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  • 1
    Language: English
    In: Geoderma, 01 June 2016, Vol.271, pp.254-255
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.geoderma.2015.11.025 Byline: Philippe C. Baveye, Magdeline Laba Article History: Received 18 September 2015; Accepted 19 November 2015
    Keywords: Proximal Sensing ; Spatial Variability ; Soil Contamination ; Remediation ; Toxicology ; Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 2
    Language: English
    In: Geoderma, Sept 15, 2011, Vol.164(3-4), p.146(9)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.geoderma.2011.05.018 Byline: Simona M. Hapca, Zi X. Wang, Wilfred Otten, Clare Wilson, Philippe C. Baveye Keywords: X-ray CT; SEM-EDX; Segmentation techniques; Spatial correlation; 3D soil images; 2D chemical maps Abstract: Recent 2-dimensional measurements reveal that soils are chemically very heterogeneous at nanometric and micrometric scales. Direct measurement techniques are still lacking to extend these observations to 3 dimensions. Sequential sectioning of soils, followed by 2-dimensional mapping of chemical elements and geometric interpolation to 3D, appears to be the only available alternative. Unfortunately, sectioning of soil samples suffers from geometric distortions that are difficult to avoid in practise. In this regard, the objective of the research described in this article was to develop a procedure enabling one to locate, in a 3D X-ray microtomographic image of a soil sample, a physical surface that is obtained by sectioning and for which a number of chemical maps are available. This procedure involves three steps: (1) the reconstitution of the physical structure of the soil layer surface, (2) the alignment of the chemical maps with the reconstituted soil surface image, and (3) the 3D alignment of the 2D chemical maps with the internal structure of the soil cube. Visual comparison of the C and Si maps and of the reconstituted CT images of the layer surfaces suggests a good correspondence between them, which is supported by Pearson correlation coefficients of -0.57, -0.58, 0.45, and 0.43 for the different surfaces and elements considered. Relative to the original 3D X-ray CT image of the soil sample, the planes associated with the C and Si maps, respectively, are nearly superposed, which further confirms the validity of the alignment procedure. Article History: Received 16 November 2010; Revised 27 May 2011; Accepted 28 May 2011
    Keywords: Soil Structure -- Analysis ; Soil Structure -- Methods ; Soils -- Analysis ; Soils -- Methods
    ISSN: 0016-7061
    Source: Cengage Learning, Inc.
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  • 3
    Language: English
    In: Geoderma, 01 January 2018, Vol.309, pp.118-123
    Description: The “4 per 1000” initiative: A credibility issue for the soil science community?
    Keywords: Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 4
    Language: English
    In: Geoderma, 15 September 2017, Vol.302, pp.14-21
    Description: Most soil structure-related physical properties are correlated to soil organic carbon (SOC) content. Texture, mineralogy, and SOC:clay ratio are also acknowledged to affect physical properties, however there is no consensus or general conclusions in this respect. Against this background, the present study aims at determining objectives for the management of SOC in terms of structural quality of agricultural soils. The large area in which 161 free-to-swell undisturbed samples were obtained for this research represents a major part of the Swiss agricultural land and belongs to one broad soil group (Cambi-Luvisols). The structural quality was scored visually, and bulk volumes (inverse of bulk density) were measured at standard matric potentials. To define the effect of SOC without interference of soil mechanical degradation, soils with good structural quality scores were considered first in studying the relationship between SOC and soil pore volumes. Results suggest that the relationship is always linear, irrespective of the clay content of the soils. No optimum of SOC corresponding to a fraction of the clay content is found, contrary to the theory of “complexed organic carbon” (Dexter et al., 2008). However, the SOC:clay ratio decreases with decreasing soil structure quality. The SOC:clay ratio of 1:8 is the average for a very good structure quality. A SOC:clay ratio of 1:10 is the limit between good and medium structural quality, thus it constitutes a reasonable goal for soil management by farmers. A SOC:clay ratio of 1:8 or smaller leads to a high probability of poor structural state. These ratios can be used as criteria for soil structural quality and SOC management, and in that context, the concept of complexed organic carbon appears relevant.
    Keywords: Soil Organic Matter ; Clay Content ; Soil Quality ; Soil Structure ; Complexed Organic Carbon ; Vess ; Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 5
    Language: English
    In: Geoderma, 2011, Vol.164(3), pp.146-154
    Description: Recent 2-dimensional measurements reveal that soils are chemically very heterogeneous at nanometric and micrometric scales. Direct measurement techniques are still lacking to extend these observations to 3 dimensions. Sequential sectioning of soils, followed by 2-dimensional mapping of chemical elements and geometric interpolation to 3D, appears to be the only available alternative. Unfortunately, sectioning of soil samples suffers from geometric distortions that are difficult to avoid in practise. In this regard, the objective of the research described in this article was to develop a procedure enabling one to locate, in a 3D X-ray microtomographic image of a soil sample, a physical surface that is obtained by sectioning and for which a number of chemical maps are available. This procedure involves three steps: (1) the reconstitution of the physical structure of the soil layer surface, (2) the alignment of the chemical maps with the reconstituted soil surface image, and (3) the 3D alignment of the 2D chemical maps with the internal structure of the soil cube. Visual comparison of the C and Si maps and of the reconstituted CT images of the layer surfaces suggests a good correspondence between them, which is supported by Pearson correlation coefficients of − 0.57, − 0.58, 0.45, and 0.43 for the different surfaces and elements considered. Relative to the original 3D X-ray CT image of the soil sample, the planes associated with the C and Si maps, respectively, are nearly superposed, which further confirms the validity of the alignment procedure. ► A procedure is developed to locate physical planes in 3D X-ray CT images of soils. ► This procedure allows alignment of 2D chemical maps with the soil structure. ► Measured C and Si maps and reconstituted CT images correspond well with each other. ► Planes associated with the C and Si maps are nearly superposed.
    Keywords: X-Ray CT ; SEM–Edx ; Segmentation Techniques ; Spatial Correlation ; 3d Soil Images ; 2d Chemical Maps ; Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 6
    Language: English
    In: Geoderma, 15 September 2017, Vol.302, pp.111-111
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.geoderma.2017.05.009 Byline: Alice Johannes, Adrien Matter, Rainer Schulin, Peter Weisskopf, Philippe C. Baveye, Pascal Boivin
    Keywords: Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 7
    Language: English
    In: Geoderma, 15 May 2016, Vol.270, pp.10-20
    Description: Steelmaking slag (SS) is an industrial byproduct generated through metal refining processes. It has been applied as an agent to stabilize farmland soils contaminated both by arsenic and heavy metals in the Republic of Korea. However, the efficacy of this technique has not been established yet under anoxic conditions such as in the case of submerged rice paddy fields. Under anoxic conditions, As might be dissociated easily from solid surfaces where it is adsorbed reversibly. In this study, laboratory-scale column tests were conducted to artificially manipulate anoxic conditions in submerged paddy fields and we observed the release behavior of As and heavy metals, mainly cadmium (Cd). Limestone (LS) was also applied in the test for the purpose of comparison because it is usually applied as a common additive. The leachate samples were collected and chemical changes were monitored during the test period. Results suggest that anoxic conditions were developed during submersion, and that As or heavy metal fractions bound to ferrous (Fe)/manganese (Mn) oxides were easily dissociated. However, it was also shown that SS and LS significantly decreased the dissolution of Cd and As in the pore water; their removal rates in the SS-treated soil were 87% and 32%, respectively, of those in the control soil. On the other hand it appeared that SS was more effective than LS to stabilize Cd as well as As under submerged conditions. Therefore, SS might be an optimal stabilizing agent for dealing with As and other heavy metal contaminants in rice paddy soils that are periodically exposed to reducing environments.
    Keywords: Arsenic ; Column Test ; Limestone ; Rice Paddy ; Stabilization Method ; Steelmaking-Slag ; Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 8
    Language: English
    In: Geoderma, 2009, Vol.151(3), pp.126-127
    Keywords: Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
    Source: ScienceDirect Journals (Elsevier)
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  • 9
    Language: English
    In: Geoderma, 2010, Vol.157(1), pp.51-63
    Description: For the investigation of many geometrical features of soils, computer-assisted image analysis has become a method of choice over the last few decades. This analysis involves numerous steps, regarding which subjective decisions have to be made by the individuals conducting the research. This is particularly the case with the thresholding step, required to transform the original (color or greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice–Boltzmann models. Limited information exists at present on whether different observers, analyzing the same soil, would be likely to obtain similar results. In this general context, the first objective of the research reported in this article was to determine, through a so-called “round-robin” test, how much variation exists among the outcomes of various image thresholding strategies (including any image pre-treatment deemed appropriate), routinely adopted by soil scientists. Three test images – of a field soil, a soil thin section, and a virtual section through a 3-dimensional CT data set – were thresholded by 13 experts, worldwide. At the same time, variability of the outcomes of a set of automatic thresholding algorithms, applied to portions of the test images, was also investigated. The experimental results obtained illustrate the fact that experts rely on very different approaches to threshold images of soils, and that there is considerable observer influence associated with this thresholding. This observer dependence is not likely to be alleviated by adoption of one of the many existing automatic thresholding algorithms, many of which produce thresholded images that are equally, or even more, variable than those of the experts. These observations suggest that, at this point, analysis of the same image of a soil, be it a simple photograph or 3-dimensional X-ray CT data, by different individuals can lead to very different results, without any assurance that any of them would be even approximately “correct” or best suited to the objective at hand. Different strategies are proposed to cope with this situation, including the use of physical “standards”, adoption of procedures to assess the accuracy of thresholding, benchmarking with physical measurements, or the development of computational methods that do not require binary images.
    Keywords: Image Analysis ; Computed Tomography ; Lattice–Boltzmann Modelling ; Pore Geometry ; Soil Architecture ; Agriculture
    ISSN: 0016-7061
    E-ISSN: 1872-6259
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  • 10
    Language: English
    In: Geoderma, August 15, 2009, Vol.152(1-2), p.171(10)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.geoderma.2009.06.002 Byline: Chun-Yu Wu (a), Astrid R. Jacobson (b), Magdeline Laba (c), Philippe C. Baveye (d) Keywords: Soil structure; Aggregation; Remote sensing; Spectroscopy; Soil water content Abstract: Near-infrared reflectance sensing (NIRS) has stimulated widespread enthusiasm in recent years among soil scientists, in part for its potential to lead to the design of new "proximal" soil sensors in support of precision agriculture, and to increase significantly the amount of information that can be obtained about soils from remote sensors. However, a practical difficulty this technique faces is that soils in the field, unlike the sieved, repacked soil samples used in the laboratory, are generally moist and have uneven surfaces, especially after tillage. Unfortunately, little is known at this point on the effect of surface roughness on NIR spectra. In this context, the present research focuses on the application of NIRS, under laboratory conditions, to chunks (artificially isolated particles or aggregates) of soil of average sizes between 0.04 and 8mm, obtained in 5 different soils with contrasting features, and repacked in Petri dishes. NIRS measurements were performed when the soils were air-dry, and after rewetting to near-saturation. In virtually all cases, except at the finest chunk size in two soils, the near-infrared reflectance decreased regularly as chunk size increased. Near-saturation of the soils with deionized water resulted in further decreases in reflectance, which obliterated to varying extent the dependence of the reflectance on chunk size. For most cases, whether the soils were dry or near-saturated, computation of the first derivative of the NIR spectra, especially when preceded by moving-average or wavelet-based smoothing, resulted in transformed signals that were virtually independent of surface roughness in a number of distinct spectral regions. These observations suggest that in the range of soil chunk sizes considered, it might be possible practically to circumvent the dependence of NIRS on surface roughness. Author Affiliation: (a) Laboratory of Geoenvironmental Science and Engineering, Bradfield Hall, Cornell University, Ithaca, NY 14853, USA (b) Plants, Soils and Climate Department, Utah State University, 4820 Old Main Hill, Logan, UT 84322-4820, USA (c) Department of Civil and Environmental Engineering, Rice Hall, Cornell University, Ithaca, NY 14853, USA (d) SIMBIOS Centre, Abertay University, Bell Street, Dundee DD1 1HG, UK Article History: Received 4 November 2008; Revised 5 June 2009; Accepted 10 June 2009
    Keywords: Soil Structure ; Soils ; Agriculture ; Soil Moisture
    ISSN: 0016-7061
    Source: Cengage Learning, Inc.
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