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dc.contributor.authorWetterlind, J.
dc.contributor.authorViscarra Rossel, Raphael
dc.contributor.authorSteffens, M.
dc.date.accessioned2023-03-16T03:57:47Z
dc.date.available2023-03-16T03:57:47Z
dc.date.issued2022
dc.identifier.citationWetterlind, J. and Viscarra Rossel, R.A. and Steffens, M. 2022. Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils. European Journal of Soil Science. 73 (4): ARTN e13263.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/91030
dc.identifier.doi10.1111/ejss.13263
dc.description.abstract

Soil organic carbon (SOC) originates from a complex mixture of organic materials, and to better understand its role in soil functions, one must characterise its chemical composition. However, current methods, such as solid-state 13C nuclear magnetic resonance (NMR) spectroscopy, are time-consuming and expensive. Diffuse reflectance spectroscopy in the visible, near infrared and mid-infrared regions (vis–NIR: 350–2500 nm; mid-IR: 4000–400 cm−1) can also be used to characterise SOC chemistry; however, it is difficult to know the frequencies where the information occurs. Thus, we correlated the C functional groups from the 13C NMR to the frequencies in the vis–NIR and mid-IR spectra using two methods: (1) 2-dimensional correlations of 13C NMR spectra and the diffuse reflectance spectra, and (2) modelling the NMR functional C groups with the reflectance spectra using support vector machines (SVM) (validated using 5 times repeated 10-fold cross-validation). For the study, we used 99 mineral soils from the agricultural regions of Sweden. The results show clear correlations between organic functional C groups measured with NMR and specific frequencies in the vis–NIR and mid-IR spectra. While the 2D correlations showed general relationships (mainly related to the total SOC content), analysing the importance of the wavelengths in the SVM models revealed more detail. Generally, models using mid-IR spectra produced slightly better estimates than the vis–NIR. The best estimates were for the alkyl C group (R2 = 0.83 and 0.85, vis–NIR and mid-IR, respectively), and the O/N-alkyl C group was the most difficult to estimate (R2 = 0.34 and 0.38, vis–NIR and mid-IR, respectively). Combining 13C NMR with the cost-effective diffuse reflectance methods could potentially increase the number of measured samples and improve the spatial and temporal characterisation of SOC. However, more studies with a wider range of soil types and land management systems are needed to further evaluate the conditions under which these methods could be used. Highlights: Diffuse reflectance spectroscopy was used to characterise and model SOC functional chemistry. NMR derived C functional groups could be modelled with vis-NIR and mid-IR diffuse reflectance spectra. The methods allow for characterisation of SOC chemical composition on whole mineral soil samples. The approach can improve the spatial and temporal characterisation of SOC composition.

dc.languageEnglish
dc.publisherWILEY
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP210100420
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectSoil Science
dc.subjectAgriculture
dc.subjectC-13 NMR
dc.subjectC functional groups
dc.subjectC turnover
dc.subjectmid-IR spectroscopy
dc.subjectNIR spectroscopy
dc.subjectsoil organic matter composition
dc.subjectsoil organic matter quality
dc.subjectNEAR-INFRARED SPECTROSCOPY
dc.subjectHYDROFLUORIC-ACID
dc.subjectIR SPECTROSCOPY
dc.subjectMATTER
dc.subjectFRACTIONS
dc.subjectQUALITY
dc.subjectPREDICT
dc.subjectREGRESSION
dc.subjectSPECTRA
dc.titleDiffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils
dc.typeJournal Article
dcterms.source.volume73
dcterms.source.number4
dcterms.source.issn1351-0754
dcterms.source.titleEuropean Journal of Soil Science
dc.date.updated2023-03-16T03:57:47Z
curtin.departmentSchool of Molecular and Life Sciences (MLS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidViscarra Rossel, Raphael [0000-0003-1540-4748]
curtin.contributor.researcheridViscarra Rossel, Raphael [B-4061-2011]
curtin.identifier.article-numberARTN e13263
dcterms.source.eissn1365-2389
curtin.contributor.scopusauthoridViscarra Rossel, Raphael [55900800400]
curtin.repositoryagreementV3


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