001044993 001__ 1044993 001044993 005__ 20250912110158.0 001044993 0247_ $$2doi$$a10.1186/s13007-025-01431-3 001044993 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-03477 001044993 0247_ $$2pmid$$a40790535 001044993 0247_ $$2WOS$$aWOS:001548547400001 001044993 037__ $$aFZJ-2025-03477 001044993 082__ $$a570 001044993 1001_ $$0P:(DE-HGF)0$$aZhu, Jianjun$$b0 001044993 245__ $$aAssessing and avoiding C isotopic contamination artefacts in mesocosm-scale 13CO2/12CO2 labelling systems: from biomass components to purified carbohydrates and dark respiration 001044993 260__ $$aLondon$$bBioMed Central$$c2025 001044993 3367_ $$2DRIVER$$aarticle 001044993 3367_ $$2DataCite$$aOutput Types/Journal article 001044993 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1755586770_15232 001044993 3367_ $$2BibTeX$$aARTICLE 001044993 3367_ $$2ORCID$$aJOURNAL_ARTICLE 001044993 3367_ $$00$$2EndNote$$aJournal Article 001044993 520__ $$aQuantitative understanding of plant carbon (C) metabolism by 13CO2/12CO2-labelling studies requires absence (or knowledge) of C-isotopic contamination artefacts during tracer application and sample processing. Surprisingly, this concern has not been addressed systematically and comprehensively yet is especially crucial in experiments at different atmospheric CO2 concentrations ([CO2]), when experimental protocols require frequent access to the labelling chambers. Here, we used a plant growth chamber-based 13CO2/12CO2 gas exchange-facility to address this topic. The facility comprised four independent units, with two chambers routinely operated in parallel under identical conditions except for the isotopic composition of CO2 supplied to them (δ13CCO2 −43.5‰ versus −5.6‰). In this setup, dδ13CX (the measurements-based δ13C-difference between matching samples X collected from the parallel chambers) is expected to equal dδ13CRef (the predictable, non-contaminated δ13C-difference ), if sample-C is completely derived from the contrasting CO2 sources. Accordingly, contamination (fcontam) was determined as fcontam = 1– dδ13CX/dδ13CRef in this experimental setup. Determinations were made for biomass fractions, water-soluble carbohydrate (WSC) components and dark respiration of Lolium perenne (perennial ryegrass) stands following growth for ∼9 weeks at 200, 400 or 800 µmol mol− 1 CO2, with a terminal two weeks-long period of extensive experimental disturbance of the chambers. 001044993 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0 001044993 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de 001044993 7001_ $$0P:(DE-HGF)0$$aHirl, Regina T.$$b1 001044993 7001_ $$0P:(DE-Juel1)194449$$aBaca Cabrera, Juan C.$$b2 001044993 7001_ $$0P:(DE-HGF)0$$aSchäufele, Rudi$$b3$$eCorresponding author 001044993 7001_ $$0P:(DE-HGF)0$$aSchnyder, Hans$$b4 001044993 773__ $$0PERI:(DE-600)2203723-8$$a10.1186/s13007-025-01431-3$$gVol. 21, no. 1, p. 111$$n1$$p111$$tPlant methods$$v21$$x1746-4811$$y2025 001044993 8564_ $$uhttps://juser.fz-juelich.de/record/1044993/files/s13007-025-01431-3-1.pdf$$yOpenAccess 001044993 909CO $$ooai:juser.fz-juelich.de:1044993$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire 001044993 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)194449$$aForschungszentrum Jülich$$b2$$kFZJ 001044993 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$$x0 001044993 9141_ $$y2025 001044993 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 001044993 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bPLANT METHODS : 2022$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bPLANT METHODS : 2022$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-04-10T15:44:10Z 001044993 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-04-10T15:44:10Z 001044993 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences$$d2024-12-28 001044993 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-28 001044993 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0 001044993 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-28 001044993 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0 001044993 980__ $$ajournal 001044993 980__ $$aVDB 001044993 980__ $$aUNRESTRICTED 001044993 980__ $$aI:(DE-Juel1)IBG-3-20101118 001044993 9801_ $$aFullTexts