Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin
In recent years, lignin analysis utilizing quantitative nuclear magnetic resonance (qNMR) has attracted considerable interest and has been the subject of numerous studies. However, evaluating the measurement uncertainty of qNMR results of lignin remains a challenge. Specifically, uncertainty origina...
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North Carolina State University
2025-01-01
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| author | Shrikant Shivaji Pawade Lauri Toom Koit Herodes Ivo Leito |
| author_facet | Shrikant Shivaji Pawade Lauri Toom Koit Herodes Ivo Leito |
| author_sort | Shrikant Shivaji Pawade |
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| description | In recent years, lignin analysis utilizing quantitative nuclear magnetic resonance (qNMR) has attracted considerable interest and has been the subject of numerous studies. However, evaluating the measurement uncertainty of qNMR results of lignin remains a challenge. Specifically, uncertainty originating from lignin sampling or subsampling has been overlooked in a large majority of articles. Although lignin is a reasonably homogeneous substance, it is nevertheless a solid, and individual samples collected from the same bulk may have somewhat different compositions depending on mixing and the amount of sample taken. The objective of this study was to evaluate the influence of sampling uncertainty on qNMR analysis of lignin-based analysis as a case study, with an exclusive focus on the relative quantification method. The results from this study demonstrate that sample-to-sample variations can contribute to approximately half of the variability in actual qNMR measurements. The relative standard deviation (RSD) of sample-to-sample variability was 2.4%. In contrast, the other sources of variability related to qNMR, including measurement, baseline irregularities, and partial peak overlap, caused an RSD of 4.4%. The total variability RSD was 5.0%. In this article, two calculation approaches were presented for evaluating the uncertainty due to sampling from replicate measurement data of different samples, which may be helpful for practitioners in the field. |
| format | Article |
| id | doaj-art-10db5185e8494225b1ebe48728f59b1c |
| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
| publisher | North Carolina State University |
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| spelling | doaj-art-10db5185e8494225b1ebe48728f59b1c2025-02-10T23:56:27ZengNorth Carolina State UniversityBioResources1930-21262025-01-01201223422422717Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of LigninShrikant Shivaji Pawade0https://orcid.org/0000-0002-8457-3644Lauri Toom1https://orcid.org/0000-0001-9693-8180Koit Herodes2https://orcid.org/0000-0003-1763-1784Ivo Leito3https://orcid.org/0000-0002-3000-4964University of Tartu, Institute of Chemistry, Ravila 14a, 50411 Tartu, EstoniaUniversity of Tartu, Institute of Chemistry, Ravila 14a, 50411 Tartu, EstoniaUniversity of Tartu, Institute of Chemistry, Ravila 14a, 50411 Tartu, EstoniaUniversity of Tartu, Institute of Chemistry, Ravila 14a, 50411 Tartu, EstoniaIn recent years, lignin analysis utilizing quantitative nuclear magnetic resonance (qNMR) has attracted considerable interest and has been the subject of numerous studies. However, evaluating the measurement uncertainty of qNMR results of lignin remains a challenge. Specifically, uncertainty originating from lignin sampling or subsampling has been overlooked in a large majority of articles. Although lignin is a reasonably homogeneous substance, it is nevertheless a solid, and individual samples collected from the same bulk may have somewhat different compositions depending on mixing and the amount of sample taken. The objective of this study was to evaluate the influence of sampling uncertainty on qNMR analysis of lignin-based analysis as a case study, with an exclusive focus on the relative quantification method. The results from this study demonstrate that sample-to-sample variations can contribute to approximately half of the variability in actual qNMR measurements. The relative standard deviation (RSD) of sample-to-sample variability was 2.4%. In contrast, the other sources of variability related to qNMR, including measurement, baseline irregularities, and partial peak overlap, caused an RSD of 4.4%. The total variability RSD was 5.0%. In this article, two calculation approaches were presented for evaluating the uncertainty due to sampling from replicate measurement data of different samples, which may be helpful for practitioners in the field.https://ojs.bioresources.com/index.php/BRJ/article/view/24185 ligninnmrquantitative nmr samplinguncertainty |
| spellingShingle | Shrikant Shivaji Pawade Lauri Toom Koit Herodes Ivo Leito Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin BioResources lignin nmr quantitative nmr sampling uncertainty |
| title | Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin |
| title_full | Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin |
| title_fullStr | Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin |
| title_full_unstemmed | Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin |
| title_short | Evaluating Sampling Uncertainty in the Quantitative 1H Nuclear Magnetic Resonance Analysis of Lignin |
| title_sort | evaluating sampling uncertainty in the quantitative 1h nuclear magnetic resonance analysis of lignin |
| topic | lignin nmr quantitative nmr sampling uncertainty |
| url | https://ojs.bioresources.com/index.php/BRJ/article/view/24185 |
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