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第 28卷 第 5期 作 物 学 报 Vol.28,No.5
2002年 9月 628～632页 ACTAAGRONOMICASINICA pp.628～632 Sept.,2002
ModelingofPhenologyforQualityProteinMaizeCultivarsunderDifferent
Environments*
FANXing-Ming1 ATTACHAIJintrawet2 YANGJun-Yun1 HUANGYun-Xiao1 TANJing1
(1InstituteofFoodCrops,YunnanAcademyofAgriculturalSciences,Kunming650205,China;2AgriculturalSystems,ChiangmaiUniversity,
Chiangmai53000,Thailand)
Abstract Traditionalagriculturalresearchresultisrecognizedassitespecific,slow,andexpensive.An
alternativetosolvethisproblemistousemodelingapproach.Anitrogen×varietyexperimentwascon-
ductedintheResearchStationofYunnanAcademyofAgriculturalSciences(25ºNLat.,109ºELong.,
1900msl.).Therewerefivenitrogenlevels,i.e.100,145,185,230,and270kgha-1.Threemaizevari-
eties,twoqualityproteinmaize(QPM),i.e.,Across8763,PozaRica8763,andonenormalmaizeMobei
1,wereused.Inordertosimulatetheeffectsofmanagementpracticeongrowthanddevelopmentofdiffer-
entmaizecultivarsbyusingtheCrop-EnvironmentResourceSynthesis(CERES)-MaizemodelinNorth-
ernThailand,onevarieties×plantingdatesexperimentwasconductedintheResearchStationoftheMul-
tipleCroppingCenter,FacultyofAgriculture,ChiangMaiUniversity(18º47NLat.,99º57ELong,300
msl.).Theexperimentwasconductedtogeneratedatasetforuseingeneticcoefficientsdetermination.
TherewerethreePlanting-datelevels:December20,1994,January5,1995,andJanuany20,1995.
Threemaizecultivarswereused,Across8763(QPM),PozaRica8763(QPM),andSuwan1.TheGeno-
typeCoefficientsCalculator(GENCAL)wasusedtodetermineasetofgeneticcoefficientsforthethree
cultivars.TheCERES-Maizemodelsatisfactorilysimulatedeffectsofplantingdatesongrowthanddevel-
opmentofdifferentmaizecultivars.Thissetofgeneticcoefficientswasthenusedtosimulateeffectsof
managementpracticesinYunnan.TheCERES-Maizemodeldemonstratedacceptableabilitytosimulate
phenologyevents,e.g,silking,andphysiologicalmaturitydates.
Keywords Qualityproteinmaize;Modeling;Phenology
在不同环境条件下优质蛋白玉米品种的物候期模型
番兴明1 ATTACHAIJintrawet2 杨峻芸1 黄云霄1 谭 静1
(1云南省农业科学院粮食作物研究所,云南 昆明 650205;2泰国清迈大学农学院农业系统项目,泰国 清迈,53000)
摘 要 传统农业研究方法的结果通常具有地域性,且周期长,且投入大,用作物生长模型模拟技术,是解决这一问
题的理想方法。为了用 CERES玉米生长模型预测栽培管理措施对不同品种生长发育的影响,在泰国北部清迈大学农
学院的多熟种植中心(北纬 18º47,东经 99º57,海拔 300m)进行品种×播种期的双因素试验,参试种为:Across8763
(QPM),PozaRica8763(QPM)和 Suwan1,3个播种期分别是 1994年 12月 20日、1995年 1月 5日、1995年 1月 20
日,然后采用模型中遗传参数计算器(GENCAL)计算出这 3个品种的遗传参数;在云南省农业科学院试验站(北纬
25º,东经 109º,海拔 1900m)进行一个品种×施氮量的双因素试验,试验有 5个施氮水平:分别是 100、145、185、230
和 270kg/hm2;3个参试种分别为:Across8763、PozaRica8763和普通玉米墨白 1号。采用泰国获得的玉米品种的遗
传参数对云南试验中两个品种的生长发育过程进行预测,结果表明 CERES玉米模型可以较准确地预测不同品种生长
发育。
关键词 优质蛋白玉米;预测;物候期
中图分类号:S513 文献标识码:A
Foundationitem:thisresearchwasfundedbytheFordFoundation.
作者简介:番兴明(1963-),男,云南腾冲人,副研究员,主要从事玉米遗传育种与栽培研究。
Receivedon(收稿日期):2000-10-30,Acceptedon(接受日期):2002-02-23
TheCrop-EnvironmentResourceSynthesis
(CERES)-Maizemodelisoneof12cropmodels
supportedintheDecisionSupportSystem forA-
grotechnology Transfer (DSSAT) software.
DatabaseandapplicationprogramsintheDSSAT
aredirectlyaccessibletothemodels.Thislinkage
providespowerfulmeansforapplyingthemodel
forstrategicdecision-makingatvariousmanage-
mentlevels.
Therearetwotypesofgeneticcoefficientsin
CERES-MaizeModel,thefirsttypeiscaleddevel-
opmentalorphenologicalorphasiccoefficientsand
designatedasPcoefficients.Thesecondtypeis
caledgrowthcoefficientsthatdesignatedasG
coefficients.ThePcoefficientsenablethemodelto
predicteventssuchasfloweringandmaturity.The
G coefficientsenablethemodeltopredictyield
componentsandyield.Thedefinitionofthegenet-
iccoefficientsofmaizeasfolows:
P1representsthegrowingdegreedaysatbase
temperatureof8℃(GDD8)fromtheseedlingemer-
gencetotheendofthejuvenilephase,andrange
from110to355.P1hasbeenmeasuredforanum-
berofcultivarsgrownincontroledenvironments
(Kiniryetal.,1983aandb).Forothercultivars,
P1canbeestimated,P1isapproximatelythe
GDD8fromseedlingemergenceto4dayspriortas-
selinitiation(Farmeretal.,1986).
P2representsthephotoperiodsensitivitychar-
acteristicsofmaize plant, and the coefficient
rangesfromzeroto0.8.P2isnormalydetermined
incontroledenvironmentstudies(Farmeretal.,
1986).
P5representsgrowingdegreedaysat8℃ base
temperaturefromsilkingtophysiologicalmaturity
andisapproximately685formostcultivarsthat
havebeen tested.However,itappearsto be
greaterinthecultivarsfrom tropical(Farmer,et
al.,1986).
G2representspotentialkernelnumberper
plantvariesfrom about560to834kernelsper
plant.
G3representspotentialkernelgrowthrate
thatisvariedfrom6to11mgkernel-1d-1.Kernel
growthratescanbeestimatedbytheexcisingker-
nelsfrommiddleportionoftheear,atleastthree
times,whichshouldbeginapproximately10days
aftersilkingandcontinuinguntiljustpriorto
physiologicalmaturity (Duncan and Hatfield,
1964).
Theobjectivesofthisstudyareasfalow:1)
todeterminatethegeneticcoefficientsoftheQPM
cultivars;2)tosimulatetheeffectsofplanting
dateson growth and developmentofdifferent
maizecultivarsbyusingtheCERES-Maizemodel
inNorthernThailand.
1 MaterialsandMethods
1.1 FieldExperimentinKunming
TheexperimentwasconductedinYunnanA-
cademyofAgriculturalSciences,Kunming,Chi-
na.Itisinsub-tropical,highlandarea(25ºNlati-
tude,and109ºE longitude,1,900msl)during
April,1994toNovember,1994.Thesoilwasa
deepsandyloam.
Twofactorswereusedintheexperimentas
folowings:Factor1:Variety,3varieties,Across
8763,PozaRica8763,andnormalmaizeMobeiNo
1.Factor2:Nitrogen,5levels,100,145,185,
230,and270kgha-1respectively.Asplitplotde-
signwiththreereplicationswasused.Mainplot
wasvarieties,sub-plotwasnitrogenlevels.The
nitrogenwasappliedtwice.Firstapplicationtook
placeatthefourthleafstage,1/3ofthefertilizer
wereapplied.Thesecondapplicationtookplace
whenthecropsreachitstenthleafstage,2/3of
thetotalfertilizerwereappliedforthesecond
time.
Cropphenology,i.e.,datesofseedlingemer-
gence,silking,tasseling,andphysiologicalmatu-
ritywasrecorded.Theeventsdateswererecorded
whenof50% ofplantsineachtreatmenthad
reachedthosestages.
1.2 FieldExperimentinThailand
TheexperimentwasconductedintheRe-
searchStationofMultipleCroppingCenter,Facul-
tyofAgriculture,ChiangMaiUniversity(18º47
Latitude,99º57Longitude,300msl.[meteres
9265期 FANXing-Mingetal.:ModelingofPhenologyforQualityProteinMaize……
abovesealevel(altilnde)])duringtheperiodfrom
December1994toMay1995.
Twofactorsusedintheexperimentwereas
folows:Factor1,Variety,3varieties,Across
8763(QPM),PozaRica8763(QPM),andnormal
maizeSuwan1.Factor2,Plantingdate(PD),3
levels,PD1:December20,1994,PD2:January5,
1995,andPD3:January20,1995.
Thedatacolectionwasconductedaccording
totheprocedureforIBSNATproject(Internation-
alBenchmarkSiteNetworkforAgrotechnology
Transfer,1988),theminimumdatasetforsystem
analysisandcropsimulation,whichisdescribedin
TechnicalReportIoftheproject.
Cropphenology,suchasdatesofseedlinge-
mergence,tasselinitiation,silking,polenshed-
ding,andphysiologicalmaturitywasvisiblyde-
tectedandrecorded.When50% plantsofeachplot
hadreachedthestageofdevelopment,thedates
wererecorded.Tasselinitiationwasestimatedby
examiningseveralplantsundermicroscopeevery
twodaysduringthecriticalperiod.
Inordertorunthemodel,thegeneticcoeffi-
cientsforthecultivarshavetobedetermined.The
GENCALutilityunderDSSAT 3.0wasusedto
determinethosecoefficientsbyusingtheobserved
silkingandmaturitydatesandobservedkernel
numbersperearfrom ChiangMaiexperiments.
Thesewereadjusteduntiltherewasmatchbe-
tweentheobservedandsimulateddatesofsilking
andmaturity.
2 ResultsandAnalysis
2.1 DeterminationofGeneticCoefficients
TheGenotypeCoefficientsCalculator(GEN-
CAL)utilitywasdevelopedtofacilitatedetermina-
tionofgenotypecoefficients(Hunt,1988;Huntet
al., 1993). GENCAL isavailable underthe
DSSAT 3.0shel.Thedatesofphenological
eventsofbothQPM cultivarsandSuwan1were
enteredintotheDSSAT3.0shelalongwithChi-
angMaiweather,soil,andmanagementpractice
data.TheGENCALutilitywasthenemployedto
determinegeneticcoefficientsforthethreemaize
cultivars.Thosecoefficients,ifsatisfy,wouldbe
usedtotestagainstexperimentsdatasetsinboth
KunmingandChiangMai.ByrunningtheGEN-
CAL,thesetofgeneticcoefficientswasdeter-
minedforthreecultivarsasshowninTable1.
Table1 GeneticcoefficientsofAcross8763,PozaRica
8763,Suwan1obtainedfromtheGENCALutilityusing
ChiangMaiexperimentaldataset,1995
Variety P1 P2 P5 G2 G3
Across8763 347.30 0.6 818.30 762.00 8.18
PozaRica8763 347.30 0.6 762.30 778.30 9.64
Suwan1 347.00 0.6 747.00 622.00 10.26
2.2 PhenologicalSimulationwithChiangMaiDa-
ta-MaturityDates
Themodeloverestimatedthetimetomaturity
ofAcross8763inPD1andPD3by1dayandun-
derestimateditby1dayinPD2.Themodelalso
underestimatedthematuritydatesofPozaRica
8763by1dayinPD1and2daysinPD2andpre-
ciselypredictedinPD3.Similarly,themodelover-
estimatedthematuritydateofSuwan1by1dayin
threeplantingdates.
Resultsoft-testontheinterceptandslopeof
the1:1regressionfortimetomaturityacrossva-
rietiesandplantingdatesindicatedsignificantdif-
ference,thatis,althoughtheslopeissignificantly
differentfrom1.0,theinterceptisnotsignificant-
lydifferentfrom0(Fig.1).Fig.1 Cmparisonofobservedandsimulateddaysto
physiologicalmaturityacrosscultivarsandplantingdates.
3 ModelValidationswithKunmingData
Set
036 作 物 学 报 28卷
Whisleretal.(1986)definedthemodelvali-
dationactivityasacomparisonbetweenthepredic-
tionofaverifiedmodelwithexperimentalobserva-
tionsotherthanthoseusedtobuildandcalibrate
themodelandidentificationorcorrectionoferrors
inthemodeluntilitissuitableforitsintended
purpose.TheCERES-Maizemodelwastestedby
comparingthedifferencebetweenobservedand
simulatedresultsintermsofphenologicalevents,
inKunmingexperiments.
Usingasetofgeneticcoefficientsdetermined
withthedatageneratedinChiangMaiforAcross
8763,andPozaRica8763,themodelunderesti-
matedthedaystosilkingofAcross8763by2days
andpreciselypredictedthoseofPozaRica8763.
Themodelpreciselypredictedthetimetophysio-
logicalmaturityofAcross8763andunderestimated
thoseofPozaRica8763byonly1day(Fig.2).Fig.2 Cmparisonofobservedandsimulateddaystosilking
andphysiologicalmaturitystagesacrosscultivarsand
nitrogenlevelsofKunmingexperiment.
4 DiscussionsandConclusion
Usingthegeneticcoefficientsgeneratedinthis
study,themodeldemonstratedanacceptableabili-
tytosimulatethephenologyeventsofthecultivars
inthetwocontrastingenvironments.Statisticalre-
sultsshowedthatregardlessofthevarietiesand
plantingdates,thet-testof1:1(observed:simu-
lated)regressionlineoftasselinitiation,silking,
physiologicalmaturityshown thelessdifferent
fromthetestofthezerointerceptandunityslope.
Thesimulationofsilkingandphysiologicalmaturi-
tyinKunmingexperimentseemedtoagreewel
withtheobservedresults.Usingthesetofgenetic
coefficientsinthisstudy,themodeldemonstrated
goodcapabilityinthesimulatingthephenology
eventsofthestudiedcultivarsinthetwocontrast-
ingenvironments.Statisticresultsshow thatre-
gardlessofthevarietiesandplantingdates,thet-
testof1:1(observed:simulated)regressionline
ofphysiologicalmaturityshowedthelessdifferent
fromthetestofthezerointerceptandunityslope.
Thesimulationofsilkingandphysiologicalmaturi-
tyagreeswelwiththeobservedresults.Thisindi-
catesthatthedevelopmentalgeneticcoefficients
(P1,P2andP5)werewelestimated,andthatthe
geneticcoefficientscalculatedwiththedatabased
ononeenvironmentbyusingGENCALcanbeap-
pliedtootherenvironments.
Ingeneralspeaking,themodelappearsto
havepassedthefirststepinmodeltesting,and
waseligibleforfuturetestingforaccurateinpre-
dictinggrowthofmaizeplants,sincethemodel
wasabletosimulatephenologysatisfactorilyforal
varieties.Thisisbecausemaizeplantphenologyis
thefactorthatinfluencesthemaizegrowthaswel
asitsgrainyieldandyieldcomponents.
TheCERES-Maizemodelisabletopredict
cropphenologyveryaccurately,itisascriticalas
theaccuracyinmodelingcropgrowthrateinorder
topredictcropproductivity.Themodelscanbe
appliedtoguidetheresearchandextensionworks
aslongasthesoilandclimaticdataareavailable
for different ecological regions in Yunnan.
CERES-Maizemodelcanhelpusstimulatecrop
growthanddevelopmentbetterandhelpthemim-
provethecropmanagementactivitiessuchasthe
fertilizerorpesticideapplication,polination,and
harvesting.Ingeneral,thismodelcanalsoprovide
usefulinformation on planting windows,plant
population,fertilizerregimes,andvarietyselec-
tion.
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=================================================
.44,1984.69～90
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236 作 物 学 报 28卷