000902681 001__ 902681
000902681 005__ 20230815122840.0
000902681 0247_ $$2doi$$a10.1007/s11104-021-05026-4
000902681 0247_ $$2ISSN$$a0032-079X
000902681 0247_ $$2ISSN$$a1573-5036
000902681 0247_ $$2Handle$$a2128/29145
000902681 0247_ $$2altmetric$$aaltmetric:111614644
000902681 0247_ $$2WOS$$aWOS:000675319900001
000902681 037__ $$aFZJ-2021-04468
000902681 082__ $$a580
000902681 1001_ $$0P:(DE-Juel1)168106$$aMorandage, Shehan$$b0
000902681 245__ $$aBayesian inference of root architectural model parameters from synthetic field data
000902681 260__ $$aDordrecht [u.a.]$$bSpringer Science + Business Media B.V$$c2021
000902681 3367_ $$2DRIVER$$aarticle
000902681 3367_ $$2DataCite$$aOutput Types/Journal article
000902681 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1637840918_22715
000902681 3367_ $$2BibTeX$$aARTICLE
000902681 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000902681 3367_ $$00$$2EndNote$$aJournal Article
000902681 520__ $$aBackground and aimsCharacterizing root system architectures of field-grown crops is challenging as root systems are hidden in the soil. We investigate the possibility of estimating root architecture model parameters from soil core data in a Bayesian framework.MethodsIn a synthetic experiment, we simulated wheat root systems in a virtual field plot with the stochastic CRootBox model. We virtually sampled soil cores from this plot to create synthetic measurement data. We used the Markov chain Monte Carlo (MCMC) DREAM(ZS) sampler to estimate the most sensitive root system architecture parameters. To deal with the CRootBox model stochasticity and limited computational resources, we essentially added a stochastic component to the likelihood function, thereby turning the MCMC sampling into a form of approximate Bayesian computation (ABC).ResultsA few zero-order root parameters: maximum length, elongation rate, insertion angles, and numbers of zero-order roots, with narrow posterior distributions centered around true parameter values were identifiable from soil core data. Yet other zero-order and higher-order root parameters were not identifiable showing a sizeable posterior uncertainty.ConclusionsBayesian inference of root architecture parameters from root density profiles is an effective method to extract information about sensitive parameters hidden in these profiles. Equally important, this method also identifies which information about root architecture is lost when root architecture is aggregated in root density profiles.
000902681 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
000902681 536__ $$0G:(GEPRIS)15232683$$aDFG project 15232683 - TRR 32: Muster und Strukturen in Boden-Pflanzen-Atmosphären-Systemen: Erfassung, Modellierung und Datenassimilation $$c15232683$$x1
000902681 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
000902681 7001_ $$0P:(DE-HGF)0$$aLaloy, Eric$$b1
000902681 7001_ $$0P:(DE-Juel1)157922$$aSchnepf, Andrea$$b2$$ufzj
000902681 7001_ $$0P:(DE-Juel1)129549$$aVereecken, Harry$$b3$$ufzj
000902681 7001_ $$0P:(DE-Juel1)129548$$aVanderborght, Jan$$b4$$eCorresponding author
000902681 773__ $$0PERI:(DE-600)1478535-3$$a10.1007/s11104-021-05026-4$$gVol. 467, no. 1-2, p. 67 - 89$$n1-2$$p67 - 89$$tPlant and soil$$v467$$x0032-079X$$y2021
000902681 8564_ $$uhttps://juser.fz-juelich.de/record/902681/files/Morandage2021_Article_BayesianInferenceOfRootArchite.pdf$$yOpenAccess
000902681 8767_ $$d2021-05-27$$eHybrid-OA$$jDEAL$$lDEAL: Springer
000902681 909CO $$ooai:juser.fz-juelich.de:902681$$pdnbdelivery$$popenCost$$pVDB$$pdriver$$pOpenAPC_DEAL$$popen_access$$popenaire
000902681 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)157922$$aForschungszentrum Jülich$$b2$$kFZJ
000902681 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129549$$aForschungszentrum Jülich$$b3$$kFZJ
000902681 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129548$$aForschungszentrum Jülich$$b4$$kFZJ
000902681 9131_ $$0G:(DE-HGF)POF4-217$$1G:(DE-HGF)POF4-210$$2G:(DE-HGF)POF4-200$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-2173$$aDE-HGF$$bForschungsbereich Erde und Umwelt$$lErde im Wandel – Unsere Zukunft nachhaltig gestalten$$vFür eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten$$x0
000902681 9141_ $$y2021
000902681 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)3002$$2StatID$$aDEAL Springer$$d2021-02-03$$wger
000902681 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000902681 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bPLANT SOIL : 2019$$d2021-02-03
000902681 915__ $$0StatID:(DE-HGF)0430$$2StatID$$aNational-Konsortium$$d2021-02-03$$wger
000902681 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2021-02-03
000902681 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000902681 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2021-02-03$$wger
000902681 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2021-02-03
000902681 915pc $$0PC:(DE-HGF)0000$$2APC$$aAPC keys set
000902681 915pc $$0PC:(DE-HGF)0001$$2APC$$aLocal Funding
000902681 915pc $$0PC:(DE-HGF)0002$$2APC$$aDFG OA Publikationskosten
000902681 915pc $$0PC:(DE-HGF)0113$$2APC$$aDEAL: Springer Nature 2020
000902681 920__ $$lyes
000902681 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000902681 9801_ $$aFullTexts
000902681 980__ $$ajournal
000902681 980__ $$aVDB
000902681 980__ $$aUNRESTRICTED
000902681 980__ $$aI:(DE-Juel1)IBG-3-20101118
000902681 980__ $$aAPC