Abstract: Recent advances in computed tomography provide measurement tools to study internal structures of soil aggregates at micrometer resolutions and to improve our understanding of specific mechanisms of various soil processes. Fractal analysis is one of the data analysis tools that can be helpful in evaluating heterogeneity of the intra-aggregate internal structures. The goal of this study was to examine how long-term tillage and land use differences affect intra-aggregate pore heterogeneity. The specific objectives were: (i) to develop an approach to enhance utility of box-counting fractal dimension in characterizing intra-aggregate pore heterogeneity; (ii) to examine intra-aggregate pores in macro-aggregates (4â6 mm in size) using the computed tomography scanning and fractal analysis, and (iii) to compare heterogeneity of intra-aggregate pore space in aggregates from loamy Alfisol soil subjected to 20 yr of contrasting management practices, namely, conventional tillage (chisel plow) (CT), no-till (NT), and native succession vegetation (NS). Three-dimensional images of the intact aggregates were obtained with a resolution of 14.6 μm at the Advanced Photon Source, Argonne National Laboratory, Argonne, IL. Proposed box-counting fractal dimension normalization was successfully implemented to estimate heterogeneity of pore voxel distributions without bias associated with different porosities in soil aggregates. The aggregates from all three studied treatments had higher porosity associated with large (>100 μm) pores present in their centers than in their exteriors. Pores 15 to 60 μm were equally abundant throughout entire aggregates but their distributions were more heterogeneous in aggregate interiors. The CT aggregates had greater numbers of pores 15 to 60 μm than NT and NS. Distribution of pore voxels belonging to large pores was most heterogeneous in the aggregates from NS, followed by NT and by CT. This result was consistent with presence of very large pores associated with former root channels in NT and NS aggregates. Our findings indicate that mechanisms of macro-aggregate formation might differ in their importance in different land use and management practices.
Abstract: Changes in total organic C (C T), water-soluble organic C (C WS), microbial biomass C (C MB), C mineralization, particulate organic C (C P), labile organic C (C L), C management index (CMI), and C storage in surface Hapli-Ustic Cambisol (0â20 cm) under straw incorporation after both 2- and 10-year durations were investigated in a maize (Zea mays L.) field experiment in northeast China, in order to examine the effectiveness of these active C fractions and CMI as early indicators for total C change. The treatments included straw removal (0%S), 50% of straw incorporation (50%S), and 100% of straw incorporation (100%S). Under the straw incorporation, C T concentration and C storage did not significantly change under 2-year duration, while were significantly increased under 10-year duration. However, C MB, total C mineralization (C TM), C P, and C L, and CMI were significantly increased under the straw incorporation even after only 2-year duration, and the responses were more significant after 10-year duration. There were positive correlations between all these C indicators with each other. Our findings demonstrate that the measured active C fractions (except for C WS) and CMI can provide an early indication of change in total soil organic C induced by straw incorporation.
Abstract: Impacts of organic manure and inorganic fertilizer on total organic carbon (CT), water-soluble organic C (CWS), microbial biomass C (CMB), particulate organic C (CP), labile organic C (CL), C storage and sequestration, and C management index (CMI) in surface soil (0â20 cm) were investigated in a 20-yr field experiment under a greenhouse vegetable system in northeast China. The treatments included unfertilized control (CK), N fertilizer (N), balanced NPK fertilizer (NPK), organic manure alone (M) and the NPK fertilizer combined with the manure (MNPK). Under the treatments of N and NPK, CT content and C storage were not significantly changed over the experimental period, while CWS, CMB, CP, CL concentrations and CMI were significantly increased compared with the unfertilized control. In comparison with the control, the manure treatments, M and MNPK, significantly increased CT content and C storage, sequestrating organic C of 8.9 and 9.2 Mg/ha, respectively. The M and MNPK treatments showed higher CWS, CMB, CP and CL concentrations and CMI than the other three treatments. Pearsonâs correlation coefficients were used to show that CWS, CMB, CP, CL and CMI could be useful indicators for assessing soil quality and total C changes. The M treatment is effective in sequestrating soil C, but resulted in lower crop yield compared with the NPK treatment. The MNPK treatment showed the greatest increases in crop yield and C sequestration in the greenhouse vegetable system.
Abstract: A 12-year field experiment was used to examine effects of return rates of crop straw residue on organic C sequestration by chemical fertilization in surface (0â20 cm) soil. The tested soil was a Hapli-Ustic Cambosol (FAO taxonomy) and the used crop was maize (Zea mays L.). The four main treatments were consisted of a gradient of return rate of straw residue, namely 0%, 25%, 50% and 100% of shattered straw residue (referred to as 0%S, 25%S, 50%S and 100%S, respectively). The three sub-treatments contained unfertilized control (CK), unbalanced N fertilization (N) and balanced NPK fertilization (NPK). Along the gradient of straw return rate, topsoil C storage significantly increased. The balanced NPK fertilization was more effective in sequestrating topsoil C than the unbalanced N fertilization. Responses of topsoil C storage to the straw return and fertilization significantly increased with the experimental duration. With increasing straw return rates, C-sequestration effects of the N, and NPK treatments in topsoil changed from not significant to significant or from significant to more significant in statistics. Our findings demonstrate that C-sequestration effects of chemical fertilization in topsoil strongly depend on return regime of straw residue.
Abstract: Advances in X-ray microtomography (μCT) are opening new opportunities for examining soil pore structures. However, usefulness of μCT data for pore structure characterization depends on how accurately the grayscale images are segmented into pore and solid components. Multiple segmentation algorithms have been developed; however, one of the difficulties in comparing the accuracy of segmentation algorithms is the lack of ground-truth information in the soil samples subjected to μCT. This means that only the criteria that do not depend on the availability of the ground-truth data can be used in assessing accuracy of the segmentation methods, yet the reliability of such criteria in soil images is unclear. In this study, we simulated 2D and 3D soil images to resolve the problem of the lack of ground-truth information. The objectives of the study were (i) to explore optimal parameter selection for indicator kriging (IK) segmentation; (ii) to compare the accuracy of several commonly used segmentation methods, namely, entropy based method, iterative method, Otsu's method, and IK method; and (iii) to evaluate performance of the region non-uniformity measure (NU), the criterion that does not depend on presence of the ground-truth image, in segmentation method selection for soil images. We found that though there was no single segmentation method that preserved pore characteristics in all the cases, IK method yielded segmented images most similar to the ground-truth in most of the cases when the histogram of image grayscale values had clearly distinguishable peaks. For the image with poorly distinguishable histogram peaks, IK did not perform well, while Otsu's method produced acceptable segmentation results. The results indicated that selecting the segmentation method based on NU did not always produce optimal representation of pore characteristics. However, overall, the NU was found to be an acceptable criterion for segmentation method selection in μCT soil images.
Abstract: Soil aggregates include sand/silt/clay, water, ion and organic matter contents combined with natural dry/wet (D/W)
cycling alters both the formation and function of intra-aggregate pore continuity, connectivity, dead-end storage volumes, and
tortuosity. Surface aggregates in the 0-5 cm depths of most soils experience from 34 to 57 D/W cycles that exceed differences in water
contents >10%. Both the rates of drying or wetting, (intensity) and the D/W range of soil water contents (severity) alter the transport
of water, C and N through micro and mesofaunal habitats among multiple size domains. This report identifies micro-niche locations
of accumulating soil C within soil aggregate regions that may affect nematode residence sites and migration pathways. Recent
advances in X-ray microtomography enable the examination of intact pore networks within soil aggregates at resolutions as small as 4 microns. Geostatistical and multi-fractal methods provide concise characteristics of pore spatial distributions within the aggregates
and are useful for comparing these alterations among soils. Aggregates subjected to multiple D/W cycles developed greater spatial
correlations that parallel increases in the 13C sorption within aggregate interiors were compared with locations of soil microbial
communities. Past research indicates microbial activities within the soil aggregate matrix are spatially heterogeneous due to complex
pore geometries within aggregates. Illumination of the ââblackboxââ interiors of soil aggregates includes a discussion of natural and
anthropogenic alterations of solution flow and carbon sequestration by soil aggregates containing biophysical gradients.
Abstract: 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 LatticeâBoltzmann 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 âround-robinâ 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 â of a field soil, a soil thin section, and a virtual section through a 3-dimensional CT data set â 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 âcorrectâ or best suited to the objective at hand. Different strategies are proposed to cope with this situation, including the use of physical âstandardsâ, 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.
Abstract: Electrically active magnetic (EAM) nanoparticles, consisting of aniline monomer polymerized around gamma iron(III) oxide (γ-Fe(2)O(3)) cores, serve as the basis of a direct-charge transfer biosensor developed for detection of surface glycoprotein hemagglutinin (HA) from the Influenza A virus (FLUAV) H5N1 (A/Vietnam/1203/04). H5N1 preferentially binds α2,3-linked host glycan receptors. EAM nanoparticles were immunofunctionalized with antibodies against target HA. Glycans preincubated with HA in 10% mouse serum were incubated with anti-HA-EAM complexes. The anti-HA-EAM complexes effectively acted as immunomagnetic separator of HA from mouse serum matrix. EAM nanoparticles served as the biosensor transducer for cyclic voltammetry measurements. The polyaniline was made electrically active by hydrochloric acid doping. Experimental results indicate that the biosensor is able to detect recombinant H5 HA at 1.4 μM in 10% mouse serum, with high specificity for H5 as compared to H1 (H1N1 A/South Carolina/1/18). This novel design applies EAM nanoparticles in a sensitive, specific, affordable, and easy-to-use biosensor with applications in disease monitoring and biosecurity.
