Articles | Volume 7, issue 2
https://doi.org/10.5194/soil-7-717-2021
© 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-7-717-2021
© 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
| 
27 Oct 2021
Original research article |
| 27 Oct 2021
| 27 Oct 2021
Estimation of soil properties with mid-infrared soil spectroscopy across yam production landscapes in West Africa
Philipp Baumann
CORRESPONDING AUTHOR
Group of Sustainable Agroecosystems, Institute of Agricultural Sciences, ETH Zurich, 8092 Zürich, Switzerland
Juhwan Lee
Department of Smart Agro-industry, Gyeongsang National University, Jinju, 52725, Republic of Korea
Emmanuel Frossard
Group of Plant Nutrition, Institute of Agricultural Sciences, ETH Zurich, 8315 Lindau, Switzerland
Laurie Paule Schönholzer
Group of Plant Nutrition, Institute of Agricultural Sciences, ETH Zurich, 8315 Lindau, Switzerland
Lucien Diby
World Agroforestry Centre (ICRAF), Côte d’Ivoire Country Programme, BP 2823 Abidjan, Côte d’Ivoire
Valérie Kouamé Hgaza
Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, 01 BP 1303 Abidjan, Côte d’Ivoire
Département d’Agrophysiologie des Plantes, Université Peleforo Gon Coulibaly, BP 1328 Korhogo, Côte d’Ivoire
Delwende Innocent Kiba
Group of Plant Nutrition, Institute of Agricultural Sciences, ETH Zurich, 8315 Lindau, Switzerland
Département Gestion des Ressources Naturelles et Systèmes de Production, Centre National de la Recherche Scientifique et Technologique, Institut de l'Environnement et Recherches Agricoles, 01 BP 476 Ouagadougou, Burkina Faso
Andrew Sila
Land Health Decisions, World Agroforestry Centre (ICRAF), Nairobi, Kenya
Keith Sheperd
Land Health Decisions, World Agroforestry Centre (ICRAF), Nairobi, Kenya
Johan Six
Group of Sustainable Agroecosystems, Institute of Agricultural Sciences, ETH Zurich, 8092 Zürich, Switzerland
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Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
SOIL, 7, 525–546, https://doi.org/10.5194/soil-7-525-2021, https://doi.org/10.5194/soil-7-525-2021, 2021
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SOIL, 7, 453–475, https://doi.org/10.5194/soil-7-453-2021, https://doi.org/10.5194/soil-7-453-2021, 2021
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Sophie F. von Fromm, Alison M. Hoyt, Markus Lange, Gifty E. Acquah, Ermias Aynekulu, Asmeret Asefaw Berhe, Stephan M. Haefele, Steve P. McGrath, Keith D. Shepherd, Andrew M. Sila, Johan Six, Erick K. Towett, Susan E. Trumbore, Tor-G. Vågen, Elvis Weullow, Leigh A. Winowiecki, and Sebastian Doetterl
SOIL, 7, 305–332, https://doi.org/10.5194/soil-7-305-2021, https://doi.org/10.5194/soil-7-305-2021, 2021
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We investigated various soil and climate properties that influence soil organic carbon (SOC) concentrations in sub-Saharan Africa. Our findings indicate that climate and geochemistry are equally important for explaining SOC variations. The key SOC-controlling factors are broadly similar to those for temperate regions, despite differences in soil development history between the two regions.
Anatol Helfenstein, Philipp Baumann, Raphael Viscarra Rossel, Andreas Gubler, Stefan Oechslin, and Johan Six
SOIL, 7, 193–215, https://doi.org/10.5194/soil-7-193-2021, https://doi.org/10.5194/soil-7-193-2021, 2021
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Simon Baumgartner, Marijn Bauters, Matti Barthel, Travis W. Drake, Landry C. Ntaboba, Basile M. Bazirake, Johan Six, Pascal Boeckx, and Kristof Van Oost
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We compared stable isotope signatures of soil profiles in different forest ecosystems within the Congo Basin to assess ecosystem-level differences in N cycling, and we examined the local effect of topography on the isotopic signature of soil N. Soil δ15N profiles indicated that the N cycling in in the montane forest is more closed, whereas the lowland forest and Miombo woodland experienced a more open N cycle. Topography only alters soil δ15N values in forests with high erosional forces.
Simon Baumgartner, Matti Barthel, Travis William Drake, Marijn Bauters, Isaac Ahanamungu Makelele, John Kalume Mugula, Laura Summerauer, Nora Gallarotti, Landry Cizungu Ntaboba, Kristof Van Oost, Pascal Boeckx, Sebastian Doetterl, Roland Anton Werner, and Johan Six
Biogeosciences, 17, 6207–6218, https://doi.org/10.5194/bg-17-6207-2020, https://doi.org/10.5194/bg-17-6207-2020, 2020
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Soil respiration is an important carbon flux and key process determining the net ecosystem production of terrestrial ecosystems. The Congo Basin lacks studies quantifying carbon fluxes. We measured soil CO2 fluxes from different forest types in the Congo Basin and were able to show that, even though soil CO2 fluxes are similarly high in lowland and montane forests, the drivers were different: soil moisture in montane forests and C availability in the lowland forests.
Jolanda E. Reusser, René Verel, Daniel Zindel, Emmanuel Frossard, and Timothy I. McLaren
Biogeosciences, 17, 5079–5095, https://doi.org/10.5194/bg-17-5079-2020, https://doi.org/10.5194/bg-17-5079-2020, 2020
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Long Ho, Ruben Jerves-Cobo, Matti Barthel, Johan Six, Samuel Bode, Pascal Boeckx, and Peter Goethals
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-311, https://doi.org/10.5194/bg-2020-311, 2020
Revised manuscript not accepted
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Marijn Van de Broek, Shiva Ghiasi, Charlotte Decock, Andreas Hund, Samuel Abiven, Cordula Friedli, Roland A. Werner, and Johan Six
Biogeosciences, 17, 2971–2986, https://doi.org/10.5194/bg-17-2971-2020, https://doi.org/10.5194/bg-17-2971-2020, 2020
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Stephen J. Harris, Jesper Liisberg, Longlong Xia, Jing Wei, Kerstin Zeyer, Longfei Yu, Matti Barthel, Benjamin Wolf, Bryce F. J. Kelly, Dioni I. Cendón, Thomas Blunier, Johan Six, and Joachim Mohn
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Julian Helfenstein, Chiara Pistocchi, Astrid Oberson, Federica Tamburini, Daniel S. Goll, and Emmanuel Frossard
Biogeosciences, 17, 441–454, https://doi.org/10.5194/bg-17-441-2020, https://doi.org/10.5194/bg-17-441-2020, 2020
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In this article we provide estimates of mean residence times of phosphorus in inorganic soil phosphorus pools. These values improve our understanding of the dynamics of phosphorus cycling and can be used to improve global land surface models.
Karl Voglmeier, Johan Six, Markus Jocher, and Christof Ammann
Biogeosciences, 16, 1685–1703, https://doi.org/10.5194/bg-16-1685-2019, https://doi.org/10.5194/bg-16-1685-2019, 2019
Tino Colombi, Florian Walder, Lucie Büchi, Marlies Sommer, Kexing Liu, Johan Six, Marcel G. A. van der Heijden, Raphaël Charles, and Thomas Keller
SOIL, 5, 91–105, https://doi.org/10.5194/soil-5-91-2019, https://doi.org/10.5194/soil-5-91-2019, 2019
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The role of soil aeration in carbon sequestration in arable soils has only been explored little, especially at the farm level. The current study, which was conducted on 30 fields that belong to individual farms, reveals a positive relationship between soil gas transport capability and soil organic carbon content. We therefore conclude that soil aeration needs to be accounted for when developing strategies for carbon sequestration in arable soil.
Elizabeth Verhoeven, Matti Barthel, Longfei Yu, Luisella Celi, Daniel Said-Pullicino, Steven Sleutel, Dominika Lewicka-Szczebak, Johan Six, and Charlotte Decock
Biogeosciences, 16, 383–408, https://doi.org/10.5194/bg-16-383-2019, https://doi.org/10.5194/bg-16-383-2019, 2019
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This study utilized state-of-the-art measurements of nitrogen isotopes to evaluate nitrogen cycling and to assess the biological sources of the potent greenhouse gas, N2O, in response to water-saving practices in rice systems. Water-saving practices did emit more N2O, and high N2O production had a lower 15N isotope signature. Modeling and visual interpretation indicate that these emissions mostly came from denitrification or nitrifier denitrification, controlled upstream by nitrification rates.
Julian Helfenstein, Jannes Jegminat, Timothy I. McLaren, and Emmanuel Frossard
Biogeosciences, 15, 105–114, https://doi.org/10.5194/bg-15-105-2018, https://doi.org/10.5194/bg-15-105-2018, 2018
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Soil solution phosphorus (P) turnover is essential for describing the bioavailability of this important nutrient. Here, we provide a derivation of calculating soil solution P turnover using parameters obtained from isotope exchange kinetic experiments. We then calculated and analyzed soil solution P turnover for 217 soils and for 18 long-term P fertilizer field experiments worldwide. Our study thus provides important insights on P dynamics in soils.
Jérôme Ebagnerin Tondoh, Issa Ouédraogo, Jules Bayala, Lulseged Tamene, Andrew Sila, Tor-Gunnar Vågen, and Antoine Kalinganiré
SOIL Discuss., https://doi.org/10.5194/soil-2016-45, https://doi.org/10.5194/soil-2016-45, 2016
Preprint withdrawn
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The present paper is intended to fill in the gap of field data on soil carbon sequestration in west african dry areas. As increased carbon concentration in soils through improved agricultural management practices is one of the options to mitigate greenhouse gases and improved soil quality, the results of this study will help designing the most promising practices in the study sites.
Emmanuel Frossard, Nina Buchmann, Else K. Bünemann, Delwende I. Kiba, François Lompo, Astrid Oberson, Federica Tamburini, and Ouakoltio Y. A. Traoré
SOIL, 2, 83–99, https://doi.org/10.5194/soil-2-83-2016, https://doi.org/10.5194/soil-2-83-2016, 2016
R. Hüppi, R. Felber, A. Neftel, J. Six, and J. Leifeld
SOIL, 1, 707–717, https://doi.org/10.5194/soil-1-707-2015, https://doi.org/10.5194/soil-1-707-2015, 2015
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Biochar is considered an opportunity to tackle major environmental issues in agriculture. Adding pyrolised organic residues to soil may sequester carbon, increase yields and reduce nitrous oxide emissions from soil. It is unknown, whether the latter is induced by changes in soil pH. We show that biochar application substantially reduces nitrous oxide emissions from a temperate maize cropping system. However, the reduction was only achieved with biochar but not with liming.
C. Decock, J. Lee, M. Necpalova, E. I. P. Pereira, D. M. Tendall, and J. Six
SOIL, 1, 687–694, https://doi.org/10.5194/soil-1-687-2015, https://doi.org/10.5194/soil-1-687-2015, 2015
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Further progress in understanding and mitigating N2O emissions from soil lies within transdisciplinary research that reaches across spatial scales and takes an ambitious look into the future.
M. S. Torn, A. Chabbi, P. Crill, P. J. Hanson, I. A. Janssens, Y. Luo, C. H. Pries, C. Rumpel, M. W. I. Schmidt, J. Six, M. Schrumpf, and B. Zhu
SOIL, 1, 575–582, https://doi.org/10.5194/soil-1-575-2015, https://doi.org/10.5194/soil-1-575-2015, 2015
C. von Sperber, F. Tamburini, B. Brunner, S. M. Bernasconi, and E. Frossard
Biogeosciences, 12, 4175–4184, https://doi.org/10.5194/bg-12-4175-2015, https://doi.org/10.5194/bg-12-4175-2015, 2015
B. Wolf, L. Merbold, C. Decock, B. Tuzson, E. Harris, J. Six, L. Emmenegger, and J. Mohn
Biogeosciences, 12, 2517–2531, https://doi.org/10.5194/bg-12-2517-2015, https://doi.org/10.5194/bg-12-2517-2015, 2015
S. Doetterl, J.-T. Cornelis, J. Six, S. Bodé, S. Opfergelt, P. Boeckx, and K. Van Oost
Biogeosciences, 12, 1357–1371, https://doi.org/10.5194/bg-12-1357-2015, https://doi.org/10.5194/bg-12-1357-2015, 2015
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We link the mineralogy of soils affected by erosion and deposition to the distribution of soil carbon fractions, their turnover and microbial activity. We show that the weathering status of soils and their history are controlling the stabilization of carbon with minerals. After burial, aggregated C is preserved more efficiently while non-aggregated C can be released and younger C re-sequestered more easily. Weathering changes the effectiveness of stabilization mechanism limiting this C sink.
E. C. Brevik, A. Cerdà, J. Mataix-Solera, L. Pereg, J. N. Quinton, J. Six, and K. Van Oost
SOIL, 1, 117–129, https://doi.org/10.5194/soil-1-117-2015, https://doi.org/10.5194/soil-1-117-2015, 2015
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This paper provides a brief accounting of some of the many ways that the study of soils can be interdisciplinary, therefore giving examples of the types of papers we hope to see submitted to SOIL.
Related subject area
Soil and methods
Spatial prediction of organic carbon in German agricultural topsoil using machine learning algorithms
On the benefits of clustering approaches in digital soil mapping: an application example concerning soil texture regionalization
An open Soil Structure Library based on X-ray CT data
Identification of thermal signature and quantification of charcoal in soil using differential scanning calorimetry and benzene polycarboxylic acid (BPCA) markers
Estimating soil fungal abundance and diversity at a macroecological scale with deep learning spectrotransfer functions
An underground, wireless, open-source, low-cost system for monitoring oxygen, temperature, and soil moisture
The central African soil spectral library: a new soil infrared repository and a geographical prediction analysis
Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring
Predicting the spatial distribution of soil organic carbon stock in Swedish forests using a group of covariates and site-specific data
Improved calibration of the Green–Ampt infiltration module in the EROSION-2D/3D model using a rainfall-runoff experiment database
Quantifying soil carbon in temperate peatlands using a mid-IR soil spectral library
Are researchers following best storage practices for measuring soil biochemical properties?
Quantifying and correcting for pre-assay CO2 loss in short-term carbon mineralization assays
The influence of training sample size on the accuracy of deep learning models for the prediction of soil properties with near-infrared spectroscopy data
Game theory interpretation of digital soil mapping convolutional neural networks
Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm
Oblique geographic coordinates as covariates for digital soil mapping
Development of pedotransfer functions for water retention in tropical mountain soil landscapes: spotlight on parameter tuning in machine learning
The 15N gas-flux method to determine N2 flux: a comparison of different tracer addition approaches
A new model for intra- and inter-institutional soil data sharing
Machine learning and soil sciences: a review aided by machine learning tools
Identification of new microbial functional standards for soil quality assessment
Identifying and quantifying geogenic organic carbon in soils – the case of graphite
Error propagation in spectrometric functions of soil organic carbon
Word embeddings for application in geosciences: development, evaluation, and examples of soil-related concepts
Soil lacquer peel do-it-yourself: simply capturing beauty
Multi-source data integration for soil mapping using deep learning
Using deep learning for digital soil mapping
No silver bullet for digital soil mapping: country-specific soil organic carbon estimates across Latin America
Separation of soil respiration: a site-specific comparison of partition methods
Proximal sensing for soil carbon accounting
Evaluation of digital soil mapping approaches with large sets of environmental covariates
Planning spatial sampling of the soil from an uncertain reconnaissance variogram
Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models
Quantitative imaging of the 3-D distribution of cation adsorption sites in undisturbed soil
Decision support for the selection of reference sites using 137Cs as a soil erosion tracer
Soil organic carbon stocks are systematically overestimated by misuse of the parameters bulk density and rock fragment content
The added value of biomarker analysis to the genesis of plaggic Anthrosols; the identification of stable fillings used for the production of plaggic manure
Synchrotron microtomographic quantification of geometrical soil pore characteristics affected by compaction
Pedotransfer functions for Irish soils – estimation of bulk density (ρb) per horizon type
Assessing the performance of a plastic optical fibre turbidity sensor for measuring post-fire erosion from plot to catchment scale
Passive soil heating using an inexpensive infrared mirror design – a proof of concept
The application of terrestrial laser scanner and SfM photogrammetry in measuring erosion and deposition processes in two opposite slopes in a humid badlands area (central Spanish Pyrenees)
Soil surface roughness: comparing old and new measuring methods and application in a soil erosion model
Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks
Eddy covariance for quantifying trace gas fluxes from soils
Ali Sakhaee, Anika Gebauer, Mareike Ließ, and Axel Don
SOIL, 8, 587–604, https://doi.org/10.5194/soil-8-587-2022, https://doi.org/10.5194/soil-8-587-2022, 2022
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As soil carbon has become a key component of climate-smart agriculture, the demand for high-resolution maps has increased drastically. Meanwhile, machine learning algorithms are becoming more widely used and are opening up new solutions in soil mapping. This paper shows which algorithms perform best, how soil inventory data can be most efficiently used for digital soil mapping, and the different available options and methods to derive high-resolution soil carbon data at the large regional scale.
István Dunkl and Mareike Ließ
SOIL, 8, 541–558, https://doi.org/10.5194/soil-8-541-2022, https://doi.org/10.5194/soil-8-541-2022, 2022
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Digital soil mapping (DSM) allows us to regionalize soil properties by relating them to environmental covariates with the help of an empirical model. Legacy soil data provide a valuable basis to generate high-resolution soil maps with DSM. We studied the usefulness of data-clustering methods to tackle potential sampling bias in legacy soil data while applying DSM for soil texture regionalization. Clustering has proved to be useful in various steps of the DSM process.
Ulrich Weller, Lukas Albrecht, Steffen Schlüter, and Hans-Jörg Vogel
SOIL, 8, 507–515, https://doi.org/10.5194/soil-8-507-2022, https://doi.org/10.5194/soil-8-507-2022, 2022
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Soil structure is of central importance for soil functions. It is, however, ill defined. With the increasing availability of X-ray CT scanners, more and more soils are scanned and an undisturbed image of the soil's structure is produced. Often, a qualitative description is all that is derived from these images. We provide now a web-based Soil Structure Library where these images can be evaluated in a standardized quantitative way and can be compared to a world-wide data set.
Brieuc Hardy, Nils Borchard, and Jens Leifeld
SOIL, 8, 451–466, https://doi.org/10.5194/soil-8-451-2022, https://doi.org/10.5194/soil-8-451-2022, 2022
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Soil amendment with artificial black carbon (BC; biomass transformed by incomplete combustion) has the potential to mitigate climate change. Nevertheless, the accurate quantification of BC in soil remains a critical issue. Here, we successfully used dynamic thermal analysis (DTA) to quantify centennial BC in soil. We demonstrate that DTA is largely under-exploited despite providing rapid and low-cost quantitative information over the range of soil organic matter.
Yuanyuan Yang, Zefang Shen, Andrew Bissett, and Raphael A. Viscarra Rossel
SOIL, 8, 223–235, https://doi.org/10.5194/soil-8-223-2022, https://doi.org/10.5194/soil-8-223-2022, 2022
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We present a new method to estimate the relative abundance of the dominant phyla and diversity of fungi in Australian soil. It uses state-of-the-art machine learning with publicly available data on soil and environmental proxies for edaphic, climatic, biotic and topographic factors, and visible–near infrared wavelengths. The estimates could serve to supplement the more expensive molecular approaches towards a better understanding of soil fungal abundance and diversity in agronomy and ecology.
Elad Levintal, Yonatan Ganot, Gail Taylor, Peter Freer-Smith, Kosana Suvocarev, and Helen E. Dahlke
SOIL, 8, 85–97, https://doi.org/10.5194/soil-8-85-2022, https://doi.org/10.5194/soil-8-85-2022, 2022
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Do-it-yourself hardware is a new approach for improving measurement resolution in research. Here we present a new low-cost, wireless underground sensor network for soil monitoring. All data logging, power, and communication component cost is USD 150, much cheaper than other available commercial solutions. We provide the complete building guide to reduce any technical barriers, which we hope will allow easier reproducibility and open new environmental monitoring applications.
Laura Summerauer, Philipp Baumann, Leonardo Ramirez-Lopez, Matti Barthel, Marijn Bauters, Benjamin Bukombe, Mario Reichenbach, Pascal Boeckx, Elizabeth Kearsley, Kristof Van Oost, Bernard Vanlauwe, Dieudonné Chiragaga, Aimé Bisimwa Heri-Kazi, Pieter Moonen, Andrew Sila, Keith Shepherd, Basile Bazirake Mujinya, Eric Van Ranst, Geert Baert, Sebastian Doetterl, and Johan Six
SOIL, 7, 693–715, https://doi.org/10.5194/soil-7-693-2021, https://doi.org/10.5194/soil-7-693-2021, 2021
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We present a soil mid-infrared library with over 1800 samples from central Africa in order to facilitate soil analyses of this highly understudied yet critical area. Together with an existing continental library, we demonstrate a regional analysis and geographical extrapolation to predict total carbon and nitrogen. Our results show accurate predictions and highlight the value that the data contribute to existing libraries. Our library is openly available for public use and for expansion.
Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
SOIL, 7, 525–546, https://doi.org/10.5194/soil-7-525-2021, https://doi.org/10.5194/soil-7-525-2021, 2021
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We developed the Swiss mid-infrared spectral library and a statistical model collection across 4374 soil samples with reference measurements of 16 properties. Our library incorporates soil from 1094 grid locations and 71 long-term monitoring sites. This work confirms once again that nationwide spectral libraries with diverse soils can reliably feed information to a fast chemical diagnosis. Our data-driven reduction of the library has the potential to accurately monitor carbon at the plot scale.
Kpade O. L. Hounkpatin, Johan Stendahl, Mattias Lundblad, and Erik Karltun
SOIL, 7, 377–398, https://doi.org/10.5194/soil-7-377-2021, https://doi.org/10.5194/soil-7-377-2021, 2021
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Forests store large amounts of carbon in soils. Implementing suitable measures to improve the sink potential of forest soils would require accurate data on the carbon stored in forest soils and a better understanding of the factors affecting this storage. This study showed that the prediction of soil carbon stock in Swedish forest soils can increase in accuracy when one divides a big region into smaller areas in combination with information collected locally and derived from satellites.
Hana Beitlerová, Jonas Lenz, Jan Devátý, Martin Mistr, Jiří Kapička, Arno Buchholz, Ilona Gerndtová, and Anne Routschek
SOIL, 7, 241–253, https://doi.org/10.5194/soil-7-241-2021, https://doi.org/10.5194/soil-7-241-2021, 2021
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This study presents transfer functions for a calibration parameter of the Green–Ampt infiltration module of the EROSION-2D/3D model, which are significantly improving the model performance compared to the current state. The relationships found between calibration parameters and soil parameters however put the Green–Ampt implementation in the model and the state-of-the-art parametrization method in question. A new direction of the infiltration module development is proposed.
Anatol Helfenstein, Philipp Baumann, Raphael Viscarra Rossel, Andreas Gubler, Stefan Oechslin, and Johan Six
SOIL, 7, 193–215, https://doi.org/10.5194/soil-7-193-2021, https://doi.org/10.5194/soil-7-193-2021, 2021
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In this study, we show that a soil spectral library (SSL) can be used to predict soil carbon at new and very different locations. The importance of this finding is that it requires less time-consuming lab work than calibrating a new model for every local application, while still remaining similar to or more accurate than local models. Furthermore, we show that this method even works for predicting (drained) peat soils, using a SSL with mostly mineral soils containing much less soil carbon.
Jennifer M. Rhymes, Irene Cordero, Mathilde Chomel, Jocelyn M. Lavallee, Angela L. Straathof, Deborah Ashworth, Holly Langridge, Marina Semchenko, Franciska T. de Vries, David Johnson, and Richard D. Bardgett
SOIL, 7, 95–106, https://doi.org/10.5194/soil-7-95-2021, https://doi.org/10.5194/soil-7-95-2021, 2021
Matthew A. Belanger, Carmella Vizza, G. Philip Robertson, and Sarah S. Roley
SOIL, 7, 47–52, https://doi.org/10.5194/soil-7-47-2021, https://doi.org/10.5194/soil-7-47-2021, 2021
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Soil health is often assessed by re-wetting a dry soil and measuring CO2 production, but the potential bias introduced by soils of different moisture contents is unclear. Our study found that wetter soil tended to lose more carbon during drying than drier soil, thus affecting soil health interpretations. We developed a correction factor to account for initial soil moisture effects, which future studies may benefit from adapting for their soil.
Wartini Ng, Budiman Minasny, Wanderson de Sousa Mendes, and José Alexandre Melo Demattê
SOIL, 6, 565–578, https://doi.org/10.5194/soil-6-565-2020, https://doi.org/10.5194/soil-6-565-2020, 2020
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The number of samples utilised to create predictive models affected model performance. This research compares the number of samples needed by a deep learning model to outperform the traditional machine learning models using visible near-infrared spectroscopy data for soil properties predictions. The deep learning model was found to outperform machine learning models when the sample size was above 2000.
José Padarian, Alex B. McBratney, and Budiman Minasny
SOIL, 6, 389–397, https://doi.org/10.5194/soil-6-389-2020, https://doi.org/10.5194/soil-6-389-2020, 2020
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In this paper we introduce the use of game theory to interpret a digital soil mapping (DSM) model to understand the contribution of environmental factors to the prediction of soil organic carbon (SOC) in Chile. The analysis corroborated that the SOC model is capturing sensible relationships between SOC and climatic and topographical factors. We were able to represent them spatially (map) addressing the limitations of the current interpretation of models in DSM.
Yosra Ellili-Bargaoui, Brendan Philip Malone, Didier Michot, Budiman Minasny, Sébastien Vincent, Christian Walter, and Blandine Lemercier
SOIL, 6, 371–388, https://doi.org/10.5194/soil-6-371-2020, https://doi.org/10.5194/soil-6-371-2020, 2020
Anders Bjørn Møller, Amélie Marie Beucher, Nastaran Pouladi, and Mogens Humlekrog Greve
SOIL, 6, 269–289, https://doi.org/10.5194/soil-6-269-2020, https://doi.org/10.5194/soil-6-269-2020, 2020
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Decision trees have become a widely adapted tool for mapping soil properties in geographic space. However, it is problematic to implement spatial relationships in the models. We present a new method which uses geographic coordinates along several axes tilted at oblique angles in the models. We test this method on four spatial datasets. The results show that the new method is at least as accurate as other proposed alternatives, has a computational advantage and is flexible and interpretable.
Anika Gebauer, Monja Ellinger, Victor M. Brito Gomez, and Mareike Ließ
SOIL, 6, 215–229, https://doi.org/10.5194/soil-6-215-2020, https://doi.org/10.5194/soil-6-215-2020, 2020
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Pedotransfer functions (PTFs) for soil water retention were developed for two tropical soil landscapes using machine learning. The models corresponding to these PTFs had to be adjusted by tuning their parameters. The standard tuning approach was compared to mathematical optimization. The latter resulted in much better model performance. The PTFs derived are of particular importance for soil process and hydrological models.
Dominika Lewicka-Szczebak and Reinhard Well
SOIL, 6, 145–152, https://doi.org/10.5194/soil-6-145-2020, https://doi.org/10.5194/soil-6-145-2020, 2020
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This study aimed at comparison of various experimental strategies for incubating soil samples to determine the N2 flux. Such experiments require addition of isotope tracer, i.e. nitrogen fertilizer enriched in heavy nitrogen isotopes (15N). Here we compared the impact of soil homogenization and mixing with the tracer and tracer injection to the intact soil cores. The results are well comparable: both techniques would provide similar conclusions on the magnitude of N2 flux.
José Padarian and Alex B. McBratney
SOIL, 6, 89–94, https://doi.org/10.5194/soil-6-89-2020, https://doi.org/10.5194/soil-6-89-2020, 2020
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Data sharing and collaboration are critical to solving large-scale problems. The prevailing soil data-sharing model is of a centralized nature and, consequently, results in the participants ceding control and governance over their data to the lead party. Here we explore the use of a distributed ledger (blockchain) to solve the aforementioned issues. We also describe the potential use case of developing a global soil spectral library between multiple, international institutions.
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 6, 35–52, https://doi.org/10.5194/soil-6-35-2020, https://doi.org/10.5194/soil-6-35-2020, 2020
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The application of machine learning (ML) has shown an accelerated adoption in soil sciences. It is a difficult task to manually review all papers on the application of ML. This paper aims to provide a review of the application of ML aided by topic modelling in order to find patterns in a large collection of publications. The objective is to gain insight into the applications and to discuss research gaps. We found 12 main topics and that ML methods usually perform better than traditional ones.
Sören Thiele-Bruhn, Michael Schloter, Berndt-Michael Wilke, Lee A. Beaudette, Fabrice Martin-Laurent, Nathalie Cheviron, Christian Mougin, and Jörg Römbke
SOIL, 6, 17–34, https://doi.org/10.5194/soil-6-17-2020, https://doi.org/10.5194/soil-6-17-2020, 2020
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Soil quality depends on the functioning of soil microbiota. Only a few standardized methods are available to assess this as well as adverse effects of human activities. So we need to identify promising additional methods that target soil microbial function. Discussed are (i) molecular methods using qPCR for new endpoints, e.g. in N and P cycling and greenhouse gas emissions, (ii) techniques for fungal enzyme activities, and (iii) field methods on carbon turnover such as the litter bag test.
Jeroen H. T. Zethof, Martin Leue, Cordula Vogel, Shane W. Stoner, and Karsten Kalbitz
SOIL, 5, 383–398, https://doi.org/10.5194/soil-5-383-2019, https://doi.org/10.5194/soil-5-383-2019, 2019
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A widely overlooked source of carbon (C) in the soil environment is organic C of geogenic origin, e.g. graphite. Appropriate methods are not available to quantify graphite and to differentiate it from other organic and inorganic C sources in soils. Therefore, we examined Fourier transform infrared spectroscopy, thermogravimetric analysis and the smart combustion method for their ability to identify and quantify graphitic C in soils. The smart combustion method showed the most promising results.
Monja Ellinger, Ines Merbach, Ulrike Werban, and Mareike Ließ
SOIL, 5, 275–288, https://doi.org/10.5194/soil-5-275-2019, https://doi.org/10.5194/soil-5-275-2019, 2019
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Vis–NIR spectrometry is often applied to capture soil organic carbon (SOC). This study addresses the impact of the involved data and modelling aspects on SOC precision with a focus on the propagation of input data uncertainties. It emphasizes the necessity of transparent documentation of the measurement protocol and the model building and validation procedure. Particularly, when Vis–NIR spectrometry is used for soil monitoring, the aspect of uncertainty propagation becomes essential.
José Padarian and Ignacio Fuentes
SOIL, 5, 177–187, https://doi.org/10.5194/soil-5-177-2019, https://doi.org/10.5194/soil-5-177-2019, 2019
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A large amount of descriptive information is available in geosciences. Considering the advances in natural language it is possible to
rescuethis information and transform it into a numerical form (embeddings). We used 280764 full-text scientific articles to train a language model capable of generating such embeddings. Our domain-specific embeddings (GeoVec) outperformed general domain embedding tasks such as analogies, relatedness, and categorisation, and can be used in novel applications.
Cathelijne R. Stoof, Jasper H. J. Candel, Laszlo A. G. M. van der Wal, and Gert Peek
SOIL, 5, 159–175, https://doi.org/10.5194/soil-5-159-2019, https://doi.org/10.5194/soil-5-159-2019, 2019
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Teaching and outreach of soils is often done with real-life snapshots of soils and sediments in lacquer or glue peels. While it may seem hard, anyone can make such a peel. Illustrated with handmade drawings and an instructional video, we explain how to capture soils in peels using readily available materials. A new twist to old methods makes this safer, simpler, and more successful, and thus a true DIY (do-it-yourself) activity, highlighting the value and beauty of the ground below our feet.
Alexandre M. J.-C. Wadoux, José Padarian, and Budiman Minasny
SOIL, 5, 107–119, https://doi.org/10.5194/soil-5-107-2019, https://doi.org/10.5194/soil-5-107-2019, 2019
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 5, 79–89, https://doi.org/10.5194/soil-5-79-2019, https://doi.org/10.5194/soil-5-79-2019, 2019
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Digital soil mapping has been widely used as a cost-effective method for generating soil maps. DSM models are usually calibrated using point observations and rarely incorporate contextual information of the landscape. Here, we use convolutional neural networks to incorporate spatial context. We used as input a 3-D stack of covariate images to simultaneously predict organic carbon content at multiple depths. In this study, our model reduced the error by 30 % compared with conventional techniques.
Mario Guevara, Guillermo Federico Olmedo, Emma Stell, Yusuf Yigini, Yameli Aguilar Duarte, Carlos Arellano Hernández, Gloria E. Arévalo, Carlos Eduardo Arroyo-Cruz, Adriana Bolivar, Sally Bunning, Nelson Bustamante Cañas, Carlos Omar Cruz-Gaistardo, Fabian Davila, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo Tacona, Fernando Fontes, José Antonio Hernández Herrera, Alejandro Roberto Ibelles Navarro, Veronica Loayza, Alexandra M. Manueles, Fernando Mendoza Jara, Carolina Olivera, Rodrigo Osorio Hermosilla, Gonzalo Pereira, Pablo Prieto, Iván Alexis Ramos, Juan Carlos Rey Brina, Rafael Rivera, Javier Rodríguez-Rodríguez, Ronald Roopnarine, Albán Rosales Ibarra, Kenset Amaury Rosales Riveiro, Guillermo Andrés Schulz, Adrian Spence, Gustavo M. Vasques, Ronald R. Vargas, and Rodrigo Vargas
SOIL, 4, 173–193, https://doi.org/10.5194/soil-4-173-2018, https://doi.org/10.5194/soil-4-173-2018, 2018
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We provide a reproducible multi-modeling approach for SOC mapping across Latin America on a country-specific basis as required by the Global Soil Partnership of the United Nations. We identify key prediction factors for SOC across each country. We compare and test different methods to generate spatially explicit predictions of SOC and conclude that there is no best method on a quantifiable basis.
Louis-Pierre Comeau, Derrick Y. F. Lai, Jane Jinglan Cui, and Jenny Farmer
SOIL, 4, 141–152, https://doi.org/10.5194/soil-4-141-2018, https://doi.org/10.5194/soil-4-141-2018, 2018
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To date, there are still many uncertainties and unknowns regarding the soil respiration partitioning procedures. This study compared the suitability and accuracy of five different respiration partitioning methods. A qualitative evaluation table of the partition methods with five performance parameters was produced. Overall, no systematically superior or inferior partition method was found and the combination of two or more methods optimizes assessment reliability.
Jacqueline R. England and Raphael A. Viscarra Rossel
SOIL, 4, 101–122, https://doi.org/10.5194/soil-4-101-2018, https://doi.org/10.5194/soil-4-101-2018, 2018
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Proximal sensing can be used for soil C accounting, but the methods need to be standardized and procedural guidelines developed to ensure proficient measurement and accurate reporting. This is particularly important if there are financial incentives for landholders to adopt practices to sequester C. We review sensing for C accounting and discuss the requirements for the development of new soil C accounting methods based on sensing, including requirements for reporting, auditing and verification.
Madlene Nussbaum, Kay Spiess, Andri Baltensweiler, Urs Grob, Armin Keller, Lucie Greiner, Michael E. Schaepman, and Andreas Papritz
SOIL, 4, 1–22, https://doi.org/10.5194/soil-4-1-2018, https://doi.org/10.5194/soil-4-1-2018, 2018
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This paper presents an extensive evaluation of digital soil mapping (DSM) tools. Recently, large sets of environmental covariates (e.g. from analysis of terrain on multiple scales) have become more common for DSM. Many DSM studies, however, only compared DSM methods using less than 30 covariates or tested approaches on few responses. We built DSM models from 300–500 covariates using six approaches that are either popular in DSM or promising for large covariate sets.
R. Murray Lark, Elliott M. Hamilton, Belinda Kaninga, Kakoma K. Maseka, Moola Mutondo, Godfrey M. Sakala, and Michael J. Watts
SOIL, 3, 235–244, https://doi.org/10.5194/soil-3-235-2017, https://doi.org/10.5194/soil-3-235-2017, 2017
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An advantage of geostatistics for mapping soil properties is that, given a statistical model of the variable of interest, we can make a rational decision about how densely to sample so that the map is sufficiently precise. However, uncertainty about the statistical model affects this process. In this paper we show how Bayesian methods can be used to support decision making on sampling with an uncertain model, ensuring that the probability of meeting certain levels of precision is high enough.
Madlene Nussbaum, Lorenz Walthert, Marielle Fraefel, Lucie Greiner, and Andreas Papritz
SOIL, 3, 191–210, https://doi.org/10.5194/soil-3-191-2017, https://doi.org/10.5194/soil-3-191-2017, 2017
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Digital soil mapping (DSM) relates soil property data to environmental data that describe soil-forming factors. With imagery sampled from satellites or terrain analysed at multiple scales, large sets of possible input to DSM are available. We propose a new statistical framework (geoGAM) that selects parsimonious models for DSM and illustrate the application of geoGAM to two study regions. Straightforward interpretation of the modelled effects likely improves end-user acceptance of DSM products.
Hannes Keck, Bjarne W. Strobel, Jon Petter Gustafsson, and John Koestel
SOIL, 3, 177–189, https://doi.org/10.5194/soil-3-177-2017, https://doi.org/10.5194/soil-3-177-2017, 2017
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Several studies have shown that the cation adsorption sites in soils are heterogeneously distributed in space. In many soil system models this knowledge is not included yet. In our study we proposed a new method to map the 3-D distribution of cation adsorption sites in undisturbed soils. The method is based on three-dimensional X-ray scanning with a contrast agent and image analysis. We are convinced that this approach will strongly aid the development of more realistic soil system models.
Laura Arata, Katrin Meusburger, Alexandra Bürge, Markus Zehringer, Michael E. Ketterer, Lionel Mabit, and Christine Alewell
SOIL, 3, 113–122, https://doi.org/10.5194/soil-3-113-2017, https://doi.org/10.5194/soil-3-113-2017, 2017
Christopher Poeplau, Cora Vos, and Axel Don
SOIL, 3, 61–66, https://doi.org/10.5194/soil-3-61-2017, https://doi.org/10.5194/soil-3-61-2017, 2017
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This paper shows that three out of four frequently used methods to calculate soil organic carbon stocks lead to systematic overestimation of those stocks. Stones, which can be assumed to be free of carbon, have to be corrected for in both bulk density and layer thickness. We used data of the German Agricultural Soil Inventory to illustrate the potential bias and suggest a unified and unbiased calculation method for stocks of soil organic carbon, which is the largest terrestrial carbon pool.
Jan M. van Mourik, Thomas V. Wagner, J. Geert de Boer, and Boris Jansen
SOIL, 2, 299–310, https://doi.org/10.5194/soil-2-299-2016, https://doi.org/10.5194/soil-2-299-2016, 2016
Ranjith P. Udawatta, Clark J. Gantzer, Stephen H. Anderson, and Shmuel Assouline
SOIL, 2, 211–220, https://doi.org/10.5194/soil-2-211-2016, https://doi.org/10.5194/soil-2-211-2016, 2016
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Soil compaction degrades soil structure and affects water, heat, and gas exchange as well as root penetration and crop production. The objective of this study was to use X-ray computed microtomography (CMT) techniques to compare differences in geometrical soil pore parameters as influenced by compaction of two different aggregate size classes.
B. Reidy, I. Simo, P. Sills, and R. E. Creamer
SOIL, 2, 25–39, https://doi.org/10.5194/soil-2-25-2016, https://doi.org/10.5194/soil-2-25-2016, 2016
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This study reviews pedotransfer functions from the literature for different soil and horizon types. It uses these formulae to predict bulk density (ρb) per horizon using measured data of other soil properties. These data were compared to known pb per horizon and recalibrated. These calculations were used to fill missing horizon data in the Irish soil database. This allowed the generation of a pb map to 50 cm. These pb data are at horizon level allowing more accurate estimation of C with depth.
J. J. Keizer, M. A. S. Martins, S. A. Prats, L. F. Santos, D. C. S. Vieira, R. Nogueira, and L. Bilro
SOIL, 1, 641–650, https://doi.org/10.5194/soil-1-641-2015, https://doi.org/10.5194/soil-1-641-2015, 2015
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In this study, a novel plastic optical fibre turbidity sensor was exhaustively tested with a large set of runoff samples, mainly from a recently burnt area. The different types of samples from the distinct study sites revealed without exception an increase in normalized light loss with increasing sediment concentrations that agreed (reasonably) well with a power function. Nevertheless, sensor-based predictions of sediment concentration should ideally involve site-specific calibrations.
C. Rasmussen, R. E. Gallery, and J. S. Fehmi
SOIL, 1, 631–639, https://doi.org/10.5194/soil-1-631-2015, https://doi.org/10.5194/soil-1-631-2015, 2015
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There is a need to understand the response of soil systems to predicted climate warming for modeling soil processes. Current experimental methods for soil warming include expensive and difficult to implement active and passive techniques. Here we test a simple, inexpensive in situ passive soil heating approach, based on easy to construct infrared mirrors that do not require automation or enclosures. Results indicated that the infrared mirrors yielded significant heating and drying of soils.
E. Nadal-Romero, J. Revuelto, P. Errea, and J. I. López-Moreno
SOIL, 1, 561–573, https://doi.org/10.5194/soil-1-561-2015, https://doi.org/10.5194/soil-1-561-2015, 2015
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Geomatic techniques have been routinely applied in erosion studies, providing the opportunity to build high-resolution topographic models.The aim of this study is to assess and compare the functioning of terrestrial laser scanner and close range photogrammetry techniques to evaluate erosion and deposition processes in a humid badlands area.
Our results demonstrated that north slopes experienced more intense and faster dynamics than south slopes as well as the highest erosion rates.
L. M. Thomsen, J. E. M. Baartman, R. J. Barneveld, T. Starkloff, and J. Stolte
SOIL, 1, 399–410, https://doi.org/10.5194/soil-1-399-2015, https://doi.org/10.5194/soil-1-399-2015, 2015
B. A. Miller, S. Koszinski, M. Wehrhan, and M. Sommer
SOIL, 1, 217–233, https://doi.org/10.5194/soil-1-217-2015, https://doi.org/10.5194/soil-1-217-2015, 2015
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There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research was to compare these two approaches for mapping SOC stocks from multiple linear regression models applied at the landscape scale via spatial association. Although the indirect approach had greater spatial variation and higher R2 values, the direct approach had a lower total estimated error.
W. Eugster and L. Merbold
SOIL, 1, 187–205, https://doi.org/10.5194/soil-1-187-2015, https://doi.org/10.5194/soil-1-187-2015, 2015
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The eddy covariance (EC) method has become increasingly popular in soil science. The basic concept of this method and its use in different types of experimental designs in the field are given, and we indicate where progress in advancing and extending the field of applications is made. The greatest strengths of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes and (2) spatial integration over
small-scale heterogeneity in the soil.
Cited articles
Abbott, L. K. and Murphy, D. V. (Eds.): Soil Biological Fertility: A Key
to Sustainable Land Use in Agriculture, Springer Netherlands, available at:
https://www.springer.com/de/book/9781402017568 (last access: 1 October 2021), 2007. a
Abdi, D., Tremblay, G. F., Ziadi, N., Bélanger, G., and Parent, L.-É.:
Predicting Soil Phosphorus-Related Properties Using Near-Infrared
Reflectance Spectroscopy, Soil Sci. Soc. Am. J., 76,
2318–2326, https://doi.org/10.2136/sssaj2012.0155, 2012. a
Baumann, P.: philipp-baumann/simplerspec: Beta release simplerspec 0.1.0 for
zenodo, Zenodo [software], https://doi.org/10.5281/zenodo.3303637, 2019. a
Baumann, P.: Philipp-baumann/yamsys-soilspec-publication: Open data and code
(manuscript submission): Estimation of soil properties with mid-infrared
soil spectroscopy across yam production landscapes in West Africa, Zenodo [data set, code],
https://doi.org/10.5281/zenodo.4358606, 2020. a, b
Bouyoucos, G. J.: A recalibration of the hydrometer method for making
mechanical analysis of soils, Agron. J., 43, 434–438, 1951. a
Breiman, L., Friedman, J., Stone, C., and Olshen, R.: Classification and
Regression Trees, The Wadsworth and Brooks-Cole
statistics-probability series, Taylor & Francis, available at:
https://books.google.ch/books?id=JwQx-WOmSyQC (last access: 1 October 2021), 1984. a
Cambou, A., Cardinael, R., Kouakoua, E., Villeneuve, M., Durand, C., and
Barthès, B. G.: Prediction of soil organic carbon stock using visible and
near infrared reflectance spectroscopy (VNIRS) in the field, Geoderma, 261,
151–159, https://doi.org/10.1016/j.geoderma.2015.07.007, 2016. a
Chong, I.-G. and Jun, C.-H.: Performance of some variable selection methods
when multicollinearity is present, Chemometr. Intell. Lab., 78, 103–112, https://doi.org/10.1016/j.chemolab.2004.12.011, 2005. a
Clairotte, M., Grinand, C., Kouakoua, E., Thébault, A., Saby, N. P., Bernoux,
M., and Barthès, B. G.: National calibration of soil organic carbon
concentration using diffuse infrared reflectance spectroscopy, Geoderma, 276,
41–52, https://doi.org/10.1016/j.geoderma.2016.04.021, 2016. a
Cornet, D., Sierra, J., Tournebize, R., Gabrielle, B., and Lewis, F. I.:
Bayesian Network Modeling of Early Growth Stages Explains Yam Interplant
Yield Variability and Allows for Agronomic Improvements in West Africa,
Eur. J. Agron., 75, 80–88, https://doi.org/10.1016/j.eja.2016.01.009,
2016. a
Cécillon, L., Barthès, B. G., Gomez, C., Ertlen, D., Genot, V., Hedde, M.,
Stevens, A., and Brun, J. J.: Assessment and monitoring of soil quality using
near-infrared reflectance spectroscopy (NIRS), Eur. J. Soil
Sci., 60, 770–784, https://doi.org/10.1111/j.1365-2389.2009.01178.x, 2009. a
Diby, L. N., Hgaza, V. K., Tie, T. B., ASSA, A., Carsky, R., Girardin, O., and
Frossard, E.: Productivity of Yams (Dioscorea Spp.) as Affected by Soil
Fertility, J. Anim. Plant Sci., 5, 494–506, 2009. a
Diby, L. N., Tie, B. T., Girardin, O., Sangakkara, R., and Frossard, E.: Growth
and Nutrient Use Efficiencies of Yams (Dioscorea Spp.) Grown
in Two Contrasting Soils of West Africa, Int. J.
Agron., 2011, 1–8, https://doi.org/10.1155/2011/175958, 2011. a
Enesi, R. O., Hauser, S., Lopez-Montez, A., and Osonubi, O.: Yam Tuber and
Maize Grain Yield Response to Cropping System Intensification in South-West
Nigeria, Arch. Agron. Soil Sci., 64, 953–966,
https://doi.org/10.1080/03650340.2017.1404580, 2018. a
Enyi, B. A. C.: Effect of Staking, Nitrogen and Potassium on Growth and
Development in Lesser Yams: Dioscorea Esculenta, Ann. Appl.
Biol., 72, 211–219, https://doi.org/10.1111/j.1744-7348.1972.tb01287.x, 1972. a
Food and Agriculture Organization of the United Nations: FAOSTAT statistics
database, available at: http://www.fao.org/3/i3794en/I3794en.pdf (last access: 1 October 2021), 2019. a
Foster, H. L.: The Basic Factors Which Determine Inherent Soil Fertility in
Uganda, J. Soil Sci., 32, 149–160,
https://doi.org/10.1111/j.1365-2389.1981.tb01693.x, 1981. a
Frossard, E., Aighewi, B. A., Aké, S., Barjolle, D., Baumann, P., Bernet, T.,
Dao, D., Diby, L. N., Floquet, A., Hgaza, V. K., Ilboudo, L. J., Kiba, D. I.,
Mongbo, R. L., Nacro, H. B., Nicolay, G. L., Oka, E., Ouattara, Y. F., Pouya,
N., Senanayake, R. L., Six, J., and Traoré, O. I.: The Challenge of
Improving Soil Fertility in Yam Cropping Systems of West
Africa, Front. Plant Sci., 1953, 1–8, https://doi.org/10.3389/fpls.2017.01953, 2017. a, b, c, d
Guerrero, C., Wetterlind, J., Stenberg, B., Mouazen, A. M., Gabarrón-Galeote,
M. A., Ruiz-Sinoga, J. D., Zornoza, R., and Viscarra Rossel, R. A.: Do We
Really Need Large Spectral Libraries for Local Scale SOC Assessment with
NIR Spectroscopy?, Soil Till. Res., 155, 501–509,
https://doi.org/10.1016/j.still.2015.07.008, 2016. a
Hendershot, W. H. and Duquette, M.: A simple barium chloride method for
determining cation exchange capacity and exchangeable cations, Soil Sci.
Soc. Am. J., 50, 605–608, 1986. a
Hgaza, V. K., Diby, L. N., Tié, T. B., Tschannen, A., Aké, S., Assa,
A., and Frossard, E.: Growth and Distribution of Roots of Dioscorea Alata
L. Do Not Respond to Mineral Fertilizer Application, Open Plant Sci.
J., 5, 14–22, 2011. a
Hillier, S., Brydson, R., Delbos, E., Fraser, T., Gray, N., Pendlowski, H.,
Phillips, I., Robertson, J., and Wilson, I.: Correlations among the
mineralogical and physical properties of halloysite nanotubes (HNTs), Clay
Miner., 51, 325–350, https://doi.org/10.1180/claymin.2016.051.3.11, 2016. a
Janik, L. J., Skjemstad, J. O., and Merry, R. H.: Can mid infrared diffuse
reflectance analysis replace soil extractions?, Aust. J.
Exp. Agr., 38, 681, https://doi.org/10.1071/EA97144, 1998. a, b
Johnson, J.-M., Vandamme, E., Senthilkumar, K., Sila, A., Shepherd, K. D., and
Saito, K.: Near-infrared, mid-infrared or combined diffuse reflectance
spectroscopy for assessing soil fertility in rice fields in sub-Saharan
Africa, Geoderma, 354, 113840, https://doi.org/10.1016/j.geoderma.2019.06.043,
2019. a
Kang, B. T. and Wilson, J. E.: Effect of mound size and fertilizer on white
Guinea yam (Dioscorea rotundata) in Southern Nigeria, Plant Soil,
61, 319–327, https://doi.org/10.1007/BF02182013, 1981. a
Kassi, S.-P. A., Koné, A. W., Tondoh, J. E., and Koffi, B. Y.: Chromoleana
Odorata Fallow-Cropping Cycles Maintain Soil Carbon Stocks and Yam Yields 40
Years after Conversion of Native- to Farmland, Implications for Forest
Conservation, Agr. Ecosyst. Environ., 247, 298–307,
https://doi.org/10.1016/j.agee.2017.06.044, 2017. a
Kiba, D. I., Hgaza, V. K., Aighewi, B., Aké, S., Barjolle, D., Bernet, T.,
Diby, L. N., Ilboudo, L. J., Nicolay, G., Oka, E., Ouattara, F. Y., Pouya,
N., Six, J., and Frossard, E.: A Transdisciplinary Approach for the
Development of Sustainable Yam (Dioscorea Sp.) Production in
West Africa, Sustainability, 12, 4016, https://doi.org/10.3390/su12104016, 2020. a
Kim, J.-H.: Estimating classification error rate: Repeated cross-validation,
repeated hold-out and bootstrap, Comput. Stat. Data Anal.,
53, 3735–3745, https://doi.org/10.1016/j.csda.2009.04.009, 2009. a
Kuhn, M., Wing, J., Weston, S., A., W., Keefer, C., Engelhardt, A., Cooper, T.,
Mayer, Z., Kenkel, B., Benesty, M., Lescarbeau, R., Ziem, A., Scrucca, L.,
Tang, Y., Candan, C., and Hunt, T.: caret: Classification and Regression
Training, available at: https://CRAN.R-project.org/package=caret (last access: 1 October 2021), R package
version 6.0-82, 2019. a
Lindsay, W. L. and Norvell, W. A.: Development of a DTPA soil test for zinc,
iron, manganese, and copper, Soil science society of America journal, 42,
421–428, 1978. a
Lyon, R. J. P. and Tuddenham, W. M.: Infra-Red Determination of the
Kaolin Group Minerals, Nature, 185, 835–836, https://doi.org/10.1038/185835a0, 1960. a
Madejová, J., Kečkés, J., Pálková, H., and Komadel, P.: Identification of
components in smectite/kaolinite mixtures, Clay Miner., 37, 377–388,
https://doi.org/10.1180/0009855023720042, 2002. a, b
Martens, H. and Naes, T.: Multivariate Calibration, Wiley Chichester, 1989. a
Mevik, B.-H., Wehrens, R., and Liland, K. H.: pls: Partial Least Squares and
Principal Component Regression, available at:
https://CRAN.R-project.org/package=pls (last access: 1 October 2021), R package version
2.7-1, 2019. a
Molinaro, A. M., Simon, R., and Pfeiffer, R. M.: Prediction error estimation: a
comparison of resampling methods, Bioinformatics, 21, 3301–3307,
https://doi.org/10.1093/bioinformatics/bti499, 2005. a
Nocita, M., Stevens, A., van Wesemael, B., Aitkenhead, M., Bachmann, M.,
Barthès, B., Ben Dor, E., Brown, D. J., Clairotte, M., Csorba, A., Dardenne,
P., Demattê, J. A., Genot, V., Guerrero, C., Knadel, M., Montanarella, L.,
Noon, C., Ramirez-Lopez, L., Robertson, J., Sakai, H., Soriano-Disla, J. M.,
Shepherd, K. D., Stenberg, B., Towett, E. K., Vargas, R., and Wetterlind, J.:
Soil Spectroscopy: An Alternative to Wet Chemistry for Soil
Monitoring, in: Advances in Agronomy, Vol. 132, Elsevier, 139–159,
https://doi.org/10.1016/bs.agron.2015.02.002, 2015. a, b, c, d
O'Sullivan, J. N. and Jenner, R.: Nutrient Deficiencies in Greater Yam
and Their Effects on Leaf Nutrient Concentrations, J. Plant
Nutr., 29, 1663–1674, https://doi.org/10.1080/01904160600851569, 2006. a, b, c, d
Padwick, G. W.: Fifty Years of Experimental Agriculture
II. The Maintenance of Soil Fertility in Tropical Africa: A
Review, Exp. Agr., 19, 293–310,
https://doi.org/10.1017/S001447970001276X, 1983. a
Parfitt, R. L., Atkinson, R. J., and Smart, R. S. C.: The Mechanism of
Phosphate Fixation by Iron Oxides, Soil Sci. Soc. Am.
J., 39, 837–841, https://doi.org/10.2136/sssaj1975.03615995003900050017x, 1975. a
R Core Team: R: A Language and Environment for Statistical Computing, R
Foundation for Statistical Computing, Vienna, Austria, available at:
https://www.R-project.org/ (last access: 1 October 2021), 2017. a
Rossel, R. A. V. and Webster, R.: Predicting soil properties from the
Australian soil visible–near infrared spectroscopic database, Europ.
J. Soil Sci., 63, 848–860,
https://doi.org/10.1111/j.1365-2389.2012.01495.x, 2012. a
Rossel, R. V. and Behrens, T.: Using data mining to model and interpret soil
diffuse reflectance spectra, Geoderma, 158, 46–54,
https://doi.org/10.1016/j.geoderma.2009.12.025, 2010. a
Sanderman, J., Savage, K., and Dangal, S. R. S.: Mid-Infrared Spectroscopy for
Prediction of Soil Health Indicators in the United States, Soil Sci.
Soc. Am. J., 84, 251–261, https://doi.org/10.1002/saj2.20009, 2020. a
Savitzky, A. and Golay, M. J. E.: Smoothing and Differentiation of Data by
Simplified Least Squares Procedures., Anal. Chem., 36, 1627–1639,
https://doi.org/10.1021/ac60214a047, 1964. a
Sila, A. M., Shepherd, K. D., and Pokhariyal, G. P.: Evaluating the utility of
mid-infrared spectral subspaces for predicting soil properties, Chemometr. Intell. Lab., 153, 92–105,
https://doi.org/10.1016/j.chemolab.2016.02.013, 2016. a, b, c, d
Six, J., Frey, S. D., Thiet, R. K., and Batten, K. M.: Bacterial and Fungal
Contributions to Carbon Sequestration in Agroecosystems, Soil
Sci. Soc. Am. J., 70, 555–569,
https://doi.org/10.2136/sssaj2004.0347, 2006. a
Soares, M. R. and Alleoni, L. R. F.: Contribution of Soil Organic Carbon
to the Ion Exchange Capacity of Tropical Soils, J.
Sustain. Agr., 32, 439–462, https://doi.org/10.1080/10440040802257348, 2008. a
Stenberg, B. and Rossel, R. A. V.: Diffuse Reflectance Spectroscopy for
High-Resolution Soil Sensing, in: Proximal Soil Sensing, edited
by: Rossel, R. A. V., McBratney, A. B., and Minasny, B., Progress in Soil
Science, Springer Netherlands, 29–47,
https://doi.org/10.1007/978-90-481-8859-8_3, 2010. a
Stevens, A., Nocita, M., Tóth, G., Montanarella, L., and van Wesemael, B.:
Prediction of Soil Organic Carbon at the European Scale by
Visible and Near InfraRed Reflectance Spectroscopy, PLoS ONE, 8,
e66409, https://doi.org/10.1371/journal.pone.0066409, 2013. a, b
Syers, J. K., Campbell, A. S., and Walker, T. W.: Contribution of organic
carbon and clay to cation exchange capacity in a chronosequence of sandy
soils, Plant Soil, 33, 104–112, https://doi.org/10.1007/BF01378202, 1970. a
Vagen, T.-G., Shepherd, K. D., Walsh, M. G., Winowiecki, L., Desta, L. T., and
Tondoh, J. E.: AfSIS technical specifications: Soil Health
Surveillance, available at:
http://www.worldagroforestry.org/sites/default/files/afsisSoilHealthTechSpecs_v1_smaller.pdf (last access: 1 October 2021),
2010. a
Viscarra Rossel, R., Behrens, T., Ben-Dor, E., Brown, D., Demattê, J.,
Shepherd, K., Shi, Z., Stenberg, B., Stevens, A., Adamchuk, V., Aïchi, H.,
Barthès, B., Bartholomeus, H., Bayer, A., Bernoux, M., Böttcher, K.,
Brodský, L., Du, C., Chappell, A., Fouad, Y., Genot, V., Gomez, C.,
Grunwald, S., Gubler, A., Guerrero, C., Hedley, C., Knadel, M., Morrás, H.,
Nocita, M., Ramirez-Lopez, L., Roudier, P., Campos, E. R., Sanborn, P.,
Sellitto, V., Sudduth, K., Rawlins, B., Walter, C., Winowiecki, L., Hong, S.,
and Ji, W.: A global spectral library to characterize the world's soil,
Earth-Sci. Rev., 155, 198–230, https://doi.org/10.1016/j.earscirev.2016.01.012,
2016. a
Viscarra Rossel, R. A., Walvoort, D. J. J., McBratney, A. B., Janik, L. J., and
Skjemstad, J. O.: Visible, near infrared, mid infrared or combined diffuse
reflectance spectroscopy for simultaneous assessment of various soil
properties, Geoderma, 131, 59–75, https://doi.org/10.1016/j.geoderma.2005.03.007,
2006. a, b
Wawire, A. W., Csorba, Á., Kovács, E., Mairura, F. S., Tóth, J. A.,
and Michéli, E.: Comparing Farmers' Soil Fertility Knowledge Systems and
Scientific Assessment in Upper Eastern Kenya, Geoderma, 396, 115090,
https://doi.org/10.1016/j.geoderma.2021.115090, 2021. a
Wold, S., Martens, H., and Wold, H.: The Multivariate Calibration Problem in
Chemistry Solved by the PLS Method, in: Matrix Pencils, edited by:
Kågström, B. and Ruhe, A., Vol. 973, Springer Berlin
Heidelberg, 286–293, https://doi.org/10.1007/BFb0062108, 1983.
a
Wold, S., Johansson, E., and Cocchi, M.: PLS-partial least squares
projections to latent structures, 3D QSAR in drug design, Springer Netherlands, 1, 523–550, https://doi.org/10.1007/0-306-46858-1, 1993. a
Short summary
This work delivers openly accessible and validated calibrations for diagnosing 26 soil properties based on mid-infrared spectroscopy. These were developed for four regions in Burkina Faso and Côte d'Ivoire, including 80 fields of smallholder farmers. The models can help to site-specifically and cost-efficiently monitor soil quality and fertility constraints to ameliorate soils and yields of yam or other staple crops in the four regions between the humid forest and the northern Guinean savanna.
This work delivers openly accessible and validated calibrations for diagnosing 26 soil...
