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

4 2ndInternationalPlantPhenotypingSymposium2011

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


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


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


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


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


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?


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


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


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.


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


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)


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


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.


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


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.


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


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


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


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


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


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


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


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


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


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


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


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.


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


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


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


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


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


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.


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


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.


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


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.


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


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.


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


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


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


POSTERS

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


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


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

POSTERS


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.


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


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.


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


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.


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


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


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


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


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.

POSTERS


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.


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


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.


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


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.”


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

POSTERS


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.


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


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.


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

POSTERS


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


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).

POSTERS


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


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


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.


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

POSTERS


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


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.

POSTERS


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.


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.

POSTERS


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


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


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.


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


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.


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


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.


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

POSTERS


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


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

POSTERS


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.


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


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]

nd international plant phenotyping symposium 2011 · 2nd international plant phenotyping symposium...

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