nd International Plant Phenotyping Symposium 2011 · 2nd International Plant Phenotyping Symposium...
Transcript of nd International Plant Phenotyping Symposium 2011 · 2nd International Plant Phenotyping Symposium...
2nd International Plant Phenotyping Symposium 2011
September 5th – 7th, 2011Jülich, Germany
Book of Abstracts
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Organizers
Sponsors & Exhibitors
COMMITTEES
Jülich, 5. – 7. September 2011 3
Scientific Organizing Committee•FabioFiorani(IBG-2PlantSciences)•RolandPieruschka(IBG-2PlantSciences)•HendrikPoorter(IBG-2PlantSciences)•UliSchurr(IBG-2PlantSciences)
Logistics and Local Organizing Committee
•AndreasMüller(IBG-2PlantSciences)•CorporateCommunications,ForschungszentrumJülich
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CONTENT
Content
Scientific program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Lectures
Alenyà,Guillemetal.:Robotizedplantprobing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12Bucksch,Alexanderetal.:Canopyparameterextractionfrom3Dterrestriallaserscan datawithSkelTre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Deery,Davidetal.:ThePhenonet:adistributedsensornetworkforfieldbasedcrop phenotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Demilly,Didieretal.:Frenchnationalplatformforhighthroughputseedphenotyping . . . . 15Dhondt,Stijnetal.:QuantitativeanalysisofvenationpatternsofArabidopsisleavesbysupervisedimageanalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Dingkuhn,Michaeletal.:Integratedmulti-phenotypingforricegrowninthefieldandinphenotypingplatforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Fedorov,Dmitryetal.:TheiPlantCollaborative:DeliveringHigh-throughputImagingtotheDesktop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Fiorani,Fabioetal.:TheJülichPlantPhenotypingCenter(JPPC)platformatFZJ . . . . . . . . 19French,Andrewetal.:CellSeT:Cell-scalesegmentationandtracking. . . . . . . . . . . . . . . . . 20Goldbach, Heiner et al.:CROP.SENSe.net–PhenotypingScienceforPlantBreedingandCropManagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Govindaraju,Diddahally:Adevelopmentaldemographicapproachforindexinggenome-phenome maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Hong,Hyundaeetal.:PhenotypicTraitAnalysisofMaizeRootTissues . . . . . . . . . . . . . . . . 23Hund,Andreasetal.:Growthpouchesforhighthroughputphenotypingofroots:strengths,weaknessesandpotentialforfuturedevelopment . . . . . . . . . . . . . . . . . . . . . . . 24Kennedy,Gavinetal.:PODD:AnOntologyDrivenArchitectureforPlantPhenomics DataManagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Khosla,Ray:PrecisionNutrientManagementandCropSensing . . . . . . . . . . . . . . . . . . . . . 26Köhl, Karin et al.:Datamanagementpipelineforplantphenotypinginamulti-site projectaimedtoidentifydroughttolerancemarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Leport,Laurentetal.:OilseedRapeleafsenescencephenotypingandidentificationofsubcellularstructuralandmetabolicchangesusingNMRtool. . . . . . . 28Marguerit,Elisaetal.:Functionalmappingofgrapevinetranspirationresponsestodrought,inducedbyrootstocks:howtocombinedatamodelingandgeneticanalysistotakeintoaccountgenotypexenvironmentinteractions? . . . . . . . . . . . . . . . . . . . . . . . . 29Massonnet,Catherineetal.:Standardizationofprotocolsandexperimentaldesignforhigh-throughputphenotyping:needsandlimits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Metzner,Ralf:Non-invasivebelowgroundphenotypingandfunctionalrootanalysis . . . . . . 31Passioura,John:PlantPhenomicsandGlobalFoodSecurity . . . . . . . . . . . . . . . . . . . . . . . . 32PereyraIrujo,GustavoAetal.:Alow-costplatformforphenotypingplantgrowthandwateruse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
CONTENT
Jülich, 5. – 7. September 2011 5
Rascher,Uwe:Fluorescingplantsandcanopies:usingfluorescencetechniquestomapplantfunctionfromthesingleorgantotheecosystem . . . . . . . . . . . . . . . . . . . . . . . . . 34Seiffert,Udo:Machinelearningapproachesindataanalysispipelinesforplantphenotypingandprecisionagriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35Sirault,Xavieretal.:Superimposingstructureandfunctionin4-D;newsensors for„DigitalAgriculture“ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Uhlmann,Normanetal.:X-RayImagingMethodsalsoforPlantPhenotyping–Opportunitiesnowandinthefuture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Usadel,Björn:Theneglectedenvironmentallongtermeffect.Whyitisnecessarytoincludegrowthconditionsinadatamanagementandanalysispipeline. . . . . . . . . . . . . . . 38vanderHeijden,Gerieetal.:SPICY:Largescalephenotypingoftallpepperplants inthegreenhouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39Virlet,Nicolasetal.:Contributionofairborneremotesensingandproxidetectiontohigh-throughputphenotypingofanappletreepopulationinresponsetosoilwater constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Winterhalter,Loïcetal.:Highthroughputphenotypingdroughtrelatedtraitsoftropicalmaizehybridsinthevegetativestage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Yang,Wannengetal.:Developmentofriceplantphenomicsfacilityequippedwithagriculturephotonics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42Zarco-Tejada,PabloJ.:High-resolutionhyperspectralandthermalimageryforestimatingphysiologicalparametersandpre-visualindicatorsofstress . . . . . . . . . . . . . . . . . . . . . . . . . 43Zimmermann,Philip:IntegratingphenotypingandgeneexpressiondatainGenevestigator . . . . . 44
Posters
Andrade,SolangeR.M.etal.:MethodologiestophenotypingWheatinfieldexperimentsfordroughttolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Barboza,Luisetal.:StudyingthegeneticsofGibberellinsensitivityandGAinhibitor responsesinArabidopsisbyusingasemi-automaticproceduretomeasurehypocotyllengthinthedarkness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47Becher,Martinaetal.:MolecularFarming–Theuseofnon-invasivephenotypingmethodstooptimizeplant-madepharmaceuticalproteinproductioninclosedsystems . . . . 48Berger,Bettinaetal.:Non-destructiveshootimagingatThePlantAcceleratortomonitorsalinitystressresponsesinbarleyandwheat . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49Bhuiyan,AtiqurRahmanetal.:Phenotypingredricetransgressivevariantderivedfrom acrossusingwildriceaccession . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Chouet,Mathiasetal.:Vitsec,aninformationsystemdedicatedtograpevineadaptation to water deficit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Comar,Alexisetal.:Wheatfieldhighthroughputphenotyping:fromconcepttoapplication . . 52Dumont,Cedricetal.:Screeningrootmorphologicalplasticitytowaterlimitationamongdifferentvinerootstocksgenotypesusing2Ddigitalimagesfromrhizotrons . . . . . . 53Engelhorn,Juliaetal.:Reversegeneticsscreen:afocussedapproachtodiscriminatephenotypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54Entzian,Alexanderetal.:Automatedanalysisofcropplantimageswiththesoftware IAP(„IntegratedAnalysisPlatform“) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
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CONTENT
Erdle,Klausetal.:Comparisonofactiveandpassivespectralsensorsindiscriminating biomassparametersandnitrogenstatusinwheatcultivars . . . . . . . . . . . . . . . . . . . . . . . . 56Faget,Marcetal.:Rootenhancementforcropimprovement . . . . . . . . . . . . . . . . . . . . . . . 57Foroozanfar,Maryametal.:TheeffectofsalinityonsomeagronomicalandphysiologicaltraitsinMedicagotruncatula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58Funk,Christophetal.:Applicationsofcomputedtomographytoplantphenotyping . . . . . . 59Goutouly,Jean-Pascaletal.:Twonon-destructivetoolsforfieldphenotypicanalysisofgrapevine:GroundNormalizedDifferenceVegetationIndexandsoilresistivitymeasurements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60Hackl,Haraldetal.:Comparingplanttemperaturemeasuredbythermalimaging,IRthermo-metryandthermistortoassessdifferencesinstresstreatmentsandwheatcultivars . . . . 61Hohmann, Marie et al.:Anovelsystemforcontrolledphenotypingofdroughtstress tolerance in oilseed rape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62Jansen,Marcusetal.:Automatedphenotypingforfunctionalgenomicsandglobal change research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Kipp, Sebastian et al.:Influenceofexternaleffectsontheaccuracyofactivecanopysensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Kiran,Ayshaetal.:GeneticvariationforrootdevelopmentaltraitsinBrassicanapusseedlings . 65Klem, Karel:Phenotypingofcompetitiveabilityinwinterwheatonthebasisofsteady-statechlorophyllfluorescenceimaging,PARtransmittanceandcanopyreflectancesensors . . . 66Larmanou,Ericetal.:TheEuropeanEcotronofMontpellier,aresearch . . . . . . . . . . . . . . . 67Ligeza,Aleksanderetal.:Aeroponicasaplatformforhighthroughputphenotypingofrootsystemarchitecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68Lootens,Peteretal.:Medium-throughputphenotypingofindividualL.perenneplantsunderfieldconditions:aneasyandlow-costprocedure . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Mairhofer, Stefan et al.:RooTrak:RecoveringRootArchitectureTraitsinSoilfromX-rayMicroComputedTomographyData . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70Maizel,Alexisetal.:LightSheet-basedFluorescenceMicroscopy(LSFM)allowslongtermimagingofArabidopsisrootgrowthattheorgan,cellularandsub-cellularlevelinclose-to-naturalgrowthconditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71Masznicz,Bogdanetal.:Dataintegrationwithinbioinformatics.TheJovianProject–AsolutiontointegratevariousdataresourcesatThePlantAccelerator. . . . . . . . . . . . . . . . 72Meyer,Rhondaetal.:BiomassandLeafAreaintheStudyofHeterosisinArabidopsisthaliana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Nagel,KerstinA.etal.:RootphenotypingattheJülichPlantPhenotypingCentre(JPPC) . . 74Paproki,Anthonyetal.:AutomatedPlantPhenomics3DAnalysis . . . . . . . . . . . . . . . . . . . . 75Parent,Borisetal.:Combininghighthroughputphenotypinginplatformsandfieldforgeneticanalysesofdroughtresponses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Peccoux,Anthonyetal.:Stomatalcontrolbyrootstock-sourcedsignalsunderwater stress:amodel-basedanalysisingrapevine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77Peressotti,Elisaetal.:Asemi-automaticnon-destructivemethodtoquantifygrapevinedownymildewsporulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78Petrozza,Angeloetal.:PlantPhenomicsPlatforminMetapontumAgrobios:PhenotypingResearchinSouthernEurope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
CONTENT
Jülich, 5. – 7. September 2011 7
Pieruschka,Rolandetal.:Remotemonitoringofphotosyntheticefficiencyusinglaserinducedfluorescencetransient(LIFT)technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80Poorter,Hendrik:Meta-phenomics:Capturingtheplantphenomein500dose-responsecurves. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Rasool,Ijaz:ContrastingPhenomicsinwheat(TriticumaestivumL.):implicationsfor effectiveuseofwaterandplantgeneticresources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Römer,Christophetal.:WaterStressRecognitionModelsbasedonHyperspectralDatawithArchetypicalSpectrumAnalysisusingSimplexVolumeMaximization . . . . . . . . . . 83Sareen,Sindhu:Phenotypingforheatstressinwheatunderfieldconditionsinchanging climate scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84Sass, László et al.:Constructionofacomplexplantstressdiagnosticsystem . . . . . . . . . . . 85Schmidt, Kai:AnalysisofHyperspectralSignaturesbyDoubleWeibullFunctions . . . . . . . . . 86Sharma,DewKumarietal.:Chlorophyllafluorescencetophenotypewheatgenotypesfor heat tolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Kien,NguyenVanetal.:TowardsphenotypePlantScience:KeyroleofScienceofPlant GermplasmConservationindevelopingPhenomeofPlants . . . . . . . . . . . . . . . . . . . . . . . . . 88Tsaftaris,Sotirios:PHIDIAS:PlantPhenotypingwithaHigh-throughput,Intelligent,Distributed,andIntegratedAnalysisSystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89VanMinnebruggen,Annemieetal.:Morphologicalandphysiologicalvariationofplant architectureinredclover(Trifoliumpratense) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Voß,Uteetal.:SystemsanalysisoflateralrootdevelopmentinArabidopsisthaliana . . . . . 91Weigelt,Kathleenetal.:Usinghigh-throughputphenotypingplatformstoidentifyandcharacterizegenescontrollingvegetativebiomassaccumulationinArabidopsisthaliana . . . 92Wiedemann-Merdinoglu,S.etal.:Developmentofaphenotypingplatformtoassessgrapevineresistancetodownyandpowderymildew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
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SCIENTIFIC PROGRAM
Scientific programMonday, 5 September
Opening
UlrichSchurr FZJülich,Germany Welcome
JohnPassioura CSIROPlantIndustry,Australia
PlantPhenomicsandGlobalFoodSecurity
Session I: Imaging modes for plant functional traits Chair:UlrichSchurr
UweRascher FZJülich,Germany Activeandpassivefluorescenceapproachestounderstandfunctionaltraitsofphotosynthesis’
AlexanderBucksch GeorgiaInstituteofTechnology,USA
Canopyparameterextractionfrom3DterrestriallaserscandatawithSkelTre
Coffee break
PabloZarco-Tejada NationalResearchCouncil,Cordoba,Spain
High-resolutionhyperspectralandthermalimageryforestimatingphysiologicalparametersandpre-visualindicatorsofstress
LoïcWinterthaler TechnicalUniversityofMünchen,Germany
Highthroughputphenotypingofdroughtrelatedtraitsoftropicalmaizehybridsinthevegetativestage
Jean-LucRegnard INRA,Montpellier,France
Contributionofairborneremotesensingandproxidetectiontohigh-throughputphenotypingofanappletreepopulationinresponse to soil water deficit
Lunch
Poster session / 1st possibility to visit the Jülich Plant Phenotyping Center (JPPC) facilities
Session II: Beyond 2D imaging of plant structure and function Chair:HannoScharr
BobFurbank CSIROPlantIndustry,Australia
Superimposingstructureandfunctionin4-D;newsensorsfor„DigitalAgriculture“
GerievanderHeijden PlantResearchInter-national,Wageningen,TheNetherlands
SPICY:Largescalephenotypingoftallpepperplantsinthegreenhouse
RalfMetzner FZJülich,Germany Non-invasivebelowgroundphenotypingandfunctionalrootanalysis
Coffee break
Session III: Novel sensors Chair:RolandPieruschka
NormanUhlmann FraunhoferIIS, Germany
X-rayimagingmethodsforplantphenotyping:state-of-the-art andfutureperspectives
LaurentLeport INRARennes,France OilseedRapeleafsenescencephenotypingandidentificationofsubcellularstructuralandmetabolicchangesusingNMRtool
RayKhosla ColoradoStateUniver-sity,UnitedStates
PrecisionNutrientManagementandCropSensing
WannengYang HuazhongUniversityofScienceandTechnol-ogy,Wuhan,China.
Developmentofriceplantphenomicsfacilityequippedwithagriculturephotonics
GuillemAlenyaiRibes CSIC,Barcelona,Spain Robotizedplantprobing
SCIENTIFIC PROGRAM
Jülich, 5. – 7. September 2011 9
Tuesday, 6 September
Session IV: Data management and analysis pipelines Chair:HendrikPoorter
BjörnUsadel RWTH,Aachen,Germany
Doplantshaveamemoryoftheirenvironment?Whyitisnecessarytoincludegrowthconditionsinadatamanagementandanalysispipeline
Karin Koehl MPIMolecularPlantPhysiology,Golm,Germany
Datamanagementpipelineforplantphenotypinginamulti-siteprojectaimedtoidentifydroughttolerancemarkers
GavinKennedy CSIROIndustry,Australia
PODD:AnOntologyDrivenArchitectureforPlantPhenomicsDataManagement
Coffee break
UdoSeiffert FraunhoferIFFMagde-burg,Germany
Machinelearningapproachesindataanalysispipelinesforplantphenotypingandprecisionagriculture
AndrewFrench UniversityofNotting-ham,UnitedKingdom
CellSeT:Cell-scalesegmentationandtracking
StijnDhondt VIB-PlantSystemsBiol-ogy,Gent,Belgium
QuantitativeanalysisofvenationpatternsofArabidopsisleavesbysupervisedimageanalysis
Lunch
Postersession/2ndpossibilitytovisittheJülichPlantPhenotypingCenter(JPPC)facilities
Session V: Plant phenotyping from an industry perspective Chair:FabioFiorani
HyundaeHong Monsanto PhenotypicTraitAnalysisofMaizeRootTissues
SebastienPraud Biogemma TheChallengesofPhenotypingforanefficientGeneDiscoveryStrategy
PhilipZimmermann Nebion Integratingphenotypingandgeneexpressiondatain Genevestigator
MatthiasEberius Lemnatec Automatedimagebasedplantphenotyping-challengesandchances
Harold Verstegen KWS Tba
RajendraBari Bayer Challengesinplantphenotypingandgrowthanalysis
Coffee break
Session VI: Data modeling and environmental simulation Chair:tbd
MichaelDingkuhn CIRAD,Montpellier,France
Integratedmulti-phenotypingforricegrowninthefieldandinphenotypingplatforms
DenesDudits HungarianAcademyofScience,Hungary
ThePhenonet:adistributedsensornetworkforfieldbasedcropphenotyping
DavidDeery CSIROPlantIndustry,Australia
ThePhenonet:adistributedsensornetworkforfieldbasedcropphenotyping(selectedabstract)
NathalieOllat INRABordeaux,France Functionalmappingofgrapevinetranspirationresponsestodrought,inducedbyrootstocks:howtocombinedatamodelingandgeneticanalysistotakeintoaccountgenotypexenvironmentinteractions?
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SCIENTIFIC PROGRAM
Wednesday, 7 September
Session VII: Data management and analysis pipelines Chair:GavinKennedy
ChristineGranier INRA,Montpellier,France
Standardizationofprotocolsandexperimentaldesignforhigh-throughputphenotyping:needsandlimits
DiddahallyGovindara-ju
DukeUniversity,UnitedStates
Adevelopmentaldemographicapproachforindexing genome-phenome maps
AndreasHund ETHZurich,Switzer-land
Growthpouchesforhighthroughputphenotypingofroots:strengths,weaknessesandpotentialforfuturedevelopment
Coffee break
Session VIII: Infrastructure for plant phenotyping Chair:UlrichSchurr
FabioFiorani FZJülich,Germany DevelopmentofinfrastructureattheJülichPlantPhenotypingCenter
MattVaughn UniversityofTexasatAustin,USA
PhytoBisque:iPlant‘scloud-enabledplatformforcollaborativephenotypinganalysisandalgorithmdevelopment
Jens Léon UniversityofBonn,Germany
CROP.SENSe.net–PhenotypingScienceforPlantBreedingandCropManagement
GustavoPereyraIrujo NationalInstituteofAgriculturalTechnol-ogy,Argentina
Alow-costplatformforphenotypingplantgrowthandwateruse
EtienneBelin INRAAngers-Nantes,France
Frenchnationalplatformforhighthroughputseedphenotyping
Conclusion
UlrichSchurr FZJülich,Germany Concludingremarks
Lunch
3rd possibility to visit the Jülich Plant Phenotyping Center (JPPC) facilities
1. Lectures
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LECTURES
Robotized plant probing Guillem Alenyà, Babette Dellen, Carme Torras
IRI,CSIC-UPC,Spain
Anewautomaticplantprobingframeworkispresented.ItreliesonaTime-of-Flight(ToF) cameraandarecentlydevelopedcuttingtool,bothmountedontheend-effectorofarobotic arm.ToFcamerasachieveagoodcompromisebetween3Dinformationgathering,infraredmagingandspeed.AmethodisproposedtosegmentplantimagesintotheircompositesurfacepatchesbycombiningahierarchicalsegmentationoftheinfraredintensityimagewithquadraticsurfacefittingusingToFdepthdata.Candidateleavesareidentifiedandranked,andthentherobot-mountedcameramovesclosertothemtovalidatetheirsuitabilitytobeingsampled.Selectedleavesarethenprobedbyautomaticallyplacingthecuttingtoolontheleafsurfacethroughappropriatemotionoftheroboticarmonthebasisofthe3Dstructureextracted.Wehavedevelopedforthisapplicationaprototypeofthetoolasanautomaticalternativetothecommonlyusedcorkborer.Thetoolisautomaticallydrivenandguaranteesthatthesampleisexpelled.Theworkisaproof-of-conceptthatdenseinfrareddatacombinedwithsparsedepthasprovidedbyaToFcamerayieldsagoodenough3Dapproximationforautomatedcuttingofleafdisksforexperimentationpurposes.
POSTERS
Jülich, 5. – 7. September 2011 13
Canopy parameter extraction from 3D terrestrial laser scan data with SkelTreAlexander Bucksch, Joshua S. Weitz
SchoolofBiologyandSchoolofInteractiveComputing,GeorgiaInstituteofTechnology, UnitedStates
Millionsoflasermeasurementscanbeobtainedbecausetheterrestriallaserscannerrotatesarounditsverticalandhorizontalaxes.Theregistrationofseveralsinglescansintoonecommoncoordinatesystemresultsinapointcloud.
Recently,skeletonizationmethodsoperatingonpointclouddatawereestablishedtorepresenttrees,e.g.[2].Thesemethodsareusefultocreaterealisticlooking3Dmodelsforcomputergraphicsapplications.SkelTre[3]isaskeletonizationmethodthatadditionallyaddresses:(i)noise,undersamplingandvaryingpointdensity;(ii)enforcescenterednessandtopologicalconstraints.Thesetwoadditionsenabletheextractionofquantitativetreeparameters.
ForsixleaflessHoneycrispappletrees(Malusdomestica‘Honeycrisp’)growinginanorchardeverybranchwithdiameter>0.5cmwasmeasured.TheSkelTreassistedparameterextractionresultedinfrequencydistributionsofbranchdiametersandbranchlengthsthataresignificantlycorrelatedwiththefrequencydistributionsofthemeasuredfielddata.TheSkeltre-skeletonincludesthebranchinghierarchyofthecanopy.WeanalyzetheresultingbranchinghierarchyinlightofoptimalnetworktheoriesusingtheHorton-Strahlerorder.
References[1]Pfeifer,Norbert;Briese,Christian(2007)Geometricalaspectsofairbornelaserscanningandterrestriallaser scanningIAPRSVolumeXXXVIPart3/W52[2]Livny,Yotam;Yan,Feilong;Olson,Matt;Chen,Baoquan;Zhang,Hao;El-Sana,Jihad(2010)AutomaticreconstructionoftreeskeletalstructuresfrompointcloudsACMTransactionsonGraphicsVolume29,Issue6,Article151[3]Bucksch,Alexander;Lindenbergh,Roderik;Menenti,Massimo(2010)RobustskeletonextractionfromimperfectpointcloudsTheVisualComputerVolume26Issue10page1283-1300.
14 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
The Phenonet: a distributed sensor network for field based crop phenotyping David Deery1, Ali Salehi2, Xavier Sirault1, Bob Furbank1
1HighResolutionPlantPhenomicsCentre,CSIROPlantIndustry,Australia 2 CSIRO,InformationCommunicationTechnologyCentre,Australia
Everyyear,Australiangrainbreedersplantupto1million10m2plotsacrossthecountry tofindthebesthighyieldingvarietiesofwheatandbarley.Theplotsareusuallylocatedinremoteplaces–oftenrequiringmorethanfourhourstravelone-waytoreach.Thechallenge istomonitorthecropperformanceandgrowingenvironmentthroughouttheseasonandreturntheinformationinaneasilyaccessibleformat.“Phenonet”wirelesssensornetworksarenowroutinelydeployedinwheatvarietytrialsthroughoutAustraliabystaffattheHighResolutionPlantPhenomicsCentre(HRPPC).
Thewirelesssensornetworktypicallyconsistsofsensorsmeasuring(a)localenvironmentaldataincluding:solarradiation,airtemperature,relativehumidity,rainfallandwindspeedand(b)cropperformancedataincluding:soilmoisture,soiltemperature,andleaf(cropcanopy)temperature.ThesensorsareradiolinkedtoabasestationforrealtimedatauploadtoaserverinCanberraviathemobilephonenetwork.However,thecollectedrawsensornetworkdataisoflittlesignificancetoresearchersunlessthedataisprocessedtoensuremeaningfulinterpretation.Thedataanalysisandvisualizationplatform(http://www.phenonet.com)canbeupdatedinrealtimeandservestoinformscientistsaboutthegrowingconditionsandcropperformanceatremoteexperiments.
Usingtheserealtimemeasurements,scientistsareabletocharacterizethegrowingenvironmentandevaluatetheperformanceofdifferentwheatvarietiesacrossthefield.Bycombiningthesemeasurementswitheachplant’sgeneticprofileandperformance,plantscientistscandecon-volvetheeffectsofmicroclimateandgenome,thusimprovingtheaccuracyandspeedofplantbreeding.
LECTURES
Jülich, 5. – 7. September 2011 15
French national platform for high throughput seed phenotypingDidier Demilly1, Etienne Belin2, Marie Hélène Wagner1, Sébastien Besson3, Sylvie Ducournau1, Joël Léchappé1, David Rousseau4, Carolyne Dürr2
1StationNationaled‘EssaisdeSemences,GEVES,France 2UMR1191UnitéPhysiologieMoléculairedesSemences(PMS),,INRAIFRQuasav,France 3Evaltech,ESEO,France 4Laboratoired‘IngéniériedesSystèmesAutomatisés(LISA),Universitéd‘Angers,France
EAphenotypingplatformwasdevelopedattheFrenchnationalseedtestingstation(SNES–GEVES)fortheautomatedphenotypingofseedsandseedlingswithintheFederativeResearchInstituteinAngers.SNEShasalongexperienceinanalyzingseedsamplesandindevelopingautomatedproceduresforacquiringandprocessingimages.Enhancedcollaborationwithresearchteamsinplantsciences(INRA)andininformationsciences(LISA,AngersUniversity)enabledustoextendhighthroughputphenotypingfromdryseedstogerminationandyoungseedlingsofseveralspeciesandtoalargenumberoftraits(initialseedcharacteristics,imbibi-tion,germination,earlygrowth).
Informationonseedsiscollectedattheindividuallevel.Thenumberofindividualssimultane-ouslycharacterizedvariesfromhundredstoseveralthousands,forinstancewhenapopula-tionofrecombinantinbredlinesisphenotyped.Themeasurementsareperformedindifferentenvironmentalconditions(lightordark,differentrangesoftemperatureandwaterpotential).Measurementsaremadeathourlyintervals,withatotalexperimentlengthofuptotwoweeks.Informationisstoredinadatabasetoenabledifferentmeasurementsonthesameseedtobelinked.
Theplatformcombinesdifferenttools:radiography,fluorescence,IRthermography,imagingondryseeds,Jacobsengerminationtables,forcesensors,andimagingforseedlingelonga-tion.Phenotypingcanbeperformedforseedcompaniesaswellasresearchteams.Theplat-formcanbeusedfordifferentpurposes:characterizationandcomparisonofseeds,seedlotsorgenotypes,searchofQTLs,ortodeterminevaluesofparameters,formodelingpurposesforexample,basetemperature.
References[1]Gardarin,Antoine;Dürr,Carolyne;Mannino,Maria-Rosaria;Busset,Hugues;Colbach,Nathalie(2010)Seedmortalityinthesoilisrelatedtotheseedcoatthickness.SeedScienceResearchvol.20,pp.243–256[2]Dias,PaulaMennaBarreto;Brunel-Muguet,Sophie;Dürr,Carolyne;Huguet,Thierry;Demilly,Didier;Wagner,Marie-Hélène;Teulat-Merah,Béatrice(2011)QTLanalysisofMedicagotruncatulaseedgerminationandpre- emergencegrowthatextremetemperaturesTheoreticalandAppliedGeneticsvol.122,pp.429–444[3]Belin,Etienne;Rousseau,David;Lechappé,Joël;Langlois-Meurinne,Mathilde;Dürr,Carolyne(2011) Ratedistortiontradeofftooptimizehigh-throughputphenotypingsystems.ApplicationtoX-rayimagesofseeds ComputersandElectronicsinAgricultureinpress(doi:10.1016/j.compag.2011.05.002)
16 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
Quantitative analysis of venation patterns of Arabidopsis leaves by supervised image analysis Stijn Dhondt1, Dirk Van Haerenborgh2, Caroline Van Cauwenbergh1, Roeland Merks3, Wilfried Philips2, Gerrit Beemster4, Dirk Inzé1
1PlantSystemsBiology,VIB,Belgium 2DepartmentofTelecommunicationsandInformationProcessing-ImageProcessingand Interpretation,GhentUniversity,Belgium 3CentrumWiskunde&Informatica,Netherlands 4DepartmentofBiology,UniversityofAntwerp,Belgium
ThestudyoftransgenicArabidopsislineswithalteredvascularpatternsrevealedkeyplayers inthevenationprocess,butthedetailsofthevascularizationprocessarestillunclear,partlybecausemostoftheselineshavebeenassessedonlyqualitatively.Therefore,quantitative analysesareneededtoidentifysubtleperturbationsinthepatternandtotestdynamicmodelinghypotheseswithbiologicalmeasurements.Wedevelopedanon-lineframework,designatedLeafImageAnalysisInterface(LIMANI),inwhichvenationpatternsareautomati-callysegmentedandmeasuredstartingfromdarkfieldimages.Imagesegmentationscanbemanuallycorrectedthroughtheuseofaninteractiveinterface,allowingsupervisionandrectificationstepsintheautomatedimageanalysispipelineandensuringhigh-fidelityanalysis.Thison-lineapproachisadvantageousfortheuserintermsofinstallation,softwareupdates,computerload,anddatastorage.Theframeworkwasusedtostudyvasculardifferentiationduringleafdevelopmentandtoanalyzethevenationpatternintransgeniclineswithcontrast-ingcellularandleafsizecharacteristics.Thestudyshowstheevolutionofvasculartraitsdur-ingleafdevelopment,suggestsaself-organizingmechanismforleafvenationpatterningandrevealsatightbalancebetweenthenumberofendpointsandbranchingpointswithintheleafvascularnetworkthatdoesnotdependontheleafdevelopmentalstageandcellularcontent,butontheleafpositionontherosette.ThesefindingsimplythatthedevelopmentofLIMANIimproves.
LECTURES
Jülich, 5. – 7. September 2011 17
Integrated multi-phenotyping for rice grown in the field and in phenotyping platformsMichael Dingkuhn1, Hei Leung2, Delphine Luquet1, Camila Rebolledo1
1BIOS,CIRAD,France 2IRRI,Philippines
TheGlobalRiceSciencePartnership(GRiSP),theCGIARResearchProgramonrice,initiatedaglobalricephenotypingnetwork.Inatwo-prongedstrategy,itaimsat(1)discoveryofnovelgenesandallelescontributingtogreateryieldpotentialandstabilityinstressfulenvironments,notablyassociatedwithclimatechange;and(2)buildingacommonresourcetosupportricemolecularbreedingglobally.Thenetwork,althoughnew,buildsmulti-environmentandmulti-traitphenotypingconductedsince2007inthecontextoftheGenerationChallengeprogram(GCP)andCIRAD’sORYTAGEproject.Themulti-phenotypingapproachconsistsinsubjectingacommonpanelof2000accessions,representingthediversityofOryzasativaL.,tomultiple phenotypingsetups,bothonfieldhubsandonspecializedplatforms,inaninternationalpartnership.Theresulting,continuouslygrowingresourceallowsnotonlygene/allelediscov-erythroughassociationanalysis),butalsothecharacterizationoflinkagesamongtraits,theirinteractionwithenvironment(GxE)andthestudyofadaptationstrategiesanddiversity.Forcomplexphysiologicalandphenologicaltraits,heuristicapproachesareusedbyfittingmodels(parameteroptimization),whichalsohelpinexploitingataobtainedinvariableenvironments.Amongtheexamplespresentedare(1)useofEcomeristeminphenotypingofmorphoge-neticreactionnorms(phenotypicplasticity)affectingearlyvigorandgrowthunderdroughtincontrolledenvironments,and(2)useofRIDEVtoextractgenotypiccardinaltemperatures,photoperiodsensitivityandthermalsensitivityofspikeletfertilityfrommultienvironment phenotypingsinthefield.Firstresultsonearlyvigoranddroughttoleranceindicatedthree agro-ecologicalstrategies.Group1produceslargebutfeworgans,hasmoderatevigor becauseofsink-limitation(resultinginhightransitoryNSCstorage),andhaspoordrought tolerance(butprobablygoodavoidance).Group2isvigorousduetorapidleafandtiller production(butsmallorgansize),storeslittleNSCandisdroughtsensitive.Andgroup3 hassmallorgans,poorvigorbuthighdroughttolerance.Anextstepwillbethegenetic characterization of the component traits.
18 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
The iPlant Collaborative: Delivering High-throughput Imaging to the DesktopDmitry Fedorov1, Steve Goff2, Kris Kvilekval1, B.S. Majunath1, Nirav Merchant2, Nathan Miller3, Edgar Spalding3, Matthew Vaughn4
1UniversityofCaliforniaatSantaBarbara,UnitedStates 2BIO5Institute,UniversityofArizona,UnitedStates 3UniversityofWisconsin-Madison,UnitedStates 4TexasAdvancedComputerCenter,UniversityofTexasatAustin,UnitedStates
TheiPlantCollaborativeaimstodevelopacommunity-extensiblecyberinfrastructurecapableofmeetingtoday’scomputationalchallenges,whileadaptingtotherapidpaceofbiotechnologicaldevelopment.Challengesinnext-generationDNAsequencing,largescalegeneticassociationstudies,dataintegration,phylogenetics,modeling,andGISguidedesignanddevelopmentoftheinfrastructure.StorageandHPCresources,includingthoseprovidedbytheXSEDEprojectarefederatedviainteroperatingmiddlewarepackagesandservices,andexposedforuseviaacollectionofRESTfulapplicationprogramminginterfaces.TheseAPIsprovideafoundationfordevelopmentofRichInternetApplicationssuchasiPlantDiscoveryEnvironment,DNASubway,andthePhytoBisqueenvironmentforhigh-throughputimageanalysis.PhytoBisqueempowersdevelopersandconsumersofimageprocessingalgorithms.Developersgaintransparently-scalableapplicationdeployment,architectureandlanguageindependence,facileaccesstotrainingdata,advanceddatatransmissionandstoragecapabilities,andvirtualizationsolutionsallowingforcollaborativedevelopmentofproofsofconceptfornewalgorithms.Consumershaveaccesstoavirtualization-based‘AppStore’enablingcommonimaging-relatedtasksviaiPlantAtmosphere.ThePhytoBisqueapplicationprovidestheabilitytostoreandworkonlargeimagedatasets,manipulatelarge-scaleimages,annotateandshareimage,linkdataandresultsintoIntelligentImagingOverlays,anddevelopshareable‘mini-app’workflows.iPlant,throughitsmultifacetedapproachtocyberinfrastructureandthePhytoBisqueapplicationarebringinghighthroughputimagingtothedesktop.
References[1]Kvilekval,Kris;Fedorov,Dmitry;Obara,Boguslaw;Singh,Ambuj;Manjunath,B.S.(2010)Bisque:APlatformforBioimageAnalysisandManagementBioinformatics544–552[2]Goff,Steve(2011)TheiPlantcollaborative:cyberinfrastructureforplantbiologyFrontiersinPlantGeneticsandGenomics 34
LECTURES
Jülich, 5. – 7. September 2011 19
The Jülich Plant Phenotyping Center (JPPC) platform at FZJFabio Fiorani, Ulrich Schurr
InstituteofBio-andGeosciences,IBG-2:PlantSciences,ForschungszentrumJülichGmbH,Germany
Theabilityandcapacitytophenotypeplantsusingstandardizedprotocolsiscurrentlythemostimportantbottlenecktogainknowledgeinfunctionalgenomeresearch.JPPC(JülichPlantPhenotypingCenter)isattheforefrontofcutting-edgeresearchinthisfield,andinpro-motingthedevelopmentofreliableexperimentalstandardsandpractices.InthispresentationwewillhighlightavailableapplicationsattheJPPCplatformfocusingonnewdevelopmentstoquantifyplanttraitsnon-invasively.Throughcasestudieswewillillustratehowtheuseofphenotypinginfrastructureandsensorstechnologycanbeusedtoaddressrelevantbiologi-calquestions.Wewillgiveexamplesofnewapplicationsthataiminparticularatmeasuringrootarchitectureparametersfromartificialgrowthmediatosoil.Theknowledgegeneratedbythesetypesofexperimentsisessentialindefiningparametersandproxiesthatwillimproveourunderstandingofwhichphenotypictraitscanbetransferredfromcontrolledenvironmentstofield,andtowhatextentthesetraitscanbetransferredfromcroptocropinpre-breedingprogramsandinagriculturalproductionenvironments.Finally,wewillgiveasyntheticover-viewofupcomingplantphenotypingprojectsattheEuropeanlevelforwhichJPPCwillplay a leading role.
20 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
CellSeT: Cell-scale segmentation and trackingAndrew French, Michael Pound, Vijay Sethuraman, Darren Wells, Malcolm Bennett, Tony Pridmore
CentreforPlantIntegrativeBiology,UniversityofNottingham,UnitedKingdom
WithintheCentreforPlantIntegrativeBiology(CPIB),therehasbeenaneedtogeneraterealisticgeometriesfrom,andquantitativelymeasuregrowthin,cell-andtissue-scaleconfocalimagesofgrowingArabidopsisroots.Tothisendasoftwaretoolwasdeveloped,CellSeT,toenablethesemi-automaticsegmentationandtrackingofcellnetworksinconfocalimage sequences[1]
AvariantoftherecentlydevelopednetworksnakesapproachhasbeenemployedtoidentifycellboundariesinconfocalimagesofgrowingArabidopsisroots.Networksnakesbothmakeexplicittheconnectionsbetweenadjacentregionboundaries(cellwalls),anddescribebound-aryshape.Thenetworkisinitialisedusingatwo-levelvariantofthewatershedalgorithmandrefinedbyhandwithinthetoolifnecessary.Theoriginalsnakeenergyfunctionemployedismodifiedtoreflectthetaskathand.
Givenimagesequencesshowingonlyslow-growingplants,theimplicittrackingabilityofnetworksnakescanbeexploitedtomaintaincellidentityovertime.Inmanycases,however,growthbetweenframesissufficienttomakethisimpossible;thesnakenetworkcannotreac-quirethecorrectboundarysetwhenreinitialisedinthesameconfigurationonthenextimage.Thisproblemhasbeenaddressedherebyincorporatingamulti-targetparticlefilterbased tracker.Thistracksthelocationsofnetworknodesbetweenframes,allowingthesnakenet-worktobewarpedontothenewimagebeforeitsenergyfunctionisminimised.
Suchtechnologycandramaticallyreducetheinputrequiredfromaresearcherwishingtostudytime-seriesbasedbehaviours.Afterinitialisationusingthegraphicaltoolandautomaticprocessingbythealgorithm,theresultantdatastructurecapturestherelationshipsbetweenthecells,aswellasthegeometriesofthecellsthemselves.Thisinformationcanbeusedtocalculateparameterssuchascellareasandlengths,anditcanbeimportedintomodellingframeworkssuchasOpenAlea[2].Thetoolcanalsosupporttargetedmeasurementsof,forexample,plasmamembranemarkers,whichexplicitlyrequiresapriorknowledgeofthenet-workgeometry.
Comparedtothelabour-intensive,manualalternative,CellSeTprovidesaneasy-to-useandhighthroughputapproachtoretrievingcellscaledatafromtissueandorgan-scaleconfocalimages.
References[1]Sethuraman,Vijay;French,Andrew;Wells,Darren;Kenobi,Kim;Pridmore,Tony(2011)Tissue-levelsegmentationandtrackingofcellsingrowingplantrootsMachineVisionandApplicationsDOI:10.1007/s00138-011-0329-9
LECTURES
Jülich, 5. – 7. September 2011 21
CROP.SENSe.net – Phenotyping Science for Plant Breeding and Crop ManagementHeiner Goldbach1, Jens Leon1, Ulrich Schurr2
1Inst.ofCropScienceandResourceConservation,UniversityofBonn,Germany 2InstituteofPlantSciences(IBG-2),ForschungszentrumJülichGmbH,Germany
CROP.SENSe.netisaninnovative,interdisciplinaryresearchnetwork,withpartnersfrom academia,researchinstitutesandtheprivatesector.Partners1acrossthenetworkareworkingtogethertonon-destructivelyandquantitativelyanalyseandscreenplantphenotypethroughoutplants’lifecycles.Theultimateaimoftheprojectisearly,nonbiasedandfasterassessmentoftraitstoenablegreaterefficiencyincropbreedingandtooptimisedecisionmakingincropmanagement.
Non-destructivesensormethodsandhighthroughputtechnologiesarebeingusedand optimisedinthelabandfieldtoobjectivelyrecordplantandsoilcharacteristicsovertimeandspace.Theresultinglargedatasetsarehandledandinterpretedusingstate-of-the-artmathe-maticalmethodsandmodels.Integrationofsensorresultswillhelpfurtherelucidatecomplex,multi-causalcharacteristics,suchasthoselinkedwithplantarchitectureandstress(e.g.yield,quality,resistance,tolerance).
Examplesofon-goingresearchwillbepresentedshowingbothoptionsaswellasconstraintsforestablishingpreciseandfastphenotyping.Resultsofphenotypingprocedureswith differentsensortypeswillbepresented.
CROP.SENSe.netisajointinitiativeoftheAgricultureFaculty,UniversityofBonnandtheInstituteofBio-andGeosciences,ForschungszentrumJülichwithpartnersfromuniversityandpublicresearchaswellasprivatepartners.ItisfundedbytheGermanFederalMinistryofEducationandResearch(BMBF)withinthescopeofthecompetitivegrantsprogramNetworksofexcellenceinagriculturalandnutritionresearch(Fundingcode:0315529).FurtherfundingbytheMinistryforInnovation,ScienceandResearchofNorthRhine-Westphalia(MIWF-NRW)isalsoexpected.
1Partners(inalphabeticalorder):BayerCropScience;UniversityofBonn,FacultiesofAgriculture,MathematicsandNaturalSciences,andInstituteofMolecularPhysiologyandBiotechnologyofPlants;CologneUniversity,InstituteofGeography;EmisensGmbH;ForschungszentrumJülich,InstitutfürBio-undGeowissenschaften,PflanzenwissenschaftenIBG2andAgrosphereIBG3;FraunhoferInstituteforHighFrequencyPhysicsandRadarTechniques(FHR);FritzmeierEnvironmentGmbH&Co.KG;JuliusKühnInstitute-Geilweilerhof;KarlsruherInstituteforTechnology(KIT),BotanicalInstitute;KielUniversity,InstituteforPlantBreeding;KWSSaatAG;LeibnizInstituteofPlantGeneticsandCropPlantResearch(IPK);MarburgUniversity,FacultyofPhysics;Nemaplot,Bonn;SAATEN-UNIONGmbH;TechnicalUniversityofMunich,ChairofPlantNutrition,andChairforComputerVisionandPatternRecognition;SouthWestphaliaUniversityofAppliedSciences;W.vonBorries-EckendorfGmbH&Co.KG
22 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
A developmental demographic approach for indexing genome-phenome mapsDiddahally Govindaraju
NationalEvolutionarySynthesisCenter,UnitedStates
Understandingthenatureandamountofgenomicvariation,andtheirrelationshiptopheno-typehasremainedafundamentalchallengeinbiologicalresearch.Recentattemptstoexploretheserelationshipsinhumans,usinggenomewideassociationstudies,havefallenwayshortofexpectation.Argumentsandcounter-argumentshavebeenpositedtoexplaintheseresults.Inthelife-historyofanorganism,genomicinformationpassesthroughatrajectoryofdevel-opmentalstagesundertheinfluenceofenvironment,ultimatelyresultinginphenotype.Thesestagesmaybedividedbroadlyintotwo:prezygoticandpostzygotic.Thegenome-phenome (G-P)mapattemptstoexplorethelinksbetweengenotypeandphenotype.Bothgenetic andenvironmentalchangesaffectthenatureandintensityofselection,whichinturnaffecttheG-Pmapacrossseeminglyseparatedemographictransitionsfromgametogenesisto senescence.Accordingly,theinfluenceofgenesonphenotypealsochangesinthecontext ofdevelopmentandenvironment.TheG-Pmapisthereforenotstatic,butdynamicandcontextual.Note,however,thatmajor,minorandmodifiergenesareknowntohavecumula-tiveandcontextualeffectsonquantitativetraits.Itisoftendifficulttomeasuretheseeffectspreciselywithintheco-evolvedcomplexofgeneticanddevelopmentalpathways.Phenomicsprovidesanexcellentopportunitytomeasuretheinfluenceofprimaryandsecondarygeneproductsintissuesandorgansfairlyprecisely,atalldevelopmentalstages,andusethemtodeterminetheproximaleffectsofgenesonthephenotype.Iwillpresenttheseideaswithexamplesfromhumangenetics,andextendthemtoplantgeneticsystems.images.
LECTURES
Jülich, 5. – 7. September 2011 23
Phenotypic Trait Analysis of Maize Root TissuesHyundae Hong1, Amarjit Basra1, Kevin Kosola1, Michael Malone1, Kathleen Brown2, Amy Burton2, Jonathan Lynch2
1MonsantoCompany,UnitedStates 2DepartmentofHorticulture,PennsylvaniaStateUniversity,UnitedStates
Plantrootsplayanessentialroleinacquiringandtransportingwaterandnutrientstotheshoot.Bothmorphologicalandanatomicalroottraitsareimportantforwaterandnutrient useefficiency.Vascularsystemanatomyaffectshydraulicconductance,whichcanregulateleafexpansion,stomatalconductance,andgasexchangerates(Stiller,Lafitteetal.2003). Additionally,corticalaerenchymaformationhasbeenshowntoimprovedroughttolerance,andisalsoexpectedtobeassociatedwithnutrientuseefficiency(Zhu,Brownetal.2010).
Wehavedevelopedcustomizedimageanalysisalgorithmstocharacterizemaizeroottissueanatomyby30differentmorphologicalmetrics.RoottissuesectionswereobtainedfromtheprimaryrootofV6stageplants,from5-7cmbelowtheseed.Histologicalsectionswereimagedat2.8xwidefieldadapterwithahighresolutionDSLRcamera.MatLabwasusedtodevelopimagepostprocessingandanalysisalgorithms.Thesealgorithmsseparatedcorticalandstelezonesandmeasuredtheirarea,diameter,andothershape-relatedmetrics.Followingidentificationofcortexandstele,identificationandmeasurementofaerenchymaandxylemwereperformed.Thedevelopedanalysismethodcanalsobeadaptedtocharacterizehypodermis,epidermisandendodermisdevelopment.
Weappliedthedevelopedalgorithmstoimagesacquiredfromroottissuesofcommercialmaizegermplasmgrowninthegreenhouse.Analysisrevealedthatmostphenotypictraitsvaryconsiderablybetweengermplasm,particularlybothxylemandaerenchymacross-sectionalareas.Experimentsareunderwaytoexploretherelationshipbetweenroottissuearchitectureandphysiologicaldifferencesbetweenthesegermplasm.
References[1]Stiller,Volker(2003)HydraulicpropertiesofriceandtheresponseofgasexchangetowaterstressPlantPhysiology1698 – 1706[2]Zhu,Jinming(2010)Rootcorticalaerenchymaimprovesthedroughttoleranceofmaize(ZeamaysL.)Plant, CellandEnvironment740–749[3]Rodríguez-Gamir,Juan(2010)Relationshipsbetweenxylemanatomy,roothydraulicconductivity,leaf/rootratioandtranspirationincitrustreesondifferentrootstocksPhysiologiaPlantarum159–169
24 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
Growth pouches for high throughput phenotyping of roots: strengths, weaknesses and potential for future developmentAndreas Hund, Peter Stamp, Achim Walter
AgriculturalandFoodSciences,ETHZurich,Switzerland
Phenotypingofrootsischallengingsincetheyareusuallynotdirectlyaccessible.Yet,theimprovementofrootsystemarchitecturetraits(RSAT)holdsgreatpromisetomaximizeyieldwithaminimalinputofresourcessuchasphosphorus,nitrogenandwater.ThecontrolofRSATisofquantitativenature.Itisthereforenecessarytoevaluatelargenumbersofgeno-typesfordirectselectionortomapthegenomiclocationoftheunderlyinggenes.Knowingthepositionofthesequantitativetraitloci(QTLs)istheprerequisiteforanindirectselectionofRSATusingmolecularmarkers.
Inthecaseofmaize,thenumberofknownQTLscontrollingrootlengthisaround40[1]. MostoftheseQTLsweredetectedbystudyingplantsattheseedlingstageinpaperrolls, hydroponicsorgrowthpouches.However,thereisonlyalimitednumberofstudiesthat examinedtheresponseofroottraitstoenvironmentalstimuli.Wedevelopedaphenotypingplatformallowingforanon-destructivemeasurementoftheresponseofRSATtoenvironmentalstresses.ThesystemissimpleandconsistsofA4blottingpaperassubstratecoveredbyblackplasticfoil.Roots,growingonthesurfaceofthepaper,werescannedinregularintervalsandtheresultingimageswereanalyzeddigitally.Thetargettraitswerethegrowthofaxileandlateralroots[2]aswellastheanglesofaxileroots[3].TheplatformwasusedtoevaluatetheresponseofrootgrowthtolowpHandaluminumtoxicity,highandlowtemperature,andlowwaterpotentialinducedbypolyethylene-glycol.Basedontheexperienceswithtestingmultiplestressesandtraitswewillhighlightthestrengthsandweaknessesoftheplatformandidentifypotentialforfurtherdevelopment.
References[1]Hund,Andreas;Reimer,Regina;Messmer,Rainer(2011)AconsensusmapofQTLscontrollingtherootlength ofmaizePlantandSoilDOI:10.1007/s11104-011-0735-9[2]Hund,Andreas;Trachsel,Samuel;Stamp,Peter(2009)Growthofaxileandlateralrootsofmaize:Idevelopment ofaphenotypingplatformPlantandSoil335–349[3]Hund,Andreas(2010)Geneticvariationinthegravitropicresponseofmaizerootstolowtemperatures.PlantRoot22–30tialforfurtherdevelopment.
LECTURES
Jülich, 5. – 7. September 2011 25
PODD: An Ontology Driven Architecture for Plant Phenomics Data ManagementGavin Kennedy1, Yuan-Fang Li2, Faith Davies3, Jane Hunter3, Bob Furbank1
1TheHighResolutionPlantPhenomicsCentre,CSIROPlantIndustry,Australia 2MonashUniversity,SchoolofIT,Australia 3UniversityofQueensland,SchoolofITEE,Australia
Ontologieshavefoundincreasingfavourintheplantsciencesbecausetheycandeliverasetofterminologiesandunderstandingsaboutbiologicalconceptsthatareagreedbetweenresearchers.Typicallyontologiesareusedtoannotatedataontheweb,butthenotionofacommonvocabularywithformallydefinedsemanticsmakesontologiesthevehiclesforrepre-sentingdataandknowledgeintheSemanticWeb.Ontologiesprovideunambiguousclassifiersanddescriptorsthataremadeavailableinaformatothercomputerscanautonomouslydiscoverandinterrogate,andthusmaybelinkedacrossdisparatedatabasesandrepositories.
InthePhenomicsOntologyDrivenDatarepository(PODD)wehavetakenthenotionofclas-sificationofexperimentalconceptsusingontologiesonestepfurtherbyusinganontology,thePODDontology,astheschemaofourdatamanagementsystem.WeutilisetheSemanticWebontologylanguagesOWLandRDFStodothisbecausetheyprovidetheextensibilityandthesemanticrigourrequired.Inthisontology-drivenarchitecturethebehavioursofdomaincon-ceptsandobjectsarecapturedentirelybyontologicalentities,aroundwhichalldatamanage-menttasksarecarriedout.
Anidealdomainforapplyingtheseprinciplesisplantphenomics,thesystematicstudyofthephenotypesofmodelandcropplantsthatareaconsequenceoftheindividualplant’sge-nomeandenvironment.Phenomicsresearchgenerateshighvolumesofheterogeneousdatathroughtheuseofemergingimagingandmeasurementtechnologiesandprocesses.Thisdataiscombinedwithmetadatatoformcomplexdigitalobjectsandthenfurtherassociatedwithprovenancemetadataontheexperimentalprocess.Inthiscontext,wedescribethedevelop-mentofaphenomicsexperimentalprocessontology,andhowwehaveappliedtheprinciplesofontology-drivenarchitectureinthedevelopmentofPODD,adatamanagementsystemforphenomics based research.
References[1]Li,Yuan-Fang;Kennedy,Gavin;Davies,Faith;Hunter,Jane(2010)PODD–TowardsanExtensible,Domain-AgnosticScientificDataManagementSystemIEEESixthInternationalConferenceone-Science137–144[2]Li,Yuan-Fang;Kennedy,Gavin;Hunter,Jane(2010)PODD:AnOntology-DrivenDataRepositoryforCollaborativePhenomicsResearchLecturenotesinComputerScienceVolume6102/2010,pp179–188
26 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
Precision Nutrient Management and Crop SensingR. Khosla
ColoradoStateUniversity,UnitePdreSctaistieos
Precisionnutrientmanagementreferstoapplicationofrightnutrient,attherighttime,at therightplaceandintherightamount.Precisionagronomistsoverthelasttwodecadeshavefocusedondevelopingtechniquestoquantifyspatialvariabilityinsoilandcropcanopiestopracticeprecisionnutrientmanagement.Studieshaveshownthatnormalizeddifferencevegeta-tionindexfromground-basedactiveremotesensorsishighlyrelatedwithleafNcontentincropssuchasmaize.Arecentstudyconductedwiththetwomostprominentground-basedactivesensorsintheUSA(GreenSeeker™redandCropCircle™amber)demonstratesthesuccesswithwhichthetwosensorscanaccuratelypredictin-seasoncropNneeds.However,thetiming(cropgrowthstage)bywhichthiscanbesuccessfullyaccomplishedstillremainsaconcern.Thereisaneedforanimprovedcropcanopysensorthatcouldaccuratelydeterminecropnutritionalneedsearlyinthecropgrowingseasontofacilitateincorporationofcropsens-ingbasedprecisionnutrientmanagementamongfarmers.Couldfluorosensingbetheanswer?OurmostrecentstudyshowsthatfluorescencesensorcandetectnitrogendeficiencyatmaizegrowthstageofV6forthemostfluorescencebasedparameters.Withbluelightinduction,thenitrogendeficiencycanevendetectnitrogendeficiencyasearlyasV5growthstageofmaize.Thereappearstobestrongpotentialforcropsensingbasedprecisionnutrientmanagementtoenhanceproductivity,nutrientuseefficiencyandenvironmentalstewardship.
LECTURES
Jülich, 5. – 7. September 2011 27
Data management pipeline for plant phenotyping in a multi-site project aimed to identify drought tolerance markersKarin Köhl, Heike Sprenger, Dirk Walther
Plantcultivation/transformation,MPIofMolecularPlantPhysiology,Germany
Inplantbreeding,plantshavetobecharacterizedpreciselyandrapidlywithinashorttime windowdictatedbythegrowthperiod.Phenotypinghastobereproducibleandindependent ofthesiteandthepersonperformingit,asgenotypesaretestedonseveralfieldsites.Addi-tionally,datahavetobestoredinastandardizedformattoallowrapidevaluationandstatisti-calanalysisfordecisionmaking(KöhlandGremmels2010).Accesstodatamustbeprovidedlong-termandindependentofbarriersbetweenorganizationswithoutendangeringdataintegrityortheintellectualpropertyrightsofindividualresearchersorcompanies.
Weestablishedadatamanagementpipelineforaprojecttoimprovedroughttoleranceincropsbymarkerassistedselection.Theprojectinvolves11groupsfromacademiaandbreedingcompanies,experimentsandfieldtrialsat11sitesandanalyticalplatformsinfourlaboratories.Dataevaluationandmodelingareontheproject’scriticalpathasanalyticalresultsarerequiredfordecisionmakingalreadyinanearlyphaseoftheproject.Fastdataac-cessisgainedbyadatawarehouseconceptcombiningcentraldatastorageindatabasesandafileserverhostedinGolm.Thedatabaseconceptcombinestwoexistingsystems,theGolmMetabolomDatabase(Kopkaetal.2005)andtheplantmanagementsystem(Köhletal.2008)withanewdatabasethatcontainsphenotypinginformation.Thefileserverstoresrawdata,picturesandmethodsfilesaswellasresultsfilesandlinksthesetodatabaseentries.Dataentryandretrivalareperformedonwebpagesbymanualentriesorfileuploadsfollowedbyparsingandthegenerationofusercopies.Thisway,thetimebetweendataproductionanditsgeneralavailabilityisreducedtoaminimum.
References[1]Köhl,Karin;Gremmels,Jürgen;Köhl,Karin(2010)Documentationsystemforplanttransformationserviceandresearch.PlantMethods4[2]Köhl,Karin;Basler,Georg;Lüdemann,Alexander;Selbig,Joachim;Walther,Dirk(2008)Aplantresourceand experimentmanagementsystembasedontheGolmPlantDatabaseasabasictoolforomicsresearch.PlantMethods11
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LECTURES
Oilseed Rape leaf senescence phenotyping and identification of subcellular structural and metabolic changes using NMR toolLaurent Leport1, Maja Musse2, Mireille Cambert2, Loriane De Franscesci1, Françoise Le Caherec1, Agnes Burel3, François Mariette2, Alain Bouchereau1
1UMR118APBVINRA–AgrocampusOuest-UniversitédeRennes1,DomainedelaMotte, 35653LeRheuCedex,INRA,France 2URTERE,17AvenuedeCucillé,CS64427,F-35044Rennes,CEMAGREF,France 3MRic(Microscopy–RennesImagingCenter),FacultédeMédecine,2avenueduProfesseur LéonBernard,CS34317RennesCedex,UniversitédeRennes1,France
Theaimofourprojectistodevelopaphenotypingtoolusingthelowfieldnuclearmagneticresonance(NMR)relaxometryinordertoassessthephysiologicalperformanceofplantleaftissueinrelationwithnutrientremobilizationprocessesfromsenescingsourcestodevelopingsinkssearchingforanintegratedevaluationofnitrogen(N)andwateruseefficiencies.NMRrelaxationtimemeasurementshavebeenusedinseveralstudiestoinvestigateleafcellsandsignalsobtainedhavebeendescribedbyamulti-exponentialbehaviorreflectingwaterstatusandinteractionbetweenwaterandmacromoleculesindifferentcellcompartments.InthisstudyweusedNMRtoinvestigatearelationshipbetweenthetransverserelaxationtime(T2)andleafsenescenceinoilseedrapeplant.Measurementswererealizedon94samplesatdif-ferentsenescencestages,characterizedbywelldescribedbiochemicalandmolecularmarkerssuchasSAG/CABgeneexpression,chlorophyll&starchcontent,waterstatus.Carbon(C)&Nreallocationwasfollowedbysugarandaminoacidmetabolicprofileswhilecellularchangeswerecharacterizedbylightmicroscopy&TEM.T2measurementswereperformedona20MHzspectrometerusingCPMGsequence.RelaxationdecaysoftheCPMGsequenceinallleafsamplesweredescribedby3to4componentscorrespondingtospecificcellcompartments.WewereabletoestablishcorrelationbetweenT2signatureandleafsenescingstatusofferingperspectivesforavaluablephenotypingtool.OuraimisnowtoassociatechangeinT2 with subcellularstructuralreorganizationtogetherwithmetabolitereleaseasCandNressourcesandtoseehowenvironmentalstresses(combiningNandwaterdepletion)affectthissignal.
POSTERS
Jülich, 5. – 7. September 2011 29
Functional mapping of grapevine transpiration responses to drought, induced by rootstocks: how to combine data modeling and genetic analysis to take into account genotype x environment interactions?Elisa Marguerit1, Oliver Brendel2, Cornelis Van Leeuwen1, Serge Delrot3, Nathalie Ollat4
1UMREcophysiologyandGenomicsofGrapevine,ENITA–ISVV,France 2UMREcologieetEcophysiologieForestières,INRA,France 3UMREcophysiologyandFunctionalGenomicsofGrapevine,Univ.Bordeaux-ISVV,France 4UMREcophysiologyandFunctionalGenomicsofGrapevine,INRA-ISVV,Franc
Grapevineisusuallygrowngrafted.Asthescionisresponsibleforwinecharacteristics,root-stockcanbemoreeasilychangedinordertoimproveadaptationtodrought.Theregulationoftranspirationisoneofthestrategiesforplantstocopewithwaterdeficit.Theobjectiveofthisworkwastoanalysethegeneticdeterminismoftranspirationresponsetowaterdeficitinducedbytherootstock.
Amappingpedigreederivedfromtheinter-specificcrossofV.vinifera×V.ripariawaspheno-typedasarootstockwiththesamescionforeveryplant.Usinga150balanceplatform(Sadoketal.,2007),irrigationwasappliedonapot-by-potbasisinordertocontrolthewaterstatus.After10daysatfieldcapacity,aprogressivewaterlimitationwasappliedfor10daysand followedbyastablewaterdeficitfor15days.Transpirationwasevaluateddailybyweighingeachpot.Leafareameasurementswereperformedweekly.Attheendofthedroughtcycle,leaf13C,transpirationefficiencyandwaterextractioncapacityweredetermined.Theexperi-mentwasrepeated3times.Theresponseoftranspirationtowateravailabilitywasmathemati-callyfitted.ThecoefficientsandremarkablepointsofthecurveswereusedinQTLanalysis.Standardyear-by-yearandmultienvironmentanalyseswereperformed.StableQTLsweredetectedon4linkagegroups.Thisworkshowsthattheregulationofsciontranspirationbytherootstockisgeneticallydeterminedandthatwaterextractioncapacityiscentraltothiscontrol.
References[1]Sadok,Walid;Naudin,Philippe;Boussuge,Benoit;Muller,Bertrand;Welcker,Claude;Tardieu,François(2007)LeafgrowthrateperunitthermaltimefollowsQTL-dependentdailypatternsinhundredsofmaizelinesundernaturallyfluctuatingconditions.PlantCellandEnvironment30:135–146
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LECTURES
Standardization of protocols and experimental design for high-throughput phenotyping: needs and limitsCatherine Massonnet1, Juliette Fabre1, Mélanie Dapp2, Sarah Cookson1, Myriam Dauzat1, Sébastien Tisné1, Christine Granier1
1EcophysiologyofPlantsunderEnvironmentalStresses,INRA,France 2 PlantGenetics,UniversityofGeneva,Switzerland
Amajorgoalofthelifesciencesistounderstandandmodelhowmolecularprocessescontrol-phenotypesandtheiralterationinresponsetobioticorabioticstresses.ThestudyofArabi-dopsisthalianagenomicsisprovidingnewinsightsintotheunderstandingoftheseprocesses.Thefunctionalanalysisofgenesassociatedwiththeseresponsesismadepossiblebythephenotypicanalysesofmutantsornaturalgeneticvariants,high-throughputgeneticmappingandlarge-scaleanalysesofgeneexpression.Tenyearsago,animportantbottleneckwasthephenotypicanalysisofthegeneticvariability,whichrequiressimultaneousanalysisofhun-dredstothousandsofplants.Automatedplatformsnowexistinmanylabsand,theyprovidelargequantitiesofmicro-meteorologicaldata,imagesandphenotypicaldataforthestudyofgenotypexenvironmentinteractioneffectsondifferentplantprocesses.Protocolshavebeenstandardisedtoallowreproducibilitybetweenexperimentsandfacilitatemeta-analyses. Standardsandontologieshavealsobeenintegratedwhenpossibletoensurethatthedataproducedbyspecificgroupscanbenefitothergroupsinanalysesofwhichthepurposesextendbeyondtheonesthathavebeenpublished.Exampleswillbepresentedthatillustrateboththelimitsandthepowerofincreasingthethroughputinplantgrowthphenotypingwithhighlystandardisedprotocols.
References[1]Granier,Christine;Aguirrezabal,Luis;Chenu,Karine;Cookson,Sarah;Dauzat,Myriam;Hamard,Philippe;Thioux,JeanJacques;Rolland,Gaelle;Bouchier-Combaud,Sandrine;Lebaudy,Anne;Muller,Bertrand;Simonneau,Thierry; Tardieu,François(2006)PHENOPSIS,anautomatedplatformforreproduciblephenotypingofplantresponsestosoilwaterdeficitinArabidopsisthalianapermittedtheidentificationofanaccessionwithlowsensitivitytosoilwater deficit.NewPhytologist169(3):623–635[2]Fabre,Juliette;Dauzat,Myriam;Negre,Vincent;Wuyts,Nathalie;Tireau,Anne;Gennari,Emilie;Neveu,Pascal;Tisné,Sébastien;Massonnet,Catherine;Hummel,Irène;Granier,Christine(2011)PHENOPSISDB:anInformationSystemforArabidopsisthalianaphenotypicdatainanenvironmentalcontextBMCPlantBiology11:
LECTURES
Jülich, 5. – 7. September 2011 31
Non-invasive belowground phenotyping and functional root analysisRalf Metzner
IBG-2Plantsciences,ForschungszentrumJülichGmbH,Germany
Thespatialandtemporaldevelopmentofthestructureandphysiologicalfunctionoftherootsystemdeterminestheefficiencyofforagingforbelowgroundresourceslikewaterandmineralnutrients,makingitcrucialforplantdevelopmentandperformance,especiallyunderresourcelimitedconditions.However,duetotheirsoilenvironmentandsusceptibilitytoextraction,investigatingthreedimensionalstructureandfunctionofrootsandtheirdevelopmentaldynamicsrequiresimagingtechniquesthatarenon-invasiveandabletodetecttherootswith-inopaquesubstrates.OnetechniquethatmeetstheserequirementsisMagneticresonanceimaging(MRI)basedonthedetectionofprotons(mainlyofwater)forwhichmanysubstratesaretransparentandwhichallowsspatialresolutionsdownto30μm.Eventhoughtheresolu-tion–withpresenttechnologies–isworsebyafactorof10whenlargersoilvolumeslikepotsareimaged,comparativelythinrootsofmanymodelandcropplantscanbeimagedin3D.Alsodynamicsofrootdevelopment,waterstatusandflowinxylemandphloemcanbeinves-tigatedandwithinlargerootslikesugarbeetseveninternalanatomicalstructures.Apriceforsuchahighlevelofdetailandwealthofinformationissomedegreeoftechnicalcomplexityandalimitedthroughputofsamplescomparedtomodernscreeningtechniques.Positronemissiontomography(PET)isacomplementarytechniquetoanalyserootfunctionbasedonradiotracerimaging.Thetypicaltracerinplantresearchistheshortlivedcarbonisotope11Cwhichisappliedtotheleavesas11CO2,fixedbyphotosynthesisandintheformofcarbo-hydratestransportedwithintheplant.3DdetectionwithinacustombuiltPETscannerenablesustofollowcarbohydrateallocationwithintheplantbodyandalsointherootswithinthesoil.Thisgivesusatooltoinvestigateandquantifyphloemflowandcarbonpartitioningandagainespeciallytheirdynamicbehaviourasanimportantsteptounderstandandoptimizeresourcelimitationandchanginggrowthconditionsfortheroots.Furthermore,duetothenon-invasivenatureofbothtechniquesrootsmaybeimagedwithbothapproachesandthecomplementarydatacombined,allowingforaverydetailedcharacterizationofthestructureandfunctionandtheirdynamiccharacteristicsofrootsystems.
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LECTURES
Plant Phenomics and Global Food SecurityJohn Passioura
SCIROPlantIndustries,Canberra,Australia,Australia
Yieldsofthemajorcropshavebeenincreasinglinearlyforsometime,butmoreslowlythantheexpectedrequirementsoverthenextfewdecades.Further,thesupplyofirrigationwater isfalling,primeagriculturallandisdisappearingunderroadsandcities,demandforbiofuels isincreasing,andtheweatherisbecomingmoredamaginglyvariable.Aninadequatesupply ofaffordablefoodwillleadtomajorsocialunrest.Whattodo?
Phenomicsofferspotentiallypowerfultoolsforenablingplantbreedersandagronomiststoincreasetheirrateofprogress.Itis,however,hardtodevelopphenomicstoolsthatfieldscientistsseeasuseful.Thereisoftenalargegapinmutualappreciationandunderstandingbetweenscientistswhoworkincontrolledenvironments,wheremostphenomicsisdone,andthosewhoworkinthefield.Therearemanysuchgapswithinbiologicalresearchgenerally,butreducingtheonebetweenfieldandlabisthemostchallenging.
Onewaytoimprovetheconnectionistodevelopfieldphenotypingfacilitieswhichcanbeusedfortestingnewgermplasmanditsinteractionswithcropmanagementandenvironment.Suchfacilitiesofferanopportunitytopractitionersofphenomicstoconverttheirideasintonovelgermplasmornewagronomictechniques,andtodosoby(1)incorporatingnoveltraitsintoexistinggermplasmthatisadaptedtothegivenenvironment,forrealistictestinginthefield,i.e.targetedprebreeding;and(2)bydevelopingandtestingnovelmeasurementstomon-itortheprogressofcrops,therebyenablingmoreflexibleandtacticalmanagement.Likewise,suchfacilitiesenablebreederstotakeaninterestinnovelmorphologicalandphysiologicaltraitsthattheynormallydonothavetimetoconsider,andtotesttheirownadvancedbreedinglinesacrossvariousagronomictreatments,whichtheyarenotnormallyabletodo.
LECTURES
Jülich, 5. – 7. September 2011 33
A low-cost platform for phenotyping plant growth and water useGustavo A. Pereyra Irujo, Emmanuel D. Gasco, Luis A. N. Aguirrezábal
UnidadIntegradaBalcarce,InstitutoNacionaldeTecnologíaAgropecuaria,Facultadde CienciasAgrarias,UniversidadNacionaldeMardelPlata,ConsejoNacionaldeInvestigacionesCientíficasyTécnicas.Ruta226Km73,7620Balcarce,Argentina.,Argentina
Advancesingenotypingtechnologieshaveloweredthecost-per-genotypetolevelsthatenabledanexplosionofgeneticstudiesinmanyfields.Asaconsequence,phenotypinghasbecomeabottleneckforunderstandingthegeneticbasisofcomplextraits(e.g.waterdeficittolerance).Availableplantphenotypingplatforms,especiallythosethatautomatenotonlymeasurement,butalsocultivationandirrigationofcropplants,haveacostwhichcanbe excessiveformanyresearchinstitutesorbreedingcompanies.Loweringthecostoftheseplatformscouldthereforeleadtoarapidexpansionofbreedingprojectstargetingcomplextraits.
Wedevelopedalow-cost,flexible,automaticplatformforhigh-throughputmeasurementofplantwateruseandgrowth.Thiswasachievedthroughasimpledesign(withfewmovingparts)andusingmostlystandardcomponents.Thisplatformconsistsoffour10m-long,bridge-likestructuressupporting120pots,andamovingkartlocatedunderthisstructure,carryinga personalcomputerconnectedtofourbalances,fourperistalticpumps,andeightwebcams.Theplatformiscontrolledbyasimplesoftware,whichusesExcelfileswithdailyorhourlyroutinesasinput,andAccessdatabasefilesasoutput.Animageanalysispipelinefortheestimationofleafareaiscurrentlybeingdeveloped.Ithasbeensuccessfullyusedtoanalyzesoybeangrowthunder7soilwatercontents,andhourlytranspirationratesinsunflower.
Theconstructionandmaintenancecostsofthisplatformaresignificantlylowerthancommer-ciallyavailableplatforms.Webelievethatthiskindoflow-costplatformisthereforesuitableformid-orlow-budgetresearchgroupsorseedcompaniesallovertheworld,mainlyindevelopingcountries.
ReferencesProjectwebsite:www.plataformabiotecsur.com.ar
34 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
Fluorescing plants and canopies: using fluorescence techniques to map plant function from the single organ to the ecosystemUwe Rascher
IBG-2,ForschungszentrumJülich,Germany
Chlorophyllfluorescenceanalyseshavebecomeoneofthemostpowerfultechniquestoquantifyphotosyntheticefficiencyandnon-photochemicalenergydissipationnondestructively.ThemostcommonlyusedtechniquetoquantifyphotosyntheticLUEisthesaturatinglightpulsemethodandnowadaysseveralfieldportableandimaginginstrumentsareavailable.Intherecentyearsthisapproachwascomplementedbylaserbasedandpassivetechniquesthathavethepotentialtomeasurechlorophyllfluorescencefromadistance,thusopeningnewpossibilitiesforfunctionalscreeningofplantsandcanopiesinthefield.
Inthispresentationwewillfirstgiveanoverviewontheprinciplesofchlorophyllfluorescencemeasurementsandhighlightbasicandadvancefluorescenceapproachesthatarecurrentlyusedtoquantifyfunctionalpropertiesofplantandcanopyphotosynthesisinspaceandtime.Specialemphasiswillbegivenontheretrievalofthesun-inducedchlorophyllfluorescencesig-nalbyactiveandpassivemethods.Especiallypassivedetectionofsun-inducedfluorescencewasrecentlyemphasizedbytheselectionofanovelsatellitemission(FLEX)oftheEuropeanSpaceAgency(ESA)thatproposedtolaunchasatellitefortheglobalmonitoringofsteady-statechlorophyllfluorescenceinterrestrialvegetation.Thismethodaimsformappingphoto-syntheticefficiencybyquantifyingsteadystatefluorescenceinthesocalledFraunhoferlines.
Inasecondpartwewillpresentresultsfromseverallaboratoryandfieldexperiments,inwhichfluorescencetechniqueswereusedtobetterunderstandfunctionalpropertiesofphoto-syntheticenergyconversionnon-invasively.Specialemphasiswillbegivenon(i)automatedfluorescenceimagingusinganovelhigh-throughputscreeningset-up,(ii)thelongtermmoni-toringofphotosynthesisfromthedistanceusingLaserInducedFluorescenceTransients(LIFT)and(iii)largescalemappingofsun-inducedfluorescencefromtheplottotheregion.
LECTURES
Jülich, 5. – 7. September 2011 35
Machine learning approaches in data analysis pipelines for plant phenotyping and precision agricultureUdo Seiffert
BiosystemsEngineering,FraunhoferIFFMagdeburg,Germany
Plantphenotypingandprecisionagricultureapplicationsoftenrequireanalysisandfusionofhigh-dimensionalandcomplexdata.Inmanycasesananalyticalmathematicaldescriptionisnotavailableandnon-explicitlygivenexpertknowledgeneedstobeincorporated.Inthesecasesmachinelearningapproacheshaveproventobeanexcellenttechniquefordataanalysisandstatisticalmodelling.Thistalkwillfeatureseveralfundamentalplantphenotypingandpreci-sionagricultureapplicationsthatsubstantiallybenefitfrommachinelearningapproaches.
References[1]Bollenbeck,Felix;Seiffert,Udo(2009)ComputationalIntelligenceinBiomedicalImageProcessingStudiesin ComputationalIntelligence,Vol.205197–222[2]Backhaus,Andreas;Kuwabara,Asuka;Fleming,Andrew;Seiffert,Udo(2010)ValidationofUnsupervisedClusteringMethodsforLeafPhenotypeScreeningProceedingsofthe18.EuropeanSymposiumonArtificialNeuralNetworksESANN2010511–516[3]Seiffert,Udo;Bollenbeck,Felix;Mock,Hans-Peter;Matros,Andrea(2010)ClusteringofCropPhenotypesbyMeansofHyperspectralSignaturesUsingArtificialNeuralNetworksProceedingsofthe2ndIEEEWorkshoponHyperspectralImagingandSignalProcessing:EvolutioninRemoteSensingWHISPERS201031–34
36 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
Superimposing structure and function in 4-D; new sensors for „Digital Agriculture“Xavier Sirault, David Deery, Richard Poire, Solene Callarec, Robert T. Furbank
HighResolutionPlantPhenomicsCentre,CSIROCanberraACT,Australia
Amajordriverforthedevelopmentofnewcropphenotypingtoolsistheneedtoincrease therateofyieldprogressinplantbreedingtomeettheneedsofourburgeoningpopulation.Currently,annualprogressinyieldsfromcerealgrainsgloballyhasfallenbelow1%.Tofeed 9billionpeople,thelikelypopulationin2050,cerealyieldsmustincreasebybetween70and100%.Improvedphenotypicselectionforevaluationofnewgermplasmandfindinggeneswhichunderpinagriculturaltraitsrequiresnewhighresolution,non-destructive,highthrough-puttools.
NovelhighthroughputtechniquesattheHighResolutionPlantPhenomicsCentrearedescribed, focusingoncropbiomass,plantarchitectureandradiationuseefficiencyincontrolledenvi-ronmentsandinthefield.Wholeplantapproachesingraincropsareparticularlychallengingduetothecomplex3-Dstructurewhichmustbeaccommodatedinmeasuringsystems.Thenewsensorsdescribedrangefromdigitalgrowthanalysisusingsimple2-Dimagesofplantsinsinglepotstofull3-DmultimodaldigitalimagingandLidar,feature extractionandtraitquantification.
LECTURES
Jülich, 5. – 7. September 2011 37
X-Ray Imaging Methods also for Plant Phenotyping – Opportunities now and in the futureNorman Uhlmann1, Michael Salamon1, Mustapha Khabta1, Christoph Funk1, Randolf Hanke2
1EZRTDevelopmentCenterX-RayTechnology,FraunhoferIIS,Germany 2EZRTDevelopmentCenterX-RayTechnology,UniversitätWürzburg,FraunhoferIIS,Germany
Theuseofx-raysfor2Dimagingand3Dvolumedatagenerationiswellestablishedin industrialandscientificprocessesfordefectdetectionandstructuralanalysisforawide rangeofpartsandspecimen.Theapplicationsvaryfrombiologicalsampleswithveryfine structuresandlowZmaterialstothe3Dimagingofcompletelargeobjectslikeengineblocks orevenseafreightcontainerswithheavyx-rayabsorbinghighZmaterials. Wewillpresentanoverviewofthestateoftheartmethodsandsystemsetupsforx-ray imagingfocussedon3Dvolumedatasetgenerationandthepossibilitiesandlimitsaccording toplantphenotypinglikegeometricandstructuralanalysisofrootsandcrops.Exampleswith resolutionsfromabout500nmorevenbelowathighestresolutionscanstotheanalysisof largerobjectswithmoderateresolutionarediscussed.
Anoutlookofnearandfarfuturedevelopmentsinx-raycomponents,imagingandvolume datasetanalysismethods,possiblesystemsetups,applicationsandpossibilitieswill concludethepresentation.
38 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
The neglected environmental long term effect. Why it is necessary to include growth conditions in a data management and analysis pipelineBjörn Usadel
MaxPlanckInstituteofMolecularPlantPhysiology,Germany
Thelastyearshaveseenamassiveincreaseinthecollectionofhighthroughput“omics”data.Thishasleadtheestablishmentofseveralstandards,describingonhowthesedatasetsshouldbecollected(MIAMI-Plant,MIAMET,ARmetetc.)complementingthegoodscientificpracticeofrequiringthedescriptionofplantgrowth.However,acomprehensivehistoryabouttheenvironmentalconditionsandmanipulationsaplantwassubjectedtountiltheactual experimentisperformedisoftenstilllacking.Furthermore,manyexperimentaldescriptionsstillfailtoreporttheperceivedtime(e.g.4haftersunrise)oftheexperiment.Thisisdespitethefactthatahighproportionofgenesandmetabolitesinplantshavebeenshowntoshow acircadianand/ordiurnalbehaviour.
Here,weshowsomenotsosubtledifferencesinplantresponseswhenplantsweregrownunder“standardconditions”.Wecomplementthisbyshowinganexamplewhereonlythetrackingofgrowthconditionsallowedfaithfuldatainterpretationandphenotypeinterpreta-tion.However,whilstitisclearlybeneficialtohavedatafromautomateddataloggers,inmostcasesitwouldbesufficientandadvantageousfordatainterpretationifjustthemajormani-pulationsandchangesinconditionswouldbedescribed.Thiscouldencompasschangesinday-nightcycle,achangeinsubstrate,fertilizing,wateringregimesetc.Thissetsthestageforamoreintegrativeviewindataintegrationwhereplantgrowthistrackedthroughtheplant’slivecyclefocusingonnecessaryenvironmentalcharacterizationandenablingbettercompari-son between data sets.
Itcanbeexpectedthatcarefulminingofthesewelldescribeddatasetswillallowabetterunderstandingofplantphenotypes.
LECTURES
Jülich, 5. – 7. September 2011 39
SPICY: Large scale phenotyping of tall pepper plants in the greenhouseGerie van der Heijden, Yu Song, Gerrit Polder, Graham Horgan, Chris Glasbey, Anja Dielemann
Biometris,WageningenUR,Netherlands
IntheEU-KP7-projectSPICY(SmarttoolsforthePredictionandImprovementofCropYield;www.spicyweb.eu),theaimistodevelopnewtoolsformolecularbreeding,usinganintegratedapproachofmoleculartechniques,advanceddataanalysistechniques,plantgrowthmodelsandphenotypingtools.TheplantmaterialusedisaRILpopulationofacrossingbetweenablockybellpeppercultivarYoloWonderandahotsmallfruitedlandracecultivarCriollodeMore-los.Inthepresentation,ashortoverviewofthedifferentaspectsoftheprojectwillbegiven.
Morespecificallyasaphenotypingtool,wehavedevelopedanimagingplatformtorecordandmeasurepepperplantswhiletheyaregrowinginthegreenhouse.Fortheanalysisoftherecordedimagestwoapproachesareadopted.Thefirstapproachistoaccuratelycountandmeasureplantpartslikeleavesandfruits.Forthisapproachacombinationofarangecameraandstereovisionisusedtoobtaina3Dreconstructionofthecanopy.Fromthe3Drecon-structedscene,plantpartsaresegmentedandmeasured.Wewillshowanexampleofleafarea.Theotherapproachisaimedattheextractionofstatisticalfeaturesfromtheimageswithouttryingtosegmentindividualplantpartsfromabackground.Thecriteriainthelatterapproacharehighheritability,i.e.,reproducibledifferencesbetweengenotypes,andstronggeneticcorrelationwithyieldoritscomponents.
40 2ndInternationalPlantPhenotypingSymposium2011
LECTURES
Contribution of airborne remote sensing and proxidetection to high-throughput phenotyping of an apple tree population in response to soil water constraintNicolas Virlet1, Sébastien Martinez2, Valentine Lebourgeois3, Evelyne Costes2, Sylvain Labbé4, Jean Luc Regnard1
1 MontpellierSupAgro–UMRAGAP,France2 INRA–UMRAGAP,France3 CIRAD–UMRTETIS,France4 Cemagref–UMRTETIS,France
Inthefuture,becauselongerperiodsofheat,scarceprecipitationandhighairvaporpressuredeficitsareexpected,climatechangewillhampertemperatefruitproductioninparticularwhereirrigationbecomeslimiting.Adaptingfruittreestoabioticstressesisthus anewchallengingissueforfruitcropswhosewateruseneedstobedeeplyre-considered.Thisstudyaddressesthequestionofappletreeresponsestodrought,wateruseefficiencyandtheirgeneticbases.Ashighthroughputphenotypingmethodsconstituteabottleneck forscreeninggeneticmaterialtoleranttoabioticstress,weexploreairborneremotesensingandproxidetectionaspossiblemethodstoevaluatebehaviorofadultapplehybridsgrowninorchard conditions.
Thestudyisperformedon‘Starkrimson’x‘GrannySmith’appleprogeny(122hybridsculti-vatedinfieldonDiaphenplatform(INRAMontpellier,France).Responsesofgraftedtreestosoildroughtareassessedthroughleafphotosynthesis,transpirationandwateruseefficiencyofthescionvariety.Ourpreviousresultsshowedthatthesetraitsarevariableandheritableacrosstheprogenyatyoungtreestage.Themethodologicalchoicesaimingatadulttreenotypinginfieldincludetwoapproaches:(i)theanalysisofairborneremotesensingimagesacquiredatplotscale(invisible,nearinfraredandthermalinfraredwavebands)forthecalcu-lationofthetreewaterdeficitindex(WDI),(ii)thecontinuousmeasurementofsurfacetemper-ature1mabovethecanopy,inordertocomputethewaterstressindex(CWSI)andcomparethebehaviorofgivengenotypesinresponsetothewaterconstraint.Possibilitiesandlimitsoftheseapproachesappliedtodiscontinuousandporouscanopieswillbediscussed.
LECTURES
Jülich, 5. – 7. September 2011 41
High throughput phenotyping drought related traits of tropical maize hybrids in the vegetative stageLoïc Winterhalter1, Bodo Mistele1, Sansern Jampatong2, Urs Schmidhalter1
1 DepartmentofPlantSciences,ChairofPlantNutrition,TechnischeUniversitätMünchen, Germany 2NationalCorn&SorghumResearchCenter,KasetsartUniversity,Thailand
InourstudywedemonstratedthatspectralindicesaswellasIR-temperaturedisplayedahighcorrelationwithcanopywatermassandthatspectralindicescouldalsoaccuratelyestimatetheaerialbiomassandabovegroundnitrogenuptakeofseventropicalmaizehybridsgrownunderfieldconditions,whiledifferentiatingthedroughtstresslevels.Inaddition,itwaspos-sibletoclassifyconsistentlythehybridsexaminedinthreegroups(above,beloworaverageperformance)undercontrolandstressenvironmentswithdestructiveandnon-destructivemeasurements.TheaccuratepositioningofthesensorandIR-thermometerwithaconstantangleofviewandanobliqueandoligoviewinggeometryallowedobtainingalargefootprintofthemaizeplotswhileminimizingthesoilinfluenceinthefieldofview.Reducingthetimerequiredforthemeasurements,beingparticularlyvitalforwaterstatusdetection,furtheraddedtoanewapproachinestimatingphenotypicandphysiotypictraitsofmaizehybridswithcarrierbased,non-destructive,highthroughputreflectanceandthermalmeasurementsco-recordingGPSdata.
ReferencesWinterhalter,L.;Mistele,B.;Jampatong,S.;Schmidhalter,U.2011Highthroughputsensingofaerialbiomassandabovegroundnitrogenuptakeinthevegetativestageofwell-wateredanddroughtstressedtropicalmaizehybrids.CropScience51,479–489.Winterhalter,L.,Mistele,B.,Jampatong,S.,Schmidhalter,U.2011Highthroughputphenotypingofcanopywatermassandcanopytemperatureinwell-wateredanddroughtstressedtropicalmaizehybridsinthevegetativestage.EuropeanJournalofAgronomy35,22–32.
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LECTURES
Development of rice plant phenomics facility equipped with agriculture photonicsWanneng Yang1, Lingfeng Duan1, Chenglong Huang1, Ni Jiang1, Wei Fang1, Lizhong Xiong2, Guoxing Chen2, Qian Liu1
1HuazhongUniversityofScienceandTechnology,China 2HuazhongAgriculturalUniversity,China
Riceplanttraitsevaluationisanessentialstepinricebreeding,geneticresearchandfunctionalgenomicsresearch.Modernplantbreedingtechnologiesareabletoproducehundredstothousandsofnewvarietiesdaily,creatingtheimpetusforrapidevaluationofplantmaterials toprovidepertinentinformationpriortoenteringthenextcycleofselection.However,theconventionalmethodsofextractingriceplanttraitsarestillmanual,whichistimeconsum-ing,subjective,wearisomeandlack-repeatability.Thisarticleaimedtodevelopariceplantphenomicsfacilityforhigh-throughputtraitsevaluationwithAgri-photonics,whichmainlyin-cludes:(1)measurementofricetillerswithx-raycomputedtomography,(2)extractionofplantheightusingvisiblelightimaging,(3)modelingofautomaticobservationsandfreshweightbasedondualcolorcameraimaging,(4)designoffacilityforautomaticinspectingthethreetraitsinasinglechamber.Aftertestunderindustrialcondition,themeanabsoluteerroroftillerobservationsandplantheightobservationswas0.67and19mm,respectively.Inordertoevaluatetheaccuracyoffreshweightextraction,twobatchesofriceatdifferentstages(jointingandheading)weremeasured,andthecorrelation.
References[1]Tester,Mark;Langridge,Peter(2010)Breedingtechnologiestoincreasecropproductioninachangingworld Science 818 – 822[2]Finkel,Elizabeth(2009)With‘phenomics,’plantscientistshopetoshiftbreedingintooverdriveScience380–381[3]Yang,Wanneng;Xu,Xiaochun;Duan,Lingfeng;Luo,Qingming;Chen,Shangbin;Zeng,Shaoqun;Liu,Qian(2011)High-throughputmeasurementofricetillersusingaconveyorequippedwithx-raycomputedtomographyReviewofScientificInstruments0251021-0251027
LECTURES
Jülich, 5. – 7. September 2011 43
High-resolution hyperspectral and thermal imagery for estimating physiological parameters and pre-visual indicators of stressPablo J. Zarco-Tejada
Agronomy,InstituteforSustainableAgriculture(IAS)–NationalResearchCouncil(CSIC),Spain
Newadvancesonvegetationstressdetectionmethodsusingamicro-hyperspectralimagerandhigh-resolutionthermalimageryacquiredovercropsgrownundernaturallightconditionswillbediscussed.Imagingsensorsinstalledonboardunmannedaerialvehiclesenabletheac-quisitionofhyperspectralimagerycomprising360spectralbandsat6nmbandwidth,obtain-inghighresolutionimageryat40cmpixelsizeinthe400-1000nmspectralrange.Biochemi-calconstituentssuchasxanthophyll,carotenoids,anthocyanins,andchlorophylla+bcanbeextractedusingopticalindicessuchasPRI,TCARI/OSAVIandnewratiosrelatedtocarotenoidandanthocyaninpigmentsfromstudyareasflownthatcomprisedagradientinstresscondi-tionsduetovaryingwaterandnutrientstresslevels.Methodsfortheretrievalofchlorophyllfluorescenceusingthein-fillingmethodthroughtheO2bandwillbediscussed,showingmapsofpure-crownphysiologicalparametersthroughautomaticobject-basedimageanalysis methodsapplied.ThestudydemonstratesthefeasibilityforhyperspectralimageryacquisitiononboardUAVsusinglightweightmicro-hyperspectralimagerssynchronizedwithlow-costIMUsystems.HyperspectralimagersonboardUAVplatformsenableflexibleairbornecampaignsforthevalidationofbiochemicalandbiophysicalparameterretrievalsforstressdetectionoverlargeagriculturalareasexceeding1000haperflight.
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LECTURES
Integrating phenotyping and gene expression data in GenevestigatorPhilip Zimmermann
NebionAG/ETHZurich,Switzerland
Genevestigatorcurrentlycontainsmicroarraydatafrommorethan60,000samples,ofwhich14,000arefromplantspecies.Allexperimentsaremanuallycuratedandannotatedatmultiplelevelsusingontologies.Theselevelsinclude,forexample,genotype,perturbation,anatomicalanddevelopmentinformation.Theinclusionoffurtherlevelsofinformation,suchasphenotypingorothertypesofcharacterizationdata,istechnicallyimplementedandalreadyinuseformammalianspecies.Forplantspecies,however,thereisaneedforfurtherdevelop-mentsatthelevelofphenotypingontologiesandforthecurationofphenotypedata.NebionAGisaspin-offcompanyfromETHZurichwhodevelopsandcommercializesGenevestigator.Welookforwardtocollaboratingwithindustrialandacademicpartnerstosupportthese developmentsandtointegratephenotypingdataintoGenevestigatorforcombinedanalysiswithexpressiondata.
2. Posters
46 2ndInternationalPlantPhenotypingSymposium2011
POSTERS
Methodologies to phenotyping Wheat in field experiments for drought toleranceSolange R. M. Andrade1, Eric S. Ober2, Walter Q. Ribeiro Júnior1, Maria L. Gerosa Ramos3, Vinícius B. Buffon1
1CropScience,EmbrapaCerrados,Brazil 2Broom‘sBarnResearchCenter,RothamstedResearch,UnitedKingdom 3Agronomy,UniversidadedeBrasília,Brazil
Researchtodeveloptechniquesfortheselectionofwheatcultivarsbettersuitedtodrycondi-tionsisbeingdonebyEmbrapa(Brazil)andRothamstedResearch(UK).IntheCerradoregionofBrazil,farmerscaneitherplantwheatduringthewinterusingirrigation,orinthesummer asasecondcrop(‘Safrinha’),whichisthemorecost-effectivemethod.However,duringthisperiod,variableperiodsofdrought(‘Veranicos’),lastingfromfourdaystoweeks,accompaniedbyhighinsolation,canlimityields.WheatcropsintheUKalsofrequentlyexperiencedroughtsofvariablelength,intensityandtiming,causingannuallossesof1-2tha-1.Weusedtwo differentmethodsofimposingcontrolledlevelsofwaterdeficitinfieldexperimentstocom-paretheresponsesofgenotypes.InBrazil,theline-sourcemethodwasusedtoapplyagradi-entofwaterlevels.Intotal,150genotypeswerecompared,resultinginaselectionofthreetolerantandtwosensitivelines.IntheUK,largepolytunnelrainoutshelterswereused toimposedroughtbeginningtwoweeksbeforeflowering.Outof120genotypes,asubsetof12genotypeswereselectedthatshowedconsistentcontrastsindroughttolerance.Asuite ofmorpho-physiologicalmeasurementsweremadeonalllinestoidentifytraitsthatcould beusedassecondaryselectioncriteria.Measurementtechniqueswereadaptedsothatlargenumbersoffieldplotscouldbeassessedrapidlyandinexpensively.Linesthatcontrastindroughttolerancecanbeusedfor1)furtherdissectionofthetraitsthatcontributetodroughttolerance;2)crossingintocurrentelitebreedinglines;3)crossingtocreatebi-parentalmappingpopulationstounderstandbetterthegeneticcontrolofdroughttoleranceandcomponenttraits.
References[1]Ober,EricS.;Clarck,ChristopherJ.A.;Perry,Anne(2010)TraitsrelatedtogenotypicdifferencesineffectivewateruseanddroughttoleranceinUKwinterwheatAspectsofAppliedBiology10513–22[2]RibeiroJunior,WalterQ.;deMoraes,AuriF.;GerosaRamos,MariaL.(2009)FenotipagemparatolerânciaàsecavisandoaomelhoramentogenéticodotrigonoCerrado(PhenotypingfordroughttolerancetowheatbreedinginBrazilianSavannah)Documentos24419–26[3]Ober,EricS.;LeBloa,Mich;Clark,ChrisJ.A.;Royal,Andy;Jaggard,KeithW.;Pidgeon,JohnD.(2005)EvaluationofphysiologicaltraitsasindirectselectioncriteriafordroughttoleranceinsugarbeetFieldCropResearch91231–249
POSTERS
Jülich, 5. – 7. September 2011 47
Studying the genetics of Gibberellin sensitivity and GA inhibitor responses in Arabidopsis by using a semi- automatic procedure to measure hypocotyl length in the darknessLuis Barboza1, Ronny Joosen2, Maarten Koornneef1
1PlantBreedingandGenetics,MaxPlanckInstituteforPlantBreedingResearch,Germany 2 SeedLaboratory,WageningenUniversity,Netherlands
Hypocotyllengthisanimportanttraittostudy.Hypocotylsareamodeltostudythemecha-nismscontrollingcellelongation(Gendreau,Traasetal.1997).Itisknownthemolecularmachineryinvolvedinhypocotylgrowthandtheroleoflightandgibberellins(LauandDeng2010).Ouraimistounderstandthenaturalvariationcontrollinghypocotylgrowthwhenbioac-tivegibberellins(GAs)anditsinhibitorsareapplied.Toachievethis,QuantitativeTraitLocianalysis(QTL)andGenomeWideAssociationMapping(GWAS)areused.Duetothesizeofthemappingpopulations,datamustbeacquiredwithhigh-throughputmethodologies.Theap-plicationoftreatmentsthataffectgermination,forexampleGAinhibitors,complicateexperi-mentsonhypocotylgrowth.Joosen,Koddeetal.2010developedamethodologytostudyseedgerminationbasedonthecolourcontrastoftheprotrudingradicleandseedcoat.Thesameprincipleandsimilarworkpipelinecanbeusedtomeasurethehypocotylsgrowthby adjustingthegrowthsurfaceandtheimageanalysisparameters.Preliminaryexperimentshavebeenconductedwiththefollowingschedulebyonepersontestingbetween720-600 genotypes:twodaystoputseedsonthemedia,threedaysincubationat4ºC,onedayger-mination(23ºCunderlight),fivedaysincubationinthedark(at23ºC),twodaystoacquireimagesandprocessthem.Thenumberofquantifiedhypocotylsperexperimentwas:8479.5±238.3(12,4±1,2hypocotyls/genotype).UsingthisprocedureQTLshavebeenmappedandassociationswithgenesrelatedwithhypocotylsgrowthhavebeenfound.
References[1]Gendreau,Emmanuel;Traas,Jan;Grandjean,Olivier;Caboche,Michel;Hofte,Herman(1997)CellularbasisofhypocotylgrowthinArabidopsisthalianaPlantPhysiol295–305[2]Joosen,RonnyV.L.;Kodde,Jan;Willems,LeoA.J.;Ligterink,Wilco;vanderPlas,LinusH.W.;Hilhorst,HenkW.M.(2010)GERMINATOR:asoftwarepackageforhigh-throughputscoringandcurvefittingofArabidopsisseedgerminationThePlantJournal148–159[3]SunLau,On;WangDeng,Xing(2010)Planthormonesignalinglightensup:integratorsoflightandhormones CurrentOpinioninPlantBiology571–577
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Molecular Farming – The use of non-invasive phenotyping methods to optimize plantmade pharmaceutical protein production in closed systemsMartina Becher1, Silvia Braun1, Frank Gilmer1, Nicole Raven2, Christoph Kühn2, Stefan Schillberg2, Ulrich Schurr1
1IBG-2:PlantSciences,ForschungszentrumJülich,Germany 2PlantBiotechnology,FraunhoferIME,Germany
TheaimofMolecularFarmingistoestablishhigh-yieldingproductionsystemsforpharmaceuticalandindustrialproteins.Efficientproductionsystemsarewholeplants,hairyrootsorplantcells.Advantagesofplant-madepharmaceuticalsareproductionatlargescaleatlowcost,speedofproduction,lackofmammalianpathogens.
TheIBG-2focusesonthecultivationofwholeplants.Tobaccoplantsarecultivatedinahydroponicsysteminclosedenvironments:inglasshouseorgrowthchamber.Wedevelopedanon-invasivemonitoringsystemforwholetobaccoplantsbasedonrecombinantproteinfluo-rescence.Theplantscontainafluorescentmarkerproteinanditsproductioncorrelateslargelywiththeproductivityofthepharmaceuticaltargetprotein.Therefore,thedeterminationoftheproteinfluorescencedistributionatdifferenttimepointsduringplantgrowthallowsalsothenon-invasivemonitoringoftargetproteinaccumulation.
Basedonthisproteinfluorescenceithasbeenexaminedatwhichstageoftheplantgrowththetargetproteinaccumulatestomaximumlevels.Withadditionalinclusionofphotosyntheticperformanceasindirectgrowthmonitoringviachlorophyllfluorescence,environmentalpara-metersaffectingtargetproteincontentandqualityweredefined.
POSTERS
Jülich, 5. – 7. September 2011 49
Non-destructive shoot imaging at The Plant Accelerator to monitor salinity stress responses in barley and wheatBettina Berger1, Joanne Tilbrook2, Nawar Shamaya2, Mark Tester3
1ThePlantAccelerator,TheUniversityofAdelaide,Australia 2AustralianCentreforPlantFunctionalGenomics,Australia 3AustralianCentreforPlantFunctionalGenomics,ThePlantAccelerator, UniversityofAdelaide,Australia
Salinitytoleranceisduetoarangeofprocesses,makinggeneticstudiesdifficult.Dissectingtraitscontributingtosalinitytoleranceisnecessaryforaforwardgeneticsapproach.However,forsuchtraitdissection,non-destructivemeasurementofgrowththroughtimeisessential.
HighexternalNaClconcentrationaffectstwomainaspectsofplantgrowth;(i)osmoticstressisimmediateandinhibitsshootgrowth;(ii)ion-specificstressoccurslaterwhenhightissueconcen-trationsofNa+haveaccumulated,andleadstoanearlieronsetofleafsenescence(MunnsandTester,2008).
AutomatedimagingatThePlantAcceleratorallowscontinuousmeasurementsofplantgrowth.Thereductioninrelativegrowthrateuponsaltapplicationincomparisontocontrolconditionscanbeusedasanindexforosmoticsensitivity.Takingadvantageofthehigh-throughputcapacityatThePlantAccelerator,weaimtoidentifyQTLsforosmotictoleranceinwheatmappingpopulationsandcompare those to field data.
Inaddition,imagebasedscreeningprotocolstoquantifytissuetolerancearebeingdeveloped.Asthedegreeofsaltinducedsenescenceofmodernwheatandbarleycultivarsisfairlylow(incon-trasttoTmonococcum:Rajendranetal.,2009),treatingtheplantasasingleobjectisinsufficientandanalysisofindividualleavesisrequired.Consequently,aprojecton4Dmodelingofwheatandbarleyplantsisunderwayandfirstresultswillbepresented.
Weexpectthattheprinciplesandtoolsdevelopedforanalyzingresponsesofplantstosalinitytoler-ance can be applied to a range of problems in plant science.
References[1]Munns,Rana;Tester,Mark(2008)MechanismsofsalinitytoleranceAnnualReviewsofPlantBiology651–681[2]Rajendran,Karthika;Tester,Mark;Roy,Stuart(2009)QuantifyingthethreemaincomponentsofsalinitytoleranceincerealsPlant,Cell&Environment237–249
50 2ndInternationalPlantPhenotypingSymposium2011
POSTERS
Phenotyping red rice transgressive variant derived from a cross using wild rice accessionAtiqur Rahman Bhuiyan1, Abdullah M Zain2, Nariamh Md Kairudin1, Wickneswari Ratnam1
1GeneticsandPlantBreeding,UniversitiKebangsaanMalaysia,Malaysia 2Agrotechnology,UniversitiMalaysiaTerengganu,Malaysia
WehavebeendevelopingapolarizedHDtargetfornuclearphysicsresearchatRCNP,Osakasince5yearsago.Nuclearpolarizatoniscreatedbythebruteforcemethodwhichusesahighmagneticfield(17T)andalowtemperature(10mK).Asoneofthepromisingapplications tothefuturelifescienceswestartedanewproject,”NSI”(NuclearSpinImaging),wheretheartificiallypolarizednuclearspinisused.TheNSIistheMRI(MagneticResonanceImaging)withthehyperpolarizednucleiwithaspin1,2¯h,suchas3He, 13C,15N,19F,and31P,createdbymeansofthebruteforcemethod.ThehighlyenhancedNMRsignalsfromtheseisotopesprovidespaceandtimestructureswithresolutionsmuchhigherthanothers.
OneoftheadvantagesofthehyperpolarizedMRIisthattheMRIisbasicallyfreefromtheradi-ationexposure,whiletheradiationexposurecausedbytheX-rayCTorPET(PositronEmissionTomography)cannotbeneglected.Infact,thedangerofcancerforJapaneseduetheradiationexposurethroughthesediagnosesisexceptionallyhighamongtheadvancednations.
AsthefirststepofourNSIproject,wearedevelopingasystemtoproduceahighlypolarized3Hegasfordiagnosisoftheseriouslungdiseases,forexample,theCOPD(ChronicObstructivePulmonaryDisease).Thesystememploysthesame3He/4Hedilutionrefrigeratorandsuper-conductingsolenoidalcoilasthoseusedforthepolarizedHDtargetwithsomemodificationallowingthe3HePomeranchukcoolingandrapidmeltingofthepolarizedsolid3HetoavoiddepolarizationduringtheFermiliquidphaseof3He.
References[1]Bhuiyan,Md.AtiqurRahman;Kairudin,NarimahM;Harun,AbdulRahim;Zain,AbdullahM;Ratnam,Wickneswari(2011)TransgressivevariantsforredpericarpgrainwithhighyieldpotentialderivedfromOryzarufipogonxOryza sativa:Fieldevaluation,screeningforblastdisease,QTLvalidationandbackgroundmarkeranalysisforagronomictraitsFieldCropResearch121:232–239[2]Sabu,KalluvettankuzhiK;Zain,Abdullah,M;Lim,LiSze;Ratnam,Wickneswari(2006)DevelopmentandevaluationofadvancedbackcrossfamiliesofriceforagronomicallyimportanttraitsCommunicationinBiometryandCrop Science1(2):111–123
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Jülich, 5. – 7. September 2011 51
Vitsec, an information system dedicated to grapevine adaptation to water deficitMathias Chouet1, Vincent Nègre1, Agnès Destrac2, Eric Lebon1, Pascal Neveu1, Pierre-François Bert2, Nathalie Ollat2
1UMRMISTEA,INRA-Supagro,France 2UMREcophysiologyandFunctionalGenomicsofGrapevine,INRA–ISVV,France
Likeothercropspecies,grapevinesareexpectedtobeaffectedbyclimatechange.Thereleaseofthegrapevinegenomesequenceandthegrowingavailabilityofhighthroughputgenomictools,togetherwithintegratedanalysesofprocessesallowacomprehensiveinvestigationofthecomplexmechanismsunderlyingdroughttolerance.Tohandlethelargeandheterogeneousdatasets generatedandthemulti-useraccess,wedevelopaninformationsystemdedicatedtodataanalysisandmanagement.Thegrapevinegenome/phenomedatabasewillassociatetranscriptexpressionlevelstoecophysiologicalandphysiologicaldata.Thisdatabasewilllinkthegenomicandpheno-typicplasticityindifferentwatersupplyconditions.
Toaddresstheproblemofmanagingheterogeneousdatainmulti-sourcescontextweproposeagenericmodelbasedontheconceptof‘object’.Anobjectcouldbeanykindofmeasuredtarget(plant,soilsample,etc…),oranysub-partorgroup.Becauseobjectscouldbeconnected,hierarchi-calrepresentationbetweenobjectsispossibleevenformulti-leveldatasets.Wedistinguishonlinemeasurements(nondestructive);offlinemeasurements(destructive)andcomplexmeasurementssuchastranscriptanalyses.XMLrepresentationisusedforitsextensibilitytoannotateanobjectorameasurement.
Toincreaseinteroperabilitywithotherinformationsystemsweadoptbio-ontologies:theGrapeOn-tology[1]andtheTraitOntologyformorphologicaltraits,ENVOandXEMLOntologiesforenviron-mentalvariables,andGeneOntologytermsfortranscriptomicdata.ComplexphenotypictraitsaredescribedusingfollowingtheEQVmodel[2].Web-servicesarealsodevelopedtoautomatequeriesandintegrateapplicationsovertheinternet.
Thisinformationsystemprovidesusefulresourcesforstudyinggenotype×environmentinter-actionsingrapevine,andaframeworkforheterogenousdatamanagement.
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POSTERS
Wheat field high throughput phenotyping: from concept to applicationAlexis Comar1, Philippe Burger1, Benoit de Solan2, Frédéric Baret1, Fabrice Daumard1, David Gouache2, Laurent Guerreiro2
1EMMAH,INRA,France 2ArvalisInstitutduvégétal,France
Infieldphenotypingismandatorytoevaluatecultivarperformanceswithinrealisticconditions.Itiscomplementarytocontrolledconditionsthatfocusonparticularcombinationsofstresses.Functionaltraitsidentificationrequiresmonitoringcanopykeystatevariablesalongthegrowthcycle.Duethelargenumberofmicroplotsconsidered(around1000)andthefrequencyofmeas-urements,highthroughputnon-destructivemethodsaremandatory.Tomatchtheserequirements,frequentmeasurementsofstatevariableaccessiblefromcloserangeremotesensingtechniquessuchasleafareaindexandbiochemicalcompositionvariablesaretargeted.Howeverestimatesofthesevariablesneedtobeindependentfromenvironmentalconditionsandthefirstordereffectsduetocanopystructure.Thisstudydescribesaframeworkthatincludesthemeasurementsystemandtheassociatedinterpretationtechniquesdesignedforwheatstandscharacterization.
Measurementsareautomaticallyacquiredfromatractorbornehyper-spectralspectrometersandcameraslookingattwozenithangles.Methodshavebeendevelopedtoaccessphysicalquantitiesincludingbi-directionalreflectancefactorandgapfractions.TheexperimentwasconductednearToulousein2010and2011,including6cultivarsconductedunder3nitrogentreatmentsandsow-ing densities.
Resultsshowthatthecombinationofgapfractionatbothnadirandobliqueviewinganglesenablestoclassifystandsaccordingtotheirleafinclination.Thisfirststepismandatorytoaccountfortheimpactofcanopystructureontheestimationofthetargetedbiophysicalvariables.Twomaingroupswereidentifiedcorrespondingtoerectophileandplanophilecultivars.Foreachofthosecultivargroups,leafareaindexestimationperformancesarecomparedbetweengapfractionsandmultispectralindices(mcari2,ndvi)basedmethods.AbsorbednitrogenisalsoestimatedviaspectralindicesdedicatedtoChlorophyllcontentestimatessuchasMTCIorTCARI/OSAVI.Thepertinenceofeachofthesespectralindiceswasassessedthroughconfrontationwithdestructivegroundmeasurements,consistencywithexpecteddifferencesbetweentreatmentsandtemporalconsistency.Finally,functionaltraitsweretentativelyextractedfromthedynamicsoftheselectedindicators.Howeverthefrequencyofoneacquisitionperweekasachievedwithintheseexperi-mentswasnotsufficienttoaccuratelycharacterizethesefunctionaltraits.Ahigherfrequencywouldrequireafullyautomatedsystem.Further,improvementsareexpectedfromexplicit3Dstructural-functionalmodelsthatwouldallowmoresynergisticwaytointerpretthemulti-sensorsdataandthereforeaccessinmorereliablewayfunctionaltraits.
References[1]Baret,Frédéric;deSolan,Benoit;Lopez-Lozano,Raul;Ma,Kai;Weiss,Marie(2010)GAIestimatesofrowcropsfromdownwardlookingdigitalphotostakenperpendiculartorowsat57.5Adegreezenithangle:Theoreticalconsid-erationsbasedon3DarchitecturemodelsandapplicationtowheatcropsAgriculturalandForestMeteorology 1393 – 1401
POSTERS
Jülich, 5. – 7. September 2011 53
Screening root morphological plasticity to water limitation among different vine rootstocks genotypes using 2D digital images from rhizotronsCedric Dumont, Thierry Robert, Guillaume Pacreau, Nathalie Ollat, Philippe Vivin
UMREcophysiologieetGénomiqueFonctionnelledelaVigne,ISVVBordeaux,France
Rootsystemarchitecture(RSA)isbelievedtobeimportantforrootstockadaptationtowaterlimitation,butgeneticinformationaboutthistraitisstillrelativelyscarceforgrapevine.Numerousapproacheshavebeendevelopedfornon-destructiveobservationsofrootarchitecturewiththesupportofadvancedopticalrecordingtechniques.Theobjectivesofthisstudyweretherefore(i)todesignandconstructaphenotypingsysteminrhizotronforquantifyinginsitufinerootmorphologyandgrowthatthewholeplantlevelwithoutaffectingshootdevelopment,and(ii)toexaminegeneticintrinsicvariationsinroottraitsamongvinerootstockgenotypessubmittedtodecreasingsoilwatercontent.Thissystemwasevaluatedthroughapreliminarytrialwithtworootstockgenotypes(RipariaGloiredeMontpellierand110Richter)grafteduponthesamescion(Cabernet-Sauvignon)andsubmittedtothreelevelsofPEG-inducedosmoticstress.Rootdevelopmentwasmonitoredtwiceaweekovera21-dperiod.RootscansusingWinRhizosoftwareallowedquantificationofalargenumberofrootmorphologicalparameterslikerootlengthindiameterclasses,surfacearea,numberofroottips.Significantdifferencesinspatialandtemporalrootmorphologywereobservedamongtestedgenotypesandtreatments,particularlyfortotalrootlengthandelongationrate,aswellasrelativeproportioninmainandlateralroots.Resultsdemonstratedthattherhizotronsystemwasefficientinscreeningroottraitsforyoungvines,allowingforrapidmeasurementsoftwo-dimensionalrootmorphologyovertimewithminimaldisturbancetowholeplantgrowth.
54 2ndInternationalPlantPhenotypingSymposium2011
POSTERS
Reverse genetics screen: a focussed approach to discriminate phenotypesJulia Engelhorn, Julia Reimer, Xue Dong, Ulrike Göbel, Franziska Turck
PlantDevelopmentalBiology,MaxPlanckInstituteforplantbreeding,Germany
PolycombGroup(PcG)proteinsmediategenerepressionbytri-methylationoflysine27ofhistone3(H3K27me3).ThisisessentialfornormalplantdevelopmentandmanyH3K27me3 decoratedgenesencodedevelopmentalregulatorsinArabidopsisthaliana.DevelopmentalfunctionsareparticularlyoverrepresentedintissuespecificsubsetsofH3K27me3 targets.
BasedonChIP-on-chipdatawedesignedareversegeneticsscreentodiscovernewgenesinvolvedinplantdevelopment.Weidentified105PcGtargetsgenesspecificallyexpressedintheshootapexandfloralorgans,whichareparticularlyenrichedforshootdevelopmentalfunctions.Byanalysingtheunknowngenesinthisgroup,wecouldidentifyfourteenputa-tiveDevelopmentrelatedPcGtargetsintheApex(DPAs).T-DNAinsertionlinesoftheDPAsshowedalterationinoverallplantsize,floweringtime,flowerformation,numberofdistinctfloralorgansandalsoinleavemarginserration.Atleastforone(DPA4)ourresultssuggestaninvolvementinauxin-mediatedsignaling.
Takentogetherdevelopmentalfunctionsofsofaruncharacterisedgenescanbedetectedinafocusedapproachwithareversegeneticsscreen.Asthephenotypicaldescriptionofmuta-tionsofputativecandidategenesisthestartingpointonlytheexactplacementofthecandi-dategeneinapathwayneedstobecharacterised.
POSTERS
Jülich, 5. – 7. September 2011 55
Automated analysis of crop plant images with the software IAP („Integrated Analysis Platform“)Alexander Entzian, Jean-Michel Pape, Christian Klukas
MolecularGAenuettoicms,aIPteKd-aGnataelryssleibseonf,Gcerormpapnlyantimages
Thefieldofhigh-throughputplantphenotypinghasexperiencedasubstantialincreaseofinter-estoverrecentyearsintheprivateandpublicsector.Onefocusistheinterpretationofplantdescriptorsbasedonvisiblelightimages(plantheight,width,digitalbiomass,etc.)anotherfocusistheanalysisofthedescriptorsderivedfromnear-infraredandfluorescenceimages.
AmongtheaimofourworkattheIPKisthedevelopmentofananalysismethodwhichisrobustagainstfluctuatinglightingconditions.Thenewalgorithmsareintegratedinthenewlydevelopedinformationsystem“IntegratedAnalysisPlatform“(IAP).
Thedynamicimageanalysispipelineispresentedwithoneexampleformaizeplants.Firstphaseistheanalysisofforegroundandbackgroundseparation.Thesecondphaseisthe determinationofdiverseplantphenotypiccharacteristics.Theresultisafullyautomatedanalysisusingallthreeimagetypes(RGB,FLUO,NIR)withouttheneedforextensivecalibra-tions.
56 2ndInternationalPlantPhenotypingSymposium2011
POSTERS
Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivarsKlaus Erdle, Bodo Mistele, Urs Schmidhalter
DepartmentofPlantSciences,ChairofPlantNutrition,Germany
Severalsensorsystemsareavailableforground-basedremotesensingincrops.Vegetation indicesofmultipleactiveandpassivesensorshaveseldombeencomparedindeterminingplanthealth.Thisstudywasaimedtocompareactiveandpassivesensingsystemsinterms oftheirabilitytorecognizeagronomicparameters.Onebi-directionalpassiveradiometer(BDR)andthreeactivesensors(CropCircle,GreenSeeker,andanactiveflashsensor(AFS))weretestedfortheirabilitytoassesssixdestructivelydeterminedcropparameters.Overtwoyears,sevenwheat(TriticumaestivumL.)cultivarsweregrownwithvaryingnitrogensupplies.Atthreedevelopmentalstages,thecropreflectancewasrecordedandsensorspecificindiceswerecalculatedandrelatedtoNlevelsandthecropparameters,freshweight,dryweight, drymattercontent,Ncontent,abovegroundNuptake,andthenitrogennutritionindex. Themajorityofthetestedindicesshowedhighr2-valueswhencorrelatedwiththecropparameters.However,theaccuracyofdiscriminatingtheinfluenceofvaryingNlevelsdifferedbetweensensors,growingseasonsanddevelopmentalstage.Visible-andredlight-basedindices,suchastheNDVIorsimpleratio(R780/R670),tendedtosaturatewithincreasingcropstanddensity.ThebestrelationshipswerefoundforN-relatedbiomassparameterswithr2-valuesofupto0.96.Thenearinfrared-basedindexR760/R730wasthemostpowerfulandtemporarilystableindexindicatingtheNstatusofwheat.ThisindexwasdeliveredbytheBDR,CropCircle,andAFS.Activespectralremotesensingismoreflexibleintermsoftimelinessandilluminationconditions,buttodate,itisboundtoalimitednumberofindices.Atpresent,thebroadspectralinformationfrombi-directionalpassivesensorsoffersenhancedoptionsforthefuturedevelopmentofcroporcultivar-specificalgorithms.
POSTERS
Jülich, 5. – 7. September 2011 57
Root enhancement for crop improvementMarc Faget1, Achim Walter2, Kerstin A. Naget1, Gregor Huber1, Ulrich Schurr1
1InstituteofBio-andGeosciences,IBG-2:PlantSciences,ForschungszentrumJülichGmbH, Germany 2Agronomyandplantbreeding,ETH,Switzerland
Withtheprognosticsofclimatechanges,increasingpopulationsizeandlackofagriculturalland,theneedtodevelopnewplantvarietieswithimproveddroughttoleranceandimproveuseoffertilizerisurgent.Optimizedrootsystemarchitecture(RSA)isrelevantinorderto overcomeyieldlimitationsincropplantscausedbyshortagesinwaterornutrients.Theobjec-tiveoftheROOTprojectwithinthePLANTKBBE2009istoexploreanddevelopanalternativeapproachforrootenhancementbyunderstandingtheregulationofRSAbycytokinin(Werneretal.2001).AnimagingbasedapproachonArabidopsisandBarleycytokininmutantswillbedevelopedtoelucidaterootgrowthtraitsathighthroughputandevaluatetheirrelevanceforfieldexperiments.Theroleofnitrateandphosphorusindeterminingrootgrowthandarchi-tecturewillbeanalyzedinthisregard.Differenttechnologieswillbeappliedasdigitalimagesequenceprocessingmethods(GROWMAPRoot,Nageletal.2006),tomography,MRI(Jahnkeetal.2009)andsimulationmethodstostudyandmodelinteractionsbetweentheRSAandthechangingenvironment.
References[1]Werner,Tomáš;Motyka,Václav;Strnad,Miroslav;Schmülling,Thomas(2001)Regulationofplantgrowthby cytokininsProc.Natl.Acad.Sci.10487–10492[2]Nagel,KerstinA.;Schurr,Ulrich;Walter,Achim(2006)DynamicsofrootgrowthstimulationinNicotianatabacuminincreasinglightintensityPlantCellEnviron.1936–1945[3]Jahnke,Siegfried;Menzel,MarionI.;VanDusschoten,Dagmar;Roeb,GerhardW.;Bühler,Jonas;Minwuyelet,Senay;PeterBlümler,Peter;Temperton,VickyM.;Hombach,Thomas;Streun,Matthias;Beer,Simone;Khodaverdi,Maryam;Ziemons,Karl;Coenen,HeinzH.;Schurr,Ulrich(2009)CombinedMRI-PETdissectsdynamicchangesinplantstructuresandfunctionsThePlantJournal.634–644
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POSTERS
The effect of salinity on some agronomical and physiological traits in Medicago truncatulaMaryam Foroozanfar, Mohammad Etemadi-Shalamzari, Ahmad Sarrafi, Hamid Hatami-Maleki, Laurent Gentzbittel
ECOLAB–INPENSAT,France
Salinityisoneofthemajorstressesthatlimitcropproductionworldwide.Legumescontributesignificantlytohumanandanimaldietsduetotheirhighproteincontent.Medicagotruncatulaiswidelyusedasamodelplantforlegumegeneticsandgenomics.Inthisstudy,sixgenotypesofM.truncatula(A17,TN1.11,F83005.5,TN1.21,DZA315.16,A20)weresubjectedtosalinitylevels(control,30,60,90,120and150mMNaCl)for37daysinmediumwhichfilledwithmixofperliteandsand(3:1V:Vratio)toinvestigatetheoptimumNaCltreatmentandexplor-ingthepotentialtolerancemechanismsortraits.MaximumquantumyieldofphotosystemII(Fv/Fm),maximumfluorescenceofdark-adaptedleaves(Fm),chlorophyllcontentandlengthofrootandshootwereaffectedbysalinity.Resultsshowedthatthebestconcentrationtofinddifferencesbetweenallgenotypeswas120mMNacl.Themaineffectoflineswassignifi-cantforshootandrootfreshweight,shootsandrootdryweight,lengthofshoot,maximumquantumyieldofphotosystemII(Fv/Fm),maximumfluorescenceofdark-adaptedleaves(Fm),minimumfluorescenceofdark-adaptedleaves(F0)andchlorophyllcontent.Itwasnotsignifi-cant for root length.
References[1]Stepien,Piotr;Johnson,GilesN.(2009)CONTRASTINGRESPONSESOFPHOTOSYNTHESISTOSALTSTRESSINTHEGLYCOPHYTEARABIDOPSISANDTHEHALOPHYTETHELLUNGIELLA:ROLEOFTHEPLASTIDTERMINALOXIDASEASANALTERNATIVEELECTRONSINK.PLANTPHYSIOLOGY149:1154–1165[2]Maury,Pierre(1996)PHOTOCHEMICALRESPONSETODROUGHTACCLIMATIONINTWOSUNFLOWER GENOTYPESPHYSIOLPLANT57–66[3]Arraouadi,Soumaya;Chardon,Fabien;Huguet,Thierry;Badri,Mounawer(2010)QTLsmappingofmorphologicaltraitsrelatedtosalttoleranceinMedicagotruncatulaActaPhysiolPlantPublishedonline
POSTERS
Jülich, 5. – 7. September 2011 59
Applications of computed tomography to plant phenotypingChristoph Funk, Markus Firsching, Frank Sukowski, Norman Uhlmann
DevelopmentCenterX-RayTechnology,FraunhoferInstituteforIntegratedCircuits,Germany
Theuseofstateoftheartx-raycomputedtomography(CT)methodsenablesnewpossibilitiesforplantphenotypinginthesproutandrootarea.IndustrialCTallowsthegenerationof acomplete3Dvolumedatasetoftheobject.Thisallowsthevisualizationandvirtualanalysisofhiddenstructureslikerootsortubersinsubstrateoradetailedstructuralanalysisofsproutfeatureslikecaulis,leavesandbranches.
TheprincipleofCTisthegenerationofmultipleprojectionsoftheobjectbypenetratingitwithx-rays.Eachprojectionistakenfromadifferentangleduetotherotationoftheobject.Fromtheresultingprojectionsathree-dimensionalCTvolumedatasetcanbegenerated.Wepresentmethodsandresultsoftwoapplications.
FirstapplicationisthemeasurementsetupanduseofCTforanevaluationofthegrowthofpotatotubersoveracertainperiodoftime.Theanalysiscouldbedonewithoutdisturbingtheplantsandexcavatingthetubersforthedatageneration.Theresultsoftheevaluation,thepossibilities are presented.
DependingontheapplicationandthegeometricaccessspecialCTacquisitionandimageevaluationmethodshavetobedevelopedandused.Ahighquality3Ddatasetrequiresafully3Daccesstotheobject.Withamethodcalledtomosynthesislargeplanarobjects,e.g.fromtherootarea,canbeanalyzed.Theadvantageofthismethodisthatfewprojectionsaresuffi-cienttorealizeacceptablevolumedatasetquality..Aninterestingapplicationoftomosynthesisisthedetectionofasparagusenablinganautomatedharvesting.Forharvestingitisimportanttoknowtheexactposition,lengthandorientationoftheasparagus,whichcanbedeterminedwithtomosynthesisonthefield.Wepresenttheprojectandfirstresults.
References[1]Ferreira,StephanusJ;Senning,Melanie;Sonnewald,Sophia;Keßling,Petra-Maria;Goldstein,Ralf;Sonnewald, Uwe(2010)ComparativetranscriptomeanalysiscoupledtoX-rayCTrevealssucrosesupplyandgrowthvelocityasmajordeterminantsofpotatotuberstarchbiosynthesis.BMCGenomics1193
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POSTERS
Two non-destructive tools for field phenotypic analysis of grapevine: Ground Normalized Difference Vegetation Index and soil resistivity measurementsJean-Pascal Goutouly1, Philippe Vivin1, Nathalie Ollat1, Serge Delrot2
1UMREcophysiologyandFunctionalGenomicsofGrapevine,INRA–ISVV,France 2UMREcophysiologyandFunctionalGenomicsofGrapevine,Univ.Bordeaux–ISVV,France
Vineleafareaisanimportantagronomicalparameterasitisrelatedtophotosyntheticcapacity,wateruse,andgrapemicroclimate.Duringthelastdecade,researchinairborneandsatelliteremotesensinghasallowedtoshowthatamultispectralindexofvegetation,computedfrommeasurementsofreflectances(redandnearinfrared),the“NormalisedDifferenceVegetationIndex”(NDVI),iswellcorrelatedtothe“LeafAreaIndex”(leafareaperunitofground)ofthevine.Nevertheless,thesemethodsofdataacquisitionandprocessingareratherconstrainingandcomplex.Recently,N-TechIndustriesdevelopedagroundsensingapparatus,theGreen-SeekerTM,whichmeasurestheNDVI.Inthisstudy,theGreenSeekerTM,activesensor,isabletooperateindependentlyoftheclimaticconditionswhenascreenisused.TheNDVIdeliveredbytheGreenSeekerTMismainlysensitivetothevariationsofporosityofthefoliage.Itcanbeusedtocarryoutafollow-upofthefoliargrowthofthevine.Itgivesthepossibilitytochartrelativevariationsofvigoratanintraplotlevel,enablingaccesstorelevantinformationforfieldphenotypicanalysis.Soilresistivity(tomography),whichisagoodwaytoevaluatesoilwatercontent,maybemeasure/estimatedduringthepreviouswinterandatseveralstagesalongthegrowingcycleusingaSYSCALR2equipment(IrisInstrument).Parallel2-Ddipole-dipolesectionsareorientatedinthelongdirectionofthestudiedrow.Thesesectionsallowtodescribetheverticalvariationsoftheelectricalresistivityandhelptospecifythe3Dgeologicalsketchdowntothreemeters.Highresolutiontomographyshowsmoisturevariationatthevinestockscaleforvariousgenotypes.
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Jülich, 5. – 7. September 2011 61
Comparing plant temperature measured by thermal imaging, IR thermometry and thermistor to assess differences in stress treatments and wheat cultivarsHarald Hackl, Bodo Mistele, Peter Baresel, Yuncai Hu, Urs Schmidhalter
TUMunich,Germany
Thetemperatureoftheleavesandcanopiesofplantshaslongbeenrecognisedasanindi-catorofplantwaterstressandcanbeassessedbydifferenttechniques;thesetechniques,however,haveseldombeencompared.Inthisstudy,therefore,wecomparedhigh-resolutionthermography,infraredthermometry,anddirectleafmeasurementswithathermistortorelatethecanopyandleafsurfacetemperaturestoleafwaterpotentialandbiomassparameters. Thespecificgoalwastotestthediscriminativepowerofthesetechniquestodifferentiatestresstreatmentsandcultivareffects.Thetreatmentsincludedtwocultivarssubjectedtocon-trol,drought,saltandcombinedsaltanddroughtinlargecontainerbasedexperimentstomim-icfieldconditions.DifferenceswithinthetreatmentswerebestascertainedbythermographyandIRthermometry,withthedifferencesvaryingbetween1–9°C,whereastheleafsurfacetemperaturesmeasuredwiththethermistorvariedonlywithabout1–2°C.Incontrast,thecultivardifferencesweremuchsmaller,rangingbetween0–2°Cforallappliedtechniques,withsignificantdifferencesfoundinsalttolerance-relatedparameters.Baresoilinfluencedthethermalimagesandthisinfluencefurtherdependedonthegrowthstageandthedensityofthecropstand.Thisinfluencewasparticularlyprominentatearlygrowthstagesandmarkedlyinfluencedthethermalinformation,witherrorsbeingaslargeas20–30%,whenconsideringtheobserveddifferencesamongthetreatments,whereassucherrorsweresmall(1–5%)atlatergrowthstagesandatahighersoilcoverage.UsingthermographyandIRthermometry,highlysignificantrelationshipswereestablishedbetweenthecanopytemperatureandtheabove-groundfreshweightandgraindryweight.Evencloserrelationshipswereobservedwiththeleafwaterpotential(R²-valuesreachingupto0.98**)asadirectandimmediateindicatoroftheprevailingstress.Overall,abetterdiscriminationamongthetreatmentsandcultivarswasobtainedwiththermographyandIRthermometrycomparedtothermistormeasurementsinthiswork.Inaddition,cautionisadvisedwhenthermistormeasurementsareusedincon-junctionwithcuvette-basedmeasurementsofstomatalconductance.
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POSTERS
A novel system for controlled phenotyping of drought stress tolerance in oilseed rapeMarie Hohmann, Benjamin Wittkop, Wolfgang Friedt, Rod Snowdon
DepartmentofPlantBreeding,JustusLiebigUniversity,Germany
CurrentexpansionofoilseedrapeproductionintoEasternEuropeanregionswithlowrainfall,coupledwiththeincreasingoccurrenceofextremeclimaticevents–includingdrought–dueto global climate change, confront breeders with the emerging problem of selecting for ad-aptationtowaterstressordroughtconditions.Inthepastconventionalpottrialswereoftenusedtocompareplantperformanceunderwater-stressandnon-stressconditions,howeverresultsofsuchtrialscouldrarelybecorrelatedtotheperformanceofplantsundernaturalfieldconditions.Onelogicalexplanationforthisisthestrongrestrictionofrootgrowth,akeyfactorinwaterstresstolerance,inpottrials.Ontheotherhand,trialsinrainoutsheltersaremoresimilartofieldconditions,howeveritcanbeverydifficulttoaccuratelycontroltheexactquantityofwateravailabletotheplantroots.
Inanefforttoobtaindetaileddataaboutwaterstresstoleranceundercontrolledconditionsthatneverthelessascloselyaspossibleresembleafieldsituation,wearetestingalargescalecontainersysteminwhichplantsaregrowninarain-outshelterin120litre,90cmdeepcontainers.Thecontainersarefilledwith50cmofsandysubsoiland40cmofsandytopsoilfromawaterstress-pronefieldlocation.Byweighingthecontainersregularlywithahydraulicmeasuringsystemitispossibletoexactlycontrolthewatercapacity(WC)ofthesoil.Datawerecollectedonchlorophyllcontent,leafwatercontent,relativeplantheight,rootmass,podandseedproductionandseedqualityunderwaterstresscomparedtonon-stresstreatments.Inapreliminarystudy,20diversewinteroilseedvarietiesthatshowstrongdifferencesintheirreactionstodroughtstressinthefieldwerephenotypedinthecontainersundertwodifferentwaterregimes(60%WCcontrol,30%WCstressvariant,stressappliedatbeginningofflower-ing).Thesamegenotypesweresimultaneouslygrowninirrigatedfieldtrialsatdrought-stresslocations.Ontheonehandthedatacollectedwillbeusedtoselectextremegenotypesforcomprehensiveanalysisofrootphysiologyanditsassociationtodroughttoleranceinoilseedrape.Ontheotherhand,throughdetailedphenotypingofmorphologicalandphysiologicaltraitsinthecontainertrial,wehopetoidentifysimpleindicatortraitscorrelatedtofieldperfor-mancethatcanbeusedtoselectforimprovedwaterstresstoleranceinwinteroilseedrape.
ThisworkispartoftheInnovationProgram“BreedingofClimate-AdaptedCrops”funded bytheGermanMinistryofConsumerProtection,NutritionandAgricultureviatheFederalInstituteofAgricultureandNutrition(BLE,Bonn).TheworkissupportedbyrapeseedbreedingcompanieswithintheSocietyforthePromotionofPrivateGermanPlantBreeding(GFPe.V.).
POSTERS
Jülich, 5. – 7. September 2011 63
Automated phenotyping for functional genomics and global change researchMarcus Jansen, Silvia Braun, Georg Dreissen, Andreas Fischbach, Kathrin Heinz, Alexander Putz, Fabio Fiorani
IBG-2,ForscThiutlnegszentrumJülichGmbH,Germany
Linkinggeneticpropertiesandenvironmentalfactorstoplantphenotypesinaquantitativemannerisanimportantissueinplantresearch.Gene-environmentinteractionsneedtobeanalysedinfunctionalgenomicsaswellasresearchonstresstoleranceandresourceuseefficiency.
Addressingtheseissues,wehavesetupasystemthatcombinesimagingPAMfluorometryandimageprocessinganalysesofplantsizeandarchitecturewithautomatedtransportationsystems.GROWSCREENFLUOROacquiresasetofphenotypicdataongrowth,morphology,andphotosynthesisof90to100Arabidopsisthalianaplantsperhour.Wehavecombinedthissystemwithacomputer-controlledtransportationrobotforplanttraysinsideaprogramma-bleclimatechamber.Thissetupenhancesplantthroughput,allowsrepeatedmeasurementsandmakesphenotypingindependentfrommanualhandling.Moreover,therobotenablesprogrammedpositionchangesoftheplanttrays,i.e.trayscanmigratethroughouttheshelfpositionsthuspositioneffectsareminimized.Therobotmoveseachplanttrayindependently,allowinganindividualprogramofmovementsandmeasurementsforalltrays.
UsingGROWSCREENFLUOROwegeneratedexemplarydataonmodulationsofA.thalianaphenotypesbygenomicdifferencesandbydifferentenvironmentalfactors,suchassubstrate,irrigation,illumination,orchemicaltreatment.Thesedatademonstratetheapplicabilityofthesensorsystemforthedetectionandquantificationofphenotypicdifferencesbetweenindividualplantsandplantpopulations.Timecoursesofphenotypicdatafacilitateanalysingthedynamicsthatunderliethedevelopmentofgivenproperties.
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POSTERS
Influence of external effects on the accuracy of active canopy sensorsSebastian Kipp, Bodo Mistele, Urs Schmidhalter
DepartmentofPlantSciences,ChairofPlantNutrition,TechnischeUniverstätMünchen, Germany
Forlandusemanagement,agriculture,andcropmanagementspectralremotesensingiswidelyused.Ground-basedsensingisparticularlyadvantageousallowingtodirectlylinkonsitespectralinformationwithagronomicalgorithms.Sensorsarenowadaysmostfrequentlyusedinsite-specificorientedapplicationsoffertilizers.Recentresearchsuggestsasfurtherinterestingfieldenhancedhigh-throughputphenotypinginbreeding.Forsuchpurposespassiveaswellasactivesensorscanbeused.Activesensorsareequippedwiththeirownlightsource,workingindependentlyoftheambientlightconditions.
Bynowitisunclearhowexternalfactorsinfluencetheaccuracyofactivesensors.Althoughmanufacturersindicatesensors’performancebeingindependentofambientlightconditions,thisattributewastestedaswellforthreedifferentactivesensors(NtechGreenSeekerRT100,HollandScientificCropCircleACS470,YARAN-SensorALS)aswellastheperformanceof activesensorsunderchangingdevicetemperatureconditions.Withtheuseofactivesen-sorsinthefieldit´sinevitablethatsensorsareexposedtovariousambientenvironmentalconditions.Especiallyradiationandairtemperaturemaytovaryingdegreeaffectthedevicetemperatureofthesensoritself.
Inthisinvestigationitcouldbeshownthatthedevicetemperatureofthethreedifferentactivesensorshasaneffectontheaccuracyofthesensors’output.However,varyinglightcondi-tionswereevaluatedasanotaffectingtheperformance.Activesensorsshowedthesameperformanceunderdarkandlightconditions.Adependencyofactivesensorsontheir distancetothecroptargetbecameapparent.Accuratemeasuringdistancestothecrop canopiesweredeterminedthatenablestabilesensoroutputsduringmeasurementsof plants with different heights.
POSTERS
Jülich, 5. – 7. September 2011 65
Genetic variation for root developmental traits in Brassica napus seedlingsAysha Kiran1, Rod Snowdon2, Wolfgang Friedt1
1PlantBreeding,JustusLiebigUniversity,Giessen,Germany 2 PlantBreeding,JustusLiebigUniversity,Germany
Theimportanceofrootarchitectureinplantproductionstemsfromthefactthatmanysoilresourcesareunequallydistributed,oraresubjecttolocalizeddepletion,sothatthespatialarrangementoftherootsystemwillinlargemeasuredeterminetheabilityofaplanttoexploitthoseresources.Rootdevelopmentplaysasignificantroleinseedlingestablishmentandvigouraftergermination.Despitetheimportanceoftheroots,fewstudieshavesystematicallyinvestigatedtheextentofgeneticvariationforrootvigourandarchitectureinBrassicanapus.Inthisstudyweareinvestigatingrootdevelopmentaltraitsinaninvitrorhizotronsystemthatenablesustodigitalizedevelopmentalparametersinlargenumbersofgenotypesundercontrolledconditions.AlargeB.napusdiversitysetcomprisingmorethan500inbredlinesrepresentingwinter,springandsemi-wintertypeoilseed,fodder,vegetableandresynthesizedrapeseedisbeinganalyzed(ERANET-ASSYSTdiversityset)alongwiththesegregating,doubledhaploidwinteroilseedrapemappingpopulationfromthecross‘Express617’x‘V8’(ExV8-DH).Datafromprimaryandlateralrootlengthandnumberoflateralrootswillbeusedforas-sociationanalysisandquantitativetraitlocus(QTL)mappingusinggenome-wideSNPdata.Preliminaryresultsshowsignificantvariationamonggenotypesthatwillenablethegeneticmappingofresponsibleloci.IdentificationofgenomicsequenceregionslinkedtoQTLcontrol-lingvariationforroottraitsisafirststeptowardsmarker-assistedselectionforimprovedrootvigour,andcouldeventuallyleadtotheidentificationofgenesinvolvedinregulationofrootdevelopmentaltraits.Thisworkispartofthetri-nationalERANETPlantGenomicsproject“ ASSYST:Associativeexpressionandsystemsanalysisofcomplextraitsinoilseedrape/canola.”
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POSTERS
Phenotyping of competitive ability in winter wheat on the basis of steady-state chlorophyll fluorescence imaging, PAR transmittance and canopy reflectance sensorsKarel Klem
GlobalChangeResearchCenterASCR,v.v.i.,CzechRepublic
Thereisincreasinginterestinreducingtheuseofherbicidesinagriculturebecauseofgeneralconcernsabouttheirenvironmentalandhealthrisks.Oneofthepromisingalternativestoher-bicideuseisscreeningandbreedingofgenotypeswithtraitsrelatedtohighcompetitiveabilityagainst weeds.
Inthree-yearfieldexperimentsacollectionofmorphologicallydifferentwinterwheatgeno-types(16–19)weregrowninweedfreeandweedytreatmentsrandomizedinthreereplica-tions.Untilcanopyclosure,thecropdevelopmentandleafcoverdistributionwasperiodicallyevaluatedbysteady-statechlorophyllfluorescenceimagingusingthemobileversionofinstru-mentFluorCam(PSIBrno,CzechRepublic).Aftercanopyclosure,theimageswereanalyzedforintensityhistogramsasaparameterdescribingverticalleafcoverdistributionwithincanopy.Additionally,transmissionofPARthroughcanopyandcanopyreflectance(inred,red-edgeandNIRwavebands)wereusedtoestimatecompetitiveabilityinlatergrowthstages.Relativeyieldlossescausedbyweedswerecorrelatedwithindividualparametersobtainedfromchlorophyllfluorescenceimages,relativePARtransmissionandreflectanceindices.
Aclosecorrelationstorelativeyieldlosswerefoundoutforestimateddistributionofleafcover(acrossrows)attheendoftillering,verticalleafcoverdistributionattheendofstemelongation,relativePARtransmissionthroughcanopyandRed/NIRreflectanceratio.Thecor-relationcoefficientsofforindividualparametersdidnotexceedR=0.7.Usingartificialneuralnetworksasmultivariatemethodwithseveralinputparameters,thecorrelationbetweenpredictedyieldlossesandobservedvaluesincreasedtoR=0.95.
ThisworkwassupportedbytheprojectNAZVno.QI111A133andbytheEuropeanCommission(projectCzechGlobe–contractCZ.1.05/1.1.00/02.0073).
References[1]Klem,Karel;Spundova,Martina(2002)Comparisonofchlorophyllfluorescenceandwhole-plantbioassaysofisoproturonWeedResearch335–341
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Jülich, 5. – 7. September 2011 67
The European Ecotron of Montpellier, a researchEric Larmanou, Jacques Roy, Olivier Ravel, Christophe Escape, Clément Piel, Damien Landais, Sébastien Devidal, Gilbert Jacquier, Hélène Lemoine, Philippe Didier
EcotronEuropéendeMontpellier,UPS3248CNRS,Montferrier-sur-Lez,France
Athoroughanalysisofplantphenotypesandunderstandingofthecomplexinteractionofplantswiththeirenvironmentismadepossiblebyconfiningecosystemsinchambersandassociatingthecontrolofabroadrangeofenvironmentalconditionswithaccuratemeasure-mentsofphysiologicalprocesses.TheEuropeanEcotronofMontpellierprovides:i)simulationofvariousenvironmentalscenariosfromdataontemperature,waterconditionsandCO2,ii)comparisonoflevelsofseveralfactorswithaminimumof12unitsperplatform,iii)accuratemeasurementofthemainfluxesgeneratedbytheecosystem,andiv)determinationofmassbudgets.Withthreeplatformsatscalesrangingfrom30m3unitstoafewdm3,theEcotroncanfocusoncomplexecosystemaswellasonindividualplants.AdistinctivefeatureoftheEco-tronconsistsinprovidingonlinemeasurementsofphotosynthesis,respiration,transpiration,methaneandnitrousoxidereleaseandCO2 isotope ratios, i.e. 13C/12Cand18O/16O.Thesemeasurementsaresupplementedbynon-invasivemeasurements(spectralreflectance,etc.)orsoilandplantsampling.TheEcotronwillbeopentotheinternationalcommunitythroughcall for proposals.
TheEcotronisnotaphenotypingcentrebutsynergiesbetweenthetwotypesofcentresareworthtobedeveloped.TheEcotronwillprovideadeeperunderstandingofplant/environmentinteractions,whichcanthenbeintegratedintonewphenotypingprocedures.Withitson-linemeasurementsofarangeofphysiologicalprocesses,itcanalsoserveasatest/calibration oftheproxy-detectionsmethods/instrumentsusedinphenotyping.TheEcotroncanuse sensorsandmethoddevelopedbyphenotypingcentres.Inaddition,theEcotronandpheno-typingcentressharesimilarconcernsindevelopingnewinstrumentationandexploitinglarge,on-line fed databases.
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POSTERS
Aeroponic as a platform for high throughput phenotyping of root system architectureAleksander Ligeza, Xavier Draye
UCL–UniversitécatholiquedeLouvain,Belgium
Inthecontextofglobalclimatechange,itiscrucialtoimprovecroptolerancetoabioticstresses,inparticulardrought.Beinginvolvedinwaterandnutrientsuptake,rootsystemarchitectureislikelytobepartofplantstrategiestocopewithabioticstreses.Traditionalmethodsofrootphenotypingarecharacterizedbylowthroughputsorfailtoaddressthetemporaldynamicsofrootgrowth.Wepresentherearootphenotypingplatformbasedonaeroponics.Thisplatformreliesonaflexibleplantholdingsystemwhichhasbeentestedwithwheat,rice,barleyandmaize.Inthisplatform,wecangrowupto679foraperiodaround3weeks(rootlength~70cm).Plantsaredistributedin97blockscirculatingallday-long.Plantsareindividuallyimagedeverytwohours(shootandroots)usingaNIRcamera.ThesequenceofimagesisthenorganisedandanalysedusinginhousesoftwarebasedonJavaandImageJ.Interactiveimageanalysisallowstocapturetheangleofinitialroottrajectory(forsomeroots),theinsertionangleandgravitropicsetpointofyounglateralroots,thedynamicsofgrowthandthenumbers(ordensities)ofvariousroottypes.Basedonpriordata,wewillalsodiscussthevalidityofaeroponicsdataasindicatorsoffieldvariables.LinkingplatformandfielddatathroughmodellingandstatisticalanalysisisgoingonintheframeworkofalargescaleFP7fundedproject(DROPs).
References[1]Zhu,Jinming;Ingram,Paul;Benfey,Philip;Elich,Tedd(2011)Fromlabtofield,newapproachestophenotypingrootsystemarchitectureCurrentOpinioninPlantBiology14:310–317
POSTERS
Jülich, 5. – 7. September 2011 69
Medium-throughput phenotyping of individual L. perenne plants under field conditions: an easy and low-cost procedurePeter Lootens1, Tom Ruttink1, Antje Rohde1, Serge Carré2, Didier Combes2, Phillipe Barre2, Isabel Roldán-Ruiz1
1ILVO,Belgium 2INRA,France
AssociationandQTLmappingstudiesinagriculturalcropsrequirephenotypiccharacterizationoflarge,replicatedcollectionsofplants.Thephenotypingisdoneundergrowingconditionssimilartothoseinthefield.Wehavedevelopedlow-costimagecaptureandanalysisprocedurestocharacterizelargecollections(about2000individuals)ofL.perenneplants.L.perenne,animportantforagegrassoftemperateregions,canbeplantedinmonoculturesorinmixedstands(grazedormown).Biomassyieldandpersistenceareimportantbreedinggoals.
WedescribedthephenotypicdiversityofarchitecturalcharacteristicsofaL.perenneas-sociationmappingpopulation(includingwildaccessions,breedingmaterialandcommercialcultivars).Toestimategrowthandregrowthcapacity,weusedamowingregimethatsimulatedpastureexploitationforeachgenotypeattwolocations(Belgium,France)overtwoseasons.Usingparametersderivedfromtopandside-viewimages,wedescribedplantvolume,habitusandgeometryinwaysthatsinglemanualmeasurementsofplantheightordiameteralonecannot.Timeseriesateitherlowresolution(bi-monthlyintervalstocapturegroundcoveragepotential)orhighresolution(weeklyintervalstocaptureleafelongation),helpedusdesigndedicatedanalysisofgrowthdynamics.
Imageanalysisassessmentswerecomparedwithclassicalmanualmeasurementssuchasplantheight,tillernumberandbiomassyield.Theimagesledustohighlyinformativepara-metersfordescribingplantarchitectureandgrowthpotential.Wediscusshowweovercometechnicalproblemsoftakingimagesundernon-standardizedconditions,theimage-analysisproceduresandthecorrelationbetweenextractedparametersandmanualmeasurements.
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POSTERS
RooTrak: Recovering Root Architecture Traits in Soil from X-ray Micro Computed Tomography DataStefan Mairhofer, Susan Zappala, Saoirse Tracy, Craig Sturrock, Malcolm Bennett, Sacha Mooney, Tony Pridmore
CentreforPlantIntegrativeBiology,UniversityofNottingham,UnitedKingdom
Plantsarefirmlyanchoredinsoilthroughouttheirlifespanandrelyontheirrootsystemtoacquirewaterandnutrients.Inreturn,theyhaveasignificantimpactonthesurroundingsoil’sphysicalandbio-chemicalproperties.Studyingtherichrelationshipbetweenplantrootsandtheirlocalenvironmentisachallengingtask,nottheleastbecausesoilisopaque.X-raymicroComputedTomography(μCT)isavaluabletoolfornon-destructivevisualisationofplantrootsystemswithintheirsoilenvironment.However,thereremainsalackofsuitablemethodsfortheanalysisoftheresultingdensitydata.AkeyobstaclehasbeenthesimilarXrayattenu-ationsofplantrootsandtheorganicmatterinsoil,alongwiththevariationsinattenuationcausedbywaterretainedinsoilpores.Togetherthesehavemadetheautomaticextraction ofrootsverydifficult.
WeviewvolumetricμCTdatasetsassequencesofimagesthroughwhichrootsectionsappeartomove,andadoptanobjecttrackingapproachtotheextractionofrootsfromtheirsurround-ings.Theadvantageofthisstrategyisthatthedataisanalysedinatop-downfashion:the trackerbuildsamodeloftheappearanceofrootmaterialandmatchesittothedata.Thisavoidstheerroraccumulationproblemscommonlyexperiencedbybottom-upapproaches.
Ourtechniqueisbasedonthelevelsetmethod(OsherandSethian1988)anduseslocalmodelsofthedistributionofattenuationvaluesobservedwithinrootsectionstoidentifyrootmaterialinsubsequentimages.Distinctappearancemodelsmaybeusedtotrackdifferentrootbranches,andtheappearancemodelusedtotrackagivenbranchmayvaryassegmenta-tionproceeds.ThishighdegreeofflexibilityallowsRooTraktosuccessfullydistinguishrootsfromothermaterialsofsimilardensity.Theresultingvolumetricdescriptionsofrootsystemarchitecturecanbefurtheranalysedtoprovideestimatesofkeytraits.
TheproposedmethodhasbeentestedonscansofMaize(ZeamaysL,Fig.1),Wheat(TriticumL)andTomato(SolanumlycopersicumL)growninsand,loamysand,andclaysoil.Resultsconfirmthesuitabilityofourstrategyandshowthatdescriptionsofbothmonocotanddicotrootsystemscanbesuccessfullyextractedfromtheirsurroundingsoilenvironment.
References[1]Mairhofer,Stefan;Zappala,Susan;Tracy,Saoirse;Sturrock,Craig;Bennett,Malcolm;Mooney,Sacha;Pridmore,Tony(UnderReview)Automatedrecoveryof3DplantrootarchitectureinsoilfromX-rayMicroComputedTomographyusingobjecttrackingNatureMethodsUnderReview
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Jülich, 5. – 7. September 2011 71
Light Sheet-based Fluorescence Microscopy (LSFM) allows long term imaging of Arabidopsis root growth at the organ, cellular and sub-cellular level in close-to- natural growth conditionsAlexis Maizel1, Daniel von Wangenheim2, Ernst HK Stelzer2
1DepartmentofStemCellBiology,CenterforOrganismalStudiesUniversityofHeidelberg, Germany 2FrankfurtInstituteforMolecularLifeSciences,JohannWolfgangGoethe-Universität FrankfurtamMain,Germany
Plantphenotypingatthecellularlevelwithhighspatialandtemporalresolutionrequires noninvasiveandviableimagingmethods.Inconventionalandconfocalmicroscopyplants sufferfrommechanicalstress,horizontalpositioningandexcessiveilluminationintensities.Wheneverasingleplaneofathree-dimensionalstackofimagesisobserved,theentirespeci-menisilluminated(Verveer2007).Therefore,wesuggesttheuseofthinlightsheets,whicharefedintothespecimenfromthesideandwhichoverlapwiththefocalplaneofawide-fieldfluorescencemicroscope(Stelzer1994;Huisken2004).Lightsheet-basedfluorescencemicroscopy(LSFM)exposesaplantto200timeslessenergythanaconventionalandto5,000timeslessenergythanaconfocalfluorescencemicroscope(forrationaleseeKeller2008).Westudythedynamicsofplantgrowthatorgan,cellularandsub-cellularlevelsoverperiodsoftime,rangingfromtensofsecondstofourdays.Duringtherecordingprocesstheplantcon-tinuestogrowinanuprightpositionwithitsleavesintheairanditsrootinthemediumwhileaperfusionsystemprovidesfresh,temperatureandgasconcentrationcontrolledmedium.Theleavesareilluminatedwithastandardlaboratorylightsourceinordertoensurephysiologicalgrowthconditions.WithLSFMweareabletoquantifythedevelopmentoflateralrootprimor-diaandthediurnalgrowthrhythmoflateralroots(Maizeletal.,acceptedforpublication).WeapplyLSFMathigherspatialandtemporalresolutionbyrecordingcelldivisionsandmove-mentsofsingleendosomesinlivegrowingrootsamples.OnamoremacroscopiclevelLSFMincombinationwithmultiple-viewimaging(Verveer2007,Swoger2007)isusedtogeneratehigh-resolutionthree-dimensionalmorphometricgenericdatasetsofarbitraryphenotypes.
References[1]Maizel,Alexis;vonWangenheim,Daniel;Federici,Fernán;Haseloff,Jim;Stelzer,ErnstHK(2011)Highresolution,liveimagingofplantgrowthinnearphysiologicalbrightconditionsusinglightsheetfluorescencemicroscopyPlantJournalinpress,acceptedforpublication
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POSTERS
Data integration within bioinformatics. The Jovian Project – A solution to integrate various data resources at The Plant AcceleratorBogdan Masznicz, Jianfeng Li, Helli Meinecke, Bettina Berger
ThePlantAccelerator,UniversityofAdelaide,Australia
ThePlantAcceleratoroffersstate-of-the-artplantphenotypingtoolsandservicestohelpacademicandcommercialplantscientistsunderstandandrelatetheperformanceofplantstotheirgeneticmake-up.
ThePlantAcceleratorisresponsibleformanagingongoingdatastorage,datamaintenance,andtheaccessibilityofdatageneratedbytheusersofthefacility.Inordertoachievethis,wehaveestablishedspecialdatamanagementrulesandhaveimplementedsophisticatedsoftwaresolutions(theJovianProject)tointegrateandcoordinateourdatamanagementactivities.
TheJovianProjectintegratesfourareasofoursoftwareactivities:–LemnaTecSystem(images,analysisdataandwateringinformation),–TresDataSuite(projectinformation,workflow,customerrelationshipmanagement),–BuildingManagementSystem(temperature,humidity,lighting),–GreenTools(dataanalysistoolintegratedwiththeLemnaTecdatabase)
TheresourcesintegratedintotheJovianProjectarealsothesourceofknowledgethatsupportotherplatforms,whichpublishdatageneratedfromtheuseofourfacilityoncereleasedforpublication,i.e.ANDS(AustralianNationalDataService),PODD(ThePhenomicsOntologyDrivenDatarepository),ALA(AtlasofLivingAustralia).
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Jülich, 5. – 7. September 2011 73
Biomass and Leaf Area in the Study of Heterosis in Arabidopsis thalianaRhonda Meyer1, Kathleen Weigelt1, Monique Seyfarth1, Fernando Arana-Ceballos1, Hanna Witucka-Wall2, Michael Melzer1, Thomas Altmann1
1MolecularGenetics,LeibnizInstituteofPlantGeneticsandCropPlantResearch(IPK), Germany 2Genetics,UniversityofPotsdam,Germany
Thediscoveryofheterosisconstitutesamajorlandmarkinplantbreeding.Heterosisdescribesanadvantageofoffspringvs.parentsingrowth,fertilityorstresstolerance.Theprinciplesunderlyingheterosisarestillunknown,mostlyduetoitsmultigenicnature.Heterosisisa widespreadoccurrenceinArabidopsisthaliana.ThisopensthepossibilitytocombineQTLanalyseswithtranscriptandmetaboliteprofilingtodiscoverphysiologicalandmolecularprocessesinvolvedinheterosis.WeanalysethemolecularbasisofheterosisinArabidopsisfollowingaforwardgeneticsapproachtoidentifygenomicsequencesthatcontributetobio-mass heterosis.
Growthrelatedparametersarerecordedinlargepopulationsofrecombinantinbredlines(RIL),introgressionlines(IL),andcollectionsofaccessions.Eventsleadingtotheestablishmentofsizedifferencesbetweenparentsandhybridstakeplaceearlyduringdevelopment.Differencesinleafsizecanbedetectedasearlyassixdaysaftersowingandaremaintaineduntillaterstages.Detailedmorphologicalanalysesofseedsandseedlingsrevealedthattheheterosiseffectisnotduetogreaterembryosizeorlargercellnumberinseeds.Theenhancedhybridseedlingsizeoccursthroughaninitialincreaseincellsizefollowedbytheformationofanincreasednumberofcells.
Theplantpopulationsweregenotypedusingsinglenucleotidepolymorphism(SNP)andsimplesequencelengthpolymorphism(SSLP)markers.QTLanalysesidentified7biomass,6leafarea,6growthrateand12heteroticQTL,individuallyexplainingbetween1%and16%ofthephenotypicvariation.TheQTLarevalidatedandfine-mappedusingheterogeneousinbredfamilies(HIFs)andassociationmappingapproaches.
References[1]Meyer,Rhonda;Kusterer,Barbara;Becher,Martina;Scharr,Hanno;Lisec,Jan;Steinfath,Matthias;Melchinger,Albrecht;Selbig,Joachim;Schurr,Ulrich;Willmitzer,Lothar;Altmann,Thomas(2010)QTLanalysisofearlystageheterosisforbiomassinArabidopsisTheoreticalandAppliedGenetics227–237
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POSTERS
Root phenotyping at the Jülich Plant Phenotyping Centre (JPPC)Kerstin A. Nagel1, Fabio Fiorani2, Andreas Averesch2, Kathrin Heinz2, Andreas Fischbach2, Bernd Kastenholz2, Ann-Katrin Kleinert2, Alexander Putz2, Hanno Scharr2, Ulrich Schurr2
1ForschungszentrumJülich,InstituteofBio-andGeosciences,IBG-2:PlantSciences,Germany 2ForschungszentrumJülich,Germany
Rootphenotypingisachallengingtask,mainlybecauseofthehiddennatureofthisplantorgan.RecentlyimagingtechnologieshavebeendevelopedattheJülichPlantPhenotypingCentre(JPPC)thatallowustoquantifyimportantfeaturesofrootsystemsautomatically.InthepostertheavailableapplicationsforrootphenotypingattheJPPCplatformwillbehigh-lighted.Digitalimagesequenceprocessingmethods(GROWMap-Root,Nageletal.2006)areusedtostudythedynamicofrootpenetrationintoasubstrateandtheadaptationofgrowthprocessestochangingenvironmentswithhighspatialandtemporalresolution.Forquantifyingthearchitectureofentirerootsystemsautomaticallyanimage-basedmethodwithahigherthroughput,GROWSCREEN-Root(Nageletal.2009)wasdevelopedrecently,whichdeterminesparametersofrootsystemslikerootlengthanddensity,distributionofrootswithinasub-strateandbranchingrates.Integratingthedynamicresponsesatthelevelofgrowingroottipswiththeperformancesofentirerootsystemsandtheirinteractionwiththeabovegroundplantpart,willgiveinsightintothemechanismsresponsibleforresourceuseefficiencyinplantstructureandfunction.Suchnovelapproachesscalabletoadesiredthroughputwillimproveourunderstandingofwhichrootphenotypictraitscanbetransferredfromcontrolledenviron-mentstofieldandwillbeavaluabletoolforbreedingprograms.
References[1]Nagel,KerstinA.(2006)DynamicsofrootgrowthstimulationinNicotianatabacuminincreasinglightintensity.PlantCellandEnvironment1936–1945[2]Nagel,KerstinA.(2009)Temperatureresponsesofroots:impactongrowth,rootsystemarchitectureandimplica-tionsforphenotyping.FunctionalPlantBiology947–959
POSTERS
Jülich, 5. – 7. September 2011 75
Automated Plant Phenomics 3D AnalysisAnthony Paproki, Jurgen Fripp, Scott Berry, Robert Furbank, Xavier Sirault
TheAustraliane-HealthResearchCenter(AEHRC,CSIRO,Australia)
The“High-ResolutionPlantPhenomicsCentre”basedinCanberrahasbuiltanadvanced platformforhigh-throughputnon-invasiveplantphenomicsdataacquisition.Thissystem captureshigh-resolutionstereographic,multi-spectralandinfra-redimagesofplantsassociatedwithLightDetectionandRangingSensorsdata.Thesedatacubesareusedtoproduce afull3Dreconstructionofeachplant.Themainchallengefromthishigh-throughputdataacquisitionistheautomationoftheanalysis.Inthispaperwepresentanadvancedimage-processingpipelineusedtoautomaticallyextractaccurateplantinformationsuchasstemsize,leafwidth,length,andareafromacquireddata.Thisinvolvesareconstructionofhigh-resolution3Dplantmesheswhicharethensegmentedinordertoidentifymeaningfulparts oftheplants.Alongitudinal3Dmatchingpipelineforplantmeshpartsallowstheevaluation oflongitudinalchangesintheplantstemandleaves.Ourinitialstudyinvolvedacquiringim-agesof6cottonplantsat4timepoints(4daysapart).ManualmeasurementsofeachplantwereperformedbyX.Sandwerecomparedwiththeautomatedimagingmeasurements.Resultsshowthat,shortaconstantratiobetweenthemeshunitandrealunit,thecomputeddataareaccuratein90%oftheplantparts,withtheprimaryproblemsduetoocclusionsbetweenleavesandatthetopoftheplantinthereconstructedmesh.Theaveragemeasure-menterrorsare4.0%forstemlength,3.8%forleafwidthand9.7%forleaflength.Thecurrentresultsillustratethataccurateandrobustautomatedplantassessmentispossible.Futureworkinvolvesincludinganatlas-basediterativefeedbackschemetoimprovethe3Dmeshreconstructionandthus,thesegmentationandautomatedanalysis.
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POSTERS
Combining high throughput phenotyping in platforms and field for genetic analyses of drought responsesBoris Parent1, Bettina Berger2, Delphine Fleury1, Peter Langridge1
1ACPFG,Australia 2ThePlantAccelerator,Australia
Highthroughputplantphenotypingplatformswererecentlyrapidlydeveloped,fillingthegapin“phenomics”comparedtoother“omics”technologies(LangridgeandFleury,2011).Byablingquantitativeanalysesofdynamicvariables,theseplatformsopennewpossibilities,espe-ciallygeneticanalysesofdroughtresponsesforwhichtraditionaltime-integratedtraitsshowgenotypeenvironmentinteractionsandoftenresultinnon-robustQTLs.However,potandfieldexperimentsmayleadtooppositeconclusions,becausetheeffectsofrootsystem(Parentetal.,2010)andinteractionsbetweenplantsarenullinpotexperiments.
Bycombiningbothapproaches,wecouldanalysevariableswhichareplatformorfieldspecific,andrapidlyapplyconclusionsintoarealfieldcontext.
ByusingtheautomatedimagingsystematThePlantAcceleratorandimagingtechniquesinthefield,weanalysedtheresponseofgrowth,development,transpiration,wateruseef-ficiency,leafsenescenceandyieldcomponentstodifferentlevelsofwaterdeficitintwelvecropspeciesandhundredsofwheatlines.Thedifferenttraitsofinterestweremodelledfromsimplevariablesextractedfrom2Dpictures,withgenotype-independentandtreatment–inde-pendentmodels.Variousgrowthmodelswerecomparedforgoodnessoffit,biologicalrelevanceofparameters,commonalitybetweencrops,genotypesandtreatments,plantdevelopmentdependencyandrangeofvalidity.Theresponsesoftraits,variablesandmodelparametervaluestothesoilwaterpotentialwerecomparedbetweenspeciesandgenotypes,showingarobustnessofparametervaluesandastronggeneticvariability.
References[1]Parent,Boris;Suard,Benoit;Serraj,Rachid;Tardieu,Francois(2010)RiceleafgrowthandwaterpotentialareresilienttoevaporativedemandandsoilwaterdeficitoncetheeffectsofrootsystemareneutralizedPlantCellandEnvironment1256–1267[2]Fleury,Delphine;Langridge,Peter(2011)Makingthemostof'omics'forcropbreedingTRENDSINBIOTECHNOLOGY33–40
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Jülich, 5. – 7. September 2011 77
Stomatal control by rootstock-sourced signals under water stress: a model-based analysis in grapevineAnthony Peccoux1, Brian Loveys2, Philippe Vivin3, Foteini Kolaki1, Serge Delrot4, Hans-Reiner Schultz5, Nathalie Ollat1, Zhan-Wu Dai1
1UMREcophysiologyandFunctionalGenomicsofGrapevine,INRA–ISVV,France 2PlantIndustry,CSIRO,Australia 3UMREcophysiologyandFunctionalGenomicsofGrapevine,INRA–ISVV,France 4UMREcophysiologyandFunctionalGenomicsofGrapevine,Univ.Bordeaux–ISVV,France 5FachgebietWeinbau,InstitütfürWeinbauundRebenzüchtung,Germany
Themechanismsunderlyingstomatalregulationarepoorlyunderstoodingraftedgrapevineunderdrought.Weinvestigatedtheroleofrootcharacteristics,planthydraulicconductivity(Kh)andchemicalsignals(ABA)intheresponseofstomatalconductance(gs)andtranspira-tion(E)towaterdeficitfordrought-sensitiveanddrought-tolerantrootstocksgraftedwiththesamescion.Theplants,grownin7Lpots,weresubjectedtoadryingcyclethroughweightmeasurementsinordertocontrolandrecordpreciselythesoilwatercontent.Amechanis-ticstomatalregulationmodel(TardieuandDavies,1993)wasusedtoevaluatetherelativecontributionsofrootcharacteristics,KhandABAsignalstorootstockalteredcontrolofstomatalapertureinthescion.Themodelcorrectlysimulatedtheconcomitantreductionsinleaf-specificgsandEandincreaseinsapABAconcentrationinallgenotypesafteraseven-daydroughtperiod.Moreover,itsuccessfullyreproducedtheobservedpatternsaccordingtowhichthemaintenanceofgsandEatlowsoilwatercontentwashighermorepronouncedinthedrought-tolerantgenotype.Onthebasisofmodelanalyseis,thesegenotypicdifferenceswereassociatedwiththerootcharacteristicsandthehydraulicpropertiesratherthanwithABAregulation.Overall,thismodel,andthebalanceplatformusedtocontrolwaterstressonlargepopulationsofplantsprovideausefultooltoanalyzegenotypicdifferences,toidentifygeneticcoefficients,andtohelpdesignideotypesofgrapevinerootstocksunderwaterlimitedconditions.
References[1]Tardieu,François;Davies,WilliamJ.(1993)IntegrationofhydraulicandchemicalsignallinginthecontrolofstomatalconductanceandwaterstatusofdroughtedplantsPlantCellEnvironnement16:341–349
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POSTERS
A semi-automatic non-destructive method to quantify grapevine downy mildew sporulationElisa Peressotti, Eric Duchêne, Didier Merdinoglu, Pere Mestre
UMR1131SantédelaVigneetQualitéduVin,68000Colmar,INRA,France
Theuseofnaturalresistancesisasustainablealternativetotheintensiveuseofpesticidesagainstcropdiseasesandbreedingstrategieshavebeenlargelyexploitedtocreateresistanthighperformingvarieties.Grapevinedownymildew(Plasomaviticola)isoneofthemost importantdiseasesaffectingviticultureantheavailabilityofamethodallowingprecisequan-tificationofpathogendevelopmentiscriticalforthedetectionofgenomicregionsdeterminingtheresistancelevel.GrapevineresistancetodownymildewistraditionallyassessedusingtheOIV452descriptorandbyquantifyingthesporeconcentrationofinfectedsamples.Althoughthefirstmethodallowsscoringdiseasedevelompmentatdifferenttimepoints,itisonlysemi-quantitative.Ontheothersidethesecondmethodisquantitativebutinvolvesthedestructionofthesampleandcanonlybeoptainedatthefinalinfectionstage.TheopensourcesoftwareImageJ(https://rsb.info.nih.gov/ij)wasusedtodevelopanimageanalysisprocessofinfectedleafdiscspictures.Thisnon-destructivemethodallowstoquantifythesporulatingsurfaceandtofollowthekineticsofinfection(Peressottietal.,2011)enablingcomparativestudies ofthefitnessofdifferentpathogenisolates.Itmakesalsopossibletoobtainfromtheverysamesamplephenotypicandmoleculardata,suchasstrainspecificgeneticmarkersorcandi-dategeneexpressionlevel.Theexperimentsundertakentothoroughlyevaluatethisinnovativemethodologydemonstrateitssuitabilityforthegeneticanalysisofgrapevineresistancetodownymildew.
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Jülich, 5. – 7. September 2011 79
Plant Phenomics Platform in Metapontum Agrobios: Phenotyping Research in Southern EuropeAngelo Petrozza, Stephan Summerer, Francesco Cellini
MetapontumAgrobios,Italy
MetapontumAgrobiosisanagriculturalresearchcenterlocatedinsouthernItalyandisownedbytheBasilicataRegion.Thecenterconsistsof7.000m2 indoor space of which 2.200 m2 belongtobiotechnologicalandchemicallaboratories.Greenhousespaceof5.400m2 along with5haofexperimentalfieldsareavailableforadvancedagronomicaltrials.ThemainobjectiveofMetapontumAgrobiosistointegratebiotechnology,agronomy,chemistryandinformatics.
MetapontumAgrobiosbiotechnologyscientistgroupcounts23researcherswithmultidiscipli-naryapproach,ensuringthesupporttoresearchactivitiesfromthelabtotheopenfield.
R&Dworkisengagedinthedevelopmentofnewplantvarietiesusingbiotechnologicaltoolscombinedwiththetraditionalandmarkerassistedbreeding.Inadditionlongtermplantnutri-tionalstudiesareongoinginacollaborativeprojectwithValagroS.p.A,animportantfertilizerproducingcompany.
Agrobioshasampleexperienceininducingplantresistancetobioticandabioticstress,in,themetabolicengineeringofplantfornutritionalquality,andhasdevelopedaTILLINGplatformforthe creation of new plant lines from different agronomic species.
MetapontumAgrobioshasrecentlyinvestedinahighthroughputPlantPhenomicsplatformbasedontheScanalyzer3DSystemofLemnatec.Thesystem,thefirstinItalyandinSouthEurope,isequippedwithtoaccommodate500pottedplants,integratedwithatrackingsystemforsafeidentificationofsingleplants.
SpecificapplicationsofPlantphenomicsconcernwiththeevaluationofplantdevelopmentandphenotypesofmutantandgenotypecollections,andwiththestudyofplantresponsesandadaptationtoenvironmentalstresses.
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POSTERS
Remote monitoring of photosynthetic efficiency using laser induced fluorescence transient (LIFT) techniqueRoland Pieruschka1, Hendrik Albrecht2, Denis Klimov3, Uwe Rascher1, Zbigniew S. Kolber4, C. Barry Osmond5, Joseph A. Berry6
1ForschungszentrumJülich,Germany 2HeinrichHeineUniversitätDüsseldorf,Germany 3MontereyBayAquariumResearchInstitute,UnitedStates 4UniversityofCalifornia,SantaCruz,UnitedStates 5AustralianNationalUniversity,Australia 6CarnegieInstitutionforScience,UnitedStates
Theinteractionofplantswiththeirenvironmentisaverydynamic.Studyingtheunderlyingprocessesisimportantforunderstandingandmodelingplantresponsetochangingenviron-mentalconditions.Photosynthesisvarieslargelybetweendifferentplantsandatdifferentlocationswithinacanopyofasingleplant.Thus,continuousandspatiallydistributedmonito-ringisnecessarytoassessthedynamicresponseofphotosynthesistotheenvironment.Yet,limitedscaleofobservationwithportableinstrumentationmakesitdifficulttoexaminelargenumbersofplants.Wereporthereontheapplicationofarecentlydevelopedtechnique,LaserInducedFluorescenceTransient(LIFT),forcontinuousremotemeasurementofphotosyntheticefficiencyofselectedleavesatadistanceofupto50m.Wepresenthere3caseexamplesoftheLIFTapplication:i)monitoringthecombinedeffectoflowtemperaturesandhighlightintensityonfourdifferentplantspecies,ii)monitoringofseasonaldynamicsofphotosynthesisofdifferenttreespecies,iii)mappingofphotosyntheticperformancewithintreecanopiesTheabilitytomakecontinuous,automaticandremotemeasurementsofphotosyntheticefficiencyofleaveswiththeLIFTprovidesanewapproachforstudyingtheinteractionofplantswiththeenvironmentandmaybecomeanimportanttoolinphenotypingplatforms.
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Jülich, 5. – 7. September 2011 81
Meta-phenomics: Capturing the plant phenome in 500 dose-response curvesHendrik Poorter
PlantSciences,FZJ,Germany
Atremendousbutnon-systematicefforthasbeenmadeduringthepast60yearstocharac-terizetheresponseofawidearrayofplantspeciestotheirenvironment.Thishashappenedatvariouslevels,suchasbiochemistry,physiology,anatomyaswellasatthelevelofwhole-plantcarbonbudgetandgrowth.Asaresult,alargenumberofphenotypicdataarepubliclyavailable.Unfortunately,thisinformationisnotunifiedinaquantitativeandstructuredwaywhichallowsforacomparativeanalysis.Myaimistofillthisimportantgapbybuildingalargedatabasecontainingtheresponsesofcirca40growth-relatedvariablesforarangeofplantspecies,andfor12differentenvironmentalfactors(Lightquantity,lightquality,UV-B,CO2,O3, nutrients,drought,water-logging,submergence,temperature,salinity,soilcompaction). InthisposterIwillshowanexampleofhowthesedatacanbeusedtoconstructdose-responsecurves.Thedatawillsubsequentlybeusedinarangeofcontraststhattestwhetherspecificsubgroupsofspecies(ecological,phylogenetical,functional)behaveinadistinctway.
Thisapproach-thatIrefertoas‘meta-phenomics’-notonlycanserveasabenchmarkforfutureandcomprehensivephenotypingefforts,butitwillalsorepresentaveryvaluabletoolperseinunderstandingtheintegratedresponseofplantstotheirenvironment.
References[1]Poorteretal.,H.(2009)Causesandconsequencesofvariationinleafmassperarea(LMA):ameta-analysis. NewPhytologist182:565–588.[2]Poorteretal.,H.(2010)Amethodtoconstructdose-responsecurvesforawiderangeofenvironmentalfactorsandplanttraitsbymeansofameta-analysisofphenotypicdata.J.Exp.Bot.61:2043–2055
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POSTERS
Contrasting Phenomics in wheat (Triticum aestivum L.) : implications for effective use of water and plant genetic resourcesIjaz Rasool
PlantBreedingandGenetics,UniversityCollegeofAgriculture,UniversityofSargodha,Pakistan
Plantphenotypinghasbeenemergedasapivotalfieldofresearchthroughouttheacademiaandagriculturalindustry,havingapersistentchallengeofintegrated,robustandquantifiablestructuralandfunctionaltraits.Phenotypingprovidesaviablelinkbetweengenomicsandplantsperformanceinthecontextofinteractionwithenvironmentalcues.Thepresentstudyaimsatexploringoptionstodeveloparoadmapofscreeningofwheatplanttounderstandthegenefunctionandinteraction,containinglab-basedandfield-orientedresearchundercontrastingenvironmentalresponse.AgricultureamainstreamactortoregulateandsustaincripplingeconomyofPakistanaswellasotherdevelopingcountries,whoseagricultureisbeingcriminallydegradedandmarginalizedbyeconomic,financialandwaterstresses.Wheatgermplasmcomprisinghundredgenotypesincludingtwoexoticvarieties,weretestedinlabconditionundernormalirrigationandwaterstressenvironments.Afterpassingthroughtoughscreeningchapter,fourteenrepresentativegenotypeswerecrossedinLinexTestermat-ingfashionresultingfortyninehybridgenotypes.Nextyearhybridsalongwithparentswereonceagainscreenedandsubjectedtowaterstressresultingtengenotypestosuccess.Thephenotypictraitsstudiedwereplantheight,flagleafarea,numberoftillersperplant,grainyield,moisturepercentage,proteincontents,glutencontentandzalenyetc.Thesignificantdif-fenceswerefoundinalltraitsunderbothenvironments.ThevarietiesDharwarDryandNesserbehavedbestinconstrastingenvironment.Thegeneactiontwistedtocontrolwaterstressprovidedaninfrastructureforplantphenotyping.Thestudycomprehendstheexploitationofwheatgeneticresourcesinfuturebreedingresearchtoovercomewaterstresswithregardtoclimaticchanges.Pragmaticproposalscanre-planandre-constructagriculturalresearchcrumblingdownintheregionbyintegratingandenergizingallrelevantplayersincludingplantbreeding,geneticsandbiotechnology.Theconcerteddevelopmentsonplantphenomicscon-centratedasanemergingfieldthatdevelopsandprovidestoolstocharacterizeplantperfor-manceandthedynamicsofplantstructuresunderdesiredenvironmentalscenarios.Extensivemeasurementsoffluctuatingasymmetryandofasynchronyhavedemonstratedthatcontrast-ingenvironmentsareimportantsourcesofphenotypicvariation.Thecontingentrelationshipsbetweengenotypeandphenotypearisesfromthenatureofstressandtheirimplicationstoyieldacrossdifferentenvironmentalscenariosareapplicablefromcasetocasebreedingpro-grams.Thefutureresearchequippedwithcontastingphenomicswillcombatpovertytoensureworldpeace,andfoodsecuritycuttingedgechallengesunderchangingclimaticcondition.
POSTERS
Jülich, 5. – 7. September 2011 83
Water Stress Recognition Models based on Hyperspectral Data with Archetypical Spectrum Analysis using Simplex Volume MaximizationChristoph Römer1, Mirwaes Wahabzada2, Agim Ballvora3, Uwe Rascher4, Jens Léon3, Christian Thurau2, Christian Bauckhage2, Kristian Kersting2, Lutz Plümer1
1Geoinformation,InstituteofGeodesyandGeoinformation,Germany 2FraunhoferInstitutfürIntelligenteAnalyseundInformationssysteme,Germany 3PlantBreedingandBiotechnology,INRES,Germany 4 ICG-3Phytosphere:EcosystemDynamics,ForschungszentrumJülich,Germany
Pre-symptomaticwaterstressrecognitionisofgreatrelevanceinprecisionplantbreeding andproduction.HyperspectralImagesensorsareanestablished,sophisticatedtechnol-ogyforearlystressdetectionwithhighspatialandtemporalresolution.Ontheotherhand,theygathermassive,highdimensionaldatacubeswhichposeasignificantchallengeeventoadvancedmethodsofdataanalysisandmachinelearning.Gettinglabelleddata,forclassicalsupervisedlearning,withinthoseimagesiscostlyanddifficult.Hence,newapproachesforunsupervisedrecognitionofrelevantpatternsareneeded.Inthisstudy,weapplyforthefirsttimearecentmatrixfactorizationtechniquebasedonsimplexvolumemaximizationtohyper-spectraldata.Itisanunsupervisedclassificationapproach,optimizedforfastcomputationonhigh-dimensionaldata.Itfollowstheideaofarchetypicalanalysis,meaningthateachspec-trumisaconvexcombinationofobservedextremespectra.Thisway,itispossibletoevaluatehow“similar”eachspectrumistohealthyorstressedleaves.OverthesesimilaritiesDirichletdistributionsarecalculated,providingthemeanstoexpresshowlikelyoneplantissufferingfromdroughtstress.ThetechniquewastestedfordroughtstressappliedtobarleycultivarScarlett.Hyperspectralimagesofplantsweretakenwitharesolutionof640x640pixelsandaspectrumof120wavelengthsintherangeof394-891nm.Theresultsshowthatitwaspos-sibletodetectandvisualizeacceleratedsenescenceinstressedplants,allowingapredictionofdroughtstressearlierthantheoccurrenceofvisiblesymptoms.Themethodpresentedisofgeneralinterestfortheautomaticanalysisofmassiveamountsofhyperspectraldata.
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POSTERS
Phenotyping for heat stress in wheat under field conditions in changing climate scenarioSindhu Sareen
CropImprovement,DirectorateofWheatResearch,India
Terminalheatisoneofthemajorabioticstressaffectingwheatproductioninmanyenviron-mentsaroundtheworldcovering36m.Withthepredictionsofglobalwarmingaddingtoincreaseintemperature,thereisneedtodevelopgenotypeswhichcansustainthesetempera-tures.Twomethodsareusedtoscreengenotypes.Eitherbygrowinginartificiallytemperaturecontrolledtunnelsorunderhotspotfieldconditions.Inthefirstmethodthedesiredincreaseintemperatureforheatstressisachievablebuttheperformanceofgenotypesinsmallplots/potsmaynotberepeatableunderlargeplotsinfield.Inthesecondmethodthedesiredheatstressmayormaynotoccurinchangingclimatescenario.AtDirectorateofWheatResearch,India,boththesemethodsareusedforphenotyping.Thirtysixgenotypeswereevaluatedforterminalheattolerancebytimelyandlateplantingduringtwoconsecutiveyears.Boththetimingofinitiationofheatstressaswellasheatintensityaffectedthegenotypicresponse.Seventeengenotypessufferedlesserreductionwhenheatstressinitiatedatlaterstageandinremaining19genotypesreductioningrainyielddidnotbearanyrelationwithtimingofinitiationofheatstress.Similarly17genotypessufferedmorereductioningrainyieldwhendifferenceinhightemperatureindexunderlatesownconditionswashigherbutthereversewastrueforremaining19genotypes.Thegenotypesfallingunderlatercategorywillperformbetterunderheatstressconditions.Thepaperconstitutestheresultsofthesestudiesforselectingcriteriaforphenotypingforterminalheatstress.
POSTERS
Jülich, 5. – 7. September 2011 85
Construction of a complex plant stress diagnostic systemLászló Sass1, János Pauk2, Dénes Dudits1, Imre Vass1
1BiologicalResearchCenter,InstituteofPlantBiology,Hungary 2CerealNon-ProfitCompany,Hungary
Breadingofcropplantsforstresstoleranceisahighlyimportanttask,whichrequiresacom-plexapproachinordertofollowthegrowthandphysiologicalstatusofplantsinthepresenceofcontrolledstressfactors.Wehavedevelopedagreenhousebasedcomplexdiagnosticsystemwiththecombinedapplicationofdigital(RGB)photographyimagingtoassessplantgrowthandcolorchanges,variablechlorophyll-fluorescenceimagingtoassessphotosynthe-ticactivity,andthermalimagingtocharacterizestomatalfunctionsviaevaporation-inducedleaftemperaturechanges.Thefacilityisoptimizedfortestingmiddlesizeplantsupto80cm(especiallywheat,barley,andrice)fordroughttolerance.Wateringofplantsisperformedby acomputercontrolledsystem,whichensurespredefined,individualwateringprotocolsforeachplantinordertoinducecontrolledwaterstress.DataacquisitionisperformedbyInter-netaccessiblesemi-roboticworkstationsforwateringandimaging.TheacquireddataaretransferredtoahighcapacityserverlocatedintheBiologicalResearchCenter,wheredataanalysisanddatastoragetakesplace.Theparametersprovidedbythesystemforindividualplantsinclude:theamountofwaterusedperplant,plantheight,totalleaf/plantarea,ratioofchlorophyllcontainingandsenescingarea,averagequantumyieldofPhotosystemII,andaverageleaftemperaturedifferencerelativetotheenvironment.Thesystemiswellequippedtotestdroughttoleranceinwheat,barleyorrice.
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POSTERS
Analysis of Hyperspectral Signatures by Double Weibull FunctionsKai Schmidt
INRESIPE,CROP.SENSe.net,UniversityofBonn,Germany
Spectralreflectancetechniqueshavebeencommonlyusedinremotesensingresearchforseveraldecades.Whiletheresolutionofsensortechnologyhasincreaseddrastically,theanalysisoftheinformationissomewhatinsufficient.Thechallengeistolinkthetechnicalsensorinformationtoaclassificationofthesensedobject.Withknownobjects,suchasplants,thespectralsignaturesshowdiverseandcomplextrajectoriesandcharacterisedif-ferentphysiologicalandbiochemicalconditionsofthecrop.Insteadofusingspecificwave-lengthsforanalysis,takingintoaccountthecompleteinformationofaspectralsignatureisseenasanadvantage.ThereforeanewalgorithmbasedonadditivedoubleWeibullfunctionsisintroduced.Themodelisapplicabletothewavelengthrangefromvisiblelight(VIS)tonearinfrared(NIR)anduptoshortwaveinfrared(SWIR).Itincludessufficientaccuracyandreducesthecomplexsensorinformationtoafewmodelparameters.Themodeliseasilyfittedtosensordataresultinginanindividualparametervectorforeachobject.Regressionanalysisshowsbothanadequateexploitationofthedataandnoparameterredundancy.Usingtheapproachfortheanalysisofexperimentsrequiresatwo-stepprocedure.Inthefirststepthemodelisfittedtothedata,takenbyaspectralreflectancesensor.Theresultingparametervectorsarethenfurtheranalysedbyadiscriminantanalysis.Thesecondstepassignstheparameterstakenfromtheregressionmodeltodifferentpredeterminedclasseswithrespecttotheunderlyingexperimentaldesign.Bothconsecutivestepsallowarapidanalysisofevenmorecomplexexperimentsanddemonstrateatoolforphenotypingsciencewithboth,highaccuracyandcapacity.Appliedexamplesofdifferentcomplexityandsizewillbepresented.Thetechniqueintroducedhereexploitsthecompletetechnicalinformationandresolutionprovidedbyspectralreflectionsensors.Thedataarecompressedtosecondarymodelparameters.Themodelisopenforstatisticalanalysis,isbroadlyapplicableandhasahighpotentialtoclassifyandseparatesensorsignals.Itisseenasanewanalysistechniquethatalsosupportstheclassicalanalysisprocedures.
References[1]Mahlein,A.-K.;Steiner,U.;Dehne,H.W.;Oerke,E.C.(2010)Spectralsignaturesofsugarbeetleavesforthe detectionanddifferentiationofdiseasesPrecisionAgriculture11413–431[2]Schmidt,K.(2009)VerfahrenzurIdentifikationundErmittlungdesZustandesvonPflanzenundanderenObjektenmittelsFernerkundungPatent102009040944.0beimDeutschenPatent-undMarkenamt19
POSTERS
Jülich, 5. – 7. September 2011 87
Chlorophyll a fluorescence to phenotype wheat genotypes for heat toleranceDew Kumari Sharma1, Sven Bode Andersen1, Carl-Otto Ottosen2, Eva Rosenqvist1
1AgricultureandEcology,CopenhagenUniversity,Denmark 2Horticulture,UniversityofAarhus,Denmark
Wheat(TriticumaestivumL.)isaheat-susceptiblecropthroughoutitsphenologicalstages,floweringphasebeingthemostsensitivestage.Earlystressdetectionmethodwithadvancedphysiologicalmeasurementsmayprovidenewdimensionstoestablishahighthroughputphenotypingmethod.ChlorophyllafluorescencehasbeenaversatiletoolinphotosynthesisresearchtomeasureplantresponsestovariousabioticstressesthataffectPSII.Weaimto establishareproducibleprotocoltomeasureresponseofwheatgenotypestohightempera-ture,basedonthephysiologicalmarker,maximumquantumyieldefficiencyofPSIIphoto-chemistry(Fv/Fm).Wesubsequentlyusedthisstandardizedprotocolformassscreeningofwheatgenotypes.Ourresultsshowedthatthetemperatureof40°Cin300μmolsm-2s-1 light for72hwasappropriatetoinduceheatstresstorevealgeneticvariationamongcultivars.Initialphenotypingof1300wheatgenotypesatamilderstressat38oCfor2hshowedaheritabilityof7%forFv/Fm.However,aharsherstressat40oCfor72hinrepeatedexperi-mentson138extremeperforminglinesresultedagenotypedependentdropinFv/Fmandanincreasedgeneticcomponentof15%.Ourprotocolseemstobestableoverenvironmentssinceinteractionbetweengenotypesandthethreerepeatedexperimentsseparatedintimewasnotstatisticallysignificant.Thechlorophyllafluorescenceprotocolmayenableidentifica-tionofwheatlinesreliablymoreorlesstoleranttoheattreatmentat40oC.Suchdifferentiallinescansubsequentlybeusedtostudythegeneticandphysiologicalnatureofstresstoler-ance,facilitatinggeneticdissectionofquantitativetraitintosimplerandmoreheritabletraits.
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POSTERS
Towards phenotype Plant Science: Key role of Science of Plant Germplasm Conservation in developing Phenome of PlantsNguyen Van Kien1, Luu Ngoc Trinh1, Nguyen Thi Ngoc Hue1, La Tuan Nghia1, Mai Thach Hoanh1, Vu Manh Hai2
1 GenebankManagementDivisions,PlantResourcesCenter,VietNam 2VietNamAcademyofAgriculturalSciences,VietNam
Asyouknow,PhenotypesofPlantsaretightlyinteractionbetweengenotypesandenvironmentconditions.TheinteractioniskeypointinstudiesofPlantSciencetowardsstrengtheningknowledgeandimprovementofqualityandproductivityofcropspeciesashuman’sdesire.AllkindofphenotypescombineintoaphenomeofPlants.Butaraisingmatterhowallphenotypesarecollectedtodevelopacompletedphenome.Reasonably,therearedifferentexpressesofphenotypesinsameenvironmentconditioningradeofindividuals,populationsandspeciesaswellasdifferentexpressesofaphenotypeinchangeableenvironmentcondition.Therefore,ScienceofPlantGermplasmConservationtobeakeyroleinformulationanddevelopmentofphenotypePlantSciencetogetherwithgenotypePlantScience.Becausealldataofob-servationandcharacterization/evaluationofcropgermplasmcollectionstobeprimarydatainforminganddevelopingdataofphenome’splants.Thiswillcontributetoanalyzinganddevelopingstructureofphenomeofplantssuchasrelationshipsbetweenthephenotypesoramongstthemandenvironment,thesearebasedonidentifyinglociandinteractionamongstthemandtoenvironments.Fromthis,towardsdesignatingkindseriesofdesiredphenotype’sPlantsintermofqualityandquantitytraits
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Jülich, 5. – 7. September 2011 89
PHIDIAS: Plant Phenotyping with a High-throughput, Intelligent, Distributed, and Integrated Analysis SystemSotirios Tsaftaris
ComputerScienceandApplications,IMT–Institutions,Markets,TechnologiesInstituteforAdvancedStudiesLucca,Italy
Currentlyautomatedandaffordablephenotypecollectionsystemsarearguablylaggingbehindpresentandfutureneeds;theyarelimitedtoafewcommerciallyavailableandcustomizedsolutions.PHIDIASincorporateslessonslearnedfrompreviouslypublishedworkstoofferanalternativeaffordable,research-friendly,andcollaborativesolutionforacquiring(non-destruc-tivelyandcontinuously)andanalyzingphenotypesfromplantexperiments.Itsnoveltyarisesfromthefactthatitallowsthecombinationofdistributedaffordablesensors(commercialcamerastocollectimagesandtransmitthemovertheinternet)withcentralizedprocessing.Withslightmodificationstotheirsoftware,commercialcamerascanbecomepowerfulimageacquisitiondevices.Toincreasethefidelityofthedata,sequentiallyacquiredimagescanbefusedtogeneratehighprecisionfullyfocusedcompositeimages,.usingalgorithmsborrowedfromcomputationalphotographyrunninginprocessingservers.Thesameserversalsoanalyzetheimagesandextractrelevantphenotypinginformation.Allthedataarestoredindatabasesandofferedtotheuserforexplorationthroughamodernweb-basedportal.Theuserswouldbeallowedtoeditandviewimagesonlinethroughtheportal.PHIDIASlearnsfromtheuser’sinputs,whicharefedbackintothelearning-basedimageprocessingalgorithms,actingasacontinuousstreamoftrainingdata.PHIDIASwhencompletedwillfosteranarenaofconstantdevelopmentandevolutionbyadoptingopenarchitecture,access,andaffordablehardwarestandards.Userswillbeabletoparticipatebycontributingdataandfunctionality.Currently,thesystemisunderdevelopmenttobeusedinArabidopsisthalianaenvironmentalstressexperimentsperformedincontrolledgrowthchamberenvironments.
Acknowledgement:ThedevelopmentofPHIDIASissupportedbyaMarieCurieInternationalReintegrationGrantundertheSeventhFrameworkProgramme.
References[1]Tsaftaris,Sotirios;Noutsos,Christos(2009)PlantPhenotypingwithLowCostDigitalCamerasandImageAnalyticsINFORMATIONTECHNOLOGIESINENVIRONMENTALENGINEERINGEnvironmentalScienceandEngineering238–251
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POSTERS
Morphological and physiological variation of plant architecture in red clover (Trifolium pratense)Annemie Van Minnebruggen1, Isabel Roldán-Ruiz2, Erik Van Bockstaele1, Gerda Cnops2
1PlantSciencesUnit–GrowthandDevelopment,InstituteforAgriculturalandFisheries Research(ILVO);GhentUniversity,FacultyBioscienceEngineering,DepartmentofPlant Production,Belgium 2PlantSciencesUnit–GrowthandDevelopment,InstituteforAgriculturalandFisheries Research(ILVO),Belgium
Grass/clovermixturescontributetoagriculturalsustainabilitybyreducingnitrogenfertilizationandincreasingthenutritionalvalueoffeedandfood(highproteinandpolyunsaturatedfattyacidlevels)(Dewhurstetal.,2003).However,thecurrentredclovercultivarshavealowpersistence.Persistencecanbeimprovedbyalteringtheplant’sarchitecture,whichiscontrolledbothbygeneticsandenvironment.Wehaveanalyzedtwoofthemanybranchingphenotypes(Cnopsetal.,2010),i.e.,ahighlybranchedandcreepinggenotype(Crossway2),andapoorlybranchinganderectgenotype(Diplomat8).Thebranchingwasobservedinclonalreplicatesgrownincontainersduringonegrowingseasonintwodifferentenvironments(openairandgrowthchamber).Thenumberofnodesandthequantityandpositionofbudoutgrowthintobranchesdifferedgreatlybetweengenotypes.Comparableresultswereobtainedforbothenvironments,whichsuggestsgoodheritabilityofbranchingpatterns.Wealsoinvestigatedhowthehormonesauxinandstrigolactoneinfluencebranchinginthetwogenotypes.Becauseofthecomplexityofaredcloverplant(nonoutgrowingmainaxis,manyfirstorderbranches),weappliedthesehormonestoisolatedsinglenodesegments(Chatfieldetal.,2000).Budoutgrowthwasinhibitedtothesamelevelinbothgenotypesafterhormoneapplication.Inthefuture,wewillstudytheinvolvementofstrigolactonegenesinthebranchingofredclover.Thisknowledge,whenappliedinredcloverbreedingprogrammes,maygenerateplantswithaddedvaluetowardsyieldandpersistence.
References[1]Dewhurst,R.J.;Fisher,W.J.;Tweed,J.K.S.;Wilkins,R.J.(2003)Comparisonofgrassandlegumesilagesformilkproduction.1.ProductionresponseswithdifferentlevelsofconcentrateJournalofDairyScience2598–2611[2]Chatfield,S.P.;Stirnberg,P.;Forde,B.G.;Leyser,O.(2000)ThehormonalregulationofaxillarybudgrowthinArabidopsisThePlantJournal159–169[3]Cnops,G.;Rohde,A.;Saracutu,O.;Malengier,M.;Roldán-Ruiz,I.(2010)Morphologicalandmoleculardiversityofbranchinginredclover(Trifoliumpratense)SustainableUseofGeneticDiversityinForageandTurfBreeding73–77
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Jülich, 5. – 7. September 2011 91
Systems analysis of lateral root development in Arabidopsis thalianaUte Voß, Mikael Lucas, Michael Wilson, Kim Kenobi, Benjamin Péret, Malcolm Bennett
TheCentreforPlantIntegrativeBiology,UniversityofNottingham,UnitedKingdom
Unlikeanimals,plantsfirstformasimpleembryowhichlacksmanyoftheorgansfoundintheadultorganismsuchasleaves,flowersandlateralroots.Sinceplantsarenon-mobiletheydothissothattheycanrespondtoenvironmentalsignalssuchaslightandnutrientlevelsbyformingleavesandlateralroots,respectively.Despiteitsimportanceforthefinalformoftheplant,weknowsurprisinglylittleaboutthemolecularandcellularmechanismsregulatingpost-embryonicorganogenesis.
Inordertostudylateralrootdevelopmentmoreprecisely,wehavedevelopedanovelmethodtosynchroniselateralrootdevelopmentusingagravitropicstimulus.Newprimordiaareinducedontheoutersideofbendingofgravitystimulatedseedlings.Confocalimaginghasrevealedthatnewprimordiafrommultipleseedlingsdevelopinahighlysynchronisedmannerovera54hourperiodaftergravitistimulation.Wemicrodissectedbendingrootsegmentsat3hourintervalsfor54hoursateverypre-andpost-emergencestageoflateralrootdevelop-mentandAffymetrixtranscriptomedatasetshavebeengeneratedforall15timepointswhichcovereachofthe13stagesoflateralrootdevelopment(Figure2C). Severalgeneshighlyupregulatedinthisdatasethavebeentargetedforknock-out,using T-DNAinsertionlines.Wehavephenotypedtherootsoftheseknock-outlinesnotonlyfor primaryrootlengthandlateralrootdensity.Wealsousedournewlydevelopedgravitropic assaytodeterminethespeedoflateralrootprimordiumdevelopment.Thisallowsusto distinguishfordefectsinlateralrootinitiation,lateralrooddevelopmentandlateralroot patterning.
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POSTERS
Using high-throughput phenotyping platforms to identify and characterize genes controlling vegetative biomass accumulation in Arabidopsis thalianaKathleen Weigelt, Rhonda C. Meyer, Monique Seyfarth, Ingo Mücke, Thomas Altmann
Leibniz-InstituteofPlantGeneticsandCropPlantResearch(IPK),Gatersleben,Germany
VariationofgrowthandmetabolictraitswereusedtoidentifyandcharacterizeatthemolecularlevellociunderlyinggrowthdifferencesinArabidopsisrecombinantinbredline(RIL)andintro-gressionline(IL)populationsderivedfromaccessionsCol-0andC24.Thedataweresubjectedtocorrelationandquantitativetraitloci(QTL)analysesandsevenQTLforbiomassand157metabolicQTLfor84metabolitescouldbeidentified(Lisecetal.,TPJ53,2008).Forthevali-dationandfurtherfine-mappingofthebiomassQTLregionsover360Arabidopsisaccessionsandseveralheterogenousinbredfamilies(HIFs)weregenotypedwithsinglenucleotidepoly-morphism(SNP)markersandanalysedforplantgrowthrateandleafareaatdifferentdevelop-mentaltimepointswiththesemi-automatedphenotypingsystemGROWSCREEN(Walteretal.,NewPhytol174,2007).Phenotypeswithcleardifferencesingrowthrelatedparameterswillbeexploredinoneofthethreefullyautomatichigh-throughputplantgrowthandphenotypingplatformsdevelopedbyLemnaTec.Thephenotypingplatformsallowgrowthundercontrolledconditionsandnon-destructivescreeningofupto4600Arabidopsis,312barleyand1584maizeplants.Eachplantislocatedinacarrieronabandconveyorandtransportedtothephotochamber,wheretheyareautomaticallyimaged,weighedandwatered.Thenon-invasiveimageacquisitioniscarriedoutwithvisible,nearinfrared,ultra-violetandinfraredlightandallowstheevaluationofplantsize,watercontent,chlorophyllcontent,andplanttemperature.ThecommercialsoftwarepackageLemnaGridwasestablishedforanalyzingthegenerateddata.
POSTERS
Jülich, 5. – 7. September 2011 93
Development of a phenotyping platform to assess grapevine resistance to downy and powdery mildewS. Wiedemann-Merdinoglu, V. Dumas, P. Coste, M.A. Dorne, E. Duchêne, P. Mestre, D. Merdinoglu
InstitutNationaldelaRechercheAgronomique,France
Downyandpowderymildewareimportantgrapevinediseasescausingsymptomsinleavesandbunchesandthusaffectingproduction.Thecurrentstrategytocontrolthesediseasesreliesonchemicaltreatments.Breedingforresistantvarietiesisanalternativetotheintensiveuseoffungicides.
Accuratephenotypingisparticularlyimportantattheearlystepsofthebreedingprocess.AfteridentificationofresistantsourcesamongwildVitisspecies,thegeneticdeterminismoftheresistanceisunveiledbyassociatinggenotypingwithmolecularmarkersandphenotypingforresistance.IfprogressinDNAmarkersenableshighthroughputgenotypingoflargeplantpopulations,phenotypingfordiseaseresistanceremainsstilllaboriousandtime-consuming.Phenotypingmethodsaretraditionallyperformedinthefieldorinthegreenhousewithlimitedcontroloftheenvironmentalconditionsthatareimportantfortheexpressionofthesymptoms.
Toovercometheseweaknesses,wedevelopedaphenotypingplatformforresistancetogrape-vinepowderyanddownymildew.Thistool,basedonalaboratoryleafdiscbioassay,mustfulfilthefollowinggoals:1)toprovidelargeplantpopulationsgrowninhomogenousandcontrolledconditions,2)toimprovethroughput,accuracyandreliabilityofresistanceassessment,3)toreducetimeandspaceneededforphenotyping.Forthispurpose,plantgrowthismonitoredfromsowingtothescoringofresistancelevel.Furthermore,severalstepsofthephenotypingprocesswerestandardizedorautomatedeitherbytheacquisitionofspecificfacilitiessuchasgrowthchambersandrobots,orbythedevelopmentofanimageanalysissystemadaptedtothescoringofresistancelevel.
References[1]Blasi,P.,Blanc,S.,Wiedemann-Merdinoglu,S.,Prado,E.,RühlEH,Mestre,P.,Merdinoglu,D.(2011).ConstructionofareferencelinkagemapofVitisamurensisandgeneticmappingofRpv8,alocusconferringresistancetograpevinedownymildew.TheorApplGenet.123:43–53.[2]Peressotti,E.,Duchêne,E.,Merdinoglu,D.,Mestre,P.(2011).Asemi-automaticnondestructivemethodtoquantifygrapevinedownymildewsporulation.Journalofmicrobiologicalmethods,84,265–271.
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Plant phenotyping is a rapidly evolving concept aiming at elucidating the
functional role of gene networks under natural conditions. How do the in-
teractions between the genome and the environment evolve, with respect
to both quality und quantity? Introducing the new high throughput and high
content plant phenotyping platform LemnaTec provides the technology to
meet the challenge.
www.lemnatec.com
n fully automated 3D plant phenotyping
n visual light, chlorophyll fluorescence,
near infra red and infra red imaging
n standardized growth conditions with
the LemnaTec moving field concept
n automated weighing, watering and
spraying of up to 4000 plants per day
Get phenotyping up to speed
IMPRESSUM
2ndInternationalPlantPhenotypingSymposium2011:BookofAbstracts Herausgeber:Forschungs-zentrumJülichGmbH|52425JülichGrafikundLayout:GrafischeMedien,ForschungszentrumJülich Bildnachweis:ForschungszentrumJülich,LemnaTecKontakt:GeschäftsbereichUnternehmens-kommunikation|Tel.:0246161-4661|Fax:0246161-4666|E-Mail:[email protected]