Models For Crop Diseases: Overview Of Approaches Scales

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Models for crop diseases:Overview of approaches & scalesS Savary, P Esker, N McRoberts,L Willocquet, T Caffi, V Rossi, J Yuen,A Djurle, L Amorim, A Bergamin Filho,N Castilla, A Sparks, J Avelino, C Allinne, K Garrett

Background Modeling plant diseases: many differentapproaches used, with different objectivesTwo main objectives in modeling plant disease: Modeling the dynamics of plant disease epidemicsModeling crop losses – the effects of plant disease (pest) oncrop growth and performanceWith the ultimate goal of improving diseasemanagement, and so: A very large number of pathosystem (Host Pathogen) ‐specific disease management models

Brief overview ofepidemiological simulation modelling– Types of epidemics and models(monocyclic; polycyclic; mixed monocyclic‐polyclic)– Spatialized models (explicit, implicitspatialization)– Primary inoculum– Polyetic processes– Genetic diversity of the pathogenepidemiological modeling

Epidemiological structural patternsPolycycle – Fraction Host TissueMonocycleFruiting Body ‐ Panicle or HeadSeed‐ or soil‐borne diseasesMixed – Shoot or TillerVector‐borneepidemiological modeling

An epidemiological example: EPIRICE'correction'factortotal diseasedsitesCDRateof growthRGRateof SIRISsenescedsitesbasic relativeinfection rateRc'removed'sitesPVanderplank J.E., 1963. Plant Diseases.Epidemics and Control. Academic Press, NewYork.Zadoks J.C. 1971., Systems analysis and thedynamics of epidemics. Phytopathology61:600-610Savary, S., Nelson A., Willocquet L., PanggaI., Aunario J., 2012. Modelling and mappingpotential epidemics of rice diseases globally.Crop Protection, In Press.epidemiological modeling

spatial scales of plant disease epidemics in EPIRICE- local infections on the foliage- 1 lesion a small fraction of leaf area- ex.: leaf blast; brown spot- rapidly expanding infections on the foliage- 1 lesion a leaf- ex.: bacterial blight- infections affecting entire tillers- 1 lesion a tiller- ex.: sheath blight- systemic infections- 1 lesion a plant- ex.: tungro epidemiologicalmodeling

Avg1997-2008BrownspotStd1997-2008epidemiological modeling

Avg1997-2008LeafblastStd1997-2008epidemiological modeling

Another epidemiological example: Modellinggrapevine powdery mildew epidemics underdifferent CC scenariosModel simulations of powdery mildew severity (%) in a scenario of low‐intermediateconduciveness (black symbols) and high conduciveness (grey symbols) forthe disease according to scenarios A2 and B2 for Cembra (higher elevation). 10‐year movingaverage lines are superimposed on the series.Caffarra, A., Rinaldi, M., Eccel, E., Rossi, V., & Pertot, I. (2012). Modelling the impact of climatechange on the interaction between grapevine and its pests and pathogens: European grapevinemoth and powdery mildew. Agriculture, Ecosystems & Environment, 148, 89‐101.

Challenges (J. Yuen, pers. comm.)time scale (epidemiological processes studied) time scale (processes in crop models) time scale (climate change scenarios)epidemiological modeling

Brief overview ofcrop loss simulation modelling–Crop (agrophysiological) growthmodels with damage mechanisms–Damage mechanisms–RI – RUE models– multiple diseases (pests) modelsYield and yield loss modeling

Production levelsProductionlevels:radiationtemperaturecrop phenologyphysiological propertiescrop architectureYielddefining factorsPotentialAttainableActualYieldlimiting factorsYieldreducing llutantscalamitiesRabbinge, R. 1993. Theecological background offood production. In: Cropprotection andsustainable agriculture.Ciba Foundation 77.Chadwick DJ, Marsh J,Eds. John Wiley & Sons,Chichester, UK.Van Ittersum, M. K., andRabbinge, R. 1997.Ecology for analysis andquantification ofagricultural input‐outputcombinations. Field CropsRes. 52:197‐208.Yield and yield loss modeling

Simulation modelling of yield losses ‐examplesCropPestReferenceRiceLeaf blastBastiaans, 1993RiceMultiple diseasesPinnschmidt et al, 1994RiceMultiple pestsWillocquet et al, 2000; 2002; 2004Rice, wheatMultiple pestsAggarwal et al, 2006a; 2006bWheatAphidsRossing, 1991WheatLeaf rustRoermund & Spitters, 1990WheatMultiple pestsWillocquet et al, 2008PotatoMultiple pestsJohnson, 1992Yield and yield loss modeling

Damage mechanisms of crop pest injuriesDamagemechanismPhysiological effectEffect in a crop growth modelExamples of pestsLight stealerReduces the interceptedradiationReduces the green LAIPathogens producing lesions on leavesLeaf senescenceacceleratorIncreases leaf senescence,causes defoliationReduces leaf biomass by increasingthe rate of leaf senescenceFoliar pathogens such as leaf spottingpathogens, downy mildewsTissue consumerReduces the tissue biomassOutflows from biomasses of theinjured organsDefoliating insectsStand reducerReduces the number andbiomass of plantsReduces biomass of all organsDamping‐off fungiPhotosyntheticRate reducerReduces the rate of carbonuptakeReduces the RUEViruses, root‐infecting pests, steminfecting pests, some foliar pathogensTurgor reducerDisrupts xylem and phloemtransportReduces the RUE, accelerates leafsenescenceVascular, wilt pathogensAssimilatesapperRemoves soluble assimilatesfrom hostOutflows assimilates from the poolof assimilatesSucking insects, e.g. aphids, someplanthoppers, biotrophic fungi exportingassimilates from host cells and an eighth mechanism: reproductive tissue transformation (smuts and gallmidges) – A. Djurle, Pers. Comm.Rabbinge, R., and Vereyken, P. H. 1980. The effects of diseases or pests upon host. Z. Pflanzenk. Pflanzensch. 87:409‐422;Rabbinge, R., and Rijsdijk, P. H. 1981. Disease and crop physiology: a modeler’s point of view. Pages 201‐220 in: Effects of Diseaseon the Physiology of the Growing Plants. P. G. Ayres, ed. Cambridge Univ. Press, Cambridge, UK;Boote, K. J., Jones, J. W., Mishoe, J. W., and Berger, R. D. 1983. Coupling pests to crop growth simulators to predict yieldreductions. Phytopathology 73:1581‐1587;Savary S, Willocquet L. 2014. Simulation Modeling in Botanical Epidemiology and Crop Loss analysis. APSnet Education Center.The Plant Health Instructor. DOI: 10.1094/PHI‐A‐2014‐0314‐01.Yield andyield lossmodeling

Incorporating different damage mechanismsinto a crop growth model: GENEPESTPhotosy ntheticrate reducerRADkTurgor reducerLight StealerRUERate of assimilate div ersionRGAssimilate sapperLAIPartLPartRPartSLeaf BPoolStemBStorBRTranslocRremLLeaf senescenceacceleratorrrsenLPartSOSavary S, Willocquet L.2014. SimulationModeling in BotanicalRootBEpidemiology and CropLoss analysis. APSnetEducation Center. ThePlant Health Instructor.DOI: 10.1094/PHI‐A‐2014‐0314‐01.Leaf consumerYield and yield loss modelingTurgor reducer

RICEPEST structureSavary S, Willocquet L. 2014. Simulation Modeling in BotanicalEpidemiology and Crop Loss analysis. APSnet Education Center. ThePlant Health Instructor. DOI: 10.1094/PHI‐A‐2014‐0314‐01.Yield and yield loss modeling

Pests included in WHEATPEST Diseases– brown rust, yellow rust, powdery mildew, Septoria triticiblotch, Stagonospora nodorum blotch– eyespot, sharp eyespot– Fusarium stem rot– Fusarium head blight– take‐allWillocquet L, Aubertot– BYDV Insects– aphids WeedsJN, Lebard S, Robert C,Lannou C, Savary S,2008. Simulatingmultiple pest damage invarying winter wheatproduction situations.Field Crops Research107: 12‐28.Yield and yield loss modeling

WHEATPEST structureB YDVTBASETM INEYSFSTWDTA KkRA DTM A XSHYRUESLADTEMPLAIAPHRGSTSNYRBRPMRSA PRDIVSTEMPWillocquet L, AubertotJN, Lebard S, Robert C,Lannou C, Savary S,2008. Simulatingmultiple pest damage invarying winter wheatproduction situations.Field Crops Research107: 12‐28.DVSPOOLRLEA FRSTEMCP LLEAFBMRRSENLCP STREA RRROOTCP RCP ESTEMBMROOTBMEARBMRDISTRSENLFHBYield andyield lossmodeling

Linking epidemiological and yield lossmodeling:Example: combining EPIRICE and RICEPEST(Courtesy Adam Sparks, IRRI)epidemiological &yield and yield loss modeling

Example: simulated yield gains from hostplant resistance to rice bacterial blight(Courtesy Adam Sparks et al., IRRI)epidemiological &yield and yield loss modeling

Assessment of achievements and needsProgress: damage mechanisms & models Much progress has been made on themodeling of the effects of harmful organimson crops (damage mechanisms) As a result, it is possible to model crop lossescaused by one or multiple injuries (diseases,pests) in a generic manner (i.e., any crop, anydisease/pest)

Assessment of achievements and needsProgress: losses to multiple injuries Disease management often has to account forthe existence of multiple diseases and pestsin order to be relevant and efficient From a crop loss – crop performance –perspective: addressing multiple diseases (andpests) is desirable Yield loss models (e.g., RICEPEST, WHEATPEST)incorporating multiple injuries (diseases,insects, weeds) have been developed

Assessment of achievements and needsObstacle: actual field injury data But the availability of injury functions – thetime course of diseases/pests under actualfield conditions – is a major obstacle

Assessment of achievements and needsChallenges Even for the main food crops worldwide (rice,wheat, maize, soybean, potato), there is acritical shortage of field data on observed(multiple) injuries The shortage of field data – not the limitationof process‐knowledge – is the main obstacle inmodeling crop pests and diseases and theirrelations to crops

Assessment of achievements and needsSteps forward A critical step forward would be to develop ageneric modeling framework for injury functions(ideotypes of injury time courses) representing the dynamics of injury over time inreference, key, conditions along with other dynamics (i.e., otherdisease/pest) These collective dynamics of injury functionsrepresenting multiple injury Crop Healthscenarios which, in turn, could be used as drivers for croploss models

Concepts for a new AgMIP GroupOur emphasis within AgMiP is on genericepidemiological and generic crop lossmodelling structures

Concepts for a new AgMIP Group Crop growth models: exist potential yield (T, rad, plant genotype) attainable yield (same, yield limiting factors) New step: add yield‐reducing factors toexisting models: implies driving functions for diseases (pests) couplers damage mechanisms Missing: driving functions for diseases develop a framework to model potential (ifnecessary, multiple) epidemics

Framework of activities for a proposedAgMiP Research Group Focusing on crop health (multiple diseases, pests)Generic simulation models for disease epidemicsEnabling to develop crop health scenariosA crop health scenario a set of injury levelscaused by different diseases, pests Crop health scenario: used as driver to modelcrop growth and crop loss Allows addressing (1) potential and actual crophealth risks and (2) crop losses and (3) yield gains(from management) in a generic manner

Targetpatho‐systemsWheatTemperateCrops and EcologiesTable to fillCheck « ecologies »NOT too many crossesXTropicalhumidTropicaldryRicePotatoSoybean CoffeeXEtc.XXTropicalmountainTo be discussed further:‐ perennial crops: grapevine‐ other or different annual cropsXXXEtc.

Std 1997-2008 Brown spot epidemiological modeling. Avg 1997-2008 Std 1997-2008 Leaf blast epidemiological modeling. Another epidemiological example: Modelling . Target

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