Portable X-ray fluorescence (pXRF) calibration for analysis of nutrient concentrations and trace element contaminants in fertilisers.

With the increasing popularity of local blending of fertilisers, the fertiliser industry faces issues regarding quality control and fertiliser adulteration. Another problem is the contamination of fertilisers with trace elements that have been shown to subsequently accumulate in the soil and be taken up by plants, posing a danger to the environment and human health. Conventional characterisation methods necessary to ensure the quality of fertilisers and to comply with local regulations are costly, time consuming and sometimes not even accessible. Alternatively, using a wide range of unamended and intentionally amended fertilisers this study developed empirical calibrations for a portable handheld X-ray fluorescence (pXRF) spectrometer, determined the reliability for estimating the macro and micro nutrients and evaluated the use of the pXRF for the high-throughput detection of trace element contaminants in fertilisers. The models developed using pXRF for Mg, P, S, K, Ca, Mn, Fe, Zn and Mo had R2 values greater or equal to 0.97. These models also performed well on validation, with R2 values greater or equal to 0.97 (except for Fe, R2val = 0.55) and slope values ranging from 0.81 to 1.44. A second set of models were developed with a focus on trace elements in amended fertilisers. The R2 values of calibration for Co, Ni, As, Se, Cd and Pb were greater than or equal to 0.80. At concentrations up to 1000 mg kg-1, good validation statistics were also obtained; R2 values ranged from 0.97-0.99, except in one instance. The regression coefficients of the validation also had good prediction in the range of 0-100 mg kg-1 (R2 values were from 0.78-0.99), but not as well at lower concentrations up to 20 mg kg-1 (R2 values ranged from 0.10-0.99), especially for Cd. This study has demonstrated that pXRF can measure several major (P, Ca) and micro (Mn, Fe, Cu) nutrients, as well as trace elements and potential contaminants (Cr, Ni, As) in fertilisers with high accuracy and precision. The results obtained in this study is good, especially considering that loose powders were scanned for a maximum of 90 seconds without the use of a vacuum pump.

A comparison of soil texture measurements using mid-infrared spectroscopy (MIRS) and laser diffraction analysis (LDA) in diverse soils.

Spectroscopic methods for the determination of soil texture are faster and cheaper than the standard methods, but how do the results compare? To address this question, laser diffraction analysis (LDA) and mid-infrared spectroscopy (MIRS) analysis have been compared to conventional sieve-pipette measurements of texture in diverse European and Kenyan soils. To our knowledge this comparison between LDA and MIRS has not been made previously. It has used soils with a broad range of organic carbon (OC) contents to investigate whether, as in other techniques, clay-OC aggregation affects the estimation of clay with MIRS. The MIRS predictions of clay content were much better than the LDA measurements, but both techniques gave good measurements of sand content. The MIRS over-estimated clay at low clay content and under-estimated at high clay content (calibration set R2 = 0.83). The LDA over-estimated clay by ~ 60% (calibration set R2 = 0.36), indicating that the widely used clay threshold of < 8 µm was too high, and < 4 µm was found to be more accurate. In samples with < 5% OC content, both the LDA and MIRS gave very good clay predictions (R2 = 0.88 and 0.81, respectively). But in predictions of clay content in samples with > 5% OC the LDA under-estimated (R2 = < 0.1) and MIRS over-estimated (R2 = 0.34) clay content. In soils with OC removed, the MIRS prediction of clay content improved, indicating interference between over-lapping spectral regions for organic and mineral constituents. Unlike granulometric measurements of texture such as the LDA, MIRS analysis is not subject to the limitations imposed by the shape and density of particles. It was concluded that in typical agricultural soils with < 5% OC and < 60% clay content, both techniques could be used for cheap, fast and reliable estimates of soil texture.