As a result of the important role played by phosphorus (P) in surface water eutrophication, the susceptibility of soils to release P requires evaluation. The degree of phosphorus saturation, assessed by oxalate extraction (DPSox), has been used as an indicator. However, most laboratories do not include DPSox in routine soil tests because of cost and time. This study evaluates the suitability of the ammonium acetate extraction in the presence of EDTA (AAEDTA), the standard soil test P (STP) in Wallonia (Southern Belgium), to predict DPSox; we also compared it with the Mehlich 3 extraction. Ninety‐three topsoil samples were collected in agricultural soils throughout Wallonia. Good correlations were found between the AAEDTA and the Mehlich 3 methods for P, Fe and Al (r = 0.85, 0.77 and 0.86, respectively). An exponential relationship was found between PAAEDTA and DPSox. Results of principal component analysis and regression demonstrated that STP can be used to predict DPSox (r = 0.93) after logarithmic transformation. Soil test Al was also a good indicator of the P sorption capacity (PSCox) of soils (r = 0.86). Including the clay fraction in regression equations only slightly improved the prediction of PSCox (r = 0.90), while other readily available data (such as pH or organic carbon) did not significantly improve either DPSox or PSCox predictions.

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The suitability of different process spectrometry techniques has been assessed, in terms of calibration requirements, accuracy, and precision, for the at-line monitoring of the sulfonation of fluorobenzene. Partial least-squares (PLS) calibration was required to analyze the spectra obtained by NIR spectrometry and low-field (29.1 MHz) 1H NMR spectrometry. The low-field (27.4 MHz) 19F NMR spectra contained well-resolved signals for the three fluorine containing compounds and univariate calibration was adequate. The Raman spectra of two of the compounds exhibited fluorescence and so this technique was not considered suitable for monitoring the reaction. The accuracy of the results obtained using univariate analysis of the 19F NMR data and PLS analysis of NIR data were comparable (average % error of 3.5 and 2.9%, respectively, for concentrations >0.5 mol dm−3 and 11.3 and 11.1%, respectively, for <0.5 mol dm−3). The least accurate results were obtained using PLS analysis of low-field 1H NMR data, as the spectra of two of the components were too similar. For concentrations >0.05 mol dm−3, the most precise results were obtained with PLS analysis of NIR data (average RSD of 1.6%), although the precision of the results obtained using univariate analysis of 19F NMR data was still good (average RSD of 3.7%).

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