Mid-infrared (mid-IR) diffuse reflectance spectroscopy can be used to effectively analyse soil, but the preparation of soil samples by grinding is time consuming. Soil samples are usually finely ground to a particle size of less than 0.250 mm because the spectrometer’s beam aperture is approximately 1–2 mm in diameter. Larger particles can generate specular reflections and spectra that do not adequately represent the soil sample. Grinding soil to small particle sizes enables the diffuse reflectance of light and more representative sample measurements. Here, we report on research that investigates the effect that grinding to different particle sizes have on soil mid-IR spectra. Our aims were to compare the effect of grinding soil to different particle sizes (2.000 mm, 1.000 mm, 0.500 mm, 0.250 mm and 0.106 mm) on the frequencies of mid-IR spectra, and compare the effect of these particle sizes on the accuracy of spectroscopic calibrations to predict organic carbon, sand, silt and clay contents. Using the Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) National visible–near infrared database, we selected 227 soil samples from the National Soil Archive for our experiments, and designed an experiment whereby each soil sample was ground in triplicate to the different particle sizes. These ground samples were measured using an FT-IR spectrometer with a spectral range of 4000–600 cm–1. Grinding to particle sizes that are ≤2.000 mm reduces subsample variability. Smaller particle sizes produce finer and sharper absorption features, which are related to organic carbon, and clay and sand mineralogies. Generally, better predictions for clay, sand and soil organic carbon contents were achieved using soil that is more finely ground, but there were no statistically significant differences between predictions that use soil ground to 1 mm, 0.5 mm, 0.25 mm. Grinding did not affect predictions of silt content. Recommendations on how much grinding is required for mid-IR analysis should also consider the time, cost and effort needed to prepare the soil samples as well as the purpose of the analysis.
The capture and storage of soil organic carbon (OC) should improve the soil's quality and function and help to offset the emissions of greenhouse gases. However, to measure, model or monitor changes in OC caused by changes in land use, land management or climate, we need cheaper and more practical methods to measure it and its composition. Conventional methods are complex and prohibitively expensive. Spectroscopy in the visible and near infrared (vis-NIR) is a practical and affordable alternative. We used samples from Australia's Soil Carbon Research Program (SCaRP) to create a vis-NIR database with accompanying data on soil OC and its composition, expressed as the particulate, humic and resistant organic carbon fractions, POC, HOC and ROC, respectively. Using this database, we derived vis-NIR transfer functions with a decision-tree algorithm to predict the total soil OC and carbon fractions, which we modelled in units that describe their concentrations and stocks (or densities). Predictions of both carbon concentrations and stocks were reliable and unbiased with imprecision being the main contributor to the models' errors. We could predict the stocks because of the correlation between OC and bulk density. Generally, the uncertainty in the estimates of the carbon concentrations was smaller than, but not significantly different to, that of the stocks. Approximately half of the discriminating wavelengths were in the visible region, and those in the near infrared could be attributed to functional groups that occur in each of the different fractions. Visible-NIR spectroscopy with decision-tree modelling can fairly accurately, and with small to moderate uncertainty, predict soil OC, POC, HOC and ROC. The consistency between the decision tree's use of wavelengths that characterize absorptions due to the chemistry of soil OC and the different fractions provides confidence that the approach is feasible. Measurement in the vis-NIR range needs little sample preparation and so is rapid, practical and cheap. A further advantage is that the technique can be used directly in the field.
Due to a combination of river regulation, dryland salinity and irrigation return, lower River Murray floodplains (Australia) and associated wetlands are undergoing salinisation. It was hypothesised that salinisation would provide suitable conditions for the accumulation of sulfidic materials (soils and sediments enriched in sulfides, such as pyrite) in these wetlands. A survey of nine floodplain wetlands representing a salinity gradient from fresh to hypersaline determined that surface sediment sulfide concentrations varied from <0.05% to ~1%. Saline and permanently flooded wetlands tended to have greater sulfide concentrations than freshwater ones or those with more regular wetting–drying regimes. The acidification risk associated with the sulfidic materials was evaluated using field peroxide oxidations tests and laboratory measurements of net acid generation potential. Although sulfide concentration was elevated in many wetlands, the acidification risk was low because of elevated carbonate concentration (up to 30% as CaCO3) in the sediments. One exception was Bottle Bend Lagoon (New South Wales), which had acidified during a draw-down event in 2002 and was found to have both actual and potential acid sulfate soils at the time of the survey (2003). Potential acid sulfate soils also occurred locally in the hypersaline Loveday Disposal Basin. The other environmental risks associated with sulfidic materials could not be reliably evaluated because no guideline exists to assess them. These include the deoxygenation risk following sediment resuspension and the generation of foul odours during drying events. The remediation of wetland salinity in the Murray–Darling Basin will require that the risks associated with disturbing sulfidic materials during management actions be evaluated.
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