Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data

Analysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC-MS or LC-MS). MS instrumentation can b...

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Main Authors: Bruhn, Anders Dalhoff, Wunsch, Urban, Osburn, Christopher L., Rudolph, Jacob C., Stedmon, Colin A.
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Online Access:https://orbit.dtu.dk/en/publications/f5c4c35b-6da8-4a10-bc11-4772bce390cf
https://doi.org/10.1002/lom3.10561
https://backend.orbit.dtu.dk/ws/files/332288087/Limnology_Ocean_Methods_2023_Bruhn.pdf
https://doi.org/10.11583/DTU.22182694.v1
https://doi.org/10.11583/DTU.22178825.v1
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spelling ftdtupubl:oai:pure.atira.dk:publications/f5c4c35b-6da8-4a10-bc11-4772bce390cf 2024-09-15T18:03:32+00:00 Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data Bruhn, Anders Dalhoff Wunsch, Urban Osburn, Christopher L. Rudolph, Jacob C. Stedmon, Colin A. 2023 application/pdf https://orbit.dtu.dk/en/publications/f5c4c35b-6da8-4a10-bc11-4772bce390cf https://doi.org/10.1002/lom3.10561 https://backend.orbit.dtu.dk/ws/files/332288087/Limnology_Ocean_Methods_2023_Bruhn.pdf https://doi.org/10.11583/DTU.22182694.v1 https://doi.org/10.11583/DTU.22178825.v1 eng eng https://orbit.dtu.dk/en/publications/f5c4c35b-6da8-4a10-bc11-4772bce390cf info:eu-repo/semantics/openAccess Bruhn , A D , Wunsch , U , Osburn , C L , Rudolph , J C & Stedmon , C A 2023 , ' Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data ' , Limnology and Oceanography: Methods , vol. 21 , no. 8 , pp. 508-528 . https://doi.org/10.1002/lom3.10561 article 2023 ftdtupubl https://doi.org/10.1002/lom3.1056110.11583/DTU.22182694.v110.11583/DTU.22178825.v1 2024-08-13T00:03:06Z Analysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC-MS or LC-MS). MS instrumentation can be relatively expensive to purchase and maintain. Here we present an improved approach for quantification of lignin phenols using LC and absorbance detection. The approach applies a modified version of parallel factor analysis (PARAFAC2) to 2 nd derivative absorbance chromatograms. It is capable of isolating individual elution profiles of analytes despite co-elution and overall improves sensitivity and specificity, compared to manual integration methods. For most lignin phenols, detection limits below 5 nmol L -1 were achieved, which is comparable to MS detection. The reproducibility across all laboratory stages for our reference material showed a relative standard deviation between 1.47% and 16.84% for all 11 lignin phenols. Changing the amount of DOM in the reaction vessel for the oxidation (dissolved organic carbon between 22 and 367 mmol L -1 ), did not significantly affect the final lignin phenol composition. The new method was applied to seawater samples from the Kattegat and Davis Strait. The total concentration of dissolved lignin phenols measured in the two areas was between 4.3-10.1 and 2.1-3.2 nmol L -1 , respectively, which is within the range found by other studies. Comparison with a different oxidation approach and detection method (GC-MS) gave similar results and underline the potential of LC and absorbance detection for analysis of dissolved lignin with our proposed method. Article in Journal/Newspaper Davis Strait Technical University of Denmark: DTU Orbit
institution Open Polar
collection Technical University of Denmark: DTU Orbit
op_collection_id ftdtupubl
language English
description Analysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC-MS or LC-MS). MS instrumentation can be relatively expensive to purchase and maintain. Here we present an improved approach for quantification of lignin phenols using LC and absorbance detection. The approach applies a modified version of parallel factor analysis (PARAFAC2) to 2 nd derivative absorbance chromatograms. It is capable of isolating individual elution profiles of analytes despite co-elution and overall improves sensitivity and specificity, compared to manual integration methods. For most lignin phenols, detection limits below 5 nmol L -1 were achieved, which is comparable to MS detection. The reproducibility across all laboratory stages for our reference material showed a relative standard deviation between 1.47% and 16.84% for all 11 lignin phenols. Changing the amount of DOM in the reaction vessel for the oxidation (dissolved organic carbon between 22 and 367 mmol L -1 ), did not significantly affect the final lignin phenol composition. The new method was applied to seawater samples from the Kattegat and Davis Strait. The total concentration of dissolved lignin phenols measured in the two areas was between 4.3-10.1 and 2.1-3.2 nmol L -1 , respectively, which is within the range found by other studies. Comparison with a different oxidation approach and detection method (GC-MS) gave similar results and underline the potential of LC and absorbance detection for analysis of dissolved lignin with our proposed method.
format Article in Journal/Newspaper
author Bruhn, Anders Dalhoff
Wunsch, Urban
Osburn, Christopher L.
Rudolph, Jacob C.
Stedmon, Colin A.
spellingShingle Bruhn, Anders Dalhoff
Wunsch, Urban
Osburn, Christopher L.
Rudolph, Jacob C.
Stedmon, Colin A.
Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
author_facet Bruhn, Anders Dalhoff
Wunsch, Urban
Osburn, Christopher L.
Rudolph, Jacob C.
Stedmon, Colin A.
author_sort Bruhn, Anders Dalhoff
title Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
title_short Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
title_full Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
title_fullStr Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
title_full_unstemmed Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
title_sort lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data
publishDate 2023
url https://orbit.dtu.dk/en/publications/f5c4c35b-6da8-4a10-bc11-4772bce390cf
https://doi.org/10.1002/lom3.10561
https://backend.orbit.dtu.dk/ws/files/332288087/Limnology_Ocean_Methods_2023_Bruhn.pdf
https://doi.org/10.11583/DTU.22182694.v1
https://doi.org/10.11583/DTU.22178825.v1
genre Davis Strait
genre_facet Davis Strait
op_source Bruhn , A D , Wunsch , U , Osburn , C L , Rudolph , J C & Stedmon , C A 2023 , ' Lignin phenol quantification from machine learning-assisted decomposition of liquid chromatography-absorbance spectroscopy data ' , Limnology and Oceanography: Methods , vol. 21 , no. 8 , pp. 508-528 . https://doi.org/10.1002/lom3.10561
op_relation https://orbit.dtu.dk/en/publications/f5c4c35b-6da8-4a10-bc11-4772bce390cf
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1002/lom3.1056110.11583/DTU.22182694.v110.11583/DTU.22178825.v1
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