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Over the last decade, X-ray computed tomography (CT) has been used increasingly to characterise the microscale architecture of soils. As a result significant progress has been made in the acquisition and interpretation of X-ray CT data, as well as in the thresholding of 3D greyscale CT images in order to produce binary (black and white) ones. Nevertheless, sizeable uncertainties persist, in particular concerning optimal instrumental settings used to generate the greyscale images. In this context, the key aim of this study is to investigate in detail the effect of scanning resolution and reconstruction settings such as noise reduction and 32-bit to 8-bit mapping interval on the 3D X-ray CT imaging of soil structure and the impact on the performance of thresholding methods. To assess the quality of the X-ray CT greyscale images, measures of contrast, noise and sharpness are proposed and tested on a series of images of five different soil samples. At the same time, performance of four segmentation algorithms, i.e., three methods recently developed to deal specifically with soil samples and Otsu's method as a benchmark, was evaluated using functional measures of 3D binary images, including Minkowski functionals and surface pore connected fraction. Results of these analyses suggest that the acquisition and reconstruction parameters investigated significantly affect the quality of soil images, and the subsequent thresholding process. In particular, it was found that thresholding by any of the four methods is greatly affected by the quality of image sharpness, which for soil images appears to be mainly controlled by the scanning resolution. As a result, it is concluded that no matter what reconstruction resolution is required in a study, in order to allow an accurate identification of the pore space, the sample should always be scanned at the highest resolution permitted by the scanning instrument and the sample size. Results also suggest that the three segmentation methods recently developed for soil images thresholding are robust to different levels of noise as well as the choice of the 32-bit mapping interval, as long as lower and upper interval limits for mapping are chosen within suitable boundaries.

During the past 10 years, multidrug-resistant Gram-negative Enterobacteriaceae have become a substantial challenge to infection control. It has been suggested by clinicians that the effectiveness of antibiotics is in such rapid decline that, depending on the pathogen concerned, their future utility can be measured in decades or even years. Unless the rise in antibiotic resistance can be reversed, we can expect to see a substantial rise in incurable infection and fatality in both developed and developing regions. Antibiotic resistance develops through complex interactions, with resistance arising by de-novo mutation under clinical antibiotic selection or frequently by acquisition of mobile genes that have evolved over time in bacteria in the environment. The reservoir of resistance genes in the environment is due to a mix of naturally occurring resistance and those present in animal and human waste and the selective effects of pollutants, which can co-select for mobile genetic elements carrying multiple resistant genes. Less attention has been given to how anthropogenic activity might be causing evolution of antibiotic resistance in the environment. Although the economics of the pharmaceutical industry continue to restrict investment in novel biomedical responses, action must be taken to avoid the conjunction of factors that promote evolution and spread of antibiotic resistance.

The role of fungi in soil ecosystem sustainability is poorly understood, as is the extent to which it is affected by the microscale heterogeneity of soils with respect to structure, chemistry and biology. This is due to the complexity of soil ecosystems, presenting significant challenges to their study in situ. Many theoretical and simulation models have been developed to link nutrient levels to colony dynamics. Unfortunately, there is currently no model that can take both structural and nutritional microscale heterogeneity into account, and is parameterised for the soil environment. In this context, the objective of this article is to develop such a 3D spatially explicit model of fungal dynamics, and to calibrate it for a soil system using data from the literature. A sensitivity analysis is carried out to better understand the uncertainties in the input parameters and their effect on colony dynamics in terms of biomass yield and respiration rates. The results highlight simulation outcomes that are most suited to validation by experimentation. The results also indicate that predictions in biomass yield are sensitive to uncertainties in model parameters relative to the soil–fungal complex that at this point are insufficiently understood experimentally and still have to be estimated by model fitting. The latter parameters, which influence biomass yield and respiration, are associated with biomass recycling processes such as adsorption (,αni) desorption (βni, βi), insulation (ζni) and biomass yield efficiency (ɛ1), and translocation (Dv). The model now opens up great opportunities for hypothesis-driven research, combining theoretical models and novel types of experimentation, especially given the recently acquired ability to generate artificial, replicable soil-like microcosms on which to test model predictions.

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.

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 pretreatment 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. (C) 2010 Elsevier B.V. All rights reserved.

Most studies on soil fungi have been carried out with little explicit characterisation of soil structure within which fungi spread and biotic interactions occur. In this paper we use a combination of epidemiological (colonisation efficiency) and soil bio-physical (thin sectioning) techniques to investigate the role of macropores in soil on the spread of a fungal colony. Macropores, in the form of gaps orientated in various directions, were artificially introduced in replicated samples of sand and a sandy loam. The pathogenic fungus Rhizoctonia solani AG4 was introduced on the surface (encountering a gap whilst the colony expands over the surface) or within soil (encountering a gap whilst the colony spreads through the bulk soil). Depending on the orientation, location and width, gaps were demonstrated to act as preferential pathways (increasing the colonisation efficiency of R. solani), or as a partial barrier (reducing the colonisation efficiency). Within bulk soil, R. solani preferentially followed larger pores, enabling the fungus to by-pass more densely areas. Study of soil thin sections revealed that hyphal densities were greater in gaps than in the surrounding bulk soil. We use the results to discuss how macropore structure in soil can either enhance or reduce the parasitic spread and saprotrophic invasion of soil by fungi.

Measurements in soils have been traditionally used to demonstrate that soil architecture is one of the key drivers of soil processes. Major advances in the use of X-ray Computed Tomography (CT) afford significant insight into the pore geometry of soils, but until recently no experimental techniques were available to reproduce this complexity in microcosms. This article describes a 3D additive manufacturing technology that can print physical structures with pore geometries reflecting those of soils. The process enables printing of replicated structures, and the printing materials are suitable to study fungal growth. This technology is argued to open up a wealth of opportunities for soil biological studies.

Fluorescent stains offer an effective means of visualising bacteria and fungi in soil or litter samples. Fluorescent brightener (FB) 28 (also known as Calcofluor White M2R) is commonly used to stain such microorganisms. However, during production of soil thin-sections we observed erratic crystallisation of this stain, particularly in soils colonised by Rhizoctonia solani. We report on the evaluation of alternative stains to FB 28 for their propensity to crystallize in interaction with fungi, staining efficiency, and suitability for application in soil thin-section production. All of the additional candidate stains namely Fluorescent Brightener Agent (FBA) 15/25, FBA 71 and SCRI Renaissance 2200 (SR 2200) were highly effective in staining agar-cultured hyphae, but differed in the degree to which they stained hyphae cultured in soil. All stains tested, except SR 2200, stained hyphae of R. solani insufficiently when growing on or through soil. These stains also showed extensive crystallisation in solutions that had been in contact with R. solani colonised soil. However, SR 2200 stained hyphae of R solani growing over soil as effectively as hyphae growing on agar and showed no evidence of crystallisation; the intensity of staining exceeded that of the ‘benchmark’ FB 28 for hyphae grown in two soil types. These excellent fluorescent properties of FBA 220 persisted in soil thin-sections, resulting in bright hyphae that could be readily visualised in situ in undisturbed soils.

Fundamental knowledge of the way fungi explore the pore volume within a soil is crucial if we are to understand how soil physical conditions affect population dynamics and invasion of many important fungal parasites and saprophytes within soil. In this study, spread of the fungus Rhizoctonia solani Kuhn (AG4), an economically important soil-borne plant pathogen and saprophyte, was quantified in relation to tortuosity and continuity of the air-filled pore space. Samples containing fine or coarse sand were equilibrated at matric potentials ranging from −1 to −7 kPa and inoculated with R. solani . We quantified the colony extent and biomass of R. solani spreading from a localized source of inoculum using microscopy and a monoclonal antibody-based immunosorbent assay. Air permeability rapidly increased when the air-filled pore space became continuous below a threshold matric potential of −2.0 kPa for the fine sand and −1.0 kPa for the coarse sand. Fungal spread was limited at high matric potentials with a colony extent of 6.6 and 4.6 mm for the fine and coarse sand, respectively, but increased to 32.6 and 28.5 mm, with a sharp transition below a threshold matric potential of −2.2 and −1.3 kPa. The average colony biomass dropped markedly at the same threshold matric potential. We conclude that the ability of the fungus to invade soil depends on the connectivity and tortuosity of the air-filled pore volume. At near-saturated conditions, the spread was spatially constrained to a relatively small volume, forming small dense colonies. In a well connected air-filled pore volume, larger colonies with low biomass density were formed. The broader implications for invasion of soil by a fungus and for transmission of fungal diseases are discussed.