Articles | Volume 9, issue 1
https://doi.org/10.5194/soil-9-155-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-9-155-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
14 Mar 2023
Original research article |
| 14 Mar 2023
| 14 Mar 2023
Potential of natural language processing for metadata extraction from environmental scientific publications
Guillaume Blanchy
CORRESPONDING AUTHOR
Department of Plant, Flanders Research Institute for Agriculture, Fisheries and Food
(ILVO), Melle, Belgium
Lukas Albrecht
Soil Fertility and Soil Protection, Agroscope, Reckenholzstrasse 191, 8046, Zurich, Switzerland
John Koestel
Soil Fertility and Soil Protection, Agroscope, Reckenholzstrasse 191, 8046, Zurich, Switzerland
Department of Soil and Environment, Institute for Soil and Environment, Swedish University of Agricultural
Sciences, Box 7014, 75007 Uppsala, Sweden
Sarah Garré
Department of Plant, Flanders Research Institute for Agriculture, Fisheries and Food
(ILVO), Melle, Belgium
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Cited
17 citations as recorded by crossref.
- Opportunities and Challenges for Sustainable Agricultural Soil Management in Switzerland K. Jarosch et al. https://doi.org/10.1111/ejss.70355
- Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies Y. Huang et al. https://doi.org/10.1016/j.xgen.2025.100845
- Response of soil biota to agricultural management practices: A systematic quantitative meta-data-analysis and method selection framework M. Lori et al. https://doi.org/10.1016/j.soilbio.2025.109815
- Evidence-Grounded Decision Support for Aircraft Line Maintenance Using Conformal Prediction and Retrieval-Augmented NLP from Technical Log Records A. Dela Peña et al. https://doi.org/10.2478/tar-2026-0009
- The soil knowledge library (KLIB) – a structured literature database on soil process research H. Vogel et al. https://doi.org/10.5194/soil-9-533-2023
- Molecular insights fast-tracked: AI in biosynthetic pathway research L. Liao et al. https://doi.org/10.1039/D4NP00003J
- Rapid evidence mapping of soil fauna responses to agricultural management assisted by large language models R. Leitao et al. https://doi.org/10.1016/j.geoderma.2026.117890
- Full-Text eBook Retrieval System in an Integrated Library Management System: Designing an Open- Source Technical Framework D. Barman et al. https://doi.org/10.17821/srels/2025/v62i4/171706
- Impact of Soil Improvers on Soil Health: A Data Mining Approach to Support Sustainable Agriculture Across the EU L. Nolfi et al. https://doi.org/10.3390/environments12120472
- Enhancing soil science research with multi-agent artificial intelligence systems B. Minasny et al. https://doi.org/10.3389/fsci.2026.1721295
- Framing Concepts of Agriculture 5.0 via Bipartite Analysis I. Bergier et al. https://doi.org/10.3390/su162410851
- Enhanced semantic classification of microbiome sample origins using large language models (LLMs) D. Gaio et al. https://doi.org/10.1093/gigascience/giag015
- Soil Data Extraction from Scientific Publications Using Large Language Models M. Soldatkina et al. https://doi.org/10.1134/S1064229325605529
- Digital integration in eco-construction 2.0: Advancing sustainability through technology A. Firoozi & A. Firoozi https://doi.org/10.1016/j.sftr.2025.101310
- Irrigation with Artificial Intelligence: Problems, Premises, Promises H. Wei et al. https://doi.org/10.1007/s44230-024-00072-4
- Artificial intelligence in soil science A. Wadoux https://doi.org/10.1111/ejss.70080
- Cd adsorption prediction of Fe mono/composite modified biochar based on machine learning: Application for controllable preparation X. Xiang et al. https://doi.org/10.1016/j.envres.2024.120466
17 citations as recorded by crossref.
- Opportunities and Challenges for Sustainable Agricultural Soil Management in Switzerland K. Jarosch et al. https://doi.org/10.1111/ejss.70355
- Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies Y. Huang et al. https://doi.org/10.1016/j.xgen.2025.100845
- Response of soil biota to agricultural management practices: A systematic quantitative meta-data-analysis and method selection framework M. Lori et al. https://doi.org/10.1016/j.soilbio.2025.109815
- Evidence-Grounded Decision Support for Aircraft Line Maintenance Using Conformal Prediction and Retrieval-Augmented NLP from Technical Log Records A. Dela Peña et al. https://doi.org/10.2478/tar-2026-0009
- The soil knowledge library (KLIB) – a structured literature database on soil process research H. Vogel et al. https://doi.org/10.5194/soil-9-533-2023
- Molecular insights fast-tracked: AI in biosynthetic pathway research L. Liao et al. https://doi.org/10.1039/D4NP00003J
- Rapid evidence mapping of soil fauna responses to agricultural management assisted by large language models R. Leitao et al. https://doi.org/10.1016/j.geoderma.2026.117890
- Full-Text eBook Retrieval System in an Integrated Library Management System: Designing an Open- Source Technical Framework D. Barman et al. https://doi.org/10.17821/srels/2025/v62i4/171706
- Impact of Soil Improvers on Soil Health: A Data Mining Approach to Support Sustainable Agriculture Across the EU L. Nolfi et al. https://doi.org/10.3390/environments12120472
- Enhancing soil science research with multi-agent artificial intelligence systems B. Minasny et al. https://doi.org/10.3389/fsci.2026.1721295
- Framing Concepts of Agriculture 5.0 via Bipartite Analysis I. Bergier et al. https://doi.org/10.3390/su162410851
- Enhanced semantic classification of microbiome sample origins using large language models (LLMs) D. Gaio et al. https://doi.org/10.1093/gigascience/giag015
- Soil Data Extraction from Scientific Publications Using Large Language Models M. Soldatkina et al. https://doi.org/10.1134/S1064229325605529
- Digital integration in eco-construction 2.0: Advancing sustainability through technology A. Firoozi & A. Firoozi https://doi.org/10.1016/j.sftr.2025.101310
- Irrigation with Artificial Intelligence: Problems, Premises, Promises H. Wei et al. https://doi.org/10.1007/s44230-024-00072-4
- Artificial intelligence in soil science A. Wadoux https://doi.org/10.1111/ejss.70080
- Cd adsorption prediction of Fe mono/composite modified biochar based on machine learning: Application for controllable preparation X. Xiang et al. https://doi.org/10.1016/j.envres.2024.120466
Saved (final revised paper)
Latest update: 06 Jul 2026
Short summary
Adapting agricultural practices to future climatic conditions requires us to synthesize the effects of management practices on soil properties with respect to local soil and climate. We showcase different automated text-processing methods to identify topics, extract metadata for building a database and summarize findings from publication abstracts. While human intervention remains essential, these methods show great potential to support evidence synthesis from large numbers of publications.
Adapting agricultural practices to future climatic conditions requires us to synthesize the...
