Articles | Volume 7, issue 1
https://doi.org/10.5194/soil-7-33-2021
© Author(s) 2021. 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-7-33-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
22 Jan 2021
Original research article |
| 22 Jan 2021
| 22 Jan 2021
Mapping soil slaking index and assessing the impact of management in a mixed agricultural landscape
Edward J. Jones
CORRESPONDING AUTHOR
School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science, The University of Sydney, New South Wales, Australia
Patrick Filippi
School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science, The University of Sydney, New South Wales, Australia
Rémi Wittig
École Nationale Supérieure d'Agronomie et des Industries Alimentaires (ENSAIA), University of Lorraine, Nancy, France
Mario Fajardo
School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science, The University of Sydney, New South Wales, Australia
Vanessa Pino
School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science, The University of Sydney, New South Wales, Australia
Alex B. McBratney
School of Life and Environmental Sciences & Sydney Institute of Agriculture, Faculty of Science, The University of Sydney, New South Wales, Australia
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Cited
14 citations as recorded by crossref.
- Depth to sodicity constraint mapping of the Murray-Darling Basin, Australia L. Pozza et al. 10.1016/j.geoderma.2022.116181
- The QuantiSlakeTest, measuring soil structural stability by dynamic weighing of undisturbed samples immersed in water F. Vanwindekens & B. Hardy 10.5194/soil-9-573-2023
- Geospatial Artificial Intelligence (GeoAI) and Satellite Imagery Fusion for Soil Physical Property Predicting F. Hosseini et al. 10.3390/su151914125
- Spatial prediction of soil aggregate stability and soil organic carbon in aggregate fractions using machine learning algorithms and environmental variables M. Zeraatpisheh et al. 10.1016/j.geodrs.2021.e00440
- Evaluation of Aggregate Stability Using the Slaking Index Method with Soil Physical Approach in Keduang Sub-Watershed, Indonesia N. Istiqomah et al. 10.29133/yyutbd.1407811
- Description of ASTAVIT, a rapid assessment method of soil structural stability based on image recognition J. Wengler et al. 10.1016/j.still.2024.106222
- Wet aggregate stability modeling based on support vector machine in multiuse soils R. Zhai et al. 10.1177/15501329221107573
- Developing and testing of pedogenons in the lower Namoi valley, NSW, Australia H. Jang et al. 10.1016/j.geoderma.2022.116182
- Relations between soil organic carbon content and the pore size distribution for an arable topsoil with large variations in soil properties J. Fukumasu et al. 10.1111/ejss.13212
- Soil Aggregate Stability Mapping Using Remote Sensing and GIS-Based Machine Learning Technique Y. Bouslihim et al. 10.3389/feart.2021.748859
- Optimising POXC effective sensitivity as a soil indicator in Australian soils E. Jones et al. 10.1016/j.soisec.2023.100116
- Machine learning-based soil aggregation assessment under four scenarios in northwestern Iran P. Nazeri et al. 10.31545/intagr/188506
- Image-based soil characterization: A review on smartphone applications M. Naeimi et al. 10.1016/j.compag.2024.109502
- Using soil erosion as an indicator for integrated water resources management: a case study of Ruiru drinking water reservoir, Kenya A. Kamamia et al. 10.1007/s12665-022-10617-0
13 citations as recorded by crossref.
- Depth to sodicity constraint mapping of the Murray-Darling Basin, Australia L. Pozza et al. 10.1016/j.geoderma.2022.116181
- The QuantiSlakeTest, measuring soil structural stability by dynamic weighing of undisturbed samples immersed in water F. Vanwindekens & B. Hardy 10.5194/soil-9-573-2023
- Geospatial Artificial Intelligence (GeoAI) and Satellite Imagery Fusion for Soil Physical Property Predicting F. Hosseini et al. 10.3390/su151914125
- Spatial prediction of soil aggregate stability and soil organic carbon in aggregate fractions using machine learning algorithms and environmental variables M. Zeraatpisheh et al. 10.1016/j.geodrs.2021.e00440
- Evaluation of Aggregate Stability Using the Slaking Index Method with Soil Physical Approach in Keduang Sub-Watershed, Indonesia N. Istiqomah et al. 10.29133/yyutbd.1407811
- Description of ASTAVIT, a rapid assessment method of soil structural stability based on image recognition J. Wengler et al. 10.1016/j.still.2024.106222
- Wet aggregate stability modeling based on support vector machine in multiuse soils R. Zhai et al. 10.1177/15501329221107573
- Developing and testing of pedogenons in the lower Namoi valley, NSW, Australia H. Jang et al. 10.1016/j.geoderma.2022.116182
- Relations between soil organic carbon content and the pore size distribution for an arable topsoil with large variations in soil properties J. Fukumasu et al. 10.1111/ejss.13212
- Soil Aggregate Stability Mapping Using Remote Sensing and GIS-Based Machine Learning Technique Y. Bouslihim et al. 10.3389/feart.2021.748859
- Optimising POXC effective sensitivity as a soil indicator in Australian soils E. Jones et al. 10.1016/j.soisec.2023.100116
- Machine learning-based soil aggregation assessment under four scenarios in northwestern Iran P. Nazeri et al. 10.31545/intagr/188506
- Image-based soil characterization: A review on smartphone applications M. Naeimi et al. 10.1016/j.compag.2024.109502
Latest update: 23 Nov 2024
Short summary
Soil physical health is integral to maintaining functional agro-ecosystems. A novel method of assessing soil physical condition using a smartphone app has been developed – SLAKES. In this study the SLAKES app was used to investigate aggregate stability in a mixed agricultural landscape. Cropping areas were found to have significantly poorer physical health than similar soils under pasture. Results were mapped across the landscape to identify problem areas and pinpoint remediation efforts.
Soil physical health is integral to maintaining functional agro-ecosystems. A novel method of...
