Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils
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 a...
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| Format: | Journal Article |
| Language: | English |
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WILEY
2022
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| Online Access: | http://purl.org/au-research/grants/arc/DP210100420 http://hdl.handle.net/20.500.11937/91030 |
| _version_ | 1848765488686956544 |
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| author | Wetterlind, J. Viscarra Rossel, Raphael Steffens, M. |
| author_facet | Wetterlind, J. Viscarra Rossel, Raphael Steffens, M. |
| author_sort | Wetterlind, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:36:03Z |
| format | Journal Article |
| id | curtin-20.500.11937-91030 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:36:03Z |
| publishDate | 2022 |
| publisher | WILEY |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-910302023-05-22T08:09:06Z Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils Wetterlind, J. Viscarra Rossel, Raphael Steffens, M. Science & Technology Life Sciences & Biomedicine Soil Science Agriculture C-13 NMR C functional groups C turnover mid-IR spectroscopy NIR spectroscopy soil organic matter composition soil organic matter quality NEAR-INFRARED SPECTROSCOPY HYDROFLUORIC-ACID IR SPECTROSCOPY MATTER FRACTIONS QUALITY PREDICT REGRESSION SPECTRA 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. 2022 Journal Article http://hdl.handle.net/20.500.11937/91030 10.1111/ejss.13263 English http://purl.org/au-research/grants/arc/DP210100420 http://creativecommons.org/licenses/by-nc-nd/4.0/ WILEY fulltext |
| spellingShingle | Science & Technology Life Sciences & Biomedicine Soil Science Agriculture C-13 NMR C functional groups C turnover mid-IR spectroscopy NIR spectroscopy soil organic matter composition soil organic matter quality NEAR-INFRARED SPECTROSCOPY HYDROFLUORIC-ACID IR SPECTROSCOPY MATTER FRACTIONS QUALITY PREDICT REGRESSION SPECTRA Wetterlind, J. Viscarra Rossel, Raphael Steffens, M. Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| title | Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| title_full | Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| title_fullStr | Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| title_full_unstemmed | Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| title_short | Diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| title_sort | diffuse reflectance spectroscopy characterises the functional chemistry of soil organic carbon in agricultural soils |
| topic | Science & Technology Life Sciences & Biomedicine Soil Science Agriculture C-13 NMR C functional groups C turnover mid-IR spectroscopy NIR spectroscopy soil organic matter composition soil organic matter quality NEAR-INFRARED SPECTROSCOPY HYDROFLUORIC-ACID IR SPECTROSCOPY MATTER FRACTIONS QUALITY PREDICT REGRESSION SPECTRA |
| url | http://purl.org/au-research/grants/arc/DP210100420 http://hdl.handle.net/20.500.11937/91030 |