My Account: Log In | Join | Renew
Table of Contents
Select All Chapters
Portable X-ray fluorescence (PXRF) spectrometry is a proximal sensing technique whereby low-power X-rays are used to make elemental determinations in soils. The technique is rapid, portable, and provides multi-elemental analysis with results generally comparable to traditional laboratory-based techniques. Elemental data from PXRF can then be either used directly for soil parameter assessment (e.g., total Ca, total Fe) or as a proxy for predicting other soil parameters of interest (e.g., soil cation-exchange capacity [CEC], soil reaction, soil salinity) via simple or multiple linear regression. Importantly, PXRF does have some limitations that must be considered in the context of soil analysis. Those notwithstanding, PXRF has proven effective in numerous, agronomic, pedological, and environmental quality assessment applications.
Agricultural practices contribute significant levels of greenhouse gas (GHG) emissions. Methods to measure net global warming potential (GWP) and greenhouse gas intensity (GHGI) that account for all sources and sinks of GHG emissions in agroecosystems are still evolving. Sources of GHGs include soil CO2, N2O, and CH4 emissions and CO2 emissions associated with farm operations, N fertilization, and other chemical inputs. Sinks of GHGs include CH4 uptake, soil C sequestration, and crop residue returned to the soil. This chapter discusses the methods of measuring net GWP and GHGI using two approaches: In the soil organic C (SOC) method, net GWP and GHGI are calculated by using N2O and CH4 emissions (or CH4 uptake), as well as CO2 emissions from farm operations, N fertilization, and other chemical inputs as GHG sources and C sequestration rate (∆SOC) as GHG sink. In the soil respiration method, soil respiration (excluding root respiration) is included as another GHG source, and the previous year’s crop residue returned to the soil instead of ∆SOC is included as GHG sink in addition to the above parameters. Advantages and drawbacks of each method of calculating net GWP and GHGI are also discussed.
The methods for gypsum content determination in soils are summarized and their applicability discussed. Special attention is given to the critical step of sample preparation, stressing the elimination of the oven heating at temperatures surpassing 40°C. Wet methods are unsuitable for soils rich in gypsum or containing other sulfates. Instead, oven-based methods playing on the mass variations due to the release of constitutional water of gypsum are preferable. Under laboratory settings, we recommend two existing methods: one directly measuring the loss of mass on heating and the other exploiting the gypsum–bassanite phase change under controlled conditions. Both reflectance and X-ray fluorescence (XRF) provide nondestructive methods for quick gypsum appraisal, and combining both methods increases the accuracy. The results are easily calibrated with gravimetric methods.
Soils are notoriously spatially heterogeneous and many soil properties are temporally variable. Spatial variability of soil properties has a profound influence on agricultural and environmental processes, such as plant–water–soil interactions, water flow, and solute transport, resulting in within-field plant yield variation and degradation of soil quality, to mention only a few. Field-scale mapping of spatial variability and monitoring of temporally dynamic soil properties is necessary for a variety of edaphic activities, such as soil surveys, reclamation, crop selection, site-specific management, and soil quality assessment. There are various approaches for characterizing soil spatial variability, but none of these has been as extensively investigated and is as reliable and cost effective as apparent soil electrical conductivity (ECa) directed soil sampling. Geospatial measurements of ECa are well suited for characterizing the spatial distribution of soil properties because they are reliable, quick, and easy to take with GPS-based mobilized ECa measurement equipment. Directed soil sampling based on geo-referenced measurements of ECa is a proven and robust means of characterizing the spatial variability of any soil property that influences ECa, including sol salinity, water content, texture, bulk density, organic matter, and cation exchange capacity. It is the goal of this methodology paper to provide an overview of the characterization of soil spatial variability across multiple scales using ECa–directed soil sampling with a focus on the field scale. Mobile ECa equipment, protocols, guidelines, special considerations, data reliability tests, and strengths and limitations are presented for characterizing spatial and temporal variation in soil properties using ECa–directed soil sampling.