Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review
Abstract Soil is a depletable and non-renewable resource essential for food production, crop growth, and supporting ecosystem services, such as the retaining and cycling of various elements, including water. Therefore characterization and preservation of soil biological health is a key point for the...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-024-06381-4 |
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| author | Roberta Pace Vincenzo Schiano Di Cola Maurilia Maria Monti Antonio Affinito Salvatore Cuomo Francesco Loreto Michelina Ruocco |
| author_facet | Roberta Pace Vincenzo Schiano Di Cola Maurilia Maria Monti Antonio Affinito Salvatore Cuomo Francesco Loreto Michelina Ruocco |
| author_sort | Roberta Pace |
| collection | DOAJ |
| description | Abstract Soil is a depletable and non-renewable resource essential for food production, crop growth, and supporting ecosystem services, such as the retaining and cycling of various elements, including water. Therefore characterization and preservation of soil biological health is a key point for the development of sustainable agriculture. We conducted a comprehensive review of the use of Artificial Intelligence (AI) techniques to develop forecasting models based on soil microbiota data able to monitor and predict soil health. We also investigated the potentiality of AI-based Decision Support Systems (DSSs) for improving the use of microorganisms to enhance soil health and fertility. While available studies are limited, potential applications of AI seem relevant to develop predictive models for soil fertility, based on its biological properties and activities, and implement sustainable precision agriculture, safeguarding ecosystems, bolstering soil resilience, and ensuring the production of high-quality food. |
| format | Article |
| id | doaj-art-aaa0645a088849a18ccc06e142565f88 |
| institution | Kabale University |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-aaa0645a088849a18ccc06e142565f882025-01-19T12:34:56ZengSpringerDiscover Applied Sciences3004-92612025-01-017211710.1007/s42452-024-06381-4Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a reviewRoberta Pace0Vincenzo Schiano Di Cola1Maurilia Maria Monti2Antonio Affinito3Salvatore Cuomo4Francesco Loreto5Michelina Ruocco6Dipartimento di Biologia, Complesso Universitario Monte S. Angelo, Università degli Studi di Napoli Federico IIDipartimento di Matematica e Applicazioni R. Caccioppoli, Complesso Universitario Monte S. Angelo, Università degli Studi di Napoli Federico IIIstituto per la Protezione Sostenibile delle Piante, Consiglio Nazionale delle RicercheEVJA s.r.l.Dipartimento di Matematica e Applicazioni R. Caccioppoli, Complesso Universitario Monte S. Angelo, Università degli Studi di Napoli Federico IIDipartimento di Biologia, Complesso Universitario Monte S. Angelo, Università degli Studi di Napoli Federico IIIstituto per la Protezione Sostenibile delle Piante, Consiglio Nazionale delle RicercheAbstract Soil is a depletable and non-renewable resource essential for food production, crop growth, and supporting ecosystem services, such as the retaining and cycling of various elements, including water. Therefore characterization and preservation of soil biological health is a key point for the development of sustainable agriculture. We conducted a comprehensive review of the use of Artificial Intelligence (AI) techniques to develop forecasting models based on soil microbiota data able to monitor and predict soil health. We also investigated the potentiality of AI-based Decision Support Systems (DSSs) for improving the use of microorganisms to enhance soil health and fertility. While available studies are limited, potential applications of AI seem relevant to develop predictive models for soil fertility, based on its biological properties and activities, and implement sustainable precision agriculture, safeguarding ecosystems, bolstering soil resilience, and ensuring the production of high-quality food.https://doi.org/10.1007/s42452-024-06381-4Soil healthMicrobial soil communityArtificial IntelligenceForecasting modelsDecision Support Systems |
| spellingShingle | Roberta Pace Vincenzo Schiano Di Cola Maurilia Maria Monti Antonio Affinito Salvatore Cuomo Francesco Loreto Michelina Ruocco Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review Discover Applied Sciences Soil health Microbial soil community Artificial Intelligence Forecasting models Decision Support Systems |
| title | Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review |
| title_full | Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review |
| title_fullStr | Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review |
| title_full_unstemmed | Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review |
| title_short | Artificial intelligence in soil microbiome analysis: a potential application in predicting and enhancing soil health—a review |
| title_sort | artificial intelligence in soil microbiome analysis a potential application in predicting and enhancing soil health a review |
| topic | Soil health Microbial soil community Artificial Intelligence Forecasting models Decision Support Systems |
| url | https://doi.org/10.1007/s42452-024-06381-4 |
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