Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms
The demand for efficient, accurate, and cost-effective methods of measuring soil carbon (C) in agriculture is growing. Traditional approaches are time consuming and expensive, highlighting the need for alternatives. This study tackles the challenge of utilizing laser-induced breakdown spectroscopy (...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Soil Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsoil.2023.1242647/full |
| _version_ | 1797348562722357248 |
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| author | Diego Victor Babos Wesley Nascimento Guedes Vitor Silveira Freitas Fernanda Pavani Silva Fernanda Pavani Silva Marcelo Larsen de Lima Tozo Marcelo Larsen de Lima Tozo Paulino Ribeiro Villas-Boas Ladislau Martin-Neto Débora Marcondes Bastos Pereira Milori |
| author_facet | Diego Victor Babos Wesley Nascimento Guedes Vitor Silveira Freitas Fernanda Pavani Silva Fernanda Pavani Silva Marcelo Larsen de Lima Tozo Marcelo Larsen de Lima Tozo Paulino Ribeiro Villas-Boas Ladislau Martin-Neto Débora Marcondes Bastos Pereira Milori |
| author_sort | Diego Victor Babos |
| collection | DOAJ |
| description | The demand for efficient, accurate, and cost-effective methods of measuring soil carbon (C) in agriculture is growing. Traditional approaches are time consuming and expensive, highlighting the need for alternatives. This study tackles the challenge of utilizing laser-induced breakdown spectroscopy (LIBS) as a more economical method while managing its potential accuracy issues due to physical–chemical matrix effects. A set of 1,019 soil samples from 11 Brazilian farms was analyzed using various univariate and multivariate calibration strategies. The artificial neural network (ANN) demonstrated the best performance with the lowest root mean square error of prediction (RMSEP) of 0.48 wt% C, a 28% reduction compared to the following best calibration method (matrix-matching calibration – MMC inverse regression and multiple linear regression – MLR at 0.67 wt% C). Furthermore, the study revealed a strong correlation between total C determined by LIBS and the elemental CHNS analyzer for soils samples in nine farms (R² ≥ 0.73). The proposed method offers a reliable, rapid, and cost-efficient means of measuring total soil C content, showing that LIBS and ANN modeling can significantly reduce errors compared to other calibration methods. This research fills the knowledge gap in utilizing LIBS for soil C measurement in agriculture, potentially benefiting producers and the soil C credit market. Specific recommendations include further exploration of ANN modeling for broader applications, ensuring that agricultural soil management becomes more accessible and efficient. |
| first_indexed | 2024-03-08T12:07:48Z |
| format | Article |
| id | doaj.art-78fbad50f8bf4c9f87d7379c396ad9c8 |
| institution | Directory Open Access Journal |
| issn | 2673-8619 |
| language | English |
| last_indexed | 2024-03-08T12:07:48Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Soil Science |
| spelling | doaj.art-78fbad50f8bf4c9f87d7379c396ad9c82024-01-23T04:38:33ZengFrontiers Media S.A.Frontiers in Soil Science2673-86192024-01-01310.3389/fsoil.2023.12426471242647Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithmsDiego Victor Babos0Wesley Nascimento Guedes1Vitor Silveira Freitas2Fernanda Pavani Silva3Fernanda Pavani Silva4Marcelo Larsen de Lima Tozo5Marcelo Larsen de Lima Tozo6Paulino Ribeiro Villas-Boas7Ladislau Martin-Neto8Débora Marcondes Bastos Pereira Milori9Brazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilInstitute of Chemistry of São Carlos, University of São Paulo, São Carlos, SP, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilCenter for Exact Sciences and Technology, Federal University of São Carlos, São Carlos, SP, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilBrazilian Agricultural Research Corporation (Embrapa), Embrapa Instrumentation, São Carlos, São Paulo, BrazilThe demand for efficient, accurate, and cost-effective methods of measuring soil carbon (C) in agriculture is growing. Traditional approaches are time consuming and expensive, highlighting the need for alternatives. This study tackles the challenge of utilizing laser-induced breakdown spectroscopy (LIBS) as a more economical method while managing its potential accuracy issues due to physical–chemical matrix effects. A set of 1,019 soil samples from 11 Brazilian farms was analyzed using various univariate and multivariate calibration strategies. The artificial neural network (ANN) demonstrated the best performance with the lowest root mean square error of prediction (RMSEP) of 0.48 wt% C, a 28% reduction compared to the following best calibration method (matrix-matching calibration – MMC inverse regression and multiple linear regression – MLR at 0.67 wt% C). Furthermore, the study revealed a strong correlation between total C determined by LIBS and the elemental CHNS analyzer for soils samples in nine farms (R² ≥ 0.73). The proposed method offers a reliable, rapid, and cost-efficient means of measuring total soil C content, showing that LIBS and ANN modeling can significantly reduce errors compared to other calibration methods. This research fills the knowledge gap in utilizing LIBS for soil C measurement in agriculture, potentially benefiting producers and the soil C credit market. Specific recommendations include further exploration of ANN modeling for broader applications, ensuring that agricultural soil management becomes more accessible and efficient.https://www.frontiersin.org/articles/10.3389/fsoil.2023.1242647/fullartificial neural networktropical soilsoil organic mattersoil analysismatrix-matching calibrationsoil texture |
| spellingShingle | Diego Victor Babos Wesley Nascimento Guedes Vitor Silveira Freitas Fernanda Pavani Silva Fernanda Pavani Silva Marcelo Larsen de Lima Tozo Marcelo Larsen de Lima Tozo Paulino Ribeiro Villas-Boas Ladislau Martin-Neto Débora Marcondes Bastos Pereira Milori Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms Frontiers in Soil Science artificial neural network tropical soil soil organic matter soil analysis matrix-matching calibration soil texture |
| title | Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms |
| title_full | Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms |
| title_fullStr | Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms |
| title_full_unstemmed | Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms |
| title_short | Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms |
| title_sort | laser induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils evaluation of calibration algorithms |
| topic | artificial neural network tropical soil soil organic matter soil analysis matrix-matching calibration soil texture |
| url | https://www.frontiersin.org/articles/10.3389/fsoil.2023.1242647/full |
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