Results 31 to 40 of about 141 (130)

Advancing Soil Organic Carbon Prediction: A Comprehensive Review of Technologies, AI, Process‐Based and Hybrid Modelling Approaches

Advanced Science, Volume 12, Issue 31, August 21, 2025.
This review highlights advances in soil organic carbon (SOC) quantification using remote sensing, proximal soil sensing, AI (ML and DL), and biogeochemical modelling. Integrating diverse data sources and models improves SOC prediction accuracy. Key priorities include enhancing data availability, refining models, incorporating microbial processes, and ...
Zijuan Ding, Ke Liu, Sabine Grunwald, Pete Smith, Philippe Ciais, Bin Wang, Alexandre M.J.‐C. Wadoux, Carla Ferreira, Senani Karunaratne, Narasinha Shurpali, Xiaogang Yin, Dale Roberts, Oli Madgett, Sam Duncan, Meixue Zhou, Zhangyong Liu, Matthew Tom Harrison   +16 more
wiley   +1 more source

Agriculture 4.0 as a way forward to sustainable agriculture in Australia

JSFA reports, Volume 5, Issue 8, Page 337-358, August 2025.
Abstract Background Agriculture in Australia faces significant challenges driven by climate change, including extreme weather events, prolonged droughts, biodiversity loss and declining productivity. These pressures demand innovative solutions to ensure the sustainability and resilience of agricultural systems.
Fahad Khan
wiley   +1 more source

A Note on Spurious Correlations and Explainable Machine Learning in Digital Soil Mapping

European Journal of Soil Science, Volume 76, Issue 4, July–August 2025.
ABSTRACT The use of machine learning as a method for knowledge discovery is often critically discussed in soil science and related environmental disciplines. Reviews of the use of machine learning in digital soil mapping identified few studies that incorporated existing soil knowledge of transformation and translocation processes in soils and ...
Tobias Rentschler, Thomas Scholten
wiley   +1 more source

Hyperspectral Soil Heavy Metal Prediction via Privileged-Informed Residual Correction

Remote Sensing
This study integrates hyperspectral remote sensing with chemical and pedological data to estimate Zn, Pb, and Cd concentrations in the upper soil layers.
Alen Mangafić, Krištof Oštir, Mitja Kolar, Marko Zupan   +3 more
doaj   +1 more source

Artificial intelligence in soil science

European Journal of Soil Science, Volume 76, Issue 2, March–April 2025.
ABSTRACT Few would disagree that artificial intelligence (AI) holds potential for advancing knowledge and innovation. Over the past decades, substantial research has been devoted to the development and application of AI in soil science. While most of today's AI applications in soil science are related to machine learning (ML), AI also encompasses other
Alexandre M. J.‐C. Wadoux
wiley   +1 more source

Development of soil spectroscopy models for the Western Highveld region, South Africa: Why do we need local data?

European Journal of Soil Science, Volume 75, Issue 6, November-December 2024.
Abstract The increasing global demand for sustainable agriculture requires accurate and efficient soil analysis methods. Conventional laboratory techniques are often time‐consuming, costly and environmentally damaging. To address this challenge, we developed and validated locally calibrated mid‐infrared (MIR) spectroscopy models for predicting key soil
Anru‐Louis Kock, Prudence Dimakatso Ramphisa‐Nghondzweni, George Van Zijl   +2 more
wiley   +1 more source

Connecting forest soil properties with ecosystem services: Toward a better use of digital soil maps—A review

Soil Science Society of America Journal, Volume 88, Issue 4, Page 981-999, July/August 2024.
Abstract The soil supports many ecosystem services (ES) essential to human well‐being. Rapid developments in digital soil mapping (DSM) allow the mapping of soil types and soil properties with improved resolution and accuracy. However, the potential of DSM to improve the assessment and mapping of ES is not fully exploited.
David Paré, Fidèle Bognounou, Erik J. S. Emilson, Jérôme Laganière, Jason Leach, Nicolas Mansuy, Christine Martineau, Charlotte Norris, Lisa Venier, Kara Webster   +9 more
wiley   +1 more source

Resistance against tree encroachment is driven by richness and identity of herbaceous resident species

Applied Vegetation Science, Volume 27, Issue 2, April/June 2024.
Herbaceous plant covers can inhibit tree encroachment in many managed and semi‐natural grasslands, yet identifying the primary influence of seed mixture composition or diversity poses challenges. This study reveals that herbaceous species identity more accurately predicts seed mixture resistance to tree encroachment.
Rolando Trejo‐Pérez, Pierre‐Luc Chagnon, Patrick Boivin, Jacques Brisson   +3 more
wiley   +1 more source

Mapping soil corrosivity potential to exclusion fencing using pedotransfer functions and open‐source soil data

Soil Use and Management, Volume 40, Issue 1, January 2024.
Abstract Soil corrosivity is a term used to describe the corroding susceptibility (risk) of metal infrastructure in different soil environments. Soil corrosivity mapping is a crucial step in identifying potentially problematic, high‐maintenance fence lines and can help improve fence longevity by identifying soil environments where the use of more ...
Andrea D. Stiglingh, Luke M. Mosley, Ronald J. Smernik, Robert W. Fitzpatrick   +3 more
wiley   +1 more source

Pedometrics Research in the Vadose Zone—Review and Perspectives

Vadose Zone Journal, 2013
Pedometrics is the application of mathematical and statistical methods for the study of the distribution and genesis of soils. Pedometrics research in the vadose zone comprises studies of the spatial and temporal dynamics of soil properties as a scientific challenge to increase our understanding of the processes at the earth's surface.
Budiman Minasny, Brett M. Whelan, John Triantafilis, Alex. B. McBratney   +3 more
openaire   +1 more source