PerformanceoftheSUBSTOR-potatomodelacrosscontrastinggrowingconditions
RubíRaymundoa,⁎
SentholdAssenga
RishiPrassada
UlrichKleinwechterb
JuanConchac
BrunoCondoric
WalterBowenj
JoostWolfd
JørgenE.Olesene
QiaoxueDongf
LincolnZotarellia
ManuelGasteloc
AshokAlvag
MariaTravassoh
RobertoQuirozc
VijayArorai
WendyGrahama
CherylPortera
aAgricultureandBiologicalloridaEngineeringDepartment,UniversityofFlorida,Gainesville,FL,USA
bInternationalInstituteforAppliedSystemsAnalysis(IIASA),Laxenburg,Austria
cInternationalPotatoCenter(CIP),Lima,Peru
dPlantProductionSystemsGroup,WageningenUniversity,TheNetherlands
eDepartmentofAgroecology,AarhusUniversity,Tjele,Denmark
fChinaAgriculturalUniversity,Beijing,China
gUnitedStatesDepartmentofAgriculture-AgriculturalResearchService(USDA-ARS),Sidney,MT,USA
1IntroductionPotatoisthemostimportantnon-graincropworldwidewithaproductionof330milliontonnesgloballyin2010(FAO,2010).Potatoproductionhasincreaseddramaticallyduringthelastdecadeinthedevelopingworld,surpassingtheproduction
levelsofthedevelopedworld(FAO,2010).Potatoconstitutesthemainsourceoffoodsecurityandincomeinthedevelopingworld(LutaladioandCastaidi,2009),andwillbecomeincreasinglyimportantasthepopulationisgrowingmorerapidlyinthe
developingworldthandevelopedregions(LutzandKC,2010LutzandKC,2010).Agrowingpopulation,alongwithclimatechangeandincreasingclimatevariability,willputadditionalpressureonpotatofoodsystems.Assessingtheimplicationsofthese
trendsrequiresintegratingcropmodelswhenevaluatingtheimpactofnewtechnologiesandstrategiesforadaptingtoclimatechange.
Atmosphericconcentrationofcarbondioxide(CO2)isexpectedtoincreasefrom400ppmin2010to–550ppmby2050(IPCC,2013).Potato,aC3crop,willrespondwithhigherphotosynthesisrate(Finnanetal.,2008)andwateruseefficiency
underelevatedatmosphericCO2concentrations(DeTemmermanetal.,2002b;Fleisheretal.,2013).ButhighlevelsofatmosphericCO2arethemaindriverofclimatechangeandwillincreaseglobaltemperatureandhigherrainfallvariability,leadingto
heatwavesandmoredroughtsinsomeregions(IPCC,2013).StudiesincontrolledexperimentchamberssuggestthatelevatedatmosphericCO2concentrationscanmitigatestressesduetowatershortage,buthightemperaturescanalsonegatethe
positiveeffectsofincreasedatmosphericCO2concentrationsoncropproduction(Kaminskietal.,2014).
Cropmodelsarepowerfultoolsthatdescribecropdevelopmentandgrowthasafunctionofcropmanagement,weather,andsoilconditions(HaverkortandTop,2011).Morethan30cropmodelshavebeendevelopedforpotato,andmanyof
themhavebeenusedtostudytheimpactsofclimatechangeonpotatoproduction(Raymundoetal.,2014).Overall,thesestudieshighlightthatdespitethepositiveeffectofatmosphericCO2concentrations,potatoproductionwilldeclineacrossmany
regionsintheworldby2100(Raymundoetal.,2014).However,Stockleetal.(2010) indicatedthat, taking intoaccount theeffectofCO2,adaptationstrategiesoncropproductionmightguaranteethecurrentproduction levelsunder futureclimate
changeconditions in thestateofWashington in theUnitedStates.Othershaveusedpotatocropmodels toassess the impactofclimatechangeonregional (Tubielloetal.,2002;Supitetal.,2012)andglobalpotatoproduction (Hijmans, 2003).
Nevertheless,modelshavebeendevelopedforspecificcultivarsandgeographicdomains(Griffinetal.,1993;;MacKerron,2004).Globalsimulationsrequiretakingintoaccountthecropvariabilityacrosstheglobeandtestingthemodelfunctionality
withastandardcultivaracrosslatitudes.Inmostoftheclimatechangestudies,potatomodelswereusedwithcultivarsandspeciesfromthedevelopedworld(Tubielloetal.,2002;Hijmans,2003;Supitetal.,2012),neglectingthecultivardiversityof
othercultivatedspecies,aswellastraditionalandmoderncultivars.CultivarsofthespeciesSolanumtuberosumaremostwidelygrown,whereassevencultivatedpotatospecies,includingSolanumandigenum(flourypotato),andSolanumjuzepzukii(bitter
potato),coexistinthetropicalAndes(HuamanandSpooner,2002).Also,severalhybridsofvariousspeciesaregrowninthedevelopingworld(Thieleetal.,2007),wheretheuseofpotatomodelsislimited.
hInstitutodeClimayAgua(INTA),LosReserosyLasCabañas,Castelar,Argentina
iDepartmentofSoilScience,PunjabAgriculturalUniversity,Ludhiana,India
jInstituteofFoodandAgriculturalSciences(IFAS),UniversityofFlorida,loridaGainesville,FL,USA
⁎Correspondingauthor.
Abstract
Cropmodelsareessentialtoolsinclimatechangeimpactassessments,buttheyoftenlackcomprehensivefieldtesting.Inthisstudy,wetestedtheSUBSTOR-potatomodelwith87fieldexperiments,including204treatmentsfrom19
countries.Thefieldexperimentsvariedinpotatospeciesandcultivars,Nfertilizerapplication,watersupply,sowingdates,soiltypes,temperatureenvironments,andatmosphericCO2concentrations,andincludedopentopchamberand
Free-Air-CO2-Enrichment(FACE)experiments.TuberyieldsweregenerallywellsimulatedwiththeSUBSTOR-potatomodelacrossawiderangeofcurrentgrowingconditionsandfordiversepotatospeciesandcultivars,includingSolanum
tuberosum,Solanumandigenum,Solanumjuzepczukiispecies,aswellasmodern, traditional,early,medium,and latematurity-typecultivars,witha relativeRMSEof37.2%for tuberdryweightand21.4%for tuber freshweight.Cultivars
‘Desiree’and‘Atlantic’weregrowninexperimentsacrosstheglobeandwellsimulatedusingconsistentcultivarparameters.However,themodelunderestimatedtheimpactofelevatedatmosphericCO2concentrationsandpoorlysimulated
hightemperatureeffectsoncropgrowth.Othersimulatedcropvariables,includingleafarea,stemweight,cropN,andsoilwater,differedfrequentlyfrommeasurements;someofthesevariableshadsignificantlargemeasurementerrors.
TheSUBSTOR-potatomodelwasshowntobesuitabletosimulatetubergrowthandyieldsoverawiderangeofcurrentgrowingconditionsandcropmanagementpracticesacrossmanygeographicregions.However,beforethemodelcan
beusedeffectivelyinclimatechangeimpactassessments,itrequiresimprovedmodelroutinestocapturetheimpactsofelevatedatmosphericCO2andhightemperaturesoncropgrowth.
Keywords:SUBSTOR-potato;Potato;Cropmodeling;Modelperformance;CO2;Hightemperature
Mostpublishedpotatocropmodelshadlimitedexposuretofieldmeasurementsfortesting,andnoneofthemhaveeverbeentestedwithobserveddataunderhightemperatureanddroughtconditions(Raymundoetal.,2014).Somepotato
cropmodelsstillignoretheeffectofincreasingatmosphericCO2concentrationsoncropgrowth(Hijmans,2003;Gobin,2010;SaueandKadaja,2011).MostmodelsincludeatheoreticalC3cropresponsetoelevatedatmosphericCO2(Raymundoetal.,
2014),butonlytwopotatomodels,LOPTCOandAQUACROP,weretestedwithexperimentaldataofyieldresponsetoelevatedlevelsofCO2concentrations(WolfandVanOijen,2003;Vanuytrechtetal.,2011).TheSUBSTOR-potatoandtheLINTUL-
potatomodelsare themostwidelyusedmodels for climatechangestudies (Frankeetal., 2013;Haverkortetal., 2013;Raymundoetal., 2014); however, bothmodels lackmodel testingwithexperimental dataunderelevatedatmosphericCO
concentrationexpectedinthefuture.Currently,publicationsofmodelapplicationsoutnumberpublicationsofmodelperformancetesting(Raymundoetal.,2014).Therefore, fieldtestingwithcurrentandpossiblefuturescenarios isrequiredtobuild
confidenceinanycropmodelapplication.ThemostextensivefieldpotatoexperimentaldatasetfromaroundtheworldhasbeenassembledtoevaluatetheperformanceoftheSUBSTOR-potatomodeltoguidemodelimprovementneedsandsupport
futuremodelapplications.
2Materialandmethods2.1Themodel
TheSUBSTOR-potatomodelbelongstoafamilyofcropmodelsintheDSSAT-CSM(DecisionSupportSystemsforAgro-technologyTransfer−—CropSimulationModel)software(Jonesetal.,2003;Hoogenboometal.,2012).Themodelinputsaredailyweather
data,soilprofileparameters,cultivarparameters,andcropmanagementinformation.TheSUBSTOR-potatomodelsimulatesthedailydynamicsofphenology,biomass,andyieldaccumulation.Themodelaccountsforsoilwaterdeficitfactorsthatreducephotosynthesis
(SWFAC)andgrowth(TURFAC)(Ritchie,1998Ritchieetal.,1995).Similarly, themodelusesanitrogendeficiencyfactor(NFAC)computedbytheactual leafnitrogencontent, thecritical leafnitrogencontentandminimumleafnitrogencontent toreducephotosynthesis
(NSTRES)andgrowth(AGEFAC)(GodwinandSingh,1998).Underwaterornitrogenstress,SWFACandNSTREShastentuberinitiationandincreasethecarbondemandoftubers.ThemodelhasbeenextensivelydescribedbyGriffinetal.(1993),Ritchieetal.(1995)
andSinghetal.(1998).Followingisabriefsummaryofthemodel.
TheSUBSTOR-potatomodelsimulatesfivephenologicalstages,including(1)pre-planting,(2)plantingtosproutelongation,(3)sproutelongationtoemergence,(4)emergencetotuberinitiation,and(5)tuberinitiationtoharvest.Fivecultivar-specificparameters
controlcropdevelopmentandgrowth.Theparameterstuberinitiationsensitivitytophotoperiod(P2,dimensionless)anduppercriticaltemperaturefortuberinitiation(TC,°C)affectphenology;andleafareaexpansionrate(G2,cm2m−2day−1),potentialtubergrowthrate
(G3,gm−2day−1),andanindexthatsuppressestubergrowth(PD,dimensionless)affectbiomassaccumulation(Griffinetal.,1993).
TheSUBSTOR-potatomodelhasdifferent trapezoidal temperature impact functions,whichsimulate theeffectof temperatureon leafgrowth (RTFVINE), rootand tubergrowth (RTFSOIL),photosynthesis (PRFT),and tuber initiation (RTFTI).Eachof these
functionshasarangefromzerotoone.ForRTFVINE,dailymeantemperatureisoptimalbetween18°Cand24°Candpotentialleafexpansionstopsat<2°Cand>35°C.ForRTFSOIL,soiltemperature(computedinthemodelfromdailymeantemperature)isoptimal
between15°Cand23°C,androotandtubergrowthstopsat<2°Cand>35°C.ForPRFT,meandailytemperatureisoptimalbetween15°Cand30°C,andphotosynthesisstopsat<3°Cand>42°C.ForRTFTI,aweightedaveragetemperatureisused(meanof0.75
timestheminimumtemperatureplus0.25timesthemaximumtemperature)andisoptimalbetween10°CandtheuppercriticaltemperaturesetwiththecultivarparameterTC.Tuberinitiationstopsat<4°Cand>TC+8°C(Griffinetal.,1993).
2.1.1TuberinitiationParametersTCandP2playakeyroleat tuber initiation. If temperature isaboveTC, the tuber initiationandtuberbulking is reducedor inhibited.Thus, theuppervalueofTCcanbe interpretedasrepresentinghigh temperature tolerance.P2describes the
sensitivitytodaylengthandhasadimensionlessvaluebetween0and1.ThecloserP2isto0,thelesssensitiveacultivaristolongphotoperiods.Bothparameters,TCandP2,areembeddedinfunctionsthatdeterminethetuberinitiationandinfluencetuberbulking.
Therelativetemperaturefunctionfortuberinitiation(RTFTI)isdescribedasfollows:
PleasealignformulatoleftRTFTI=1−(1/64)*(TEMP-TC)2;(TEMP>TC&TEMP<=TC+8)
Here,RTFTIisafunctionofweightedaveragetemperature(TEMP=tmin*0.75+tmax*0.25)andcriticaltemperature(TC).
Therelativedaylengthfunctionfortuberinitiation(RDLFTI)isdescribedasfollows:
RTFTI=0;(TEMP<=4)
RTFTI=1−(1/36)*(10-TEMP)2;(TEMP>4&TEMP<=10)
RTFTI=1;(TEMP>10&TEMP<=TC)
RDLFTI=(1-P2)+0.00694*P2*(24-PHPER)2
Here,RDLFTIisafunctionofdaylengthinhours(PHPER)andsensitivitytodaylength(P2).RDLFTIequals1whenphotoperiodislessthan12hours.
2.1.2BiomassaccumulationaftertuberinitiationandpartitioningIntheSUBSTOR-potatomodel,CO2concentrationsaffectthedailypotentialcarbonfixationandpotentialtubergrowth.Thepotentialcarbonfixationrateisdescribedasfollows:
Here,thePCARBisafunctionofradiationuseefficiency(RUE,gMJ−1),photosyntheticallyactiveradiation(PAR,MJm−2),andleafareaindex(LAI,dimensionless),whereplantdensity(PLANTS,plantsm−2)isusedtoexpressthepotentialcarbonfixationperunit
area.RUEis3.5gMJ−1fromemergencetotuberinitiationand4.0gMJ−1fromtuberinitiationtoharvest.PCARBismodifiedwithincreasedatmosphericCO2byapplyingarelativeCO2responsefactor(PCO2)forC3crops(Curryetal.,1990).Thisfactoris1atatmospheric
CO2concentrationof330ppmandincreasesasymptoticallyupto1.43ataCO2concentrationof990ppm.Theactualcarbonfixationrateiscalculatedbymultiplyingthepotentialcarbonfixationratewiththeminimumreductionfactorsforwatershortage(SWFAC),nitrogen
stress(NSTRES),ortemperaturefactorthataffectsphotosynthesis(PRFT)(Griffinetal.,1993).
Biomassaccumulationatthisstageisinfluencedbythethreeremainingcultivar-specificparameters,PD,G3,andG2.Aftertuberinitiation,themodelcomputestubergrowthintwosteps.First,itestimatesthepriorityformaximumtubergrowth(TIND)usingthe
sinkstrength(DTII)andthecarbondemandoftubersaftertuberinitiation(DEVEFF):
DTIIavgisathree-daymovingaverageofdailyvaluesofthesinkstrength(DTII).DTIIisestimatedasarelativefunctionoftemperature(RTFTI)andstressconditions.DEVEFFrepresentsthecarbondemandoftubersaftertuberinitiation,whereXSTAGEindicates
theprogressionthrougheachphenologicalstageasafunctionofthecumulativeleafthermaltime(CUMRTFVINE);theparameterPDrangesbetween0and1anddetermineshowfasttubersgetfullpriorityoverleafgrowth.Theconstant10multiplythefactorstomaintain
theresultbetween0and1.
Second,themodelestimatesthepotentialtubergrowth(PTUBGR,gplant−1day−1)asafunctionofpotentialtubergrowthrate(G3),relativetemperaturefactorforrootgrowth(RTFSOIL),andplantdensity(PLANTS,plantsm−2):
Actualtubergrowth(GROTUB,gplant−1day−1)isafunctionofpotentialtubergrowthaffectedbyTIND,andwaterandnitrogenshortages:
Actualleafexpansion(PLAG)isafunctionofpotentialleafexpansion(G2),limitedbytemperature(RTFVINE),water(TURFAC)andnitrogen(AGEFAC)shortages:
Leaf(GROLF),stem(GROSTM)androot(GRORT)growtharecomputedasfollows:
wheretheleafareatoleafweightratio(LALWR,270cmg−1)isaconstantthroughthecropdevelopment.
PCARB=RUE*PAR/PLANTS*(1-EXP(-0.55*LAI))*PCO2
TIND=DTIIavg*(1/NFAC)*DEVEFF;NFAC>1
TIND=DTIIavg*DEVEFF;NFAC<1
DTII=RTFTI;ifnostress
DTII=RTFTI+0.5*(1-min(SWFAC,NSTRES,1))
DEVEFF=min((XSTAGE-2)*10*PD,1)
XSTAGE=2.0+(CUMRTFVINE)/100
PTUBGR=G3*PCO22*RTFSOIL/PLANTS
GROTUB=PTUBGR*min(TURFAC,AGEFAC,1)*TIND
PLAG=G2*RTFVINE/PLANTS*min(TURFAC,AGEFAC,1)
GROLF=PLAG/LALWR
GROSTM=GROLF*0.75
GRORT=(GROLF+GROSTM)*0.2
Themodelconvertstuberdryweighttotuberfreshweightassumingadrymattercontentof20%.Otherwise,themodelestimatesonlydryweightforleaves,stems,androots.
Finally,inDSSAT-CSM,includingtheSUBSTOR-potatomodel,atmosphericCO2concentrationof550ppmincreasesthestomatalresistanceby37%(Allen,1990).Thiseffect,whichisassociatedwiththeboundarylayerandcanopyresistance,causesanincrease
intranspirationefficiency.
3ExperimentaldataFor thisstudy,weuseddata fromexperimentsconducted inpotatoproduction regionsacross theworld (Fig.1a).Theexperimentswereclassified into temperate,subtropics,and tropic regions (CIP,1992).Theaveragephotoperiods for
experimentsintemperate,subtropics,andtropicregionswere14.90,11.21,and12.06hours,respectively.Inthesubtropics,thephotoperiodwasshorttomoderatelylongdependingontheseason,whereasinthetropicsthephotoperiodwasconstant
throughouttheyear(Fig.1b).Theexperimentsrepresentawiderangeofgrowingenvironments,includingdifferentelevationsandsoiltypes.Thus,theexperimentscovereddifferenttemperatureregimes(Fig.1c)andalsoawiderangeofcultivartypes,
cultivarspecies,andcropmanagementpractices,acrossatotalof87experimentsconductedfrom1970to2013in19countries,consistingof12soiltypes,32cultivars,and204treatments.Theexperimentshavebeencarriedouttostudydrymatter
allocation;yieldresponsetovarioustreatments,includingnitrogen(N)fertilizerapplications,watersupplyrates,radiationdeficit,impactofhightemperature;theadaptabilityofcultivarsacrosslocationsandyears;andtheeffectofincreasedatmospheric
CO2concentrationsoncropdevelopmentinOpenTopChambers(OTC)andFree-Air-CO2-Enrichment(FACE)facilities(Table1a).Experimentsselectedforthisstudywerefullycontrolledtoprevent,pests,diseases,andweeds.
Fig.1(a)Globalpotatoproducingareas(gray)withmodeltestsites(Monfredaetal.,2008),(b)photo-period,and(c)weightedaveragetemperatures(=0.75×minimumtemperature+0.25×maximumtemperature)duringcropgrowthperiodsatmodeltestsites.
alt-text:Fig.1
Table1(a)Experimental−sitesandmeasuredvariablesusedinthesimulation–observationcomparisons–sortedalphabeticallybycountryname.(b)Experimentalsitesandmanagementtreatmentsusedinthemodeltesting—sortedalphabetically
bycountryname.
alt-text:Table1
(A)Location Year lata lonb altc Objectived tre cultf repg In-seasonsampling Measuredvariablesh SoilTexturei Reference
Argentina,Balcarce 1991 −37.8 −58.3 97 Nrates 4 1 5 tu CL Travassoetal.(1996)
Australia 1970 −35.0 149.0 Radiationdeficit 3 1 10 tuf,LAI SC Hoogenboometal.(2012)
Belgium,Tervuren 1998–1999 50.8 4.5 97 CO2OTC 1 1 3–6 2 tu,le,st,to,LAI SiL DeTemmermanetal.(2002a)
Bolivia,Belen 1997 −16.0 −68.7 3640 Cultivaradaptation 1 3 3 3 tu,le CL Condorietal.(2010)
Bolivia,Chinoli 1997 −19.6 −65.3 3450 Cultivaradaptation 1 1 3 4 tu,le,st,ro,to SL Condorietal.(2010)
Bolivia,Koari 1997 −17.4 −65.6 3500 Cultivaradaptation 1 3 3 3 tu,le,st CL Condorietal.(2010)
Bolivia,Patacamaya 1997 −17.2 −68.0 3780 Cultivaradaptation 1 2 3–4 tu,le,st,ro SiCL Condorietal.(2010)
Bolivia,Patacamaya 1998(2) −17.2 −68.0 3780 Cultivaradaptation 1 2 3 3–4 tu,le,st,ro SCL Condorietal.(2010)
Bolivia,Toralapa 1993 −17.5 −65.7 3430 Cultivaradaptation 2 3 4 7 tu,le,st,ro, CL Condorietal.(2010)
China,Huhhot 1996 40.5 111.4 1065 Partitioning 1 1 6 tu,LAI SL Gaoetal.(2003)
China,Huhhot 1998 40.5 111.4 1065 Partitioning 1 2 6 tu,le,st,to SL Liuetal.(2003b)
China,Jining 1999 41.0 113.0 Partitioning 1 2 6 tu,le,st,to SL Gaoetal.(2004)
China,Zhalan 1997 48.0 123.0 Various 1 2 7 tu,le,st,to SL Liuetal.(2003a)
China,Zhalan 1998 48.0 123.0 Partitioning 1 3 7 tu,le,st,to SL Gaoetal.(2004)
Colombia,Cundinamarca 1999 4.4 −74.1 Modelvalidation 1 1 9 tu,le,st,to,LAI SiL ForeroHernandezandGarzonMontaño(2000)
Denmark,Jyndevad 1982–1983 54.9 9.1 10 Various 3 4 14–15 tu,to S Jørgensen(1984)
Denmark,Jyndevad 1990–1993 54.9 9.1 10 Nrates 4 1 6–7 tu,ro,to,tuN,roN,toN S Edlefsen(1991)
Denmark,Jyndevad 1984–1986 54.9 9.1 10 Nrates 2 1 5–7 tu,to,tuN S JørgensenandEdlefsen(1987)
Denmark,Tylstrup 1981–1983 57.2 10.0 10 Various 4 4 13–14 tu,to S BachandNielsen(1985)
Ecuador,SanGabriel 1985 0.6 −77.8 Nrates 3 2 4 tu SL ClavijoPonce(1999)
Finland,Jokioinen 1998–1999 60.8 23.5 84 CO2OTC 1 1 3 2 tu,le,st SL DeTemmermanetal.(2002a)
Germany,Giessen 1998–1999 50.6 8.7 68 CO2OTC 1 1 1–6 2 tu,le,st,to,LAI SL DeTemmermanetal.(2002a)
Germany,Giessen 1998–1999 50.6 8.7 68 CO2FACE 1 1 2–6 2 tu,le,st,to,LAI SL DeTemmermanetal.(2002a)
India,Ludhiana 2008–2011 30.9 75.8 244 Nratesandirrigation 4 1 1 tuf SL Aroraetal.(2013)
India,Modipuran 2002–2009 28.7 77.2 228 Various 1 1 1 tuf L,SiCL
Ireland,Carlow 1998–1999 52.9 −6.9 57 CO2OTC 1 1 3 2 tu,le,st,to SiC DeTemmermanetal.(2002a)
Italy,Rapolano 1998–1999 42.7 11.9 38 CO2FACE 1 1 3–4 2 tu,le,st,to,LAI SL DeTemmermanetal.(2002a)
Peru,LaMolina 2003–2010 −12.1 −77.0 244 Cultivaradaptation 1 1 1 tuf SL
Peru,LaMolina 2013 −12.1 −77.0 244 Cultivaradaptation 1 3 3 5 tu,le,st SL
Peru,LaMolina 1985 −12.1 −77.0 244 Cultivaradaptation 2 3 5 tu,le,st,to,LAI SL,SCL,SL TrebejoandMidmore(1990)
Peru,SanRamon 1984 −11.1 −75.3 800 Hightemperaturetolerance 1 3 4 tu,le,st,to SL Nelson(1987)
Peru,SanRamon 2013 −11.1 −75.3 800 Hightemperaturetolerance 1 3 3 5 tu,le,st,to SL
Scotland,Dundee 1984–1985 56.5 −3.1 40 Nrates 2 1 8 tu,le,st,to,LAI,de,tuN,leN,stN,toN SL MarshallandVanDenBroek(1995)
Scotland,Dundee 1986–1987 56.5 −3.1 40 Irrigation 4 1 8 tu,le,st,to,LAI,SWC SL MarshallandVanDenBroek(1995)
Sweden,Goteborg 1998–1999 57.9 12.4 58 CO2OTC 1 1 4–6 2 tu,le,st,to SL DeTemmermanetal.(2002a)
Uganda,Kalengyere 2001–2009 −1.2 29.8 2400 Various 1 1 1 tuf C
UnitedKingdom,Sutton 1998–1999 52.8 −1.3 87 CO2OTC 1 1 3 2 tu,le,st,to,LAI SL
UnitedStates,Benton 2003 45.9 −119.5 Nrates 2 1 5–6 tu,le,st,to,LAI,tuN,leN,stN,toN S Alvaetal.(2010)
UnitedStates,Hastings 2011–2012 29.7 −81.5 2 Nrates 2 3 3 1 tu,le,st,tuN,leN,stN,toN,soN S Zotarellietal.(2014)
UnitedStates,NewYork 1980 42.4 −76.5 Various 1 1 5 tu,le,st,to SL Hoogenboometal.(2012)
UnitedStates,Idaho 1988 45.8 −119.3 Various 1 9–15 tu,le,st,to,LAI SL Hoogenboometal.(2012)
UnitedStates,Suwanee 2010–2013 30.1 −83.1 13.7 Nmassbalance 1 1 12 1 tuf S Prasadetal.(2015)
UnitedStates,Suwanee 2001 30.1 −83.1 13.7 Nmassbalance 1 1 4 3–5 tu,le,st,soN,SWC S Albert(2002)
UnitedStates,Suwanee 2003 30.1 −83.1 13.7 Nmassbalance 1 1 8 3–5 tu,le,st,soN,SWC S Warren(2003)
(B)Location Year Ntr* Sowingdate
DOYEmergence
dateDOY
HarvestdateDOY Napplication(kg ha−1)** Irrigation(mm) Rainfall(mm) Typeofirrigation CO2(ppm) Cultivar
Argentina,Balcarce 1991 1 298 n.a. 64 0 113 540 Mixed Default Spunta
2 298 n.a. 64 60(1) 113 540 Mixed Default Spunta
3 298 n.a. 64 120(1) 113 540 Mixed Default Spunta
4 298 n.a. 64 160(1) 113 540 Mixed Default Spunta
Australia 1970 1 222 273 356 425(2) n.a. 219 Full Default Sebago
2 222 273 356 425(2) n.a. 219 Full Default Sebago
3 222 273 356 425(2) n.a. 219 Full Default Sebago
Belgium,Tervuren 1998+ 1N 127 135 257 205(2) 373 423 Mixed 380 Bintje
2N 127 135 257 205(2) 373 423 Mixed 386 Bintje
3N 127 135 257 205(2) 373 423 Mixed 676 Bintje
1999+ 1N 131 144 250 220(2) 182 204 Full 365 Bintje
2N 131 144 250 220(2) 181 204 Full 370 Bintje
3N 131 144 250 220(2) 183 204 Mixed 664 Bintje
Bolivia,Belen 1997 1 288 316 84 110(1) n.a. 264 Full Default Waycha
2 288 316 84 110(1) n.a. 264 Full Default Lucky
Bolivia,Chinoli 1997 1 301 340 62 124(1) n.a. 275 Full Default Desiree
Bolivia,Koari 1997 1 281 329 111 100(1) – 540 Rainfed Default Waychacal
2 281 329 111 100(1) – 540 Rainfed Default Alphacal
3 281 329 111 100(1) – 540 Rainfed Default Luckycal
Bolivia,Patacamaya 1997 1N 300 351 112 110(1) n.a. 341 Full Default Waycha
2N 300 351 112 110(1) n.a. 341 Full Default Lucky
Bolivia,Patacamaya 1998–1 1 292 347 110 110(1) n.a. 334 Full Default Waycha
2 292 347 110 110(1) n.a. 334 Full Default Lucky
Bolivia,Patacamaya 1998–2 1N 292 342 110 110(1) n.a. 334 Full Default Waycha
2N 292 342 110 110(1) n.a. 334 Full Default Lucky
Bolivia,Toralapa 1993 1N 295 351 103 120(1) n.a. 440 Full Default Waycha
2N 295 351 103 120(1) n.a. 440 Full Default Alpha
3N 295 351 103 120(1) n.a. 440 Full Default Lucky
4N 295 351 103 120(1) – 440 Rainfed Default Waycha
5N 295 351 103 120(1) – 440 Rainfed Default Alpha
6N 295 351 103 120(1) – 440 Rainfed Default Lucky
China,Huhhot 1996 1 118 n.a. 250 150(2) n.a. 252 Full Default Desiree
China,Huhhot 1998 1 115 n.a. 253 150(2) n.a. 470.9 Full Default Desiree
China,Jining 1999 1 119 n.a. 234 74(2) n.a. 156 Full Default Desiree
2 119 n.a. 234 74(2) n.a. 156 Full Default Kexin1cal
3 119 n.a. 234 74(2) n.a. 156 Full Default Jinguancal
China,Zhalan 1997 1 119 n.a. 253 180(2) n.a. 89 Full Default Desiree
China,Zhalan 1998 1 119 n.a. 242 90(2) – 754 Rainfed Default Kexin1
2 119 n.a. 242 90(2) – 754 Rainfed Default Neishu7cal
Colombia,Cundinamarca 1999 1 119 143 262 100(1) – 392 Rainfed Default Capiro
Denmark,Jyndevad 1981 1 119 149 225 155(1) 169 431 Mixed Default Bintje
1982 1 119 148 236 155(1) 222 521 Mixed Default Bintje
1983 1 122 148 215 155(1) 156 370 Mixed Default Bintje
Denmark,Jyndevad 1990 1 107 n.a. 267 180(1) 107 499 Mixed Default Bintjecal
2 107 n.a. 267 180(4) 104 499 Mixed Default Bintjecal
3 107 n.a. 267 180(4) 105 499 Mixed Default Bintjecal
1991 1 101 149 273 180(1) 137 390 Mixed Default Bintje
2 101 149 273 180(3) 137 390 Mixed Default Bintje
3 101 149 273 180(3) 137 390 Mixed Default Bintje
1992 1 100 139 224 180(1) 231 195 Mixed Default Bintje
2 100 139 224 180(3) 231 195 Mixed Default Bintje
3 100 139 224 180(4) 231 195 Mixed Default Bintje
1993 1 110 133 263 180(1) 70 350 Mixed Default Bintje
2 110 133 263 180(3) 70 350 Mixed Default Bintje
3 110 133 263 180(4) 70 350 Mixed Default Bintje
Denmark,Jyndevad 1984 1 117 151 278 150(1) 71 519 Mixed Default Tilvacal
2 117 151 278 200(1) 71 519 Mixed Default Tilva
1985 1 119 149 270 150(1) 27 465 Mixed Default Tilva
2 119 149 270 200(1) 27 465 Mixed Default Tilva
1986 1 118 146 293 150(1) 186 488 Mixed Default Tilva
2 118 146 293 200(1) 186 488 Mixed Default Tilva
Denmark,Tylstrup 1981 1 120 155 272 140(1) 25 405 Mixed Default Bintje
2 120 152 272 140(1) 25 405 Mixed Default Savacal
3 120 149 272 140(1) 25 405 Mixed Default Posmocal
4 120 150 272 140(1) 25 405 Mixed Default Kaptahcal
5 120 145 272 140(1) 25 405 Mixed Default Dianellacal
1982 1 109 149 270 180(1) 185 607 Mixed Default Bintje
2 109 155 270 180(1) 185 607 Mixed Default Sava
3 109 152 270 180(1) 185 607 Mixed Default Posmo
4 109 152 270 180(1) 185 607 Mixed Default Kaptah
5 109 149 298 180(1) 185 607 Mixed Default Dianella
1983 1 109 154 298 160(2) 135 566 Mixed Default Bintje
2 109 154 298 160(2) 135 566 Mixed Default Sava
3 109 150 298 160(2) 135 566 Mixed Default Posmo
4 109 154 298 160(2) 135 566 Mixed Default Kaptah
5 109 149 298 160(2) 135 566 Mixed Default Dianella
Ecuador,SanGabriel 1985 1 45 76 241 168(2) – 426 Rainfed Default INIAP-maria
2 45 76 241 117(1) – 426 Rainfed Default INIAP-gabriela
3 45 76 241 168(2) – 426 Rainfed Default INIAP-maria
4 45 76 241 117(1) – 426 Rainfed Default INIAP-gabriela
Finland,Jokioinen 1998+ 1 152 163 270 80(2) – 329 Full 375 Bintje
1999+ 1 149 159 264 80(2) – 122 Full 550 Bintje
Germany,Giessen 1998+ 1N 124 134 250 150(2) 67 365 Mixed 373 Bintje
2N 124 134 250 150(2) 67 365 Mixed 541 Bintje
3N 124 134 250 150(2) 67 365 Mixed 690 Bintje
1999+ 1N 130 147 258 116(2) 152 267 Full 380 Bintje
2N 130 147 258 116(2) 152 267 Full 541 Bintje
3N 130 147 258 116(2) 148 267 Full 708 Bintje
Germany,Giessen 1998 + + 1N 125 135 257 150(2) 186 417 Mixed 401 Bintje
2N 125 135 257 150(2) 186 417 Mixed 429 Bintje
1999 + + 1 130 145 239 156(2) 128 250 Full 374 Bintje
2 130 145 239 156(2) 126 250 Full 491 Bintje
India,Ludhiana 2008 1 290 n.a. 29 0 80 18 Mixed Default KufriBahar
2 290 n.a. 29 136(2) 80 18 Mixed Default KufriBahar
3 290 n.a. 29 180(2) 80 18 Mixed Default KufriBahar
4 290 n.a. 29 224(2) 80 18 Mixed Default KufriBahar
5 290 n.a. 29 0 160 18 Mixed Default KufriBahar
6 290 n.a. 29 136(2) 160 18 Mixed Default KufriBahar
7 290 n.a. 29 180(2) 160 18 Mixed Default KufriBahar
8 290 n.a. 29 224(2) 160 18 Mixed Default KufriBahar
9 290 n.a. 29 0 200 18 Mixed Default KufriBahar
10 290 n.a. 29 136(2) 200 18 Mixed Default KufriBahar
11 290 n.a. 29 180(2) 200 18 Mixed Default KufriBahar
12 290 n.a. 29 224(2) 200 18 Mixed Default KufriBahar
2010 1 285 n.a. 29 0 80 32 Mixed Default KufriBahar
2 285 n.a. 29 136(2) 80 32 Mixed Default KufriBahar
3 285 n.a. 29 180(2) 80 32 Mixed Default KufriBahar
4 285 n.a. 29 224(2) 80 32 Mixed Default KufriBahar
5 285 n.a. 29 0 160 32 Mixed Default KufriBahar
6 285 n.a. 29 136(2) 160 32 Mixed Default KufriBahar
7 285 n.a. 29 180(2) 160 32 Mixed Default KufriBahar
8 285 n.a. 29 224(2) 160 32 Mixed Default KufriBahar
9 285 n.a. 29 0 200 32 Mixed Default KufriBahar
10 285 n.a. 29 136(2) 200 32 Mixed Default KufriBahar
11 285 n.a. 29 180(2) 200 32 Mixed Default KufriBahar
12 285 n.a. 29 224(2) 200 32 Mixed Default KufriBahar
India,Modipuran 2002 1 288 n.a. 3 181(2) n.a. 0 Full Default KufriBahar
2003 1 299 n.a. 18 181(2) n.a. 30 Full Default KufriBahar
2004 1 293 n.a. 11 181(2) n.a. 0 Full Default KufriBahar
2005 1 289 n.a. 8 181(2) n.a. 1 Full Default KufriBahar
2006 1 294 n.a. 13 181(2) n.a. 0 Full Default KufriBahar
2007 1 298 n.a. 17 181(2) n.a. 0 Full Default KufriBahar
2008 1 290 n.a. 8 181(2) n.a. 12 Full Default KufriBahar
2009 1 302 n.a. 21 181(2) n.a. 0 Full Default KufriBahar
Ireland,Carlow 1998N 1 128 138 280 250(2) 61 343 Full 372 Bintje
2 128 138 280 250(2) 31 343 Full 693 Bintje
1999N 1 140 152 249 250(2) 89 392 Full 372 Bintje
2 140 152 249 250(2) 91 392 Full 670 Bintje
Italy,Rapolano 1998 + + 1 141 149 237 240(2) 309 554 Full 366 Bintje
2 141 149 237 240(2) 294 554 Full 552 Bintje
3 141 149 237 240(2) 285 554 Full 367 Bintje
1999 + + 1 126 147 237 250(2) 462 146 Mixed 367 Bintje
2 126 147 237 250(2) 462 146 Mixed 552 Bintje
3 126 147 237 250(2) 462 146 Mixed 367 Bintje
Peru,LaMolina 2003 1 181 n.a. 314 310(2) 450 0 Irrigated Default Amarilis
2004 1 177 n.a. 307 310(2) 350 0 Irrigated Default Amarilis
2005 1 164 n.a. 281 298(2) 450 0 Irrigated Default Amarilis
2006 1 186 n.a. 319 310(2) 350 0 Irrigated Default Amarilis
2007 1 152 n.a. 275 350(2) 400 0 Irrigated Default Amarilis
2008 1 182 n.a. 294 235(2) 350 0 Irrigated Default Amarilis
2009 1 183 n.a. 292 235(2) 400 0 Irrigated Default Amarilis
2010 1 196 n.a. 307 227(2) 350 0 Irrigated Default Amarilis
Peru,LaMolina 2013 1 179 200 288 210(2) 215 14 Full Default Achirana
2 179 198 288 210(2) 215 14 Full Default Atlantic
3 179 198 288 210(2) 215 14 Full Default Sarnavcal
Peru,LaMolina 1985 1 30 60 122 160(2) 449 3 Irrigated Default DTO-33
2 30 60 130 160(2) 480 3 Irrigated Default LT1
3 30 60 144 160(2) 485 3 Irrigated Default Revolucion
4 176 206 285 160(2) 315 1 Irrigated Default DTO-33
5 176 206 291 160(2) 257 1 Irrigated Default LT1
6 176 206 274 160(2) 272 1 Irrigated Default Revolucion
Peru,SanRamon 1984 1 109 122 199 200(2) n.a. 336 Full Default DTO-33
2 109 126 199 200(2) n.a. 336 Full Default Desiree
3 109 128 199 200(2) n.a. 336 Full Default Revolucion
Peru,SanRamon 2013 1 213 228 301 300(2) 449 303 Mixed Default Achiranacal
2 213 228 301 300(2) 449 303 Mixed Default Atlantic
3 213 228 301 300(2) 449 303 Mixed Default Sarnav
Scotland,Dundee 1984 1N 104 150 268 0 187 202 Mixed Default Marispiper
2N 104 150 268 240(1) 187 202 Mixed Default Marispiper
1985 1N 114 154 262 0 15 373 Mixed Default Marispiper
2N 114 154 262 240(1) 15 373 Mixed Default Marispiper
1986 1N 135 166 266 175(1) 91 200 Mixed Default Marispiper
1987 1N 119 155 258 175(1) 39 346 Mixed Default Marispiper
Sweden,Goteborg 1998+ 1N 145 154 252 88(2) 480 357 Mixed 708 Bintje
2N 145 155 252 88(2) 480 357 Mixed 404 Bintje
Uganda,Kalengyere 2004 1 61 n.a. 169 100(1) – 294 Rainfed Default Asante
2005 1 80 n.a. 189 100(1) – 318 Rainfed Default Asante
2006 1 82 n.a. 186 100(1) – 399 Rainfed Default Asante
2009 1 273 n.a. 355 120(1) – 501 Rainfed Default Asante
UnitedKingdom,Sutton 1998+ 1N 126 136 239 110(2) 98 251 Full 379 Bintje
2N 126 136 239 110(2) 97 251 Full 563 Bintje
3N 126 136 239 110(2) 99 251 Full 673 Bintje
1999+ 1N 132 144 249 250(2) 131 247 Full 399 Bintje
2N 132 144 249 250(2) 134 247 Full 543 Bintje
3N 132 144 249 250(2) 132 247 Full 694 Bintje
UnitedStates,Benton 2003 1 87 110 231 324(9) 666 164 Mixed Default RussetBurbank
2 87 110 231 669(5) 666 164 Mixed Default RussetBurbank
UnitedStates,Hastings 2011 1 12 43 108 168(3) n.a. 255 Full Default Atlantic
2 12 43 108 224(3) n.a. 258 Full Default Atlantic
3 19 45 117 168(3) n.a. 258 Full Default Atlantic
4 19 45 117 224(3) n.a. 258 Full Default Atlantic
5 20 45 116 168(3) n.a. 258 Full Default Atlantic
6 20 45 116 224(3) n.a. 258 Full Default Atlantic
UnitedStates,NewYork 1980 1 143 157 257 275(2) 209 297 Full Default Kathadin
UnitedStates,Idaho 1988 1 105 129 264 367(10) 669 136 Full Default RussetBurbank
2 89 115 174 354(15) 580 123 Full Default RussetBurbank
3 98 118 174 433(16) 687 136 Full Default RussetBurbank
4 117 134 264 349(15) 644 136 Full Default RussetBurbank
5 75 105 221 771(17) 598 123 Full Default RussetBurbank
6 81 114 250 375(11) 669 123 Full Default RussetBurbank
7 107 131 174 375(11) 605 123 Full Default RussetBurbank
8 91 120 174 175(7) 686 135 Full Default RussetBurbank
9 116 136 264 375(11) 686 136 Full Default RussetBurbank
10 98 125 174 375(11) 740 136 Full Default RussetBurbank
UnitedStates,Suwanee 2010 1 41 74 140 265(4) 281 758 Mixed Default RedLasoda
2011 1 28 57 118 278(5) 297 537 Mixed Default RedLasoda
2 43 62 140 285(5) 291 558 Mixed Default RedLasoda
2012 1 31 51 123 285(5) 349 320 Mixed Default RedLasoda
2 50 69 141 248(4) 343 356 Mixed Default RedLasoda
2013 1 45 65 140 248(4) 287 448 Mixed Default RedLasoda
UnitedStates,Suwanee 2001 1 46 62 141 313(5) 507 290 Mixed Default RedLasoda
2 46 62 141 280(5) 507 290 Mixed Default RedLasoda
2002 1 43 60 137 292(5) 343 481 Mixed Default RedLasoda
2 46 64 138 261(5) 272 489 Mixed Default RedLasoda
2003 1 41 64 138 278(4) 242 576 Mixed Default RedLasoda
cal:Treatmentsusedforcalibration.N:TreatmentswithestimatedinitialsoilN.
*:Numberortreatments.
**:Numberofnitrogenapplicationsareinparenthesis.
+:OTC.
++:FACE.
n.a.:Notavailable.
−:Notapplicable.
Full:Automaticirrigation.
Default:AtmosphericCO2concentrationcalculatedbyDSSAT-CSM.
a Latitude.
b Longitude.
c Altitude.
d FACE:Free-Air-CO2-Enrichment,OTC:OpenTopChambers.
e nNumberoftreatments.
f nNumberofcultivars.
g sSamplingrepetitions.
h tu:tTuberdryweight(Mgha−1,tubf:Ttuberfreshweight(Mgha−1,le:Lleafdryweight(Mgha−1,st:Sstemdryweight(Mgha−1,to:abovegrounddryweight(Mgha−1,LAI:leafareaindex,de:deadtissuedryweight(Mgha−1;tuN:tuberNuptake
(kgha−1;le:LeafNuptake(kgha−1;stN:StemNuptake(kgha−1,toN:abovegroundnitrogenuptake(kgha−1),SoN:SoilNcontent(ppm),SWC:Soilwatercontent(m3m−3.
i C:clay;S:sand;Si:silt;L:loam.
Measurementsinmanyofthesepotatoexperimentsdiffered.Forexample,65oftheexperimentshadinformationabouttuberdryweight,while22experimentshadinformationabouttuberfreshweight.Mostexperimentshadin-seasontuber
growthmeasurements(oftenwithmore than twomeasurements),and21experimentsonlyhad informationabout the final tuberyield.Table1aandb lists theexperimentsweusedwith themeasuredexperimentalvariablesand themanagement
information.
3.1WeatherdataThe experiments included daily measurements of solar radiation, maximum and minimum temperatures, and precipitation. Missing data were filled in with data from NASA Prediction of Worldwide Energy Resource (http://power.larc.nasa.gov/cgi-
bin/cgiwrap/solar/agro.cgi).
3.2SoilparametersSeveralofthefieldexperimentshadmeasurementsofsoilparameters.Ifthisinformationwasnotavailable,itwascomputedusingtheSbuildsoilparameterestimationtoolavailableintheDSSAT-CSMsuiteofapplicationswhenquantitativeinformationofsoil
textureandorganiccarbonwereavailable.Genericsoilprofiles,availableinDSSAT-CSM,wereassignedonlywhenqualitativesoiltypeinformationwasavailable.
3.3CalibrationofcultivarparametersCultivarparametersP2,TC,G2,G3,andPDwereobtainedfromliteratureandotherwisefromtheDSSAT-CSMdatabase(Table2).ToestimatenewparametersfornewcultivarsweusedtheGeneralizedLikelihoodUncertaintyEstimation(GLUE)toolofDSSAT-
CSM(Jonesetal.,2011),whichrequiresadefaultsetofparametersandobserveddata.Thedefaultsetofparameterswasassignedfromarandomlyselectedcultivarorwasassignedfromaspecificcultivaronlyifanewcultivarsharedthepedigree(Berlooetal.,2007Berloo
etal.,2007)withaknowncultivarinTable2.Table1bshowsthetreatmentsusedforcalibration.WeevaluatedthemodelperformancewiththedefaultsetofparametersandwiththenewsetofparametersestimatedwithGLUE.ParametersTCandP2weremanually
adjustediftuberyieldsimulationsfailedinoneofcontrastinglocations(LaMolinaandSanRamon).Theseresultswerediscussedwithpotatoexperts(breeders)whoprovidedtheexperimentaldatasets.Aftercultivarparametersweredetermined,theywerekeptunchanged
acrossexperimentsandlocations.Table2liststhecultivarparametersusedinsimulationsperformedwiththeSUBSTOR-potatomodel.
Table2CultivarparametersusedintheSUBSTOR-potatomodel.
alt-text:Table2
Cultivar Species Maturitytype Country G2(cm2m−2day−1)G3
(gm−2day−1)PD(−) P2(−) TC(°C) Source
Achirana S.tuberosum Early Peru 2000 21 0.8 0.5 17
Alpha S.tuberosum Late Bolivia 1000 25 0.9 0.4 20
Amarilis S.tuberosum Medium Peru 2000 30 0.9 0.9 20 (U.Kleinwechter,pers.comm.,2014)
Asante S.tuberosum Medium Uganda 2000 26 0.7 0.9 21 (U.Kleinwechter,pers.comm.,2014)
Atlantic S.tuberosum Early Peru,UnitedStates 1000 25 0.9 0.6 17 Hoogenboometal.(2012)
Bintje S.tuberosum Late Europe 1000 30 0.8 0.1 19
Capiro S.tuberosum Late Colombia 1000 22 0.6 0.7 17 Bowenetal.(1999)
Desiree S.tuberosum Early China,Peru,andBolivia 2000 25 0.9 0.6 16 Hoogenboometal.(2012)
Dianella S.tuberosum Late Denmark 1500 24 0.6 0.3 18
DTO-33 S.tuberosum Early Peru 2000 25 0.7 0.6 17 Bowenetal.(1999)
INIAP-Gabriela S.tuberosum Late Ecuador 2000 19 0.9 0.3 19 Bowenetal.(1999)
INIAP-Maria S.tuberosum Late Ecuador 2000 22 0.4 0.5 19 Bowenetal.,(1999)
Jinguan S.tuberosum – China 2000 24 0.9 0.8 17
Kaptah S.tuberosum Late Denmark 1800 24 0.6 0.4 18
Kathadin S.tuberosum Late UnitedStates 2000 25 0.5 0.7 20 Hoogenboometal.(2012)
Kexin1 S.tuberosum – China 2000 25 0.9 0.8 17
KufriBahar S.tuberosum Early India 2000 22 0.9 0.8 23 (U.Kleinwechter,pers.comm.,2014)
LT-1 S.tuberosum Early Peru 2000 25 0.9 0.8 17 Hoogenboometal.(2012)
Luky S.juzepczukii Late Bolivia 2000 21 0.4 0.8 15
MarisPiper S.tuberosum Late Scotland 2000 25 0.8 0.4 17 Hoogenboometal.(2012)
Neishu7 S.tuberosum – China 1600 23 0.7 0.8 18
Posmo S.tuberosum Late Denmark 1500 24 0.6 0.3 18
RangerRusset S.tuberosum Late UnitedStates 1100 26 0.9 0.6 17 Hoogenboometal.(2012)
RedLasoda S.tuberosum Medium UnitedStates 2000 22 0.7 0.4 19 Hoogenboometal.(2012)
Revolucion S.tuberosum Late Peru 2000 30 1 0.6 17 Bowenetal.(1999)
RussetBurbank S.tuberosum Late UnitedStates 1100 26 0.9 0.6 17 Hoogenboometal.(2012)
Sarnav S.tuberosum Late Peru 1000 30 0.2 0.6 18
Sava S.tuberosum Late Denmark 1300 24 0.6 0.4 21
Spunta S.tuberosum Medium Argentina 1800 24 0.5 0.1 19 Travassoetal.(1996)
Tilva S.tuberosum Late Denmark 1500 24 0.9 0.3 18
Waycha S.andigenum Late Bolivia 1200 23 0.6 0.3 15
Zibaihua S.tuberosum – China 2000 25 0.9 0.8 17
G2:Leafexpansionrate,G3:Ttubergrowthrate,PD:Iindexthatsuppresstubergrowthaftertuberinduction,P2:Ssensitivitytophotoperiod,TC:Uuppercriticaltemperaturefortuberinitiation(°C).−:nNotavailable.
3.4SimulationsSimulated experiments were set to non-water-limiting conditions (automatic irrigation), when irrigation was known to be applied but actual rates weremissing and when the involved researchers confirmed non-water-limiting conditions. Additionally, some
experimentswereconfirmedtobenon-nitrogenlimitedbytheresearchers.Initialsoilconditionsweremissinginabout20%oftheexperiments;inthesecases,simulationswithvariousamountsofinitialmineralsoilNwerecarriedoutforonetreatmentandtheamountof
initialmineralNthatfittedthefinalyieldbestwasappliedtoallothertreatments.ThisprocesswasrepeatedforeveryexperimentwithnoinformationofinitialsoilN.InexperimentswithNratetreatments,theplantNuptakeofthelowestNtreatment(usuallyatreatment
withoutNfertilizer)wassetastheinitialmineralsoilN(Ritchieetal.,1995).Inexperimentswithinformationonsoilorganiccarbon,weinitializedthesoilcarbonpoolswiththeCENTURYmodel(Bassoetal.,2011;Porteretal.,2014),providingthestableorganiccarbonfor
eachsoillayer.Weassumed82%and90%ofthetotalorganiccarbonasstableorganiccarbonbetween0 to60cmandbelow60cm,respectively.
WeperformedsimulationswiththeSUBSTOR-potatomodel−–embodiedinDSSAT-CSM−–forallexperiments.EvapotranspirationwascalculatedwiththePriestley-Taylor/Ritchieformula;soilwaterinfiltrationwascomputedwiththecapacityapproachmethod;
soilevaporationwasestimatedwiththeSuleiman-Ritchiemethod;andthedynamicofcarbonandnitrogenwassimulatedwiththeCENTURYmodel(Hoogenboometal.,2012).
Finally,wesimulatedtheexperimentsfromemergencetoharvestdatewithinformationaboutweather,soilandcultivarcharacteristics,andcropmanagementpractices,asgiveninTable1aandb.Simulationsstartedatplantingdateiftheemergencedaywasnot
available.
3.5EvaluationofmodelperformanceCropmodelperformancewasevaluatedbycomparingsimulatedandobservedin-seasonandend-of-seasonvalues.Experimentalcropmeasurementsincludedtuberdryweight(Mgha−1),tuberfreshweight(Mgha−1),abovegrounddryweight(Mgha−1),rootdry
weight(Mgha−1),leafdryweight(Mgha−1),stemdryweight(Mgha−1),deadmaterialdryweight(Mgha−1),leafareaindex(LAI,−),abovegroundN(kgNha−1),tuberinitiation(days),tuberNcontent(kgNha−1),rootNcontent(%),leafNcontent(kgNha−1),andstemN
content(kgNha−1).Experimentalsoilmeasurementsincludedsoilwatercontent(m3m−3),soilNO3
-N(ppm),andsoilNH4
-N (ppm).We evaluated themodel simulations by comparing withmeasured data from experiments, using statistical indices of coefficient of determination (R2), slope of a linear regression (m), root mean square error (RMSE) (Wallach andGoffinet, 1987), and
relativeRMSE(RRMSE).TheregressiontocalculatetheR2wasfor the1:1 lineandforcedthroughtheorigin.ThisR2valuemeasuresthetruedeviationof theestimates fromtheobservations(Yangetal.,2014).Theslopemquantifiesapossibleoverestimationor
underestimationbythemodel.TheRMSEwascomputedtoprovideameasureoftheabsolutemagnitudeoftheerror.AllcalculationsandgraphsweremadeusingtheRstatisticalsoftware(RCoreTeam,2015).
4ResultsFig.2showsacomparisonofsimulatedandobservedyieldsofthreepotatospecies,S.andigenum(cv. ‘Waycha’),S.tuberosum(cv. ‘Alpha’),andS.juzepczukii(cv. ‘Lucky’)atToralapa,Bolivia(1993)at3430m.a.s.l.Thein-seasontuberdry
weightwaswell-simulatedforthesethreespecies.Thesimulatedin-seasonleafdryweightaccumulation(Fig.2b,d,andf)followedthetrendoftheobservations,althoughitwaslessaccuratethanthetuberdryweightsimulations(Fig.2a,c,ande).
–and
Fig.3showstheperformanceofthemodelforcv.‘Desiree’indifferentlocationswithcontrastingtemperatureandphotoperiodenvironments.Thephotoperiodinthesefourlocationsrangedfrom11.4hoursinPeru(SanRamon)to14.8hours in
northernChina(HuhhotandWumeng).InHuhhot(Fig.3a)andWumeng(Fig.3b),thesimulationcapturedthedynamicsoftheobservationswell,buttendedtooverestimatefinalyieldsinHuhhot(Fig.3a).InSanRamonandChinoli,thesimulatedtuber
growthcorrespondedwellwiththeobservedtubergrowthduringtheinitialpartofthegrowthperiod(Fig.3Fig.3candd).However,attheselocationsobservedtubergrowthstoppedearlierthanassumedinthesimulation,resultinginadifferenceinthe
finaltuberyield.
Fig.2Simulated(—)versusobserved(●)tuberdryweight(Mgha−1)andleafdryweight(Mgha−1)forthreepotatospecies:(a,b)Solanumandigenum−cv.‘Waycha’,(c,d)Solanumtuberosum−—cv.‘Alpha’and(e,f)Solanumjuzepczukii−—cv.‘Lucky’inToralapa,Bolivia,1993.Errorbars
indicatestandarderrorofmeasurementswhenavailable.
alt-text:Fig.2
Fig.4showsacomparisonofsimulatedandobservedvaluesoftuberdryweight,leafareaindex,andtuberNuptakefortwoNtreatments(N0andN240,withapplicationratesof0and240kgNha−1,respectively)onasandyloamsoilat
Dundee,Scotlandin1985.ThemodelsimulatedaccuratelythetimecourseoftheobservedtuberdryweightsforthetwoNtreatments(Fig.4a).ThesimulatedresultsforbothLAIandtuberNuptakesometimesdifferedfromthemeasuredvalues(Fig.
4Fig.4bandc).Forexample,themodeloverestimatedthetuberNuptakefortheN0treatmentbutshowedagoodagreementfortheN240treatment.TheseresultsshowthatingeneralthemodelcanpredicttuberproductionwellfordifferentNfertilizer
treatments,althoughsometimesthesimulatedtimecoursesofLAIandtuberNuptakemaydifferfromtheobservedvalues(Fig.4).
Fig.3Simulated(—)versusobserved(●)tuberdryweight(Mgha−1)forcv.‘Desiree’at(a)Huhhot,China,1996,(b)Wumeng,China,1999,(c)SanRamon,Peru,1984,and(d)Chinoli,Bolivia,1997.Dottedlinesshowtheweightedaveragetemperatureforeachlocation.Errorbarsindicate
standarderrorofmeasurementswhenavailable.
alt-text:Fig.3
Fig.5presentsthemodelresultsfor87experimentsundervarioustreatmentsandconditions, includingnon-stress,water limited,hightemperature,andNlimitedconditions,andbothcurrentandelevatedatmosphericCO2concentrations.
Overall,themodelresultscorrespondedwellwiththeobservedtuberdryandfreshweights(Fig.5a,b).NotethatforsomeOTCtreatmentsthemodelunderestimatedthetuberdryweightdespitethenon-limitingconditionsofwaterandNmanagement
(Fig.5a).Forleafdryweight,stemdryweightandLAI(Fig.5c–f)thecorrespondencebetweensimulatedandobservedvaluesappearedtobelimited.Thetuberinitiationperiodwasgenerallysimulatedwellforallregions,althoughsomeunderestimated
valuesweresimulatedforthehighAndes(Patacamaya−3700m.—3700m.a.s.l)andhightemperatureconditions.
Fig.4Simulated(lines)versusobserved(symbols)tuberdryweight(Mgha−1),leafareaindex(LAI),andtuberNuptake(kgNha−1),fortwonitrogentreatments:N0,andN240atDundee,Scotland,1985.TreatmentN0(dottedlines,opensymbols)andtreatmentN240(solidlinesandsolid
symbols).
alt-text:Fig.4
Thesimulated tuberNcontentsand leafNcontentscorrespondedwellwith theobservedvalues(Fig.6aandc),but thesimulatedabovegroundandstemNcontentsshowed largediscrepancies (Fig.6bandd).Fig.6eand f presents a
comparisonofsimulatedandmeasuredsoilmineralNandsoilwatercontentsintheexperimentsatSuwanee,UnitedStates(subtropicalregion)andatDundee,Scotland(temperateregion).TheseresultsshowthatsoilmineralNasNO3
-NandNH4-NandNH4
N(notshowninfigure)werepoorlysimulated;additionally,theobserveddatahadlargemeasurementerrors.ThesoilwatercontentsweremoderatelywellsimulatedforSuwanneebutunderestimatedforDundee.
Fig.5Modelperformancefor(a)tuberdryweight(Mgha−1),(b)tuberfreshweight(Mgha−1),(c)stemdryweight(Mgha−1),(d)leafdryweight(Mgha−1),(e)leafareaindex,and(f)tuberinitiation(dap−—daysafterplanting)intropical(○),subtropical(△),andtemperate(+)regionsandfor
atmosphericCO2concentrations:380ppm(*),400ppm(×),500ppm(♢),550ppm(▽),680ppm(●),700ppm(□),forFACEandOTCexperiments.Errorbarsindicatestandarderrorofmeasurementswhenavailable.
alt-text:Fig.5
Fig.7providesthetuberyieldresponseofcv. ‘Achirana’undernon-high(LaMolina,Peru)andhightemperature(SanRamon)environments.ThiscultivarhasaTCof18°C;therefore,weightedaveragetemperaturesabovethisthreshold
inhibited tuber initiationandreduced tuberbulking. InLaMolinaandSanRamon,weightedaverage temperatures for tuber initiationweresuitable (<17°C)andunsuitable (>20°C), respectively.Undernon-high temperature conditions, themodel
providedsatisfactorysimulations.However,underhightemperatureconditions,themodelreproducedthefinalyieldwell,butoverestimatedthetuberinitiationandunderestimatedthetuberdryweightsduringthegrowthperiod.Thisshowsthatunder
hightemperatureconditionsthroughoutthegrowingseason,SUBSTOR-potatofailedtosimulatetheobservedgrowthdynamicswell.
Fig.6Modelperformanceof(a)tuberNuptake(kgNha−1),(b)abovegroundNuptake(kgNha−1),(c)leafNuptake(kgNha−1),(d)stemNuptake(kgNha−1),(e)soilmineralNasaNO3
N(ppm),and(f)soilwatercontent(m3m−3)forsubtropical(△),andtemperate(+)regions.Errorbarsindicatethestandarddeviationofmeasurementswhenavailable.Forpanel(e)and(f)errorbarswereavailablebutnotshown.
alt-text:Fig.6
Fig.8showsthetuberyieldresponsetoelevatedatmosphericCO2concentrationsinaFACEexperimentin1999atRapolano,Italy.SUBSTOR-potatosimulatedthetubergrowthunderambientCO2concentrationsreasonablywell,butfailedto
simulatethelargepositiveobservedyieldresponsetoelevatedatmosphericCO2.
Table3summarizestheperformanceoftheSUBSTOR-potatomodelversusexperimentalobservationsfor17variables.Simulationswiththemodelwerecomparedto5345actualmeasurements.ValuesofRRMSEwere37.2%fortuberdry
weight,21.0%fortuberfreshweight,22.6%fortuberinitiation,40.4%fortuberNuptake,and52.3%forleafNuptake.RRMSEforstemNcontent,abovegroundNcontent,andsoilNO3andNH4were>80%.
Table3SummaryofmodelperformanceofSUBSTOR-potatomodellingforallexperiments(seeTable1).
alt-text:Table3
Variable Numberofpaireddata Observedrange R2 Slope RMSEa RRMSEb
Tuberdryweight(Mgha−1) 946 0.00c–32.08 0.93 1.01 2.12 37.20
Tuberfreshweight(Mgha−1) 79 0.50–54 0.97 0.96 5.23 21.04
Abovegrounddryweight(Mgha−1) 758 0.03–9.75 0.69 0.64 1.93 85.33
Rootsdryweight(Mgha−1) 213 0.02–1.08 0.63 0.45 0.34 253.07
Fig.7Simulated(lines)versusobserved(symbols)tuberdryweight(Mgha−1)underhightemperatureatSanRamon,Peru,2013andalowtemperatureenvironmentatLaMolina,Peru,2013forcv.‘Achirana’.Hightemperaturesconditionswithdottedlinesandopensymbols,andlow
temperaturesconditionswithsolidlinesandsolidsymbols.Errorbarsindicatestandarderrorofmeasurementswhenavailable.Weightedaveragetemperatureforbothlocationsisembeddedinthegraphic.
alt-text:Fig.7
Fig.8Simulated(lines)versusobserved(symbols)cumulativepotatotuberdryweight(Mgha−1)forcv.‘Bintje’,FACEexperimentwithambient(370ppm)andelevatedatmosphericCO2concentration(560ppm)atRapolano,Italyin1999.TreatmentwithelevatedatmosphericCO2withdottedlines
andopensymbols,andtreatmentwithambientCO2withsolidlinesandsolidsymbols.Errorbarsindicatestandarderrorofmeasurementswhenavailable.
alt-text:Fig.8
Leafdryweight(Mgha−1) 504 0.01–3.67 0.61 0.64 0.97 90.34
Stemdryweight(Mgha−1) 471 0.02–4.32 0.51 0.48 1.32 141.42
Deaddryweight(Mgha−1) 57 000d–2.56 0.26 0.79 0.62 151.42
LAI 378 0.01–8.39 0.70 0.67 2.24 81.95
Tuberinitiation(dap) 116 26.00–113 0.96 0.93 10.54 22.65
TuberN(kgha−1) 184 0.10–318.20 0.92 0.90 44.78 40.40
AbovegroundN(kgha−1) 160 76.48–132.72 0.78 0.65 76.48 86.23
RootsN(kgha−1) 96 0.63–8.19 0.60 0.37 6.95 153.83
LeafN(kgha−1) 64 21.48–52.32 0.86 0.89 21.48 52.31
StemN(kgha−1) 64 0.62–59.25 0.74 0.28 47.18 309.57
Soilwatercontent(m3m−3) 891 0.03–0.49 0.89 0.89 1.55 62.08
NO3 -N(ppm) 240 0.10–58.10 0.42 1.35 9.82 95.45
NH4 -N(ppm) 240 0.60–185.60 0.05 1.66 19.42 140.09
a Rootmeansquareerror(Mgha−1).
b Relativerootmeansquareerror(%).
c 0.00002.
d 0.00002.
5Discussion5.1Cultivarsofthedevelopedworld
Thisstudypresentsacomprehensivemodeltestingforapotatocropmodel,usingmultiplecultivars,locations,andtreatments.Previousstudiesalsotestedvariouspotatocultivarsbutwereoftenlimitedinthenumberofcultivars.Otherstudieshadanalyzedmodel
performanceforasinglecultivarwiththemodelsSIMPOTATOandDANUBIA(Hodgesetal.,1992;Gayleretal.,2002;Lenz-Wiedemannetal.,2010);sixcultivarswiththemodelSUBSTOR-potato(Griffinetal.,1993);sevencultivarswiththemodelDAISY(Heidmannet
al.,2008);and10cultivarswiththemodelINFOCROP(Aggarwaletal.,2006).Onlyonemodel,SOLANUM,wasusedtocomparesimulatedandobservedyieldsforalargenumberofpotatospecies(Condorietal.,2010).Inourstudy,weanalyzedtheperformanceofthe
SUBSTOR-potatomodelforthreepotatospeciesand32potatocultivars.TheresultsindicatedthattheSUBSTOR-potatomodelcaningeneralreproducethetuberandleafdevelopmentfordifferentpotatospeciesandcultivars.
5.2CultivaruseacrossclimaticregionsAnimportanttestforanycropmodelistoperformsimulationsforonecultivargrownacrossawiderangeofclimaticregions.Cultivarparametersinsuchevaluationstudymustbekeptconstantacrossthedifferentenvironmentstobeconsideredtrulycultivar-
specific.WolfandVanOijen(2003)usedcv.‘Bintje’totestthemodelLPOTCOacrosseightlocationsinEurope,whereasHeidmannetal.(2008)usedcv.‘Agria’totestthemodelDAISYatthreelocationsofEurope.However,thelocationsusedintheirstudieswereallpart
ofthesametemperateregion.Inourstudy,acropmodelwastestedforthefirsttimewithacultivaracrossseveralclimaticregionsusingconstantcultivarparameters.Observedtuberyieldswerewellsimulatedforcv.‘Desiree’intemperate(China)andtropical(Peru,
Bolivia)regions.Similarly,simulationswereacceptableforcv.‘Atlantic’inthetropics(Peru)andsubtropics(southernUnitedStates)regions.Notethatconditionsbetweenthetemperateandtropicalregionsweremorecontrasting,whereasconditionsofthesubtropicsand
tropicsweremorealike.Tuberyieldsofcultivars‘Sarnav’and‘Achirana’werewellsimulatedinthetropics.Despitethelackofexperimentalmeasurementsofthesecultivarsintemperateandsubtropicsregions,wepresumethatthesamesetofparameterscanbeusedin
temperateregionsofUzbekistan,Argentina,andTheNetherlands,wherethesecultivarswereusedinvariousstudies(Butzonitchetal.,1994;Inceogluetal.,2010;Carlietal.,2014).TheseresultsindicatethatthecultivarparametersintheSUBSTOR-potatomodeldo
representcultivar-specificcharacteristicsandsupportthegeneralfunctionalityandtransferabilityofthismodel.
5.3NresponseTheSUBSTOR-potatomodelreproducedthetuberyieldresponsetovariousNtreatments.TheresultsvariedwithapplicationofNandthelevelsofsoilorganiccarbon(OC).InsoilswithhighOC,themineralizationofsoilorganicNcontributestothecropNsupply
duringthegrowingseason(Bassoetal.,2011).Therefore,themodelsimulatedhightuberyieldsforN0treatments(7.7Mgha−1ofdryweight)inDundee(OC=2.2%).Also,othermodelshavebeenshowntoreproducepotatoyieldsunderoptimumNrates(higherthan
150kgha−1ofN)(Hodges,1998;Gayleretal.,2002).TheSUBSTOR-potatomodelshowedreasonableresultsforN0treatmentsinasoilwithloworganiccarboncontent(OC=0.3%)(Aroraetal.,2013);however,usingthesameexperimentalsoilparameterizationdidnot
allowustoreproduceobservedplantgrowthdynamicsfortheN0simulationsobtainedbyAroraetal.(2013).ThesimulatedNmassbalancesuggestedthatothersourcesofNmusthavebeenavailable,buttheinformationprovidedbyAroraetal.(2013)didnotallowthese
sourcestobeidentified.EstimatesbyBobbinketal.(2010) indicatedthatatmosphericNdeposition inIndia,calculatedwithatransportanddepositionNmodel,couldrangebetween15 to–30kgyear−1andcouldpotentiallybeasignificantsourceofadditionalN for
croppingsystems,asalsoshownforotherregionsoftheworld(Assengetal.,2000).Similarly,wecouldnotsatisfactorilyreproducetheobservationsforsomeoftheNratetreatmentsforArgentinawhereNavailabilitylimitedcropgrowth(Travassoetal.,1996).
5.4SimulationoftuberyieldandothervariablesTheSUBSTOR-potatomodel simulated tuber dry and tuber freshweights in current growing conditions reasonablywell (Fig.5a and b). However, themodel indicated limitations for simulations under high temperature environments (Fig. 7) and elevated
atmosphericCO2concentrations(Fig.8).CropmodelsforcerealshavebeenshowntosimulateelevatedatmosphericCO2concentrationswell(O’learyetal.,2014),butthesemodelsstillrequireimprovementstosimulatetheimpactofheattemperaturestress(Assenget
al.,2015)andinteractionsofCO2withhightemperatures(Assengetal.,2013).
Othercropvariableswerelesswellsimulatedthantuberyields,includingabovegroundbiomass,LAI,androotdryweight.Thisshowsthatitisdifficulttosimulateleafandstemdryweightsandleafareaindexprecisely,butalsomeasurementerrorsareoftenlarge
forthesevariables(vanOijenandEwert,1999).Thepotentialbiomassisafunctionofphotosyntheticallyactiveradiation(PAR),radiationuseefficiency(RUE),andlightinterception.LightinterceptionsaturatesatLAIhigherthanthree;therefore,anyLAIhigherthanthis
valuewillhavethesameimpactonpotentialbiomass.
Leafareaismodeledbyconvertingtheincrementofleafweightintoleafareausingthespecificleafarea-weightratio(LALWR,270cmg-1).NgandLoomis(1984)reportLALWRfromdifferentpotatoexperimentsrangingfrom202to303cmg−1,howeverthe
variabilityofLALWRinpotatocropduringthecropdevelopmentandphenologyisnotwelldocumented.TheuseofvariousmethodstomeasuretheLAIofamaizecrophaveshownsubstantialdifferencesinasingleplotexperiment(Yangetal.,2012Yangetal.,2014
Consequently,someofthediscrepanciesbetweensimulationsandobservationsareduetofieldexperimentswithrelativelargemeasurementerrorcomprisedfromexperimentsfromdifferentsources.Inaddition,inthepotatomodel,biomassandyieldaccumulationarea
functionofLAI,lightinterceptionandRUE.However,otherfactors,suchnon-optimaltemperatures,waterandnitrogenstresscanlimitactualcarbonfixationinthemodel.Inaddition,understressconditionstubergrowthhaspriorityforcarbonallocationwithlesscarbon
allocationtoleavesandstems.Hence,whileLAIisimportantforlightinterception,itisoftennotthelimitingfactorforyield.
ThispartlyexplainsthediscrepanciesofobservedandsimulatedLAInotaffectinggrowthandyieldinthesameway.Thisphenomenonwasalsoreportedforothercrops(Assengetal.,1998;Assengetal.,2000).Otherpotatomodels,suchastheSPUDSIM
model,alsohaddifficulties insimulatingrootdryweight(Datheetal.,2014).Growthhabits(HuamanandSchmiediche,1999)androoting traits (Wishartetal.,2013)varyacrosscultivars,species,and regions.Forexample,S.tuberosum ismore robustand taller in
temperate regions,andsmaller in the tropics (VanderZaagetal.,1990); thiswould implicatediscrepancies instemweightofasamecultivar incontrasting regions.Traditionalandmoderncultivarsgivehigherharvest indexes thannon-improvedspeciessuchasS.
andigenumandS.juzeppzukii(Condorietal.,2010).Assomeof theexistingcultivarvariability isnot taken intoaccountvia thecurrentcultivar-specificmodelparameters, thiscouldpartlyexplain theratherpoorlysimulatedresults forabovegroundbiomassandroot
weights.Inaddition,thequalityofrootmeasurementsinpotatoescouldbeafactorinsomemodelobservationdiscrepancies(Ahmadietal.,2014).
Someofthemodeldiscrepancieswiththeobservedsoilwatercontent(SWC)andsoilmineralNcanbeattributedtotheone-dimensionalwatermovement(tippingbucket)oftheDSSATmodel(Ritchieetal.,1995)andthetwo-dimensionalstructureofridgesand
valleysinpotatofields.
5.5OverestimationattheendofthegrowingseasonIngeneral,theSUBSTOR-potatomodelresultsweremoreaccurateinexperiments,inwhichNsupplyfromthesoilwasexhaustedtowardtheendofthegrowingseason.However,themodeloftenoverestimatedthefinalyieldinsituationsinwhichthesoilNsupply
was large.Such overestimated yields are attributed to the lack of simulatingmaturity in theSUBSTOR-potato. The simulated crop growth requires constantwater andN supplies and stops under terminalwater andN limitations. The concept of cropmaturity and
senescenceiswidelydiscussedforpotato(MackerronandDavies,1986;Khanetal.,2013),andtheimpactofwaterorNstressoncropsenescenceandthematuritytypeofcultivars(early,medium,orlate)isnotclear.Themodelalsolackstheabilitytoaccelerateleaf
senescenceduetohightemperatures.Increasingtemperaturesinthesubtropicsattheendoftheseason(Rahmanetal.,2014)oftenacceleratecropsenescence(KoomanandHaverkort,1995).Thispartlyexplainswhypotatocultivarsinthesubtropicsusuallyhave
shortergrowingperiods(Santhoshetal.,2014).
5.6SimulationsunderhightemperaturesIntheSUBSTOR-potatomodel,hightemperaturehasnoeffectonabovegrounddevelopment,buthasadirectimpactontuberinitiationandtuberdevelopment.Therefore,underconstantlyhightemperaturesinlowlandtropics,themodelsimulatesadelayedtuber
initiationandunderestimatedthein-seasontubergrowth.Incontrast,experimentalobservationsinSanRamon,Peru,suggestedthattuberinitiationoccurreddespitehightemperatures.Somestudieshaveexploredtheeffectofhightemperaturesontuberinitiation(O’Brien
etal.,1998;LevyandVeilleux,2007).Theirresultsindicatedthathightemperaturesaffectedtheallocationofglucose,stimulatingabovegroundbiomassgrowthandsimultaneouslyreducingtuberaccumulationbutnotnecessarilyinhibitingtuberinitiation(Ewing,1981;
Gawronskaetal.,1992;BasuandMinhas,1999).OurresultsshowedthelimitedcapabilityoftheSUBSTOR-potatomodeltosimulatehightemperatureresponseswhenhightemperaturesarefrequentthroughoutthegrowingseason(e.g.,lowlandtropics).Ontheother
hand,themodelmatchedtheobserveddatawhenhightemperaturesoccurredaftertuberinitiationorattheendofthegrowingseason.Theseconditionswerefrequentinthesubtropics(UnitedStates)andinthetemperate(northernChina)regions.
5.7CO2effectFinnanetal.(2008)showedthatthefertilizationeffectsofincreasedCO2(550ppmto680ppm)ontuberyieldsofpotatoinOTCandFACEfacilitieswerehighlyvariable,rangingfrom−7.3%to+54%.TheFACEexperiments(550ppm)fromItalyandGermany
showedanincreaseontuberyieldof46%and5.75%respectively(Finnanetal.,2008).Jaggardetal.(2010)usedtherelativechangeofFACEexperimentsfromItalytoindicateayieldincreaseof36%by2050.Migliettaetal.(1998)indicatedanincreaseoftuberyieldof
10%forevery100ppmofCO2.TheFACEexperiments in Italypresented in thisstudywerealsoused to test theperformanceof themodelsLPOTCOandAQUACROP(WolfandVanOijen,2003;Vanuytrechtetal.,2011).Theobservedyield responseofpotato to
increasedCO2intheseexperimentswashighbutunderestimatedintheSUBSTOR-potatosimulations.AnunderestimationdidalsooccurbuttoalesserextentinthesimulationresultsfromthemodelLPOTCO(WolfandVanOijen,2003).IntheSUBSTOR-potatomodel,
thepotentialcarbonfixationandpotentialtubergrowthincreasesby17%,whenatmosphericCO2increasesfrom330ppmto550ppm.FortheFACEexperimentsinRapolano,Italy in1999,themodelsimulationsindicatedthatNstressshouldhavelimitedthecarbon
fixation.ThisresultedinalowersimulatedyieldresponsetoincreasedCO2ofonly3%,whereastheobservedyieldresponsewasashighas45%.However,simulationsoftheseexperimentsundersufficientNsupplyresultedinoverestimationoftheobserveddata.The
interactionsbetweenincreasedCO2anddifferentNfertilizerrateshavenotbeenstudiedinpotatofieldexperiments,althoughstudiesinothercropsindicatedthatincreasingNshortagereducestheyieldresponseofmostcropstoincreasedatmosphericCO2(Wolf,1996;
Kimetal.,2003;;Franzaringetal.,2011).Notethatintheexperimentsdoneinthe“CHangingclimateandpotentialImpactonPotatoyieldandquality”(CHIP)project(DeTemmermanetal.,2002b),theyieldresponseofpotatotoincreasedCO2wasmuchlower(i.e.,about
+20%to+30%iftheCO2concentrationincreasedfrom380to550ppm)thanthatobservedintheFACEexperimentsinRapolano(DeTemmermanetal.,2002b;WolfandVanOijen,2003).
6ConclusionTuberyieldsweregenerallywellsimulatedwiththeSUBSTOR-potatomodelfordifferentpotatospeciesandcultivars,acrossawiderangeofmanagementandenvironmentsundercurrentgrowingconditions.Thesimulationresultsforother
cropgrowthvariables(e.g.,leafareaindex,leafandstembiomass)werelessaccurateincomparisontoexperimentaldata,whichwaspartlyduetothelimitedparametersforcultivarcharacterizationintheSUBSTOR-potatomodel.However,someof
thesevariablesalsohadsignificantlargemeasurementerrors.ConsistentunderestimationsoccurredunderhightemperatureandelevatedatmosphericCO2concentrationsandrequireimprovementsbeforethemodelcanbeusedforclimatechange
impactassessments.
Implementingasenescenceroutineaffectedbyhighmaximumtemperaturesandmaturitytypeshouldimprovethemodelsimulationsunderhightemperatureenvironments.Thesenescenceroutineshouldtriggertuberinduction,affecttherate
anddurationof tuberbulking,anddecrease thewaterandnitrogenuptakeat theendof thegrowingseason. In theSUSBTOR-potatomodel, the relative response function toatmosphericCO2 is too lowanddoes requireadjustmentsbasedon
experimentaldata.UncitedreferencesAlbert(2002),BerlooR.v.Huttenetal.(2007),ZZZZ(2016),LutaladioandCastaidi(2009),Lutz(2010).
AcknowledgementsWethanktheInternationalResearchFoodPolicyResearchInstitute(IFPRI)andtheUSAIDlinkagefundproject“CollaborationbetweentheInternationalPotatoCenter(CIP)andtheUniversityofFlorida(UF)tobetterunderstandandprioritize
climatechangeadaptationneedsforfoodsecurityintheAndes”.
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QueriesandAnswersQuery:Theauthornameshavebeentaggedasgivennamesandsurnames(surnamesarehighlightedintealcolor).Pleaseconfirmiftheyhavebeenidentifiedcorrectly
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Highlights
• TheSUBSTOR−—potatomodelwastestedwith87experimentsand204treatments,including32cultivarsandthreepotatospecies.
• Themodel-observationcomparisonshowedthattheSUBSTOR-potatomodelcaningeneralsimulatetuberyieldsacrosscontrastingenvironments.
• However,theSUBSTOR-potatomodelcannotaccuratelysimulatetuberyieldunderelevatedCO2concentrationsandhightemperatureswhichneedstobeimproved.
Ng,E.,Loomis,R.S.,1984.Simulationofgrowthandyieldofthepotatocrop.Centreforagriculturalpublishinganddocumentation,Wageningen,TheNetherlands.
Remove:Singetal.1998andGodwinandSingh1998
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Answer:OK.
Query:PleasechecktheauthornamesinRef."Finnanetal.,2008"andcorrectifnecessary.
Answer:Pleasereplacewith:
Finnan,J.M.,Donnelly,A.,Jones,M.B.,Burke,J.I.,2008.Theeffectofelevatedlevelsofcarbondioxideonpotatocrops.JournalofCropImprovement13,91-111.
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Answer:Pleasekeeptables1aand1bseparate,alsokeepthefootnotesbeloweachcorrespondingtable(assubmittedintheoriginaldocument).
Query:PleasechecktheeditsmadeinTables1aandbandcorrectifnecessary.
Answer:Pleasekeeptables1aand1bseparate,alsokeepthefootnotesbeloweachcorrespondingtable(assubmittedintheoriginaldocument).