RESUMEN
In boundary line analysis a biological response (e.g., crop yield) is assumed to be a function of a variable (e.g., soil nutrient concentration), which limits the response in only some subset of observations because other limiting factors also apply. The response function is therefore expressed by an upper boundary of the plot of the response against the variable. This model has been used in various branches of soil science. In this paper we apply it to the analysis of some large datasets, originating from commercial farms in England and Wales, on the recorded yield of wheat and measured concentrations of soil nutrients in within-field soil management zones. We considered boundary line models for the effects of potassium (K), phosphorus (P) and magnesium (Mg) on yield, comparing the model with a simple bivariate normal distribution or a bivariate normal censored at a constant maximum yield. We were able to show, using likelihood-based methods, that the boundary line model was preferable in most cases. The boundary line model suggested that the standard RB209 soil nutrient index values (Agriculture and Horticulture Development Board, nutrient management guide (RB209), 2017) are robust and apply at the within-field scale. However, there was evidence that wheat yield could respond to additional Mg at concentrations above index 0, contrary to RB209 guidelines. Furthermore, there was evidence that the boundary line model for yield and P differs between soils at different pH and depth intervals, suggesting that shallow soils with larger pH require a larger target P index than others. HIGHLIGHTS: Boundary line analysis is one way to examine how soil variables influence crop yield in large datasets.We showed that boundary line models could be applied to large datasets on soil nutrients and crop yield.The resulting models are consistent with current practice for P and K, but not for Mg.Models suggest that more refined recommendations for P requirement could be based on soil pH and depth.
RESUMEN
The distribution of elemental species of chromium (Cr) in potentially-contaminated soil samples warrants investigation due to the differing mobilities and toxicities of trivalent [Cr(III)] and hexavalent chromium [(Cr(VI)]. In addition, the possibility of species interconversions requires the implementation of robust methods that can correct for changes at the point of sampling, extraction and analysis. This work presents the application of speciated isotope dilution mass spectrometry (SIDMS) to accurately quantify Cr(VI) in agricultural soils within close proximity to a mine tailings dam in the Copperbelt Province of Zambia. Interpolated plots of total Cr, produced from data collected through a nested sampling design, were used to optimise the sampling across the spatial domain. Extraction of Cr(VI) was undertaken using a microwave assisted reaction system (80 °C for 5 min) with 50 mM EDTA, to complex Cr(III) and reduce the likelihood of oxidation during the extraction. Isotopically-enriched 53Cr(VI) was added to each sample prior to extraction to account for species interconversions. The accuracy of the method was confirmed using NIST SRM 2700 and 2701. Cr(VI) concentrations in the soil samples ranged between 0.03 and 0.29 mg kg-1, significantly lower than the residential UK screening value for Cr(VI) of 21 mg kg-1. The data indicate that this site poses a low environmental/human health risk with respect to Cr(VI) exposure.