Disease_Research_Unit_Pullman,_WA_99164-6420,

USA

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received23February2016

Receivedinrevisedform20June2016 Accepted22June2016

Availableonline6July2016

Keywords:

Spectralreﬂectanceindices PaciﬁcNorthwest Winterwheat Droughttolerance

a

b

s

t

r

a

c

t

TheUSPacificNorthwest(PNW)ischaracterizedbyhighlatitudeandMediterraneanclimatewhere wheatproductionispredominantlyrain-fedandoftensubjecttolowsoilmoisture.Asaresult,selection fordrought-adaptivetraitsinmoderncultivarshasbeenanintegralcomponentoftheregionalbreeding programs.Thegoalofthisresearchwastoevaluatephenotypicassociationsofmorpho-physiological traitsandtheirresponsetosoilmoisturevariationinwinterwheatgermplasmadaptedtothePNW.A panelof402winterwheataccessions(87hardand315soft)wasevaluatedforspectralreflectanceindices (SRIs),canopytemperature(CT),plantstature,phenology,grainyield,andyieldcomponentsunder rain-fedandirrigatedconditionsin2012–2014.Variationinsoilmoistureandtemperaturecumulatively explained86%oftotalyieldvariationacrossyearsandlocations.Thephenotypicassociationsofyield withphenology,plantheight,andCTwereenvironmentdependent.VariousSRIsrelatedtobiomass,stay green,pigmentcomposition,andhydrationstatusshowedconsistentpatternsofresponsetodrought andstrongcorrelationswithyield(p<0.001).Thecompensatoryinteractionofgrainnumberandweight wasindicatedinthenegativecorrelationbetweenthousandkernelweightandgrainnumberperspike acrossmoistureregimes.Areaundervegetationindexcurve(AUVIC)explained53–88%ofthetotal vari-ationinstaygreenestimatedfromvisualscoreofflagleafsenescence(p<0.001).Principalcomponent analysisrevealedthreemajorclustersthatexplainedmorethan76%ofinterrelationsamongtraits.The marketclasseswithinthestudypopulationshoweddifferentiationwithrespecttothesetraits.Thisstudy highlightsthepotentialuseofspectralradiometryinfieldscreeningofwinterwheatforgrainyieldand droughtadaptationinMediterranean-likeenvironments.

1. Introduction

WinterwheatproductionintheUSPacificNorthwest(PNW)is characterizedbyhighlatitude,relativelycooltemperature,anda Mediterranean-likeclimatewithmostannualprecipitation occur-ringinthewinter(Mote,2003).Annualprecipitationrangesfrom lessthan200mmtomorethan500mm(SchillingerandPapendick, 2008).Inadditiontosoilmoisturedeficitsinsemiaridareas, sea-sonalprecipitationfluctuationbetweenAprilandJuneisamajor constraintofwheatproductionintheentireregion(Lopezetal., 2003).Soildepthrangesfromlessthan1mtoover7m,causing spatialheterogeneityinwaterholdingcapacityandstress sever-ityintheregion(ShillingerandPapendick,2008).Directselection

∗Correspondingauthor.

E-mailaddresses:ahcarter@wsu.edu,shif.abets@gmail.com(A.H.Carter).

for grainyieldhas beensuccessfully practiced formore than a centurytoimproveyieldacrosstheprecipitationzones.However, thegeneticgain fromthis approachisgenerally lowinthe dri-estfarmsbecauseofhighgenotype-environmentinteractionand unaccountedspatialheterogeneity(Blum,2006).

Highergeneticprogressinyieldcanbeachievedbyselecting secondarytraitsotherthanyieldperse.Grainyieldisdetermined bynumberof spikesperarea, numberof kernelsper spikeand kernelweightwhichareinterrelatedtoeachotherandinfluenced bymorpho-physiologicaltraitssuchasearlyvigor,plantstature, floweringtime,andphysiologicalmaturity(Alexanderetal.,1984; McNealet al.,1978;El-Mohsenetal.,2012; Mohammadietal., 2012;Wuetal.,2012).Theinfluenceofenvironmentonthese sec-ondarytraitsisrelativelylowandpredictableresultinginhigher geneticprogresscomparedtoyieldbasedselection(Fischeretal., 2012;Wuetal.,2012).Recentreportssuggestthatsomeofthe com-ponenttraitsaregeneticallyindependentsuggestingthepossibility

http://dx.doi.org/10.1016/j.fcr.2016.06.018

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ofcombiningmultipletraitsinmodernwheatcultivars(Dhungana etal.,2007).

The compensatoryinteractions and relative contributions of grainweight,grainnumberperspike,andspikenumberperarea towardsoverallyieldareaffectedbydevelopmental characteris-ticsandenvironmentalfactors(Cutforthetal.,1988;Duguidand Brule-Babel,1994;Santraetal.,2009).Semi-dwarfstature(shorter and stifferthanstandard height), earlygrowthvigor, and early maturity are adaptive features for environments withterminal heatanddroughtstresses(Baietal.,2004;vanGinkeletal.,1998; Morgan,1995;Álvaroetal.,2008;Kirkegaardetal.,2001).Onthe otherhand,dwarfstatureandlonggrain-ﬁlldurationhaveyield advantageinoptimumconditions(Baietal.,2004;Blum,1996; Gomezetal.,2014).Asa result,indirectselectionisananalytic approach that involvesunderstandinginterrelationships among variousattributes,theiryieldadvantages,andresponsesto envi-ronmentalvariation(McNealetal.,1978;El-Mohsenetal.,2012).

Somephysiologicalattributescontributetograinyieldandyield componentslike kernel weightby maintaininghigher rateand duration of grain filling (Duguid and Brule-Babel, 1994).These physiologicalattributesincluderadiationuseandphotosynthetic efficiency,transpiration efficiency,water availability and reten-tioncapacity,biomasscapacity,andassimilatetranslocationtothe grain(El-Mohsenet al.,2012; Reynolds et al.,2012).However, directmeasurementsofthesephysiologicalattributesarelaborand resource-intensivewhichlimitstheirapplicationtocharacterize largesetsofgermplasm.

Spectralradiometryandotherindirectsensingmethodsbecame high-throughputphenotypingalternativesthatenableevaluation oflargegermplasmcollectionsovermultipletargetenvironments (FioraniandSchurr,2013).Spectralreﬂectanceindices(SRIs)are calculated in the visible (VIS) and near infrared (NIR) ranges (␭=400–700and␭>700nmrespectively).Threemaincategories oftraitscanbeestimatedusingtheseindices:(1)biomass, pig-mentabundance,andareaofphotosyntheticcanopy(Wiegandand Richardson,1990;Haboudaneetal.,2004;Naumannetal.,2009; Reynoldsetal.,2012);(2)wateravailabilityandplanthydration status(TuckerandSellers,1986;Zarate-Valdezetal.,2012);and(3) compositionofphoto-andthermo-protectantmolecules(Pe ˜nuelas etal.,1995;Ollinger,2011).

A combinationof both visible and infraredspectra areused toderivethevegetationindicesofsimpleratio(SR),normalized differencevegetationindex(NDVI),andgreennormalized vege-tationindex(GNDVI)todiscernminutedifferencesinvegetative greenness,rateofsenescence,andstaygreenduration(Gitelson etal.,1996;Stenbergetal.,2004;Babaretal.,2006;Edaeetal., 2014;LopezandReynolds,2012;Liuetal.,2015).Theanthocyanin reflectanceindex(ARI)is derivedfromwavelengthsinboththe VISandNIRregionsasa surrogateforanthocyanincomposition (Gitelsonetal.,2002).Photochemicalreflectanceindex(PRI), nor-malizedchlorophyll-pigmentratioindex(NCPI),andXanthophyll pigmentepoxidationstate(XES)arederived fromreflectanceat theVISlight rangetoestimatethecompositionand abundance of plantpigments(Pe ñuelas et al., 1993;Pe ñuelas etal., 1995; Ollinger,2011),whereasnormalizedwaterindex(NWI)isderived fromreflectanceatNIRrangetoestimateplanthydrationstatus (Babaretal.,2006).

CharacterizingtheinterrelationsofSRIs,developmentaltraits, andyieldwithrespecttotargetenvironmentsiscrucialtofacilitate anintegrateduseofremotely-sensedandagronomicinformationin adaptationbreeding(Edmeadesetal.,1997;Farshadfaretal.,2013).

Rigorousinvestigationshavebeencarriedouttofullyaccountfor theresponsesofSRIsinirrigated,warm,andlowlatitudespring wheatenvironments.Effectsofenvironmentandgrowthstageson SRIswerereportedtobesigniﬁcant(Aparicioetal.,2002;Babar et al., 2006; Lopez and Reynolds, 2012). Aparicio et al. (2000)

reportedthatassociationofSRIswithgrainyield,biomasscapacity, andleafareaindex(LAI)washigherinrain-fedthanirrigated con-dition.Thesereportssuggesttheneedtocarefullydeterminewhich growthstageandselectionenvironmentismostinformative.

However,littleornopreviousassessmenthasbeendoneonthe propertiesandpotentialuseofcanopyspectralreflectanceinthe environmentswithahighlatitude,cooltocoldwinterseason,and strongphotoperiodrequirement.Themaingoalofthis research wastoevaluatevariousspectralreflectanceindicesassociatedwith grainyieldunderdry,moist-cool,andirrigatedconditionsin win-terwheatgenotypesadaptedtothePNWenvironment.Specific objectiveswere: (i) toevaluatephenotypicassociations of SRIs withgrainyieldandmorpho-physiologicaltraits;(ii)todetermine theinteractionofthesetraits withenvironmentalvariablesand developmentaltraits suchasear emergence,and (iii) to exam-inethetrendsofphenotypicassociationsacrossmultiplegrowth stagesinthecrop’slifecycle.Understandingtheinterrelationship and drought-responsesof these developmental traits, morpho-physiologicalcomponents,andagronomicperformancewillhelp incombiningtheyieldadvantageofmultipleattributesthrough focusedidentificationandintrogressionoftraitsthathave syner-geticeffectsonyield.

2. Materialsandmethods

2.1. Studypopulation

ThestudywasconductedontwoPNWwinterwheat subpopu-lations:hardwinter(n=87),andsoftwinter(n=315).Thewinter wheatgermplasmintheregionhasbeencontinuouslysubjected to selection for yield,yield stability, end-usequalities, farming preferences, and disease resistance(Barrettand Kidwell,1998; Chen,2005;SchillingerandPapendick,2008).Donaldson(1996) indicatedthatwheatcultivarsadaptedtotheregioncontain signif-icantvariationsforemergence,earlycanopyestablishment,root growth and development,winter survival, osmoticadjustment, optimum maturity, and plant architecture. Barret and Kidwell (1998)attributedthebroadandstratiﬁedgeneticbasisforthese agronomictraitstothebreedingeffortinregionthathasbeenin placeformorethanacentury.Similarly,thestudypopulationis knowntohaveageneticstratiﬁcationthatalignwithmarketclass andbreedinghistory.Inparticular,populationstructureanalysis differentiatedhardwintergenotypesfromclubwintergenotypes withonlyaslightoverlap(Naruokaetal.,2015).

Genotypeswereselectedfrommappingpopulations,advanced breedinglines,and cultivars fromPNWbreedingprograms tar-getedtoOregon,Washington,andIdaho.Thehardredwinterwheat cultivar‘Norwest553’(PI655030)andthesoftwhitewinter cul-tivar‘Madsen’(PI511673)wereincludedaslocalchecks.Madsen isknownforitswideadaptationanddiseaseresistanceandhas beengrowninthePNWforover20years,whereasNorwest553 hashighyieldpotential,gooddiseaseresistance,andwasthemost commonlygrownhardredcultivarinthePNWwhenthetrialwas initiated.Becausebothaccessionshavesemi-dwarfplantheight andphotoperiodsensitivity,thevariationacrossyearsand loca-tionsisexpectedtohaveloweffectontheirperformancemaking themideallysuitedtoaccountforspatialvariationswithineach trial.

2.2. Experimentalconditionsandﬁelddesign

The studypopulationwas grownin three moisture regimes atthefollowingWashingtonStateUniversityagronomyresearch farms:CentralFerry(46◦4N;117◦8W),Pullman(46◦4N;117◦ 5W),andOthello(46◦5N;119◦2W)(Table1).CentralFerryhasa

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Table1

Geographicallocation,soiltype,precipitation,andgrowingdegreedaysofthethreeexperimentalsites.

Variable CentralFerry Pullman Othello

Geographicposition(Lat,Long) 46.4;117.8 46.4;117.5 46.5;119.2

Altitude(masl) 206 717 323

Precipitation(mm)a ₃₁₇ ₅₃₃ ₂₁₄

Growingdegreedays(GDD,◦_C)b ₃₄₀₈ ₂₁₃₈ ₂₇₇₄

Soiltype Chardsiltloam Palousesiltloam Shanosiltloam

YearsofexperimentRain-fed 2012–2014(3) 2012–2014(3) 2013(1)

Irrigated 2013–2014(2) 2013(1)

a_Cumulative_{precipitation}_in_the_growing_seasons_in_millimeters.

b _Calculated_for_growing_seasons_of_the_study_periods_using₀◦_C_as_base_temperature.

well-drainedandmoderatelypermeableChardsiltloamsoilwith waterholdingcapacityrangingfrom220–280mm.Othellohasa well-drainedandmoderatelypermeableShanosiltloamsoilwith 170–220mmwaterholdingcapacity.ThePalousesiltloamsoilin Pullmanisthemostfertileandhighlycultivated soilwithdeep proﬁle,moderatepermeability,andhighwaterholdingcapacity. Plantingofwinterwheatinthestudyareaisusuallybetweenlate Septemberandmid-October.Theannualrainfallishighestin Pull-manfollowedbyCentral FerryandOthello(Table1).In Central FerryandOthello,thepopulationwasplantedintwotreatments,a rain-fedplantingrepresentingthedroughtconditionandirrigated treatmentrepresentingthewateroptimumcondition.InPullman, thepopulationwasplantedonlyinarain-fedcondition represent-ingthemoist-coolcondition.Theirrigatedtrialswereconducted usingsolid-setsprinklersystemsfor4–8h,oneortwotimesaweek dependingontheweather.Overheadsprinklerirrigationsystemis recommendedintheregiontominimizerunoff.Thissystem deliv-eredapproximately600mm of waterover thegrowingseason. Irrigationstartedonbooting(Feekes9),beforethesoilmoisture depletesandanysignofstresswasdetected,andcontinueduntil theonsetofphysiologicalmaturity.

In all trials, a modiﬁed augmented design (Federer and Raghavarao, 1975; Lin and Poushinsky, 1983) was used with 16–20%oftheplotsassignedtothereplicatedlocalchecks, Nor-west553andMadsen.PlantingwasdoneusingaWintersteigerplot seeder(WintersteigerAG,Austria).Theseedingrateswere5.4g/m2

fordroughtand10.8g/m2_for_both_irrigated_and_moist-cool

rain-fedtreatmentsin4.65m2_plots._Pre-plant_seed_treatment_was_done

with Sedaxane+Difenoconazole+Mefenoxam+Thiamethoxam (Cruisermaxx Vibrance®_, _EPA _Reg. _No. _100-1383, _at _0.06% _by

weight of the product; Syngenta Crop Protection, Greensboro NC) for healthy root growth. Fungicide (Quilt®_, ₁₄₀_g/ha) _and

herbicides (HuskieTM_—840_g/ha, _Starene®_—7m00_g/ha, _and

PowerFlex®_—140_g/ha)_were_applied_at_Feekes_stages_4–6

follow-inglabelinstructions.Thiswasdonetoeliminatetheconfounding effects ofstripe rustresistanceand herbaceous weedsonyield potential.

2.3. Measurementandcalculationoftraits

Headingdatewasrecordedasthenumberofdaysfrom sow-inguntilfullexposureofspikesin50%oftheplot.Plantheight (PHT)wasmeasuredbetweenthebaseoftheplantstandandthe tipoffullyemergedspikeexcludingawns.Peduncleextrusion(PE) wasmeasuredastheportionofpedunclethatemergedoutofits sheath.Degreeofflagleafgreennesswasvisuallyscoredona1–10 scale(1=fullysenescedand10=fullygreen)threetimesbetween headingdateandphysiologicalmaturity.Canopyreflectancewas measuredusingahandheldCROPSCANmultispectralradiometer (CROPSCAN,Inc.Rochester,USA)installedwithfiltersthat selec-tively measure incident and reflected radiation at 16 different wavelengthsbetween 430and 970nm. Threeto five measure-mentsweretakenperplotatonetotwoweekintervalsbetween

headingandlategrain-fill.Whiletheup-wellingsensormeasures theincomingradiation,thedown-wellingsensorpositioned40cm abovethecanopymeasurethereflectionfromplantsurface.All reflectancemeasurement wasdonebetween10a.m.and 2a.m. avoidingshadow,cloud,andstrongwind.Ahandheldinfrared ther-mometer(SixthSenseLT300,TotalTemperatureInstrumentation, Inc.,Burlington,VT)wasusedtomeasurecanopytemperature(CT) duringthegrainfillstages(Feekes10–11).Plotswereharvested withaWintersteigerNurseryMastersmallplotcombine (Winter-steigerAG,Austria)afterripening(Feekes11).Grainyield(t/ha) wascalculatedfromthegrainweightperplot.Thousandkernel weight(g)andtest weight(kg/hl)wereprocessedfromsample grainwhereasgrainnumberperspike (count)wasobtainedby hand-threshingandcountinggrainnumbersinfivespikes sam-pledfromtheplots.In2014,spectralreflectancevalueswerenot collectedonallplotentries,andthusthesedataonlyrepresent2012 and2013measurements.

Genotypicstaygreen(SG)wascalculatedfrommultiplescores ofﬂagleafgreennessasareaundergreennesscurvebyslightly modifyingthemethodtoestimatetheareaunderSPADdecline curve(AUSDC)inRosyaraetal.(2007):

SG=n−1 i=1

_G₍_i₎₊_G₍_i₊₁₎ 2

∗[D(i+1)−D(i)]

whereG(i)andG(i+1)areconsecutivescoresofﬂagleaf green-ness,andD(i)andD(i+1)aredaysaftersowingfor(Gi)andG(i+1) measurements,respectively.

Reflectancevalueswereusedtoderivesevenvegetationindices thatarepresentedinTable2.Threedifferentparametersderived fromNDVIhavebeenpreviouslyreportedtobeeffectiveestimators ofthedegreeofgreenness(pigmentabundance),rateof senes-cence, and stay green duration:NDVIat specificgrowth stages (Babaretal.,2006;Edaeetal.,2014;Liuetal.,2015),slopeofNDVI over growthstages (Lopes andReynolds, 2012), andarithmetic meanofNDVIovergrowthstages(Babaretal.,2006).Wetested theseapproachesalongwithtwonewparameters:areaunder veg-etationindexcurve(AUVIC)modifiedfromRosyaraetal.(2007) andweightedmean,whichusesthepopulationmeanofeach mea-surementasaweightingfactor.Wecalculatedtheseparameters forallstudiedvegetationindicesandtestedtheirphenotypic asso-ciationswithgrainyield.Staygreenestimatesbasedonflagleaf senescencewerealsocomparedwithgrowth-specificreflectance indicesandthederivedparameters.

2.4. Dataanalysis

Traitvalueswereadjustedforspatialvariationwithineachﬁeld experiment(calledtrialhereafter)usingtheMIXEDprocedure(SAS, Cary,NC)whichaccountsfortheﬁxedeffectofun-replicated geno-types and random effect of blocks in a mixed linear model as follows:

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Table2

Vegetationindicesevaluatedasproxiesforstaygreen,grainyield,anddroughttoleranceinPaciﬁcNorthwestwinterwheat.

VegetationIndex Formulab _References

Normalizeddifferencevegetationindex(NDVI) (R800−R680)/(R800+R680) Rouseetal.,1973

Simpleratio(SR) R800/R680 Stenbergetal.,2004

Green-NDVI(GNDVI) (R780−R550)/(R780+R550) Gitelsonetal.,1996

Photochemicalreﬂectanceindex(PRI) (R530−R570)/(R530+R570) Pe ˜nuelasetal.,1993

Normalizedchlorophyllpigmentratioindex(NCPI) (R680−R430)/(R680+R430) Pe ˜nuelasetal.,1993

Anthocyaninreﬂectanceindex(ARI) R800(1/R550−1/R700) Gitelsonetal.,2002

Normalizedwaterbandindex(NWI)a _(R

900−R970)/(R900+R970) Babaretal.,2006

Xanthophyllpigmentepoxidationstate(XES) R531 Pe ˜nuelasetal.,1995

a_The_formula_for_NWI_is_slightly_modiﬁed_so_that_it_has_similar_dimension_to_hydration_status. b_The_letter_“R”_followed_by_three_digit_number_stands_for_wavelength_of_respective_{reﬂectance.}

where␮istheoveralltraitmean,␶ijisthecalculatedestimatorused

toadjustmeanofgenotypeiwithintheblockj,bjistheeffectof

blockj,andeijismodelresidualcalculatedfromreplicatedchecks.

Adjustedtraitvalueisobtainedbyadding␮and␶ij.

Analysisofvariancewasperformedusingthefollowing equa-tion to determine if there was signiﬁcant effect of genotype, environment(years,locationsandmoistureregimes),and geno-type×environmentinteractiononthetraits:

Yijkl= ␮+Ei+Bji+Gk+GEik+eijkl

whereYijklisthemeasurementofgenotypekonplotlinblockj,and

triali;␮istheoverallmeanofallplotsinalltrials;Eiistheeffectof

triali;Bjiistheeffectofblockjwithintrialiusingreplicatedcheck;

Gkistheeffectofgenotypek;GEikistheinteractionofgenotypei

withtrialk;eijklistheplotresidual.

Stressintensityofeachmoistureregimewascalculated accord-ingtoFischerandMaurer(1978):

SI=1−

¯ i ¯ p

where−Yi ismeanyieldunderstressand

−

Ypismeanyieldunder

optimumcondition.Cumulatedgrowingdegreedays(GDD)was calculatedfromthemaximumdayandnighttemperatureusing 0◦Casbaselineinawheatthermalmodel(modiﬁedfromSaiyed etal.,2009).

The phenotypic correlation coefﬁcients (r) between the LS-means of spectral reﬂectance and grain yield were calculated overallpopulationand withinnarrowphenology groups(lower 25percentile—early;25–75percentile—intermediate;andtop25 percentile—late ear emergence) using multivariate CORR func-tion(SAS,Cary,NC).Principalcomponentanalysiswasperformed amongtraitsusing genotypictraitvaluesin ordertoinfer pop-ulationdifferentiation,covariance among traits,and reducethe numberofyieldpredictivevariables.

3. Results

3.1. Environmentalconditionsandgermplasmresponses

Moisturedeficitindroughttreatmentstartedatbootingstage (Feekes9)andprogressivelyincreasedthroughmaturity.Pullman receivedthehighestprecipitationandlowesttemperaturewhereas Othelloreceivedlowest precipitationand intermediate temper-atureand CentralFerryreceivedintermediate precipitationand highesttemperature(Fig.1).TheirrigatedtrialsinCentralFerry and Othello differedin theirmaximum temperatureas wellas respectiveaccumulatedgrowingdegreedays.Themoistureand temperaturegradientobservedinthisstudyrepresentdistinctive growingconditionswithconsiderableyielddifferences.The pres-enceofpopulationstratificationhadsignificanteffectonalltraits (p<0.05),thehighesteffectbeingongrainnumberperspike(38%).

3.2. Responseingrainyieldandyieldcomponents

Thehighestyieldwasrecordedin moist-coolrain-fed condi-tion followed by irrigated and drought conditions, respectively (Table3).Stressintensity(SI)inthedroughtcondition,calculated asreductionofgrainyieldinreferencetomoist-cooltreatment, was52%forhardwinterand55%forsoftwinterwheat.Thisresult suggeststhatdroughtintensityandyieldresponseofwinterwheat germplasmwasaffectedbythecombinationofhightemperature andsoilmoisturedeﬁcit(Fig.1).Thetwoclasses ofwheat(soft andhard)respondedsimilarlytothewatertreatments.The irri-gatedconditionshowed36 and 30%SI in hard andsoft winter subpopulations,respectively.Theyieldvariationacrossyearsand locationswassigniﬁcantinalltreatments(p<0.001,Fig.2a).The yieldincreaseinresponsetoirrigationwas15%inCentralFerryand 45%inOthello.Alinearregressionmodelindicatedthatdifferences inwaterregimeandtemperatureexplained77%(p<0.001)ofthe variationinyieldwithabout10%moreyieldvariationattributedto theinteractionofavailablemoistureandtemperature(Fig.2b).

Likegrainyield,thousandkernelweightwaslowestindrought, intermediateinirrigated,andhighestinmoist-coolrain-fed condi-tion.Themoist-coolrain-fedconditionshowedhighesttestweight andlowestgrainnumberperspike.Irrigatedanddrought condi-tionsdidn’tshowconsistentandstatisticallysignificantdifference ingrainnumberandtestweight.Thesoftwinterwheatsubgroup hadhighergrainnumberperspikecomparetohardwinterinall environmentalconditions.Thousandkernelweightandtestweight were significantly higher in hard winter wheat under drought condition,butdidn’tshowsignificantdifferencebetweenthe sub-groupsundermoist-coolrain-fedandirrigatedconditions.

3.3. Responseinphenology:headingdateandstaygreen

Headingwaslateinmoist-coolrain-fedcondition,intermediate in irrigated,and earlyindroughtconditions (Table3).In refer-encetomoist-coolcondition,earlyearemergencewasobserved underdrought(4.7–6.3%)andirrigation(3.0–4.2%).Headingdate andstay greenshowedadirectrelationship,thehighest degree ofstaygreenbeingobtainedinlateheadinggenotypesfollowedby mediumandearlygenotypes(Fig.3).Differenceinphenologyposes aconfoundingeffectonhydrationstatusandsubsequentlyonthe relationshipbetweenyieldandcomponenttraits.Tominimizethis confoundingeffect,thestudypopulationwasdividedintoearly, intermediate,andlatephenologysubgroups.Genotypeswith head-ingdatelowerthanthe25percentilecutoffweregroupedasearly phenologygroups.Genotypeswithheadingdatebetween25and 75percentileweregroupedasintermediatephenology;and geneo-typeswithheadingdateabovethe25percentileweregroupedas latephenologygroups.

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Fig.1. Cumulativeprecipitationandtemperatureoftheexperimentalsitesin2012–2013growingseason:Lowesttemperatureandhighestprecipitationwasobtainedin Pullman;intermediatetemperatureandlowestprecipitationinOthello;andhighesttemperatureandintermediateprecipitationinCentralFerry.

Table3

Descriptivesummaryofgrainyield,yieldcomponents,headingdate,stay-green,andspectralreﬂectanceindicesinPNWwinterwheat:Meansandstandarderrors(SE)were calculatedfrommultipletrialswithintreatments.

Traita _Hardb _Soft

Drought Irrigated MoistcoolRFc _Drought _Irrigated _Moist_cool_RF

Mean SEd _Mean _SE _Mean _SE _Mean _SE _Mean _SE _Mean _SE

DTH 222.26c _0.208 _226.52b _0.201 _234.06a _0.323 _225.46c _0.076 _229.53b _0.118 _236.04a _0.182 SG 0.87c _0.023 _1.01b _0.028 _1.10a _0.027 _1.02c _0.015 _1.16a _0.013 _1.09b _0.017 Yield 3.61c _0.052 _4.91b _0.100 _7.42b _0.097 _3.60c _0.028 _5.68b _0.051 _8.04a _0.047 GNS 36.32b _0.727 _41.05a _0.675 _31.29c _0.602 _46.10a _0.444 _44.74b _0.446 _36.49c _0.341 TKW 32.83c _0.306 _34.68b _0.334 _35.73a _0.363 _31.06c _0.176 _34.63b _0.175 _36.52a _0.240 TW 75.15b _0.166 _73.51c _0.181 _76.93a _0.141 _73.48b _0.089 _73.06b _0.090 _76.09a _0.062 PHT 93.54c _0.975 _112.33a _1.176 _108.73b _1.242 _81.66c _0.391 _103.39a _0.399 _95.13b _0.470 PE 13.24b _0.387 _20.96a _0.576 _21.20a _0.483 _9.44c _0.163 _18.74a _0.191 _14.93b _0.173 CT 26.32a _0.115 _23.11b _0.086 _23.07b _0.088 _24.58b _0.076 _22.27c _0.129 _28.33a _0.207 NDVI 0.66c _0.006 _0.76a _0.012 _0.75b _0.006 _0.68c _0.003 _0.81a _0.005 _0.77b _0.003 SR 5.69c _0.075 _7.72a _0.239 _6.36b _0.085 _6.19c _0.050 _8.76a _0.117 _6.81b _0.051 GNDVI 0.66c _0.004 _0.70a _0.009 _0.69b _0.004 _0.67c _0.002 _0.74a _0.004 _0.71b _0.002 NWI 0.04c _0.001 _0.08a _0.002 _0.08a _0.001 _0.05c _0.001 _0.09a _0.001 _0.08b _0.001 PRI −0.11a _0.001 ₋_0.11a _0.001 ₋_0.12b _0.001 ₋_0.10a _0.000 ₋_0.10a _0.001 ₋_0.11b _0.001 NCPI 0.46a _0.006 _0.34c _0.015 _0.39b _0.006 _0.40a _0.003 _0.31c _0.007 _0.36b _0.002 ARI 0.89a _0.035 ₋_0.33c _0.103 _0.40b _0.038 _0.62a _0.016 ₋_0.58c _0.055 _0.21b _0.018 XES 5.01a _0.023 _4.94a,b _0.026 _4.78b _0.028 _4.94a _0.026 _4.38b _0.028 _4.38b _0.023

Differentsuperscriptacrossmoistureregimeswithinthesamemarketclassshowsstatisticallysigniﬁcantdifference(Alpha=0.05).

a_DTH_days_to_heading_(measured_in_days_after_sowing),_NWI_normalized_water_index,_PRI_{photochemical}_reﬂectance_index,_NCPI_normalized_{chlorophyll-pigment}_ratio

index,ARIanthocyaninreﬂectanceindexSGstaygreen,NDVInormalizeddifferencevegetationindex,SRsimpleratio,XESxanthophyllpigmentepoxidationstate,Yield

measuredin(t/ha),GNSgrainnumberperspike,TKWthousandkernelweight(g),TWtestweight(kg/hl),PHTplantheight(cm),PEPeduncleextrusion(cm),CTcanopy temperature(◦_C).

b _Hard_and_soft_groups_represent_the_two_market_classes_that_delineate_the_two_{subpopulations.} c _Moist-cool_rain-fed_environment_was_the_high_{precipitation}_condition_in_Pullman,_WA. d _SE_was_calculated_from_multiple_trials_within_treatments.

3.4. Responsesinplantheightandpeduncleextrusion

Plantheightwaslowestindrought,intermediateinhigh pre-cipitation,andhighestinirrigatedenvironments.Thesoftwinter

subgrouphadsigniﬁcantlylowermeanplantheightthanthehard wintersubgroup.Peduncleextrusionshowedthesecondhighest responsetodrought(40–50%reduction)nexttoyieldreduction.

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Fig.2.(a)Meangrainyieldovertrials(CF,OTandPUstandsforCentralFerry,OthelloandPullmanexperimentalsites,respectively;andthetwodigitsstandsforyearof experiment2012and2013)and(b)modelexplaininggrainyield(t/ha)byenvironmentalvariables(precipitationandthermaltime).

Fig.3. Meanstaygreenestimatebasedonﬂagleafsenescencescoreinearly, medium,andlateheadinggenotypesofhardwintersubgroupindrought,irrigated, andhighprecipitationconditions.

3.5. Responseinreﬂectanceindicesandcanopytemperature

Treatmentsshowedsignificantdifferencesingrowth-specific SRImeasurements,theirmeans,andrateofdeclineovergrowth stages(Table3).NDVI,SR,GNDVI,andNWIwerehighestin irri-gatedcondition,intermediateinmoistcoolrain-fed,andlowestin droughtcondition(Table3).Conversely,NCPIandARIwere low-estinirrigatedcondition,intermediateinmoist-coolrain-fed,and highestindroughtcondition.Therewasnosignificantdifferencein meanPRIbetweentreatments.TheoverallrateofNDVIdeclinewas highestindrought,intermediateinmoist-coolrain-fed,and low-estinirrigatedcondition.NDVIdeclinebetweenheadingandearly grainfillwaslowestinmoist-coolrain-fedfollowedbyirrigated anddrought(Fig.4).Canopytemperatureinrain-fedconditionwas higherthanirrigatedconditions.TheCTmeasurementunder moist-coolrain-fedconditioninsoftwinterwheatwasexcludedfrom analysisforitsinconsistency.

3.6. Phenotypicassociationbetweengrainyieldandvarioustraits

Grainyieldshowedpositivecorrelationwithgrainnumberper spikeinhardwinterwheatandwiththousandkernelweightin

Fig.4.TrendofNDVIdeclineovergrowthstagesinPNWwinterwheatpopulation underdrought,irrigated,andmoist-coolrain-fedconditions.

softwinterconsistentlyacrossmoistureregimes(Table4).Insoft winterwheat,grainnumberperspikeandthousandkernelweight werenegativelycorrelatedunderallenvironmentswhereasinhard winter,thenegativecorrelationwasstatisticallysigniﬁcantonlyin theirrigatedcondition.

Thecorrelationbetweengrainyieldanddaystoheadingunder droughtconditionwasnotstatisticallysigniﬁcantinboth subpopu-lations.Inthehardwintersubgroup,grainyieldanddaystoheading werepositivelycorrelatedunderirrigatedandmoist-coolrain-fed conditions,whereasinsoftwintersubgroupslightlynegative cor-relationwasobtainedunderirrigatedcondition(Table4).Insoft winterwheat,thousandkernelweightwasnegativelycorrelated withdays to headingin both subpopulations and across mois-tureregimeseventhoughtheassociationinhardwinter wheat wasweakandstatisticallyinsigniﬁcantunderdroughtcondition (r=0.13;p=0.26).

Negativecorrelationbetweengrainyieldandplantheightwas obtained in hard winter wheat under all moisture conditions whereasinsoftwinterwheat,thesetwotraitsshowedpositive cor-relationunderdrought,negativeunderirrigation,andstatistically insigniﬁcantundermoist-coolrain-fedcondition.Peduncle extru-sionandgrainyieldwerepositivelycorrelatedunderdroughtand moistcoolrain-fedconditionsinsoftwinterwhereasthetwotraits didn’tshowsigniﬁcantassociationinhardwinterwheat.

Yield was positively correlated with NDVI, SR, GNDVI, and PRI,andnegativelycorrelatedwithNCPI,ARI,andXES(p<0.001) (Table5).Generally,reﬂectanceindicestakenatmid-grain-ﬁllstage showedstrongercorrelationwithgrainyieldascomparedtoother

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Table4

PhenotypiccorrelationsofdevelopmentaltraitsandyieldcomponentsinPaciﬁcNorthwestwinterwheatunderdrought,irrigated,andmoist-coolrain-fedenvironments (associationinsoftwinterispresentedinupperdiagonalandtheassociationinhardwinterwheatispresentedinlowerdiagonal).

Variablea _TRTb _GY _GNS _TKW _TW _DTH _PHT _PE _CT

Rc _Sig.d _r _Sig. _r _Sig. _r _Sig. _r _Sig. _r _Sig. _r _Sig. _r _Sig.

GY I 0.10 0.08 0.20 *** 0.24 **** −0.08 ns 0.34 **** 0.33 **** −0.15 * II −0.03 ns 0.21 **** 0.11 0.07 −0.14 −0.19 ** −0.02 ns −0.09 ns III 0.08 ns 0.26 *** −0.12 * 0.09 ns 0.08 ns 0.21 *** −0.24 **** GNS I 0.28 * −0.38 **** −0.39 **** 0.16 ** −0.10 ns −0.19 *** 0.16 ** II 0.36 ** −0.19 ** −0.36 **** 0.18 ** 0.00 ns −0.17 ** −0.05 ns III 0.23 0.06 −0.22 *** −0.25 **** 0.08 ns −0.12 * −0.21 *** 0.22 *** TKW I 0.16 ns 0.07 ns 0.34 **** −0.23 **** 0.17 ** 0.15 * −0.21 *** II 0.02 ns −0.31 ** 0.14 * −0.28 **** −0.08 ns −0.04 ns 0.05 ns III 0.02 ns −0.03 ns 0.25 **** −0.15 ** 0.03 ns 0.09 ns 0.01 ns TW I −0.02 ns 0.15 ns −0.07 ns −0.07 ns 0.33 **** 0.24 **** −0.11 0.06 II −0.01 ns −0.26 * 0.04 *** −0.26 **** 0.14 * 0.05 ns −0.05 ns III −0.14 ns −0.09 ns 0.11 *** −0.20 *** 0.19 ** 0.11 0.07 −0.13 * DTH I −0.05 ns −0.08 ns −0.13 *** −0.41 *** 0.14 * −0.10 0.07 0.08 ns II 0.23 8 0.18 ns −0.23 * −0.20 0.07 0.34 **** 0.01 ns −0.10 ns III 0.35 ** 0.15 ns −0.36 ** −0.43 *** 0.31 **** 0.22 *** −0.04 ns PHT I −0.21 0.07 −0.04 ns −0.04 ns 0.02 ns 0.02 ns 0.32 **** −0.20 *** II −0.28 ** 0.07 ns −0.20 0.07 0.15 ns −0.04 ns 0.33 **** −0.18 ** III −0.32 ** 0.17 ns −0.19 ns −0.16 ns 0.07 ns 0.47 **** −0.38 **** PE I 0.09 ns 0.03 ns −0.05 ns 0.08 ns −0.11 ns 0.47 **** −0.19 ** II 0.08 ns 0.01 ns −0.12 ns 0.22 * 0.07 ns 0.11 ns −0.06 ns III −0.15 ns 0.29 * −0.25 * −0.19 ns 0.23 0.06 0.71 **** −0.21 *** CT I −0.05 ns 0.01 ns −0.35 ** −0.03 ns 0.03 ns −0.35 ** −0.24 * −0.05 II −0.22 * −0.04 ns −0.08 ns −0.03 ns −0.03 ns 0.17 ns −0.08 ns −0.22 III −0.03 ns −0.14 ns −0.06 ns 0.07 ns −0.06 ns 0.09 ns −0.13 ns −0.03

a_GY_Grain_yield,_GNS_Grain_number_per_spike,_TKW_thousand_kernel_weight,_TW_test_weight,_DTH_days_to_heading,_PHT_plant_height,_PE_peduncle_extrusion,_CT_canopy

temperature.

b _Treatments_representing_drought_(I)_irrigated_(II),_and_moist_cool_rain-fed_(III)_conditions. c _r_Correlation_{coefﬁcient.}

d _Statistical_{significance}_as_indicated_by_p_-value_ns_{nonsignificant:}_*_p_<_0.05,_**_p_<_0.01,_***_p_<_0.001,_****_p_<_0.0001._{Non-significant}_associations_close_to_the_0.05_thresholds

areindicatedasactualpvalue.

Table5

PhenotypiccorrelationofgrainyieldwithmeanvegetationindicesderivedfrommultiplemeasurementsacrossgrowthstagesinPaciﬁcNorthwestwinterwheat.

Subgroup Traita _Drought _Irrigated _Moist-cool_rain-fed

Earlyb _Medium _Late _Early _Medium _Late _Early _Medium _Late

Hardwinterwheat NDVI 0.51c _0.62 _0.45 _0.70 _0.48 _0.62 _0.73 _0.67 _0.66

SR 0.60 0.61 0.47 0.82 0.62 0.70 0.84 0.77 0.77 GNDVI 0.50 0.55 0.40 0.81 0.65 0.73 0.77 0.69 0.71 NWI 0.69 0.78 0.66 0.72 0.53 0.63 0.82 0.76 0.69 PRI 0.38 0.45 0.27 0.74 0.52 0.48 0.66 0.63 0.52 NCPI −0.52 −0.73 −0.61 −0.71 −0.46 −0.53 −0.75 −0.70 −0.68 ARI −0.59 −0.70 −0.69 −0.71 −0.46 −0.51 −0.82 −0.79 −0.74 XES −0.59 −0.13 −0.25 −0.67 −0.41 −0.75 −0.61 −0.46 −0.66

Softwinterwheat NDVI 0.65 0.68 0.68 0.49 0.51 0.35 0.54 0.37 0.41

SR 0.64 0.60 0.65 0.51 0.54 0.31 0.66 0.51 0.50 GNDVI 0.65 0.68 0.68 0.50 0.62 0.21 0.56 0.41 0.50 NWI 0.76 0.75 0.70 0.63 0.67 0.46 0.68 0.59 0.39 PRI 0.24 0.20 0.43 0.33 0.21 0.23 0.27 0.30 0.26 NCPI −0.59 −0.55 −0.60 −0.50 −0.38 −0.33 −0.54 −0.46 −0.38 ARI −0.65 −0.57 −0.66 −0.48 −0.44 −0.31 −0.68 −0.59 −0.51 XES −0.35 −0.41 −0.40 −0.33 −0.33 −0.26 −0.47 −0.35 −0.29

a_NDVI_normalized_difference_vegetation_index,_NWI_normalized_water_index,_PRI_{photochemical}_reﬂectance_index,_NCPI_normalized_{chlorophyll-pigment}_ratio_index,_ARI

anthocyaninreﬂectanceindex,SGstaygreen,SRsimpleratio,XESxanthophyllpigmentepoxidationstate.

b _Early,_medium,_and_late_represents_phenology_groups_based_on_the_respective_heading_date. c _All_correlations_were_signiﬁcant_at_p₌_0.01.

growthstages(Table6).However,thegrowthstagespeciﬁc mea-surementsandtheirslopeovergrowthstagewerelessconsistent amongtrials(Table6).

Grainyieldshowedconsistentlypositivecorrelationwithstay greenacrossmoisturecategories(S.Fig.1).Thecorrelationsofgrain number perspike and thousandkernel weightwith NWIwere statistically signiﬁcant and consistent across moisture regimes

(p<0.05)whereastheassociationswithotherindiceswereeither populationorenvironmentdependent(datanotshown).Canopy temperatureshowednegative correlationswithgrainyield and thousandkernelweightthatwerestatisticallysigniﬁcantatleast inonemoistureregime(p<0.05).Canopytemperaturewasalso signiﬁcantlyassociatedwithplantheight(Table4)andvarious

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veg-Table6

Phenotypiccorrelationofgrainyieldwithgrowthstage-speciﬁcNDVImeasurementsandparametersderivedfrommultiplemeasurements. Subgroupa _Parameterb _Trialsc

I II III IV V VI VII Hard AUVIC 0.65 0.42 0.48 0.50 0.69 0.50 0.57 Slope 0.06 0.48 0.43 0.38 0.66 0.49 0.25 Mean 0.66 0.50 0.50 0.45 0.67 0.70 0.55 Heading 0.55 0.39 0.13 0.22 0.11 0.47 0.30 EarlyGF 0.67 0.44 0.54 0.52 0.09 0.69 0.46 MidGF 0.60 0.52 0.47 0.50 0.73 0.70 0.58 LateGF 0.41 0.47 0.40 0.35 0.62 0.68 0.37 Soft AUVIC 0.71 0.64 0.36 0.28 0.64 0.65 0.50 Slope 0.31 0.47 0.25 0.10 0.53 0.66 0.30 Mean 0.72 0.50 0.37 0.28 0.64 0.67 0.50 Heading 0.56 0.02 0.10 0.33 0.56 0.41 0.29 EarlyGF 0.58 0.49 0.42 0.32 0.39 0.64 0.47 MidGF 0.71 0.54 0.43 0.29 0.63 0.64 0.45 LateGF 0.55 0.42 0.11 0.06 0.56 0.67 0.43

a_Hard_and_soft_market_classes_were_considered_as_population_subgroups.

b_AUVIC_area_under_vegetation_index_curve,_slope_and_mean_of_NDVI_calculated_from_growth.

c _I_Central_Ferry₂₀₁₂_(rain-fed),_II_Central_Ferry₂₀₁₃_(rain-fed),_III_Central_Ferry₂₀₁₃_(irrigated),_IV_Pullman₂₀₁₂_(rain-fed),_V_Pullman₂₀₁₃_(rain-fed),_VI_Othello₂₀₁₃

(rain-fed),VIIOthello2013(irrigated).

etationindicesatleastindroughtandirrigatedconditions(datanot shown).

Overall,higheryieldwasassociatedwithhigherNDVIat grain-fillstages(Feekes10–Feekes11)(S.Fig.3)andalowrateofNDVI declineovergrowthstages(Fig.5).Correlationcoefficientswere strongandconsistentacrossenvironmentsandsubgroupswhen theaverageof SRIwasused. Genotypesthat havelow yield in rain-fedconditionsexhibitedthelowestmeanNDVIandsharpest declineovergrowthstages.Themoistcoolrain-fedconditionhad lower meanNDVI than that of irrigated conditionat all stages exceptattheearlygrain-fill(Fig.5).DespitethislowerNDVI, high-estyieldwasscoredinthemoist coolrain-fedconditiondueto thelongervegetativeperiod(pre-heading)anddelayedonsetof physiologicalmaturity.

Similar to the stay green character, growth stage-specific reflectanceindicesandtheirderivedparameterswerestrongly cor-relatedwithheadingdate.Ingeneral,ARI,andNCPIwerehigherin earlygenotypesfollowedbyintermediateandlate.GNDVI,NDVI, NWI,PRI,andSRweregenerallyhigherinlateheadinggenotypes followedbymediumandearlyheadinggroupswiththeexception thatNWIunderdroughtandPRIunderirrigationdidn’tshow sig-nificantdifferencesamongearly,intermediate,andlateheading genotypes.

Thestaygreen estimatecalculatedfromflagleafsenescence wasmoderatelycorrelatedwithcanopylevelstaygreen.The cor-relationofstaygreenwithAUVICrangedfrom0.41to0.73inthe overallpopulationandfrom0.26to0.76withinphenology-based subgroups.Amongthegrowthstage-specificNDVImeasurements, thehighestcorrelationwasobtainedeitherinthemidorlategrain fillstage(r=0.58to0.78;p<0.001).Theassociationwasstatistically significantandindependenttothetimeoftransitioningbetween vegetativeandreproductivephases(S.Fig.3).

3.7. Principalcomponentanalysisoftraits

The principal component analysis based on covariance of agronomicandremotelysensedtraitsrevealedaremarkable dif-ferentiationofthePaciﬁcNorthwestwinterwheatthatalignwith thesoft andhardwinterwheatmarketclasses(Fig.6).Thesoft whiteandclubwhitesubgroupsshowedhighdegreeofoverlapin thisanalysis.Theﬁrstthreeprincipalcomponentsexplained76%of traitcovarianceacrosstrials,twoofwhichaccountedforthe53%. Thethreecomponentscumulativelyexplained75%,89%,and84% ofcovarianceamongtraitsunderdrought,irrigated,andmoistcool

rain-fedconditions,respectively.Inallconditions,ARI,NCPI,and CTwerepositionedincloseproximitywitheachotheranddistant fromtheothertraitsincludingyield(Fig.6),whichisinagreement withthenegativeassociationobtainedthroughcorrelation anal-ysis(Table5).Thetraitsthatweredifferentiatedacrosstheﬁrst dimensionofPCAarepresumedtobeinformativeforcomparative assessmentofgenotypesacrossthesubgroupsthatwereslightly differentiatedin theseconddimension.However,this hastobe furtherinvestigatedtodeterminetherelevantdimensionsthatcan betranslatedtoindicationofagronomicperformance.

Likewise,thepositions ofGNDVI,NDVI,NDVI,NWI,PRI,and SRweremostlywithina90◦radiusrelativetoyieldindicatingthe positivephenotypicassociation.Similarevaluationoftherelative distanceamongindicessuggeststhatARI,NCPI,PRI,andNDVIhave moderateco-linearityamongoneanotherandshowbetter repre-sentationoftheprincipalcomponents.Ontheotherhand,GNDVI andSRwerepositionedin closeproximitywithNDVIand NWI, respectively,indicatingstrongerco-linearityandpossible redun-dancyofinformation.

4. Discussion

Thehighestyieldrecordedinmoistcoolrain-fedconditionis consistentwiththehistoricalyieldaverageofthesiteandismainly attributed toits cool-moist growingcondition. In contrast, the droughtstressobservedinthisstudy(Fig.1)isatypicalpatternin PNWsemiaridareasthatstartswithlowsoilwaterbudgetduring plantingandprogressivelyworsensthroughgrainfill(Donaldson, 1996).OthelloandCentralFerryexperiencewarmersummersthat exacerbatethedroughtstress.Evenwhenoptimumsoilmoisture wasmaintainedthroughirrigation,theheatstresswassufficient totriggerearlysenescenceinmostofthePNWwinterwheat.The modelthataccountsforbothtemperatureandsoilmoistureclearly showedthatthedroughtstresswasacombinedeffectofmoisture deficitandhightemperaturewhichisatypicaldroughtscenarioin theregion(Milesetal.,2010).

ThehigheryieldresponsetoirrigationinOthellothanin Cen-tralFerrywasduetotherelativelyhightemperaturethatspedup theonsetofsenescenceandshortenedthegrain-filldurationin theCentralFerry.Theextendedpre-floweringgrowthandbiomass accumulation should be balanced with post-flowering assimi-lateusetomaximizeyieldgain fromirrigation(Reynoldsetal., 2001).Thephenologicaleventsbetweenplantingandphysiological maturityarehighlymodulatedbygenescontrollingvernalization

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Fig.5.Growthstage-speciﬁcmeasurementsofNDVIanditsdeclinecurveovergrowthstages.TheY-axisshowsthemeanNDVIvalueandtheX-axisshowsthegrowthstage foreachNDVImeasurement.ThetrendofeachlineshowsthechangeinmeanNDVIacrossgrowthstages.

requirement(Vrn)andphotoperiodsensitivity(Ppd)which deter-minethestemelongation,ﬂowering,andonsetofsenescence(Chen etal.,2010).PriorinformationindicatesthatPNWwinterwheatis predominantlyphotoperiodsensitive,meaningtheaccessionsdo nottransitiontoreproductivephasebeforefulﬁllingthe photope-riodrequirement(Santraetal.,2009).Asaresult,onlyafewlines ofthePNWaccessionswereobservedtoexhibitearlytransition toreproductivephaseandphysiologicalmaturity.Onthecontrary, linesthathavegeneticrelatednesstotheMidwestbreedinglines suchasJagger(PI593688)andKarl(PI564245)showedsubstantial degreeof earliness. Someof the allelic variationsin vernaliza-tionandphotoperiodresponsivenessgenesreportedlyhavestress adaptiveapplications.Such variants havebeenused todevelop earlymaturingwinterwheatvarietiesthataredesignedtoescape severeterminaldroughtandheatstress.Weobservedastrong cor-relationbetweenthetimetoheadingandphysiologicalmaturity.As aresult,mostoftheearlyvarietieshadlowbiomassaccumulation comparedtothelategenotypesasinferredfromNDVI measure-ments(Fig.4).

Inourstudy, thevariation inear emergencebetween treat-mentswasmainlyinresponsetotemperaturedifferences.Early earemergenceasaresultofmoisturedeﬁcitwaslessthan2%when comparedtotheirrigatedconditionsinthesametemperature con-dition.Suchminimaldroughtresponseinphenologyisexpected

whenwaterdeficitoccursaftertheonsetofthereproductivestage. Insupporttothisclaim,thewaterstressinthisexperimentstarted atbootingstageandprogressivelyincreasedafterwards. Addition-ally,thesoilwaterbudgetmayhavedelayedtheonsetofdrought responseuntilafterheading.Thisfindingalsosuggeststhatgrain yieldishighlydeterminedbythosetraitsthatareexpressedduring thegrainfillstage.

4.1. Phenotypicassociationamongagronomictraits

Earlyheadingandcompletionoflifecyclebeforetheonsetof terminalheatanddroughtstressisperceivedasayield-positive adaptivemechanism. Suchadaptive mechanismsarecommonly usedinMidwestthroughcultivarslikeJagger andKarltoavoid terminalheatstress.However,wedidn’tobservea yield advan-tageofearlyheadingandearlyphysiologicalmaturityinourstudy. Earlymaturity doesn’thaveoverall yieldadvantagein environ-mentswheresoilmoisturedeficitoccurpost-floweringandannual rainfallfluctuatesbetweenyears(Foulkesetal.,2007).Early transi-tioningtoreproductivestagefollowedbyearlyonsetofsenescence hasapparentyieldadvantageinyearsofseverterminaldrought. Thispositiveassociationwasevidentin2013and2014growing seasonswhendroughtandhightemperaturestartedpostflowering andprogressedthereafter.However,earlytransitioningto

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repro-Fig.6. Theﬁrsttwoprincipalcomponentsofgeneticcovarianceamongmajormarketclasses(left)andagronomicandphysiologicaltraits(right)inPaciﬁcNorthwest winterwheatpopulation:DTHdaystoheading,SGstaygreen,PHTplantheight,PEpeduncleextrusion,GYgrainyield,TWtestweight,TKWthousandkernelweight,CT

canopytemperature,NDVINormalizeddifferencevegetationindex,SRsimpleratio,NWINormalizedwaterindex,PRIPhotochemicalreﬂectanceindex,NCPINormalized chlorophyll-pigmentratioindex,ARIAnthocyaninreﬂectanceindex,XESXanthophyllpigmentepoxidationstate.

ductivestageinresponsetocombinedeffectofhightemperature andwaterdeﬁcitwouldnothaveyieldadvantagewhenremnant soilmoistureisleftunusedasevidentin2012trial.These contrast-ingeffectsmighthavecompensatedwitheachotherresultinga neutraleffectofearlinessduringthestudyperiod.

Thelongvegetativeperiod(lateheading)observedunder irriga-tiondidn’tincreaseyield(Table4),suggestingthattheaccumulated assimilatesduringlongpre-floweringperiodwerenotcompletely utilized during the short grain fill duration (Understande and Christiansen,1986;SlaferandRawson,1994;Wheeleretal.,1996). Additionally,lackofstandardplantstatureinsomeaccessionsled tocontinuousincreasesinheightandverylatetransitionto repro-ductivephase,reducingoverallefficiencyofassimilatepartitioning (Marri etal.,2005).Ontheotherhand,thepositiveassociation betweenheadingdateandgrainyieldobservedinmoistcool rain-fedconditionresultedfromthelowertemperatureandoptimum soilmoisturewhichextendedthephysiologicallyactiveperiodfor assimilatesynthesis,reserve,andrelocationfornormalgrain devel-opment(LopesandReynolds,2012).Asaresult,geneticvariation inthis traitcouldbeutilized toimproveyield inenvironments thathavemoderatethermaltimeandremnantsoilmoistureasthe plantsareclosetomaturity.

Thetraitsthatshowedconsistentassociationwithgrainyield acrossenvironmentsmaybethemostdesiredtraitstostabilize yieldinthechangingenvironment.Thousandkernelweight,grain number perspike, andstay green fallin this category andwill allowfurtheryieldimprovement inwiderangeofenvironment. Thecompensatoryinteractionofgrainnumberandgrainweight washighlightedbythenegativecorrelationofthesetraitsinall moistureregimes.Thisrelationshipisattributedtoinsufficientrate anddurationofgrainfillasdiscussedinDuguidandBrule-Babel (1994).Duetothiscompensationeffect,breedersoftenimprove grainyieldeitherthroughimprovinggrainweightorgrainnumber perplant.Suchdifferentialselectionhistorymayhavecausedthe remarkabledifferentiationbetweensoftandhardmarketclassesof PNWwinterwheatinthedegreeofphenotypicassociationbetween thousandkernelweight,grainnumberperspike,andgrainyield. Ontheotherhand,theenvironmentspecificassociationsofgrain

yieldwithcanopytemperature,plantheight,anddaystoheading indicatethepossibilityofimprovinglocalproductivitybyselecting alternativevariantsofthesetraits.

Positive associationbetween yield and the stay green char-acterwasfoundinallstudiedconditions.Unlikephenologyand plantstature,staygreenisthegenotypicabilitytomaintain hydra-tionstatusandsystemintegrityandtosustainphotosynthesisand assimilaterelocation(ThomasandSmart,1993;Christopheretal., 2008).Thisresultsuggeststhat variation canbeutilized to co-improvebothyieldpotentialanddroughttoleranceinPNWwinter wheat.Genotypicstaygreencharacteristicscouldbeattributedto variousmorpho-physiologicaltraitssuchasrootaccesstodeepsoil moisture,efﬁcienttranspirationsystem,andplantarchitecturethat wereintrogressedin duecourseoftheregionalbreedingeffort. Genotypesthathavehigherstaygreeninthisstudycanbefurther evaluatediftheypossess distinctivecompositionofthese alter-nativetraitsandexplorethepossibilityofaccumulatingthemto furtherincreaseagronomicperformance.

4.2. Relationshipbetweenreﬂectanceindicesandgrainyield

Ingeneral,SRIsmeasuredatmid-grain-ﬁllweremorestrongly associatedwithyieldthanatothergrowthstages.Previousreports havesuggestedthatthisstageismoreinformativebecause geno-typicvariationsinleafareaindexandsubsequentlyinSRIsarelow duringheadingandearlyvegetativestages(Babaretal.,2006).In addition,earlymeasurementsarealsoconfoundedbysaturation problemsofsomeindices(unabletodiscerngenotypesfor sub-tledifferences)neartheirpeakvalue(JiangandHuete,2010).The correlationsacrossenvironmentsandsubgroupswereless consis-tentforgrowthstagespeciﬁcmeasurementsascomparedtothe parametersderivedfrommultiplegrowthstages(Table6).

ThecorrelationcoefficientsofgrainyieldwithNDVImeasuredat heading,earlygrainfill,andlategrainfillwerenotsignificantinat leastonetrial.Ontheotherhand,thecorrelationofgrainyieldwith AUVIC,weightedmean,andarithmeticmeanwerecomparableto thehighestcorrelationsofgrowthstagespecificmeasurements. Asaresult,selectionofhighyielding genotypesatthegrainfill

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stageseemsmoreefﬁcient.However,theenvironmentalvariation inmulti-locationandmulti-yearphenotypingmaycausehigher genotype-by-environmentinteractiononsinglecomparedto mul-tiplemeasurements(Babaret al.,2006).In suchcases,multiple measurementsacrossgrowthstagesmaybepreferredtocapture theresponseofvariousphysiologicalattributesthatcumulatively affectyield.

4.3. Relationshipbetweenstaygreenandvegetationindices

Therelationshipbetweenspectralreﬂectanceandstay green canbefurtherutilizedtodevelopathroughputphenotyping alter-nativeforthestaygreentrait.Staygreeninwheatisnotjustadelay inleafsenescence,butalsoaslowlyprogressinglossofgreenness inthepeduncleandspike(Reynoldsetal.,2009).Asaresult,the canopylevelspectralreﬂectanceprovidesamoreinclusive esti-mateofstaygreen.

4.4. Multico-linearityoftraitsanddimensionreduction

Asamajorlimitationatleastfromastatisticalpointofview, spectralreflectanceindicesexhibitsubstantialmultico-linearity amongthemselves.Thisisbecausemostindicesarederivedfrom eitherinfrared,visible,orbothlightspectrawhichplantsexhibit similarabsorptionandreflectancebehavior.TheclusteringofNDVI, SR,GNDVI,andPRIinonedimensionofcomponentanalysiswas oftheirphysiologicalconnectiontovegetative growth,biomass, andpigmentcomposition.Asdemonstratedinthisstudy,analysis ofgenotypiccovariancefordifferentindicescanbeeffectivelyused toreduceinformationredundancybyidentifyingdistinctiveindices thatrepresentdifferentphysiologicalattributes.Thisanalysiswill helpindevelopingareduced-dimensionpredictivemodelforgrain yield.Theobservationthatsomeindiceswerefoundtobe distinc-tivefromeachothervalidatespreviousreportsthattheseindices representdifferentphysiologicalattributesofyieldandyield sta-bility:NDVIwithbiomass,pigmentabundance, and staygreen; NCPIwithphotosyntheticefficiencyinstressedcondition, compo-sitionofstressrelatedpigments;NWIforandplanthydrationstatus (Babaretal.,2006;Reynoldsetal.,2012).

5. Conclusions

Droughtintensityin easternWashingtonand yield response ofthelocallyadaptedwinterwheatgermplasmwasaffectedby thecombinationofhighergrowingdegreedaysandsoilmoisture deﬁcit.Therefore,itisimportanttoconsiderbothgrowingdegree daysandavailablemoisturetocharacterizeyieldandyield stabil-ity.Thestudyalsohighlightedtheimportanceofcharacterizing droughtresponsesandphenotypicassociationofyielddetermining traitstofullyunderstandthemechanismsofdroughttolerance.The variationinphenologyamongtreatmentswasmainlyinresponse totemperature variation between thesites. Because the effect ofearlinessperseonyieldcanbeneutral,positive, ornegative dependingonthetimingandintensityofthestress,breeders usu-allystandardizetheirgeneticmaterialswithdesired phenology thatmaximizesthecultivar’sperformanceintargetenvironments. Themoderate to highstatisticalpower of SRI-based modelsto predictyieldinallconditionsshowsanimpendingsolutionto over-comephenotypingbottleneckandcharacterizelargergermplasm collections.PositiveassociationsbetweenyieldandSRI-based esti-matesofstaygreenwerefoundinallconditionsmakingthistrait oneofthepromisingphysiological traitsthatcanbeutilizedto co-improvebothyieldpotentialanddroughttolerance.Ingeneral, theproxymeasurementswillbeusefultofurtherimproveyield potentialandyieldstabilitybyfacilitatingselectionforyield

pos-itivetraitssuchasstaygreen, abovegroundbiomass,andplant hydrationstatus.

Acknowledgments

This projectwas supportedby Washington State University Hatchproject#0232,theWashingtonGrainCommissionProject #3234,andtheNationalResearchInitiativeCompetitiveGrants CAPproject2011-68002-30029fromtheUSDANationalInstitute ofFoodandAgriculture.WegreatlyappreciateRyanHigginbotham andGarySheltonformaintenanceoftheﬁeldscreeninglocations. WethankDr.MichaelPumphreyandDr.AsaphCousinsfortheir helpfulreviewofthemanuscript.

AppendixA. Supplementarydata

Supplementarydataassociatedwiththisarticlecanbefound,in theonlineversion,athttp://dx.doi.org/10.1016/j.fcr.2016.06.018.

References

Álvaro,F.,Isidro,J.,Villegas,D.,GarcíaDelMoral,L.F.,Royo,C.,2008.Oldand moderndurumwheatvarietiesfromItalyandSpaindifferinmainspike components.FieldCropsRes.106,86–93.

Alexander,W.,Smith,E.,Dhanasobhan,C.,1984.Acomparisonofyieldandyield componentselectioninwinterwheat.Euphytica33,953–961.

Aparicio,N.,Villegas,D.,Casadesus,J.,Araus,J.L.,Royo,C.,2000.Spectralvegetation indicesasnondestructivetoolsfordeterminingdurumwheatyield.Agron.J. 92,83–91.

Aparicio,N.,Villegas,D.,Araus,J.L.,Casadesús,J.,Royo,C.,2002.Relationship betweengrowthtraitsandspectralreﬂectanceindicesindurumwheat.Crop Sci.42,1547–1555.

Babar,M.A.,Reynolds,M.P.,vanGinkel,M.,Klatt,A.R.,Raun,W.R.,Stone,M.L., 2006.Spectralreﬂectancetoestimategeneticvariationforin-seasonbiomass, leafchlorophyll,andcanopytemperatureinwheat.CropSci.46,1046–1057. Bai,G.,Das,M.K.,Carver,B.F.,Xu,X.,Krenzer,E.G.,2004.Covariationfor

microsatellitemarkerallelesassociatedwithRht8andcoleoptilelengthin winterwheat.CropSci.44,1187–1194.

Barrett,B.A.,Kidwell,K.K.,1998.AFLP-basedgeneticdiversityassessmentamong wheatcultivarsfromthePaciﬁcNorthwest.CropSci.38,1261–1271. Blum,A.,1996.Cropresponsetodroughtandtheinterpretationofadaptation.

PlantGrowthRegul.20,135–148.

Blum,A.,2006.Droughtadaptationincerealcrops:aprolog.In:Ribault,J.M.(Ed.), DroughtAdaptationinCereals.FoodProductsPress,NewYork,pp.3–11. Chen,X.M.,2005.Epidemiologyandcontrolofstriperust[Pucciniastriiformisf.sp.

tritici]onwheat.Can.J.PlantPathol.27,314–337.

Chen,Y.,Carver,B.F.,Wang,S.,Cao,S.,Yan,L.,2010.Geneticregulationof developmentalphasesinwinterwheat,Mol.Breed.118,1339–1349. Christopher,J.T.,Manschadi,A.M.,Hammer,J.T.,Borrell,A.K.,2008.Developmental

andphysiologicaltraitsassociatedwithhighyieldandstay-greenphenotype inwheat.Aust.J.Agric.Res.59,354–364.

Cutforth,H.W.,Campbell,C.A.,Jame,Y.W.,Clarke,J.M.,Depauw,R.M.,1988. Growthcharacteristics,yieldcomponentsandrateofgraindevelopmentof twohigh-yieldingwheatsHY320andDT367,comparedtotwostandard cultivars,NeepawaandWakooma.Can.J.PlantSci.68,915–928.

Dhungana,P.,Eskridge,K.M.,Baenyiger,P.S.,Campbell,B.T.,Gill,K.S.,Dweikat,I., 2007.Analysisofgenotype-by-environmentinteractioninwheatusinga structuralequationmodelandchromosomesubstitutionlines.CropSci.47, 477–484.

Donaldson,E.,1996.Croptraitsforwaterstresstolerance.Am.J.Altern.Agr.11, 89–94.

Duguid,S.D.,Brule-Babel,A.L.,1994.Rateanddurationofgrainﬁllinginﬁvespring wheat(TriticumaestivumL.)genotypes.Can.J.PlantSci.74,681–686. Edae,E.A.,Byrne,P.F.,Manmathan,H.,Haley,S.D.,Moragues,M.,Lopes,M.S.,

Reynolds,M.P.,2014.Associationmappingandnucleotidesequencevariation inﬁvedroughttolerancecandidategenesinspringwheat.PlantGenome6, 1–13.

Edmeades,G.O.,Bola ˜nos,J.,Chapman,S.C.,1997.Valueofsecondarytraitsin selectingfordroughttoleranceintropicalmaize.In:Edmeades,G.O.,Bänziger, M.,Nickelson,H.R.,Pe ˜na-Valdivia,C.B.(Eds.),DevelopingDroughtandLow-N TolerantMaize.CIMMYT,Mexico,DF,pp.222–234.

El-Mohsen,A.A.A.,Hegazy,S.R.A.,Taha,M.H.,2012.Genotypicandphenotypic interrelationshipsamongyieldandyieldcomponentsinEgyptianbreadwheat genotypes.J.PlantBreedCropSci.4,9–16.

Farshadfar,E.,Elyas,P.,Hasheminasab,H.,2013.Incorporationofagronomicand physiologicalindicatorsofdroughttoleranceinasingleintegratedselection indexforscreeningdroughttolerantlandracesofbreadwheatgenotypes.Intl. J.Agron.Plant.Prod.4,314–325.

(12)

Fiorani,F.,Schurr,U.,2013.FutureScenariosforplantphenotyping.Annu.Rev. PlantBiol.64,267–291.

Fischer,K.S.,Fukai,S.,Kumar,A.,Leung,H.,Jongdee,B.,2012.Fieldphenotyping strategiesandbreedingforadaptationofricetodrought.Front.Physiol.3,282. Fischer,R.A.,Maurer,R.,1978.Droughtresistanceinspringwheatcultivars.I.

Grainyieldresponse.Aust.J.Agric.Res29,897–912.

Foulkes,M.J.,Sylvester-Bradley,R.,Weightman,R.,Snape,J.W.,2007.Identifying physiologicaltraitsassociatedwithimproveddroughtresistanceinwinter wheat.FieldCropsRes.103,11–24.

Gitelson,A.,Kaufman,Y.,Merzlyak,M.,1996.Useofagreenchannelinremote sensingofglobalvegetationfromEOS-MODIS.RemoteSens.Environ.58, 289–298.

Gitelson,A.A.,Zur,Y.,Chivkunova,O.B.,Merzlyak,M.N.,2002.Assessingcarotenoid contentinplantleaveswithreﬂectancespectroscopy.Photochem.Photobiol. 75,272–281.

Gomez,D.,Vanzetti,L.,Helguera,M.,Lombardo,L.,Fraschina,J.,Miralles,D.J.,2014. EffectofVrn-1,Ppd-1genesandearlinessperseonheadingtimein

Argentineanbreadwheatcultivars.FieldCropsRes.158,73–81.

Haboudane,D.,Tremblay,N.,Miller,J.R.,Vigneault,P.,2004.Remoteestimationof cropchlorophyllcontentusingspectralindicesderivedfromhyperspectral data.IEEETrans.Geosci.Rem.Sens.46,423–437.

Jiang,Z.,Huete,A.R.,2010.LinearizationofNDVIBasedonitsrelationshipwith vegetationfraction.Photogramm.Eng.RemoteSens.76,965–975. Kirkegaard,J.A.,Howe,G.N.,Pitson,G.,2001.Agronomicinteractionsbetween

droughtandcropsequence.Proceedingsofthe10thAustralianAgronomy ConferenceHobart.

Lin,C.S.,Poushinsky,G.A.,1983.modiﬁedaugmenteddesignforanearlystageof plantselectioninvolvingalargenumberoftestlineswithoutreplication. Biometrics39,553–561.

Liu,K.,Li,Y.,Hu,H.,Zhou,L.,Xiao,X.,Yu,P.,2015.Estimatingriceyieldbasedon normalizeddifferencevegetationindexatheadingstageofdifferentnitrogen applicationratesinsoutheastofChina,J.Environ.Ag.Ric.Sci.2,13.

Lopes,M.S.,Reynolds,M.P.,2012.Stay-greeninspringwheatcanbedeterminedby spectralreﬂectancemeasurements(normalizeddifferencevegetationindex) independentlyfromphenology.J.Exp.Bot.63,3789–3798.

Lopez,C.G.,Banowetz,G.M.,Peterson,C.J.,Kronstad,W.E.,2003.Dehydrin expressionanddroughttoleranceinsevenwheatcultivars.CropSci.43, 577–582.

Marri,P.R.,Sarla,N.,Reddy,L.V.,Siddiq,E.A.,2005.Identiﬁcationandmappingof yieldandyieldrelatedQTLsfromanIndianaccessionofOryzaruﬁpogon.BMC Gene13,33–39.

McNeal,F.H.,Qualset,C.O.,Baldridge,D.E.,Stewart,V.R.,1978.Selectionforyield andyieldcomponentsinwheat.CropSci.18,795–799.

Miles,E.L.,Elsner,M.M.,Littell,J.S.,Binder,L.W.,Lettenmaier,D.P.,2010.Assessing regionalimpactsandadaptationstrategiesforclimatechange:theWashington ClimateChangeImpactsAssessment.Clim.Change102,9–27.

Mohammadi,M.,Shariﬁ,P.,Karimizadeh,R.,Shefazadeh,M.K.,2012.Relationships betweengrainyieldandyieldcomponentsinbreadwheatunderdifferent wateravailability(drylandandsupplementalirrigationconditions).Not.Bot. HortiAgrobo.40,195–200.

Morgan,J.M.,1995.Growthandyieldofwheatathighsoilwaterdeﬁcitinseasons ofvaryingevaporativedemand.FieldCropsRes.40,143–152.

Mote,P.W.,2003.TrendsintemperatureandprecipitationinthePaciﬁc Northwest.NorthwestSci.77,271–281.

Naruoka,Y.,Garland-Campbell,K.A.,Carter,A.H.,2015.Genome-wideassociation mappingforstriperust(PucciniastriiformisF.sp.tritici)inUSPaciﬁcNorthwest winterwheat(TriticumaestivumL.).Theor.Appl.Genet.128,1083–1101.

Naumann,J.C.,Young,D.R.,Anderson,J.E.,2009.Spatialvariationsinsalinitystress acrossacoastallandscapeusingvegetationindicesderivedfromhyperspectral imagery.PlantEcol.202,285–297.

Ollinger,S.V.,2011.Sourcesofvariabilityincanopyreﬂectanceandtheconvergent propertiesofplants.NewPhytol.189,375–394.

Pe ˜nuelas,J.,Filella,I.,Biel,C.,Serrano,L.,Save,R.,1993.Thereﬂectanceatthe 950–970nmregionasanindicatorofplantwaterstatus.Int.J.RemoteSens. 14,1887–1905.

Pe ˜nuelas,J.,Baret,F.,Filella,I.,1995.Semi-empiricalindicestoassess

carotenoids/chlorophyllaratiofromleafspectralreﬂectance.Photosynthetica 31,221–230.

Reynolds,M.P.,Ortiz-Monasterio,J.I.,McNab,A.(Eds.),2001.CIMMYT,ElBatan, Mexico.

Reynolds,M.P.,Manes,Y.,Izanloo,A.,Langridge,P.,2009.Phenotypingapproaches forphysiologicalbreedingandgenediscoveryinwheat.Ann.Appl.Biol.155, 309–320.

Reynolds,M.P.,Pask,A.J.D.,Mullan,D.M.(Eds.),2012.CIMMYT,Mexico,DF. Rosyara,U.R.,Pant,K.,Duveiller,E.,Sharma,R.C.,2007.Variationinchlorophyll

content,anatomicaltraitsandagronomicperformanceofwheatgenotypes differinginspotblotchresistanceundernaturalepiphytoticconditions. Australas.PlantPathol.36,245–251.

Rouse,J.W.,Haas,R.H.,Schell,J.A.,Deering,D.W.,1973.Monitoringvegetation systemsinthegreatplainswithERTS.3rdERTSSymposiumNASASP-351I, 309–317.

Saiyed,I.M.,Bullock,P.R.,Sapirstein,H.D.,Finlay,G.J.,Jarvis,C.K.,2009.Thermal timemodelsforestimatingwheatphenologicaldevelopmentand weather-basedrelationshipstowheatquality.Can.J.PlantSci.89,429–439. Santra,D.K.,Santra,M.,Allan,R.E.,Campbell,K.G.,Kidwell,K.K.,2009.Geneticand

molecularcharacterizationofvernalizationgenesVrn-A1Vrn-B1,andVrn-D1 inspringwheatgermplasmfromthePaciﬁcNorthwestregionoftheUSA.Plant Breed.128,576–584.

Schillinger,W.F.,Papendick,R.,2008.Thenandnow:125earsofdrylandwheat farmingintheInlandPaciﬁcNorthwest.Agron.J.100,S-166–S-182. Slafer,G.A.,Rawson,H.M.,1994.Sensitivityofwheatphasicdevelopmenttomajor

environmentalfactors:are-examinationofsomeassumptionsmadeby physiologistsandmodellers.Aust.J.PlantPhysiol.21,393–426.

Stenberg,P.,Rautiainen,M.,Manninen,T.,2004.Reducedsimpleratiobetterthan NDVIforestimatingLAIinFinnishpineandsprucestands.SilvaFenn.38,3–14. Thomas,H.,Smart,C.M.,1993.Cropsthatstaygreen.Ann.Appl.Biol.123,193–201. Tucker,C.J.,Sellers,P.J.,1986.Satelliteremotesensingofprimaryproduction.Int.J.

RemoteSens.7,1395–1416.

Understande,D.J.,Christiansen,S.,1986.Interactionsofwatervariablesand growingdegreedaysonheadingphaseofwinterwheat.Agr.ForestMeteorol. 38,169–180.

Wheeler,T.R.,Hong,T.D.,Ellis,R.H.,Morison,J.I.L.,Hadley,P.,1996.Theduration andrateofgraingrowth:andharvestindexofwheat(TriticumaestivumL.)in responsetotemperatureandCO2.J.Exp.Bot.47,623–630.

Wiegand,C.L.,Richardson,A.J.,1990.Useofspectralvegetationindicestoinferleaf area,evapotranspirationandyield:i.Rationale.Agron.J.82,623–629. Wu,X.,Chang,X.,Jing,R.,2012.Geneticinsightintoyield-associatedtraitsof

wheatgrowninmultiplerain-fedenvironments.PLoSOne7,e31249. Zarate-Valdez,J.L.,Whiting,M.L.,Lampinen,B.D.,Metcalf,S.,Ustin,S.L.,Brown,

P.H.,2012.Predictionofleafareaindexinalmondsbyvegetationindexes. Comput.Electron.Agric.85,24–32.

vanGinkel,M.,Calhoun,D.S.,Gebeyehu,G.,Miranda,A.,Tian-you,C.,PargasLara, R.,Trethowan,R.M.,Sayre,K.,Crossa,J.,Rajaram,S.,1998.Planttraitsrelatedto yieldofwheatinearly,late,orcontinuousdroughtconditions.Euphytica100, 109–121.